Initial commit

diag_openifs.sh

+#!/bin/bash
+#
+# Diagnostics of OpenIFS run
+#
+
+# Load modules
+module load cdo/1.9.2
+module load nco
+
+obs_file=$1
+obs_name=$2
+model_file=$3
+model_name=$4
+model_off=$5
+model_frac=$6
+date1=$7
+date2=$8
+echo "dates " $date1 $date2
+
+tmp_dir="tmp"
+mkdir -p ${tmp_dir}
+
+names=(${obs_name} ${model_name})
+files=(${obs_file} ${model_file})
+interp_files=()
+
+newname=${model_name}
+
+cdo="cdo"
+   
+for (( ii=0 ; ii<=1 ; ii++ ))
+do
+   
+   datafile=${files[$ii]}
+   varname=${names[$ii]}
+   echo " Make climatology and regrid ${varname} in ${datafile}"
+
+   interp_method="remapbil"
+   target_grid="r180x90"
+   
+   # Get filename without extension
+   filename=$(basename -- "$datafile")
+   extension="${filename##*.}"
+   filename="${filename%.*}"
+   
+   # Filenames
+   diff_file=${tmp_dir}/${filename}_${varname}_diff.nc 
+   clim_file=${tmp_dir}/${filename}_${varname}_clim.nc
+   interp_file=${tmp_dir}/${filename}_${varname}_clim_${target_grid}.nc 
+   
+   # Make climatology
+   MAKE_CLIM=1
+   if [ ${MAKE_CLIM} -gt 0 ]
+   then
+      echo " Make climatology to ${clim_file} "
+      ${cdo} yseasmean -seldate,${date1},${date2} -selname,${varname} ${datafile} ${clim_file}
+   else
+      echo " Not making climatology "
+      ${cdo} seldate,${date1},${date2} -selname,${varname} ${datafile} ${clim_file}
+   fi
+   
+   # Interpolate data to coarse grid
+   echo " Interpolate data to ${interp_file}"
+   echo "${cdo} -sellonlatbox,-180,180,-90,90 -${interp_method},${target_grid} ${clim_file} ${interp_file}"
+   ${cdo} -sellonlatbox,-180,180,-90,90 -${interp_method},${target_grid} -chname,${obs_name},${newname} ${clim_file} ${interp_file}
+   
+   if [ $ii -gt 0 ]
+   then
+      # For model data, convert units  
+      conv_file=${interp_file}_conv
+      ${cdo} -O addc,${model_off} ${interp_file} ${conv_file}
+      ${cdo} -O mulc,${model_frac} ${conv_file} ${interp_file}
+      rm -rf ${conv_file} 
+   fi
+   
+   # Add final file to list of files to analyse
+   interp_files+=(${interp_file})
+   
+done
+
+echo ${interp_files[*]}
+
+COMPARE=1
+if [ $COMPARE -gt 0 ]
+then   
+   
+   # Compare files
+   echo " Compare ${interp_files[1]} and ${interp_files[0]} "
+   ${cdo} sub ${interp_files[1]} ${interp_files[0]} ${diff_file}
+    
+fi
+

diagnose_and_plot_openifs.sh

+#!/bin/bash
+
+module load anaconda2
+
+PRECIP=0
+UVEL=1
+
+if [ $PRECIP -gt 0 ]
+then
+   DATE1=1997-01-01T00:00:00
+   DATE2=2010-01-01T00:00:00
+   PRECIP_OBS=/gfs1/work/shkjocke/data/OBS/gpcp_v01r03_monthly_1996-2017.nc4
+   PRECIP_OBS_NAME=precip
