******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-23 13:23:03.533513 UTC inp1= 20190423.00 ncores= 10 var= wind lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s wind False *************---------------------****************** ndt: 1 it: 0 ndt: 1 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var wind **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-23 13:23:03.562533 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -2 no impact estimation ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-23 13:25:24.352249 UTC inp1= 20190423.00 ncores= 10 var= rain lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s rain False *************---------------------****************** ndt: 1 it: 0 ndt: 1 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -3 classifications rain ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 00:00:00 ndt: 0 delta: 6 nt 72 alldate: DatetimeIndex(['2019-04-23'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 00:00:00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... False no past >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.00_Final_completed_rain.txt FINAL alldate: DatetimeIndex(['2019-04-23'], dtype='datetime64[ns]', freq='6H') 1 **FIRST cp /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain.tif /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/rain_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.00/rain_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.00_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/final/rain_popDensValues_final.xml ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-23 13:39:16.647936 UTC inp1= 20190423.00 ncores= 10 var= wind lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s wind False *************---------------------****************** ndt: 1 it: 0 ndt: 1 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var wind **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-23 13:39:16.672683 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -2 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 00:00:00 ndt: 0 delta: 6 nt 72 alldate: DatetimeIndex(['2019-04-23'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 00:00:00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... False no past >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.00_Final_completed_wind.txt FINAL alldate: DatetimeIndex(['2019-04-23'], dtype='datetime64[ns]', freq='6H') 1 **FIRST cp /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind.tif /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/wind_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/wind_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/wind_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.00/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.00/wind_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.00_final_completed_wind.txt input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/final/wind_popDensValues_final.xml ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-23 13:43:03.288922 UTC inp1= 20190423.00 ncores= 10 var= rain lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s rain False *************---------------------****************** ndt: 1 it: 0 ndt: 1 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 00:00:00 ndt: 0 delta: 6 nt 72 alldate: DatetimeIndex(['2019-04-23'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 00:00:00 processing all past bull only if Past=True... False no past >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.00_Final_completed_rain.txt ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast t0 completed t0 completed >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.00_final_completed_rain.txt ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-23 14:58:27.800621 UTC inp1= 20190423.00 ncores= 10 var= wind lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 06:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s wind False *************---------------------****************** ndt: 2 it: 0 ndt: 2 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var wind **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-23 14:58:27.834567 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 1 ndt: 2 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-23 14:58:27.855945 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -2 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 06:00:00 ndt: 6 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 06:00:00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.06_Final_completed_wind.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00'], dtype='datetime64[ns]', freq='6H') 2 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/wind_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/wind_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.06/wind_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.06_final_completed_wind.txt input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-23 15:04:23.828908 UTC inp1= 20190423.00 ncores= 10 var= rain lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 06:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s rain False *************---------------------****************** ndt: 2 it: 0 ndt: 2 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 2 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 06:00:00 ndt: 6 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 06:00:00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.06_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00'], dtype='datetime64[ns]', freq='6H') 2 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.06/rain_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.06_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-24 07:15:51.830037 UTC inp1= 20190423.00 ncores= 10 var= wind lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 18:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s wind False *************---------------------****************** ndt: 4 it: 0 ndt: 4 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var wind **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 07:15:51.863991 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 1 ndt: 4 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 07:15:51.884023 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 2 ndt: 4 idate: 2019-04-23 12:00:00 running case from 2019-04-23 12:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.12 RUNNING 2019-04-23 12:00:00 for 72 hours prevCalcDate 2019-04-23 06:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 07:15:51.900077 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.12.