+   PRECIP_MODEL=/gfs1/work/shkjocke/data/OIFS/T159L91/g001/NETCDF/g001_surface_diff_1m_1982-2009.nc
+   PRECIP_MODEL_NAME=TP
+   ./diag_openifs.sh ${PRECIP_OBS} ${PRECIP_OBS_NAME} ${PRECIP_MODEL} ${PRECIP_MODEL_NAME} 0 4000 ${DATE1} ${DATE2}
+   
+   python plot_diags.py --file=tmp/g001_surface_diff_1m_1982-2009_TP_diff.nc --vars=TP --diff
+   python plot_diags.py --file=tmp/g001_surface_diff_1m_1982-2009_TP_clim_r180x90.nc --vars=TP --file2=tmp/gpcp_v01r03_monthly_1996-2017_precip_clim_r180x90.nc
+fi
+
+if [ $UVEL -gt 0 ] 
+then 
+   DATE1=1982-01-01T00:00:00
+   DATE2=2010-01-01T00:00:00
+   UVEL_OBS=/gfs1/work/shkjocke/data/OBS/ERAinterim/uas.reana.eraint.1979-2017.r144x73.nc
+   UVEL_OBS_NAME=uas
+   UVEL_MODEL=/gfs1/work/shkjocke/data/OIFS/T159L91/g001/NETCDF/g001_surface_1m_1982-2009.nc
+   UVEL_MODEL_NAME=U10M
+   ./diag_openifs.sh ${UVEL_OBS} ${UVEL_OBS_NAME} ${UVEL_MODEL} ${UVEL_MODEL_NAME} 0 1 ${DATE1} ${DATE2}
+   
+   python plot_diags.py --file=tmp/g001_surface_1m_1982-2009_U10M_diff.nc  --vars=${UVEL_MODEL_NAME} --diff
+fi

ifs2nc_10.sh

+#!/bin/bash
+#
+#  ifs2nc.sh
+#  
+#  Purpose
+#  -------
+#  Convert OpenIFS output to netCDF files
+#
+#  Methods
+#  -------
+#  * Use CDO to split the ICMSH and ICMGG files 
+#    to one file vertical coordinate, e.g. hybrid, surface etc.
+#    As surface variables are always stored as GRIB1 and hybrid variables
+#    are always stored as GRIB2, this will not cause problems for CDO. 
+#    It may be necessary to split according to GRIB edition sometime later
+#  * Use CDO to convert from reduced Gaussian or spectral to regular Gaussian grid
+#  * Use CDO to convert the grib file to netCDF4/HDF5. 
+#    Level of compression set by CDO_ZIP variable.
+#
+#  History
+#  -------
+#  2018-07-27:  J. Kjellsson. First version
+#
+#
+
+# Here we need CDO and grib
+module load cdo
+
+GRIB_API_DIR=/sw/rhel6-x64/grib_api/grib_api-1.15.0-intel14/
+grib_copy=${GRIB_API_DIR}/bin/grib_copy
+
+OIFS_OUTPUT_DIR=$5
+OIFS_TMP_DIR=./TMP-IFS2NC/
+OIFS_PROCESSED_DIR=$4
+OIFS_EXPID=$6
+OIFS_FIRSTSTEP=$1
+OIFS_LASTSTEP=$2
+OIFS_STEP=$3
+
+mkdir -vp $OIFS_TMP_DIR
+mkdir -vp $OIFS_PROCESSED_DIR
+
+# Level of zipping (1-9). 0 means no zipping. 
+# This can reduce the data size by up to 90%
+# It adds a little bit to the processing time. 
+CDO_ZIP=1
+
+echo " Process data from ${OIFS_FIRSTSTEP} to ${OIFS_LASTSTEP} "
+for (( step=${OIFS_FIRSTSTEP} ; step<=${OIFS_LASTSTEP} ; step=step+${OIFS_STEP} ))
+do
+
+   timestamp=$( printf "%010d" $step )
+   
+   # We split the data into one file per vertical grid
+   # For writing in netCDF files, I think it makes no sense
+   # to put data on different grids into the same file. 
+   #
+   # Each netCDF file will have either surface, hybrid or isobaricInhPa as vert. coord
+   # Other types could be depthBelowLandLayer
+   
+   for typeOfLevel in surface isobaricInhPa hybrid
+      do
+      
+      FILES_ARRAY=()
+      FILES_STRING=" "
+      
+      for GRID in SH GG 
+      do 
+         
+         ORIGINAL_FILE=ICM${GRID}${OIFS_EXPID}+${timestamp} 
+         echo " Get data to ${OIFS_TMP_DIR}/${ORIGINAL_FILE}_${typeOfLevel}.grb "
+         $grib_copy -w typeOfLevel=$typeOfLevel ${OIFS_OUTPUT_DIR}/${ORIGINAL_FILE} ${OIFS_TMP_DIR}/${ORIGINAL_FILE}_${typeOfLevel}.grb
+         
+         LEVEL_FILE=${OIFS_TMP_DIR}/${ORIGINAL_FILE}_${typeOfLevel}.grb
+         REGULAR_FILE=${OIFS_TMP_DIR}/${ORIGINAL_FILE}_${typeOfLevel}_R.grb
+         NETCDF_FILE=${OIFS_TMP_DIR}/${ORIGINAL_FILE}_${typeOfLevel}_R.nc
+          
+         if [ -e ${LEVEL_FILE} ]; then
+            
+            if [ $GRID == "GG" ]; then
+               echo " Convert ${LEVEL_FILE} to ${REGULAR_FILE} (reduced Gaussian to regular Gaussian)"
+               cdo -O setgridtype,regular ${LEVEL_FILE} ${REGULAR_FILE}
+            elif [ $GRID == "SH" ]; then
+               echo " Convert ${LEVEL_FILE} to ${REGULAR_FILE} (spectral harmonics to regular Gaussian)"
+               cdo -O sp2gpl ${LEVEL_FILE} ${REGULAR_FILE} 
+            fi
+            
+            rm -f ${LEVEL_FILE}
+            
+            # Using grib_to_netcdf to convert data has the advantage of retaining variable names
+            # but does not get the correct longitudes and latitudes. It also does not put a,b coeffs
+            # into files with hybrid coordinates. 
+            #OPTS="-u time -k 3 -D NC_FLOAT"
+            #grib_to_netcdf ${OPTS} ${REGULAR_FILE} -o ${NETCDF_FILE}
+            
+            # CDO 
+            OPTS="-t ecmwf -f nc4c -z zip_1 copy -sellonlatbox,-180,180,-90,90"
+            cdo ${OPTS} ${REGULAR_FILE} ${NETCDF_FILE}
+            
+            rm -f ${REGULAR_FILE}
+            
+            #if [ $CDO_ZIP -gt 0 ]; then
+            #   cdo -O -f nc4c -z zip_1 copy ${NETCDF_FILE} ${NETCDF_FILE}4
+            #   rm ${NETCDF_FILE}; mv ${NETCDF_FILE}4 ${NETCDF_FILE}               
+            #fi 
+            
+            dtime=$(cdo -s showtimestamp ${NETCDF_FILE})
+            dtime2=$(echo $dtime | sed -r 's/T/ /g') 
+            DTIME=$(date -d "$dtime2" "+%F_%H%M%S")
+            
+            echo " Datetime for file ${NETCDF_FILE} is ${DTIME} "
+            
+            FILES_ARRAY+=(${NETCDF_FILE})
+            FILES_STRING=${FILES_STRING}" "${NETCDF_FILE}
+         
+         else
+            
+            echo " No file named ${LEVEL_FILE}. No such data in your output? "
+
+         fi
+      done
+      GLUED_FILE=${OIFS_PROCESSED_DIR}/${OIFS_EXPID}_${typeOfLevel}_${DTIME}.nc
+      echo " Glue files $FILES_STRING to one file $GLUED_FILE "
+      cdo -O merge $FILES_STRING $GLUED_FILE
+      rm -f ${FILES_STRING}
+      
+      if [ "${typeOfLevel}" == "hybrid" ]; then
+         ZH_FILE=${OIFS_PROCESSED_DIR}/${OIFS_EXPID}_${typeOfLevel}_zh_${DTIME}.nc
+         NEW_GLUED_FILE=${OIFS_PROCESSED_DIR}/${OIFS_EXPID}_${typeOfLevel}_with_zh_${DTIME}.nc
+         echo " Calculate geopotential height from hybrid data " ${NEW_GLUED_FILE}
+         cdo -O geopotheight -chname,lnsp,lsp ${GLUED_FILE} ${ZH_FILE} 
+         cdo -O merge ${GLUED_FILE} ${ZH_FILE} ${NEW_GLUED_FILE}
+         rm ${GLUED_FILE} ${ZH_FILE}
+         mv ${NEW_GLUED_FILE} ${GLUED_FILE}
+         
+         PLEV_FILE=${OIFS_PROCESSED_DIR}/${OIFS_EXPID}_plevel_${DTIME}.nc
+         STD_LEVELS="100000,92500,85000,77500,70000,60000,50000,40000,30000,25000,20000,15000,"
+         STD_LEVELS=${STD_LEVELS}"10000,7000,5000,3000,2000,1000,700,500,300,200,100,50,20,10,5,2,1 "
+         echo " Interpolate to pressure levels ${PLEV_FILE} "
+         cdo -O ml2pl,${STD_LEVELS} ${GLUED_FILE} ${PLEV_FILE}
+         
+      fi
+      
+   done
+   
+done

plot_diags.py

+#
+#
+# Plot two fields
+#
+# Author: Joakim Kjellsson, Dec 2018
+#
+# Alexa: Play Despacito!