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.12.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 3 ndt: 4 idate: 2019-04-23 18:00:00 running case from 2019-04-23 18:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.18 RUNNING 2019-04-23 18:00:00 for 72 hours prevCalcDate 2019-04-23 12:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 07:15:51.915859 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.18.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.18.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -2 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 18:00:00 ndt: 18 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 18:00:00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed itdate, istime 2019-04-23 06:00:00 20190423.06 meteo-processing past forecast already completed itdate, istime 2019-04-23 12:00:00 20190423.12 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.18_Final_completed_wind.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00'], dtype='datetime64[ns]', freq='6H') 4 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-23 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-23 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_res_t0.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_res_t0.tif. 0......1010......20.20....30..30....40...40....50..50.60......6070......8070......9080......90...100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_popfile_t0_clipped.tif. 0......1010......2020.....30...30..40....40..50..50....60.....6070....70.....8080......9090......100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_countryfile_t0_clipped.tif. 0......1010......2020......3030......4040......5050......6060......7070......8080......9090......100 - done. 100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/wind_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_res_all.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_res_all.tif. 0......1010......2020......3030......4040......5050......6060......7070......8080......9090......100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_popfile_all_clipped.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_popfile_all_clipped.tif. 0...10....10..20...20....30...30..40...40....50.50.....60..60....70..70.....8080......9090......100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_countryfile_all_clipped.tif. 0..Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_countryfile_all_clipped.tif. 0..10.....2010......3020.....40..30.....40...5050.....60..60....70...70..80....80.90......90...100 - done. 100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/wind_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.12/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.18/wind_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.18_final_completed_wind.txt input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-24 07:24:36.014210 UTC inp1= 20190423.00 ncores= 10 var= rain lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-23 18:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s rain False *************---------------------****************** ndt: 4 it: 0 ndt: 4 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 4 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 4 idate: 2019-04-23 12:00:00 running case from 2019-04-23 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.12 RUNNING 2019-04-23 12:00:00 for 72 hours prevCalcDate 2019-04-23 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 4 idate: 2019-04-23 18:00:00 running case from 2019-04-23 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.18 RUNNING 2019-04-23 18:00:00 for 72 hours prevCalcDate 2019-04-23 12:00:00 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-23 18:00:00 ndt: 18 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-23 18:00:00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed itdate, istime 2019-04-23 06:00:00 20190423.06 meteo-processing past forecast already completed itdate, istime 2019-04-23 12:00:00 20190423.12 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190423.18_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00'], dtype='datetime64[ns]', freq='6H') 4 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-23 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-23 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_res_t0.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_res_t0.tif. 0......1010......2020......3030......4040......5050......6060......7070......8080......9090......100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_popfile_t0_clipped.tif. 0......1010......2020......3030......4040......5050......6060......7070......8080......9090......100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_countryfile_t0_clipped.tif. 0......1010......2020......3030......4040......5050......6060......7070......8080......9090......100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_res_all.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_res_all.tif. 0......1010......2020......3030......4040......50.50....60..60....70..70....80..80....90..90.....100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_popfile_all_clipped.tif. 0......1010......2020......3030......4040......5050.....60..60....70..70.....8080.....90..90.....100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_countryfile_all_clipped.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_countryfile_all_clipped.tif. 0...10....10..20....20..30....30..40....40....50..50..60.....6070......7080......8090......90...100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.12/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190423.