+#
+
+import os,sys
+import argparse
+import numpy as np
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+from netCDF4 import Dataset
+from mpl_toolkits.basemap import Basemap
+
+def parse_args():
+   # Parse input arguments
+   long_line = ' --------------------------------------------- '
+   
+   ## Parse input arguments
+   parser = argparse.ArgumentParser(description='Plot geospatial data')
+   parser.add_argument('--file', dest='file', action='store', default='data.nc',\
+                       help='Name of file (must be netCDF)')
+   parser.add_argument('--file2', dest='file2', action='store', default='None',\
+                       help='Name of second file (for comparison)') 
+   
+   parser.add_argument('--vars', dest='vars', action='store', default='T2M',\
+                       help='Comma-separated list of variables to plot')
+   parser.add_argument('--vmin', dest='vmin',action='store', default='None',\
+                       help='Comma-separated list of minimum for colour levels') 
+   parser.add_argument('--vmax', dest='vmax',action='store', default='None',\
+                       help='Comma-separated list of maximum for colour levels')
+
+   parser.add_argument('--figname', dest='figname', action='store', default='plot',\
+                       help='Name of plot (no extension)')
+   
+   parser.add_argument('--fig_format', dest='fig_format', action='store', default='png',\
+                       help='Format of figure (default: png)')
+   
+   parser.add_argument('--diff', action='store_true',\
+                       help='Difference plot')
+   
+   args = parser.parse_args()
+   
+   return args
+
+
+def read_netcdf_data(filename,varlist=[]):
+   """
+   """
+   
+   data = {}
+   
+   print(' Read %s ' % (filename,))
+   nc = Dataset(filename,'r')
+   vars = nc.variables.keys()
+   for lonname in ['longitude','lon','nav_lon']:
+      if lonname in vars:
+         lons = nc.variables[lonname][:]
+   for latname in ['latitude','lat','nav_lat']:
+      if latname in vars:
+         lats = nc.variables[latname][:]
+   
+   for timename in ['time','time_counter','time_centered']:
+      if timename in vars:
+         id_time = nc.variables[timename]
+         nt      = id_time[:].shape[0]
+         
+   if lons.ndim == 2 and lats.ndim == 2:
+      data['lons'] = lons
+      data['lats'] = lats
+   elif lons.ndim == 1 and lats.ndim == 1:
+      lon2,lat2 = np.meshgrid(lons,lats)
+      data['lons'] = lon2
+      data['lats'] = lat2
+   else:
+      print(' Weird shapes of lons,lats: ',lons.shape,lats.shape)
+      sys.exit()
+   
+   if 1:
+      data['nt'] = nt
+   
+   if len(varlist) > 0:
+      for var in varlist:
+         data[var] = nc.variables[var][:]
+   else:
+      print(' No variables to read. Varlist = ',varlist)
+      print(' nc = ',nc)
+      sys.exit()
+   
+   nc.close()
+   
+   return data
+   
+             
+   
+
+def setup_map(ax,map='global'):
+   """
+   """
+   
+   if map == 'global':
+      m = Basemap(projection='cyl',llcrnrlat=-90,urcrnrlat=90,\
+                  llcrnrlon=-180,urcrnrlon=180,resolution='c',ax=ax)
+      parallels = np.arange(-90.,91.,30.)
+      meridians = np.arange(-180.,181.,60.)