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190423.18/rain_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190423.18_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-24 10:31:30.124414 UTC inp1= 20190423.00 ncores= 10 var= rain lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-24 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s rain False *************---------------------****************** ndt: 5 it: 0 ndt: 5 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 5 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 5 idate: 2019-04-23 12:00:00 running case from 2019-04-23 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.12 RUNNING 2019-04-23 12:00:00 for 72 hours prevCalcDate 2019-04-23 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 5 idate: 2019-04-23 18:00:00 running case from 2019-04-23 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.18 RUNNING 2019-04-23 18:00:00 for 72 hours prevCalcDate 2019-04-23 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 4 ndt: 5 idate: 2019-04-24 00:00:00 running case from 2019-04-24 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190424.00 RUNNING 2019-04-24 00:00:00 for 72 hours prevCalcDate 2019-04-23 18:00:00 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-24 00:00:00 ndt: 24 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-24 00:00:00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed itdate, istime 2019-04-23 06:00:00 20190423.06 meteo-processing past forecast already completed itdate, istime 2019-04-23 12:00:00 20190423.12 meteo-processing past forecast already completed itdate, istime 2019-04-23 18:00:00 20190423.18 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190424.00_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00'], dtype='datetime64[ns]', freq='6H') 5 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-23 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-23 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-24 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif lonminH 19.41 latminH -36.01 lonmaxH 59.73 latmaxH -3.01 [[ -3.01 -3.01 -3.01 ..., -3.01 -3.01 -3.01] [ -3.03 -3.03 -3.03 ..., -3.03 -3.03 -3.03] [ -3.05 -3.05 -3.05 ..., -3.05 -3.05 -3.05] ..., [-35.97 -35.97 -35.97 ..., -35.97 -35.97 -35.97] [-35.99 -35.99 -35.99 ..., -35.99 -35.99 -35.99] [-36.01 -36.01 -36.01 ..., -36.01 -36.01 -36.01]] [[ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] ..., [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73]] 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/rain_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.00/rain_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190424.00_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-24 14:37:47.403091 UTC inp1= 20190423.00 ncores= 10 var= wind lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-24 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s wind False *************---------------------****************** ndt: 5 it: 0 ndt: 5 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var wind **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 14:37:47.432991 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 1 ndt: 5 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 14:37:47.461280 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 2 ndt: 5 idate: 2019-04-23 12:00:00 running case from 2019-04-23 12:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.12 RUNNING 2019-04-23 12:00:00 for 72 hours prevCalcDate 2019-04-23 06:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 14:37:47.482499 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.12.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.12.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 3 ndt: 5 idate: 2019-04-23 18:00:00 running case from 2019-04-23 18:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.18 RUNNING 2019-04-23 18:00:00 for 72 hours prevCalcDate 2019-04-23 12:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 14:37:47.503760 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.18.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.18.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 4 ndt: 5 idate: 2019-04-24 00:00:00 running case from 2019-04-24 00:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190424.00 RUNNING 2019-04-24 00:00:00 for 72 hours prevCalcDate 2019-04-23 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-24 14:37:47.524787 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -2 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-24 00:00:00 ndt: 24 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-24 00:00:00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed itdate, istime 2019-04-23 06:00:00 20190423.06 meteo-processing past forecast already completed itdate, istime 2019-04-23 12:00:00 20190423.12 meteo-processing past forecast already completed itdate, istime 2019-04-23 18:00:00 20190423.18 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190424.00_Final_completed_wind.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00'], dtype='datetime64[ns]', freq='6H') 5 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-23 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-23 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-24 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif lonminH 19.41 latminH -36.01 lonmaxH 59.73 latmaxH -3.01 [[ -3.01 -3.01 -3.01 ..., -3.01 -3.01 -3.01] [ -3.03 -3.03 -3.03 ..., -3.03 -3.03 -3.03] [ -3.05 -3.05 -3.05 ..., -3.05 -3.05 -3.05] ..., [-35.97 -35.97 -35.97 ..., -35.97 -35.97 -35.97] [-35.99 -35.99 -35.99 ..., -35.99 -35.99 -35.99] [-36.01 -36.01 -36.01 ..., -36.01 -36.01 -36.01]] [[ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] ..., [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73]] 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/wind_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/wind_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/wind_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.00/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.00/wind_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190424.00_final_completed_wind.txt input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-29 12:50:27.403443 UTC inp1= 20190423.00 ncores= 10 var= wind lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-26 06:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s wind False *************---------------------****************** ndt: 14 it: 0 ndt: 14 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var wind **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.466184 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 1 ndt: 14 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.520549 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 2 ndt: 14 idate: 2019-04-23 12:00:00 running case from 2019-04-23 12:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.12 RUNNING 2019-04-23 12:00:00 for 72 hours prevCalcDate 2019-04-23 06:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.568320 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.12.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.12.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 3 ndt: 14 idate: 2019-04-23 18:00:00 running case from 2019-04-23 18:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190423.18 RUNNING 2019-04-23 18:00:00 for 72 hours prevCalcDate 2019-04-23 12:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.615190 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.18.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190423.18.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 4 ndt: 14 idate: 2019-04-24 00:00:00 running case from 2019-04-24 00:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190424.00 RUNNING 2019-04-24 00:00:00 for 72 hours prevCalcDate 2019-04-23 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.662235 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 5 ndt: 14 idate: 2019-04-24 06:00:00 running case from 2019-04-24 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190424.06 RUNNING 2019-04-24 06:00:00 for 72 hours prevCalcDate 2019-04-24 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.709757 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 6 ndt: 14 idate: 2019-04-24 12:00:00 running case from 2019-04-24 12:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190424.12 RUNNING 2019-04-24 12:00:00 for 72 hours prevCalcDate 2019-04-24 06:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.753538 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.12.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.12.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 7 ndt: 14 idate: 2019-04-24 18:00:00 running case from 2019-04-24 18:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190424.18 RUNNING 2019-04-24 18:00:00 for 72 hours prevCalcDate 2019-04-24 12:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.798304 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.18.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190424.18.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 8 ndt: 14 idate: 2019-04-25 00:00:00 running case from 2019-04-25 00:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190425.00 RUNNING 2019-04-25 00:00:00 for 72 hours prevCalcDate 2019-04-24 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.846119 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 9 ndt: 14 idate: 2019-04-25 06:00:00 running case from 2019-04-25 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190425.06 RUNNING 2019-04-25 06:00:00 for 72 hours prevCalcDate 2019-04-25 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.892454 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 10 ndt: 14 idate: 2019-04-25 12:00:00 running case from 2019-04-25 12:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190425.12 RUNNING 2019-04-25 12:00:00 for 72 hours prevCalcDate 2019-04-25 06:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.939425 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.12.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.12.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 11 ndt: 14 idate: 2019-04-25 18:00:00 running case from 2019-04-25 18:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190425.18 RUNNING 2019-04-25 18:00:00 for 72 hours prevCalcDate 2019-04-25 12:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:27.985967 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.18.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190425.18.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 12 ndt: 14 idate: 2019-04-26 00:00:00 running case from 2019-04-26 00:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190426.00 RUNNING 2019-04-26 00:00:00 for 72 hours prevCalcDate 2019-04-25 18:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:28.032598 ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190426.00.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190426.00.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False it: 13 ndt: 14 idate: 2019-04-26 06:00:00 running case from 2019-04-26 06:00:00 for 72 h start= 0 var wind **** gometeo: 72 listWindows rundate:20190426.06 RUNNING 2019-04-26 06:00:00 for 72 hours prevCalcDate 2019-04-26 00:00:00 ============================================ process meteo ============================================ 1. process meteo, starting at 2019-04-29 12:50:28.079261 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done ..1.1 calling HWRF_2_netcdf... inputDir: /mnt/input/grib_HWRF/2019/1000559/ output netCDF file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190426.06.run_1.2.nc ...file netcdf already existing : /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/netcdf/20190426.06.run_1.2.nc ret= -2 removing submitted ret= -2 newcase= False forceFinal= False forceBulletin= False home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -2 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-26 06:00:00 ndt: 78 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00', '2019-04-24 06:00:00', '2019-04-24 12:00:00', '2019-04-24 18:00:00', '2019-04-25 00:00:00', '2019-04-25 06:00:00', '2019-04-25 12:00:00', '2019-04-25 18:00:00', '2019-04-26 00:00:00', '2019-04-26 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-26 