+   
+   if 1:
+      m.drawcoastlines()
+   if 0:
+      m.fillcontinents(color='Gainsboro')
+   if 1:
+      m.drawparallels(parallels)
+      m.drawmeridians(meridians)
+      #m.drawmapboundary(fill_color='aqua')
+      #m.drawcoastlines()
+   
+   return m
+   
+
+def simple_cf_plot(bmap,ax,x,y,zplot,diff=False,set_levels=True,cflevels=np.arange(0,1,0.1),cbar=False,ct=False,vmin=999,vmax=999):
+   if set_levels and vmin == 999 and vmax == 999:
+      zmin = np.percentile(zplot,1)
+      zmax = np.percentile(zplot,99)
+      if diff:
+         vmax = max(zmax,-zmin)
+         vmin = -vmax
+      else:
+         vmax = zmax
+         vmin = zmin
+      cflevels = np.linspace(vmin,vmax,20)
+      ctlevels = np.linspace(vmin,vmax,11)
+   elif (not set_levels) and (vmin != 999) and (vmax != 999):
+      cflevels = np.linspace(vmin,vmax,20)
+   else:
+      ctlevels = cflevels[1::2]
+   
+   if diff:
+      cmap = plt.cm.RdBu_r
+   else:
+      cmap = plt.cm.viridis
+      
+   if 1:
+      cf1 = bmap.contourf(x,y,zplot,levels=cflevels,cmap=cmap,extend='both')
+   if ct:
+      ct1 = bmap.contour(x,y,zplot,levels=ctlevels,colors='k')
+   else: 
+      ct1 = None
+   if cbar:
+      cb1 = plt.colorbar(cf1,ax=ax)
+   else:
+      cb1 = None
+      
+   return cf1,ct1,cb1
+
+
+def single_diff_plot(lons,lats,zplot):
+   fig1 = plt.figure()
+   ax1  = fig1.add_subplot(111)
+   bm1  = setup_map(ax=ax1)
+   x,y  = bm1(lons,lats)
+   cf, ct, cb = simple_cf_plot(bm1,ax1,x,y,zplot,diff=True,cbar=True)
+   return fig1
+
+def compare_two_fields(lon1,lat1,zplot1,lon2,lat2,zplot2):
+   fig1 = plt.figure()
+   ax1  = fig1.add_axes([0.025,0.2,0.45,0.3])
+   ax2  = fig1.add_axes([0.525,0.2,0.45,0.3])
+   cax  = fig1.add_axes([0.2,0.15,0.6,0.02])
+   
+   bm1  = setup_map(ax=ax1)
+   bm2  = setup_map(ax=ax2)
+   x1,y1 = bm1(lon1,lat1)
+   x2,y2 = bm2(lon2,lat2)
+   
+   cf1,ct1,cb1 = simple_cf_plot(bm1,ax1,x1,y1,zplot1)
+   levels = cf1.levels
+   cf2,ct2,cb2 = simple_cf_plot(bm2,ax2,x2,y2,zplot2,set_levels=False,cflevels=levels,cbar=False)
+   cb = plt.colorbar(cf1,cax=cax,orientation='horizontal',ticks=[levels[0],levels[-1]])
+   
+         
+   return fig1
+
+if 1:
+   args = parse_args()
+   varlist = args.vars.split(',')
+   vminlist = args.vmin.split(',')
+   vmaxlist = args.vmax.split(',')
+   
+   print(' Plotting variables: ')
+   for var in varlist: 
+      print(' %s ' % (var,))
+   print(' From file %s ' % (args.file,))
+   data = read_netcdf_data(args.file,varlist=varlist)
+   lons = data['lons'][:]
+   lats = data['lats'][:]
+   
+   if args.file2 != 'None':
+      print(' and file2 %s ' % (args.file2,))
+      data2 = read_netcdf_data(args.file2,varlist=varlist)
+      lons2 = data2['lons'][:]
+      lats2 = data2['lats'][:]
+   
+   if args.diff:
+      for var in varlist:
+         if 1:
+            for jn in range(0,data['nt']):
+               zplot = data[var][jn,:,:]
+               fig1 = single_diff_plot(lons,lats,zplot)
+               figname = '%s_%s_%d.%s' % (args.figname,var,jn,args.fig_format)
+               fig1.savefig(figname,format=args.fig_format)
+               print(' Saved figure %s ' % (figname,))
+               
+   if args.file2 != 'None':
+      for var in varlist:
+         print('Comparing two fields, %s ' % (var,))
+         if 1:
+            for jn in range(0,data['nt']):
+               zplot1 = data[var][jn,:,:]
+               zplot2 = data2[var][jn,:,:]
+               fig1 = compare_two_fields(lons,lats,zplot1,lons2,lats2,zplot2)
+               figname = '%s_%s_compare_%d.%s' % (args.figname,var,jn,args.fig_format)
+               fig1.savefig(figname,format=args.fig_format)
+               print(' Saved figure %s ' % (figname,))
+   

plot_diffs_foci.py

+# load modules needed 
+import numpy as np
+import matplotlib.pyplot as plt
+from netCDF4 import Dataset
+from mpl_toolkits.basemap import Basemap
+
+def setup_map(ax,map='global'):
+   """
+   """
+   
+   if map == 'global':
+      m = Basemap(projection='cyl',llcrnrlat=-90,urcrnrlat=90,\
+                  llcrnrlon=-180,urcrnrlon=180,resolution='c',ax=ax)
+      #m = Basemap(projection='moll',lon_0=30,resolution='c',ax=ax)
+      parallels = np.arange(-90.,91.,30.)