06:00:00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed itdate, istime 2019-04-23 06:00:00 20190423.06 meteo-processing past forecast already completed itdate, istime 2019-04-23 12:00:00 20190423.12 meteo-processing past forecast already completed itdate, istime 2019-04-23 18:00:00 20190423.18 meteo-processing past forecast already completed itdate, istime 2019-04-24 00:00:00 20190424.00 meteo-processing past forecast already completed itdate, istime 2019-04-24 06:00:00 20190424.06 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-24 12:00:00 20190424.12 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-24 18:00:00 20190424.18 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 00:00:00 20190425.00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 06:00:00 20190425.06 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 12:00:00 20190425.12 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 18:00:00 20190425.18 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-26 00:00:00 20190426.00 forcing HWRF verifying that input file is present start reading nc... wind ntNC: 25 ntmax 25 use all data in nc file ...create velAll 25 1651 2017 ...start calculating velAll ...end calculating velAll 25 1651 2017 nt,nx,ny, ntmax 25 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind.jpg dtk,nt,ntmax 2 25 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190426.06_Final_completed_wind.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00', '2019-04-24 06:00:00', '2019-04-24 12:00:00', '2019-04-24 18:00:00', '2019-04-25 00:00:00', '2019-04-25 06:00:00', '2019-04-25 12:00:00', '2019-04-25 18:00:00', '2019-04-26 00:00:00', '2019-04-26 06:00:00'], dtype='datetime64[ns]', freq='6H') 14 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_wind_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-23 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-23 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-24 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-24 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-24 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-24 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-25 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-25 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-25 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-25 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-26 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" date: 2019-04-26 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif --calc="maximum(A,B)" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif lonminH 19.41 latminH -36.01 lonmaxH 59.73 latmaxH -3.01 [[ -3.01 -3.01 -3.01 ..., -3.01 -3.01 -3.01] [ -3.03 -3.03 -3.03 ..., -3.03 -3.03 -3.03] [ -3.05 -3.05 -3.05 ..., -3.05 -3.05 -3.05] ..., [-35.97 -35.97 -35.97 ..., -35.97 -35.97 -35.97] [-35.99 -35.99 -35.99 ..., -35.99 -35.99 -35.99] [-36.01 -36.01 -36.01 ..., -36.01 -36.01 -36.01]] [[ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] ..., [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73]] 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_res_t0.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_res_t0.tif. 0......1010.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_res_t0.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_res_t0.tif. 0...Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_res_t0.tif. 0.......2020.10Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_res_t0.tif. 0......10Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_res_t0.tif. 0....10Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_res_t0.tif. 0..........Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_res_t0.tif. 010203030.........10.....20......2010....102030.....40..40..20............30...3020203040..........30.............4030404030......4050..50.........50.40.......40.....6060..50.60....50...50.50.........70706050.70.........60....60.5060.........7060.80.8080............70..70......6070.80..70.90.....9090......80...........80.90708080............90........9090.8090.............90...100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_popfile_t0_clipped.tif. 0............Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_popfile_t0_clipped.tif. 0.........101010101010........................101010202020202020...............202020..................303030303030.........3030....30.............404040404040..........4040......40.........5050505050..50....505050.....................606060606060........................606060707070707070...............707070..................808080808080............8080.80...........909090909090.....................9090.90...........100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_countryfile_t0_clipped.tif. 0........Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_countryfile_t0_clipped.tif. 0...............10101010101010........................1010202020.202020.....20.....................3030303030302020.......30..................404040..404040....3030...40.....................4040......505050505050505050.........................60606060606060.........6060................707070..70707070................7070.........80808080808080........................80.8090909090909090...........................9090......100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/wind_popDensValues_t0.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind_t0.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/wind_popDensValues_t0.xml outDir created popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/wind_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_res_all.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_res_all.tif. 0....10Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_res_all.tif. 0...10....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_res_all.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_res_all.tif. 0.20..Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_res_all.tif. 0.10..20.....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_res_all.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_res_all.tif. 0..10.....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_res_all.tif. 030.....10.....301020.....10.....20.10....40.....10.....4020...20.3020.....30.....20..........20...3030..304040.........3050...50.......30.40..40....40.......6060..40.......5040...50....70...70...50....60......50.506080..80.....60..50.70........50.....6090.60..9070..70......80....60..........60...70.70..808090..........70.......70..908080..90.........80......80.9090........90....90.....100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_popfile_all_clipped.tif. 0.........Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_popfile_all_clipped.tif. 0..........1010101010......................10101010.20202020....20.............20202020.................303030.30........3030303030.................40404040.........40404040.............4050.50.5050........50505050.50...............6060..6060................60.......6060707060607070............70.......70707070..................80808080..80.......80808080..............90909090....90..............90909090.................100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_countryfile_all_clipped.tif. 0..............Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_countryfile_all_clipped.tif. 0.......1010..1010101010.........................202020201010202020........................3030...3030..2020303030....................40404040.........4040403030.......................4040......50505050505050.......5050................60..606060606060.............6060............70707070..707070....................70708080...8080......808080..................908080909090.........909090.....................9090......100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/wind_popDensValues_all.xml >> 7. remove files done input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_wind.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//wind10m_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/wind_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/wind_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.06/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.12/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.18/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.00/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.06/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.12/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.18/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190426.00/wind_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/wind_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190426.06/wind_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190426.06_final_completed_wind.txt input var: wind10m Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/wind_final.tif hurName: hdate: var: wind10m description: wind10m: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//wind10m_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/wind_popDensValues_final.xml >> 7. remove files done ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-04-29 15:09:00.922802 UTC inp1= 20190423.00 ncores= 10 var= rain lw= aa.txt stormname= 1000559/24s submitting calc 2019-04-23 00:00:00 2019-04-26 06:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 HWRF 72 15 True GDACS/1000559/3_HWRF 6 1 False False 10 aa.txt 20190423.00 1000559/24s rain False *************---------------------****************** ndt: 14 it: 0 ndt: 14 idate: 2019-04-23 00:00:00 running case from 2019-04-23 00:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190423.00 RUNNING 2019-04-23 00:00:00 for 72 hours prevCalcDate 2019-04-22 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 14 idate: 2019-04-23 06:00:00 running case from 2019-04-23 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.06 RUNNING 2019-04-23 06:00:00 for 72 hours prevCalcDate 2019-04-23 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 14 idate: 2019-04-23 12:00:00 running case from 2019-04-23 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.12 RUNNING 2019-04-23 12:00:00 for 72 hours prevCalcDate 2019-04-23 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 14 idate: 2019-04-23 18:00:00 running case from 2019-04-23 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190423.18 RUNNING 2019-04-23 18:00:00 for 72 hours prevCalcDate 2019-04-23 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 4 ndt: 14 idate: 2019-04-24 00:00:00 running case from 2019-04-24 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190424.00 RUNNING 2019-04-24 00:00:00 for 72 hours prevCalcDate 2019-04-23 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 5 ndt: 14 idate: 2019-04-24 06:00:00 running case from 2019-04-24 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190424.06 RUNNING 2019-04-24 06:00:00 for 72 hours prevCalcDate 2019-04-24 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 6 ndt: 14 idate: 2019-04-24 12:00:00 running case from 2019-04-24 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190424.12 RUNNING 2019-04-24 12:00:00 for 72 hours prevCalcDate 2019-04-24 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 7 ndt: 14 idate: 2019-04-24 18:00:00 running case from 2019-04-24 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190424.18 RUNNING 2019-04-24 18:00:00 for 72 hours prevCalcDate 2019-04-24 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 8 ndt: 14 idate: 2019-04-25 00:00:00 running case from 2019-04-25 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190425.00 RUNNING 2019-04-25 00:00:00 for 72 hours prevCalcDate 2019-04-24 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 9 ndt: 14 idate: 2019-04-25 06:00:00 running case from 2019-04-25 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190425.06 RUNNING 2019-04-25 06:00:00 for 72 hours prevCalcDate 2019-04-25 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 10 ndt: 14 idate: 2019-04-25 12:00:00 running case from 2019-04-25 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190425.12 RUNNING 2019-04-25 12:00:00 for 72 hours prevCalcDate 2019-04-25 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 11 ndt: 14 idate: 2019-04-25 18:00:00 running case from 2019-04-25 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190425.18 RUNNING 2019-04-25 18:00:00 for 72 hours prevCalcDate 2019-04-25 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 12 ndt: 14 idate: 2019-04-26 00:00:00 running case from 2019-04-26 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190426.00 RUNNING 2019-04-26 00:00:00 for 72 hours prevCalcDate 2019-04-25 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 13 ndt: 14 idate: 2019-04-26 06:00:00 running case from 2019-04-26 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190426.06 RUNNING 2019-04-26 06:00:00 for 72 hours prevCalcDate 2019-04-26 00:00:00 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done 0 .. 