+      meridians = np.arange(-180.,181.,60.)
+   
+   if map == 'tatl':
+      m = Basemap(projection='cyl',llcrnrlat=-20,urcrnrlat=20,\
+                  llcrnrlon=-70,urcrnrlon=20,resolution='c',ax=ax)
+      parallels = np.arange(-90.,91.,30.)
+      meridians = np.arange(-180.,181.,60.)
+   
+   if 1:
+      m.drawcoastlines()
+   if 0:
+      m.fillcontinents(color='coral')
+   if 1:
+      m.drawparallels(parallels)
+      m.drawmeridians(meridians)
+   
+   return m
+
+
+if 0:
+   ofile1 = 'OBS/N80/HadISST_sst_N80_ymonmean_1950-1990.nc'
+   ofile = 'OBS/N80/HadISST_sst_N80_ymonmean_1950-1990.nc'
+   file1 = 'esm-experiments/foci17/outdata/nemo/foci17_1m_19510101_19541231_grid_T_ymonmean_N80.nc'
+   file2 = 'esm-experiments/foci25/outdata/nemo/foci25_1m_19510101_19541231_grid_T_ymonmean_N80.nc'
+   dlevels = np.linspace(-2,2,11)
+
+if 0:
+   ofile = '/work/bb0519/foci_input-joakimkjellsson/NEMO/input/r0001/ORCA05/Levitus_p2.1_1m_01_12_Tpot_ORCA_R05.nc'
+   file1 = 'esm-experiments/foci17/outdata/nemo/foci17_1m_19510101_19541231_grid_T_ymonmean.nc'
+   file2 = 'esm-experiments/foci25/outdata/nemo/foci25_1m_19510101_19541231_grid_T_ymonmean.nc'
+   dlevels = np.linspace(-2,2,11)
+
+if 1:
+   bdir = '/scratch/usr/shkjocke/esm-experiments/'
+   ofile = '/scratch/usr/shkjocke/foci_input-gitlab/NEMO/input/r0001/ORCA05/Levitus_p2.1_1m_01_12_Tpot_ORCA_R05.nc'
+   file1 = bdir + 'foci5/outdata/nemo/foci5_1m_19500101_19541231_grid_T_ymonmean.nc'
+   file2 = bdir + 'foci5/outdata/nemo/foci5_1m_19500101_19541231_grid_T_ymonmean.nc'
+   dlevels = np.linspace(-2,2,11)
+
+
+lonname = 'nav_lon'
+latname = 'nav_lat'
+ovar = 'votemper'
+mvar = 'votemper'
+region = 'global'
+ltimmean = True
+
+ilev = 0
+steps = [0]
+
+if 1:   
+   for step in steps:
+      print(ofile)
+      nc = Dataset(ofile,'r')
+      olon = nc.variables[lonname][:]
+      olat = nc.variables[latname][:]
+      if ltimmean:
+         odata = nc.variables[ovar][:].mean(axis=0)
+      else:
+         odata = nc.variables[ovar][step,:]
+      if ilev >= 0:
+         odata = odata[ilev,:]
+      nc.close()
+      print(file1)
+      nc = Dataset(file1,'r')
+      lon1 = nc.variables[lonname][:]
+      lat1 = nc.variables[latname][:]
+      if ltimmean:
+         data1 = nc.variables[mvar][:].mean(axis=0)
+      else:
+         data1 = nc.variables[mvar][step,:]
+      if ilev >= 0:
+         data1 = data1[ilev,:]
+      nc.close()
+      print(file2)
+      nc = Dataset(file2,'r')
+      lon2 = nc.variables[lonname][:]
+      lat2 = nc.variables[latname][:]
+      if ltimmean:
+         data2 = nc.variables[mvar][:].mean(axis=0)
+      else:
+         data2 = nc.variables[mvar][step,:]
+      if ilev >= 0:
+         data2 = data2[ilev,:]
+      nc.close()
+      print('Plot')
+      fig = plt.figure()
+      ax1 = fig.add_subplot(121)
+      ax2 = fig.add_subplot(122)
+      ax1.set_title('Low res')
+      ax2.set_title('High res')
+      bm1 = setup_map(ax1,map=region)
+      bm2 = setup_map(ax2,map=region)
+      if lonname != 'nav_lon':
+         lon11,lat11 = np.meshgrid(lon1,lat1)
+         lon22,lat22 = np.meshgrid(lon2,lat2)
+      else:
+         lon11 = lon1
+         lat11 = lat1
+         lon22 = lon2
+         lat22 = lat2
+         
+      x1,y1 = bm1(lon11,lat11)
+      x2,y2 = bm2(lon22,lat22)
+      x1 = x1.flatten()
+      y1 = y1.flatten()
+      z1 = np.ma.masked_where(data1 == 0, data1-odata)
+      z1 = z1.flatten()
+      x2 = x2.flatten()
+      y2 = y2.flatten()
+      z2 = data2-odata
+      z2 = np.ma.masked_where(data2 == 0, data2-odata)
+      z2 = z2.flatten()
+      cf1 = bm1.contourf(x1,y1,z1,levels=dlevels,extend='both',cmap=plt.cm.RdBu_r,tri=True)
+      cf2 = bm2.contourf(x2,y2,z2,levels=dlevels,extend='both',cmap=plt.cm.RdBu_r,tri=True)
+      plt.colorbar(cf1,ax=ax1,orientation='horizontal')
+      plt.colorbar(cf2,ax=ax2,orientation='horizontal')
+      fig.savefig('%s_%s.png' % (mvar,region),format='png')
+      plt.show()

post_oifs.sh

+#!/bin/bash
+#SBATCH -t 24:00:00
+#SBATCH -N 1
+#SBATCH --cpus-per-task=16
+#SBATCH -p large:shared
+
+sleep_time=2
+max_jobs=16
+
+esteps=(35040 70080 105216 140256 175296)
+
+for ((run=0 ; run<=0 ; run++ ))
+do
+   rrun=$(printf "%03d" $(($run+1)))
+   estep=${esteps[$run]} 
+   fstep=$((${esteps[$(($run-1))]}+24)) 
+   estep=43824
+   fstep=0
+   echo $fstep $estep 
+   
+   OIFS_FIRSTSTEP=$fstep
+   OIFS_LASTSTEP=$estep
+   OIFS_STEP=24 
+   OIFS_OUTDIR=/scratch/usr/shkjocke/esm-experiments/foci5/outdata/oifs/${rrun}/nc4/ 
+   OIFS_INDIR=/scratch/usr/shkjocke/esm-experiments/foci5/outdata/oifs/${rrun}/ 
+   OIFS_EXPID=KCM2
+
+   mkdir -vp $OIFS_OUTDIR
+   echo " starting loop "
+   
+   for ((STEP=${OIFS_FIRSTSTEP}; STEP<=${OIFS_LASTSTEP}; STEP=STEP+${OIFS_STEP} )) ; do
+       # If too many jobs run at the same time, wait                                                                                               
+       while (( $(jobs -p | wc -l) >=  max_jobs )); do sleep $sleep_time;  done
+        (
+            echo "convering "
+            ./ifs2nc_10.sh $STEP $STEP $OIFS_STEP $OIFS_OUTDIR $OIFS_INDIR $OIFS_EXPID
+            echo " Completed $i"
+        ) &
+   done
+   echo "Now I wait..."
+   wait
+
+   echo 'OPENIFS-to-netCDF conversion done' $fstep $estep
+
+done