10 .. 20 .. 30 .. 40 .. 50 .. 60 .. 70 .. 80 .. 90 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-04-23 00:00:00 currdate 2019-04-26 06:00:00 ndt: 78 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00', '2019-04-24 06:00:00', '2019-04-24 12:00:00', '2019-04-24 18:00:00', '2019-04-25 00:00:00', '2019-04-25 06:00:00', '2019-04-25 12:00:00', '2019-04-25 18:00:00', '2019-04-26 00:00:00', '2019-04-26 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-04-26 06:00:00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 processing all past bull only if Past=True... True itdate, istime 2019-04-23 00:00:00 20190423.00 meteo-processing past forecast already completed itdate, istime 2019-04-23 06:00:00 20190423.06 meteo-processing past forecast already completed itdate, istime 2019-04-23 12:00:00 20190423.12 meteo-processing past forecast already completed itdate, istime 2019-04-23 18:00:00 20190423.18 meteo-processing past forecast already completed itdate, istime 2019-04-24 00:00:00 20190424.00 meteo-processing past forecast already completed itdate, istime 2019-04-24 06:00:00 20190424.06 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-24 12:00:00 20190424.12 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-24 18:00:00 20190424.18 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 00:00:00 20190425.00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 06:00:00 20190425.06 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 12:00:00 20190425.12 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-25 18:00:00 20190425.18 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 itdate, istime 2019-04-26 00:00:00 20190426.00 forcing HWRF verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 24 1651 2017 25 nt,nx,ny, ntmax 24 1651 2017 25 [19.399999999999999, 0.02, 0, -3.0, 0, -0.02] *********** 6 3 2 varMAX.shape (1651, 2017) lonmin 19.4 latmin -36.0 lonmax 59.72 latmax -3.0 float64 latitude(latitude) units: degrees_north point_spacing: even unlimited dimensions: current shape = (1651,) filling off float64 longitude(longitude) units: degrees_east point_spacing: even unlimited dimensions: current shape = (2017,) filling off 19.4 59.72 -36.0 -3.0 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain.jpg dtk,nt,ntmax 2 24 25 23 k1, k2, ht 0 2 0 k1, k2, ht 2 4 6 k1, k2, ht 4 6 12 k1, k2, ht 6 8 18 k1, k2, ht 8 10 24 k1, k2, ht 10 12 30 k1, k2, ht 12 14 36 k1, k2, ht 14 16 42 k1, k2, ht 16 18 48 k1, k2, ht 18 20 54 k1, k2, ht 20 22 60 k1, k2, ht 22 24 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/20190426.06_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-04-23 00:00:00', '2019-04-23 06:00:00', '2019-04-23 12:00:00', '2019-04-23 18:00:00', '2019-04-24 00:00:00', '2019-04-24 06:00:00', '2019-04-24 12:00:00', '2019-04-24 18:00:00', '2019-04-25 00:00:00', '2019-04-25 06:00:00', '2019-04-25 12:00:00', '2019-04-25 18:00:00', '2019-04-26 00:00:00', '2019-04-26 06:00:00'], dtype='datetime64[ns]', freq='6H') 14 date: 2019-04-23 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.00/20190423.00_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.06/20190423.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-23 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.12/20190423.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-23 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190423.18/20190423.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-24 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.00/20190424.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-24 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-24 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-24 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-25 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-25 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-25 12:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-25 18:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-26 00:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" date: 2019-04-26 06:00:00 python /mnt/output/SSCS/scripts_dev/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif lonminH 19.41 latminH -36.01 lonmaxH 59.73 latmaxH -3.01 [[ -3.01 -3.01 -3.01 ..., -3.01 -3.01 -3.01] [ -3.03 -3.03 -3.03 ..., -3.03 -3.03 -3.03] [ -3.05 -3.05 -3.05 ..., -3.05 -3.05 -3.05] ..., [-35.97 -35.97 -35.97 ..., -35.97 -35.97 -35.97] [-35.99 -35.99 -35.99 ..., -35.99 -35.99 -35.99] [-36.01 -36.01 -36.01 ..., -36.01 -36.01 -36.01]] [[ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] ..., [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73] [ 19.41 19.43 19.45 ..., 59.69 59.71 59.73]] 19.41 59.73 -36.01 -3.01 lon 2017 lat 1651 savemap /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_res_t0.tif. 0..Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_res_t0.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_res_t0.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_res_t0.tif. 0....10....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_res_t0.tif. 0.....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_res_t0.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_res_t0.tif. 0101010.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_res_t0.tif. 0......20..Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_res_t0.tif. 0.......10..........1010202020.10.......30..10.......20..........2020303030.20.......40...20.....30..........30.30404040..30..........30...40.........4040..4050........40......50.5050..60...........605050.50.6060..5070.........50.....70......60.60...6070.70..6080.........6080..........70..70....70.8080..9070...90.....70.............8080...80.9090.80.......80.............90909090.....90...........100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_popfile_t0_clipped.tif. 0...Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_popfile_t0_clipped.tif. 0...Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_popfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_popfile_t0_clipped.tif. 0.........101010..................101010...10101020...2020..................202020202020............3030......30............303030303030.........404040.................404040.40.40405050....................50505050505050............6060....................6060606060607070.....................60707070707070.........70.....8080....................808080809090....808080.................90...909090........909090................100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_countryfile_t0_clipped.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_countryfile_t0_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_countryfile_t0_clipped.tif. 0................10.........1010..10101010....1010......20...............2020...202020...202030.....20................3030..30303040..3030...................30...4040...404040..4040...................40.....50505050.5050505050................60.........606060..606060....6060.......70...............707070..7070.70...7070..80....................808080..80809080...8080......................909090..909090...9090.....................100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_res_all.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_res_all.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_res_all.tif. 0.........101010.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_res_all.tif. 0..Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_res_all.tif. 0..Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_res_all.tif. 0.....20.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_res_all.tif. 0...Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_res_all.tif. 0.Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_res_all.tif. 0....2020..10...10......10...30.......10..10.10....3030.20..20.......40.20.........20..20..20..40.40..30.30........30.........30.30.30....40.40......40..50....40.40.4050.50..............60......60.605050.....70.50......5050..50..70...7060..60.....80....60.........6060...60.80....8070.70.90..........70.......70.70..70..90...908080.........80.........8080....80..90.90...90.........9090...90..........100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_popfile_all_clipped.tif. 0...Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_popfile_all_clipped.tif. 0.....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_popfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_popfile_all_clipped.tif. 0........1010....10....10....10....1010........10..102020...20.....20...20...2020.....2020.............30.30.......30.30303030.30.30..............40..40.....40.40...4040..40..40.40...........50.50.....50505050...505050..................60...60.6060.60.....60......60........7060.60..707070.70..........70.70....7070...............80..8080...80808080...........8080....90..9090...........90909090...........90...........90....100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_countryfile_all_clipped.tif. 0...Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_countryfile_all_clipped.tif. 0....Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_countryfile_all_clipped.tif. 0Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_countryfile_all_clipped.tif. 0.....101010...............10........10..20202010101010....................20..2030....3030....20202020...................4030404030..........30303030.................4040......40404040................50505050.......5050505050........606060.........60.............6060606070.707060................70..........80808070707070.70....................8090....9090.....8080808080..................90......9090909090.................100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.18/20190424.18_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.00/20190426.00_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.06/20190425.06_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.12/20190425.12_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190426.06/20190426.06_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.06/20190424.06_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.00/20190425.00_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190425.18/20190425.18_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/20190424.12/20190424.12_rain.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 4841P x 3962L. Processing input file /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 4841P x 3962L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.06/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.12/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190424.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190424.18/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.00/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.06/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.12/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190425.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190425.18/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190426.00/rain_popDensValues_all.xml copy: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/20190426.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/delft3d/20190426.06/rain_popDensValues_all.xml >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/20190426.06_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (HWRF) OutDir: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333334 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000559/3_HWRF/class/final/rain_popDensValues_final.xml >> 7. remove files done ==============================================================