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To plot binary SST, ICEC, mask (within GEOS-ESM)
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| #!/usr/bin/env python | |
| ''' | |
| to plot the SST and SIC boundary conditions (binary files) that are used by the GCM | |
| SA, Jul 2018, Aug 2020, Mar 2022 | |
| ''' | |
| #----------------------------------------------------------------- | |
| import argparse | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| from datetime import datetime | |
| import cartopy.crs as ccrs | |
| import cartopy.feature as cfeature | |
| # read a binary file, uses f2py, see file for compile instructions... change as you may please! | |
| import sys | |
| sys.path.append('/discover/nobackup/sakella/geosMom6/extData/GEOSgcm/install/bin/') | |
| from read_ops_bcs import read_bin_data | |
| #----------------------------------------------------------------- | |
| def file_names(data_path_, date_in): | |
| data_path = data_path_+ '/' | |
| sst_file_ = data_path + 'Ostia_sst_' + date_in.strftime('%Y%m%d') + '.bin' | |
| sic_file_ = data_path + 'Ostia_ice_' + date_in.strftime('%Y%m%d') + '.bin' | |
| mask_file_= data_path + 'mask' + '.bin' | |
| return sst_file_, sic_file_, mask_file_ | |
| #----------------------------------------------------------------- | |
| def main(): | |
| comm_args = parse_args() | |
| data_path = comm_args['data_path'] | |
| year_ = comm_args['year'] | |
| month_ = comm_args['month'] | |
| day_ = comm_args['day'] | |
| date_ = datetime( year_, month_, day_, 00, 0, 0) | |
| [sst_file, sic_file, mask_file] = file_names( data_path, date_) | |
| # read the OPS SST & SIC. Both are of dimension(1440, 2880); see read_ops_bcs.pyf | |
| [date_ofSST, nlon, nlat, lon, lat, sst_] = read_bin_data(sst_file, date_.strftime('%Y%m%d')) # SST is in K | |
| [date_ofSIC, nlon, nlat, lon, lat, sic_] = read_bin_data(sic_file, date_.strftime('%Y%m%d')) # SIC is non-dimensional | |
| [date_ofMask,nlon, nlat, lon, lat, mask_]= read_bin_data(mask_file,date_.strftime('%Y%m%d')) # MASK is non-dimensional | |
| sst_[sst_ == -999.] = np.nan | |
| sic_[sic_ == -999.] = np.nan | |
| #----------------------------------------------------------------- | |
| print('Plotting for [%s] using\n[%s]\n[%s]'%(date_.strftime('%Y%m%d'), sst_file, sic_file)) | |
| # Plot | |
| fig = plt.figure(figsize=(10,6)) | |
| # plot sst | |
| ax1 = plt.subplot(221, projection=ccrs.PlateCarree()) | |
| # ax1 = plt.subplot(221, projection=ccrs.PlateCarree( central_longitude=180)) | |
| # ax1.set_global() | |
| ax1.coastlines() | |
| # ax1.stock_img() | |
| ax1.add_feature(cfeature.LAND, facecolor='white') | |
| # ax1.add_feature(cfeature.LAKES, edgecolor='gray') | |
| im1 = ax1.pcolormesh(lon, lat, sst_, transform=ccrs.PlateCarree(),\ | |
| cmap=plt.cm.jet)#, vmin=270., vmax=310.) | |
| plt.colorbar(im1, pad=0.01, shrink=0.75) | |
| plt.title(r'SST (deg K) for %s'%(date_.strftime('%Y%m%d'))) | |
| plt.axis('off') | |
| # plot sic | |
| ax2 = plt.subplot(222, projection=ccrs.PlateCarree()) | |
| # ax2.set_global() | |
| ax2.coastlines() | |
| ax2.add_feature(cfeature.LAND, facecolor='white') | |
| # ax2.add_feature(cfeature.LAKES, edgecolor='gray') | |
| im2 = ax2.pcolormesh(lon, lat, sic_, transform=ccrs.PlateCarree(),\ | |
| cmap=plt.cm.jet)#, vmin=0.0, vmax=1.0) | |
| plt.colorbar(im2, pad=0.01, shrink=0.75) | |
| plt.title(r'SIC for %s'%(date_.strftime('%Y%m%d'))) | |
| plt.axis('off') | |
| # ----------------------------------------------------------------- | |
| # plot mask | |
| ax3 = plt.subplot(223, projection=ccrs.PlateCarree()) | |
| # ax3.set_extent([-180, 180, 20, 55], ccrs.PlateCarree()) | |
| ax3.coastlines() | |
| ax3.add_feature(cfeature.LAND, facecolor='white') | |
| ax3.add_feature(cfeature.LAKES, edgecolor='gray') | |
| im3 = ax3.pcolormesh(lon, lat, mask_, transform=ccrs.PlateCarree(),\ | |
| cmap=plt.cm.jet)#, vmin=280., vmax=310.) | |
| plt.colorbar(im3, pad=0.01, shrink=0.75) | |
| plt.title(r'Mask (=0 or 1, latter over Great Lakes and Caspian Sea') | |
| plt.axis('off') | |
| # ----------------------------------------------------------------- | |
| ax4 = plt.subplot(224, projection=ccrs.PlateCarree()) | |
| ax4.set_extent([-180, 180, 10, 60], ccrs.PlateCarree()) | |
| ax4.coastlines() | |
| ax4.add_feature(cfeature.LAND, facecolor='white') | |
| ax4.add_feature(cfeature.LAKES, edgecolor='gray') | |
| im4 = ax4.pcolormesh(lon, lat, mask_, transform=ccrs.PlateCarree(),\ | |
| cmap=plt.cm.jet)#, vmin=280., vmax=310.) | |
| plt.colorbar(im4, pad=0.01, shrink=0.75) | |
| plt.title(r' Zoom in mask') | |
| plt.axis('off') | |
| #----------------------------------------------------------------- | |
| fName_fig = 'bcs_SST_SIC_%s'%(date_.strftime('%Y%m%d')) | |
| plt.savefig(fName_fig + '.png', dpi=120) | |
| plt.close('all') | |
| #----------------------------------------------------------------- | |
| def parse_args(): | |
| p = argparse.ArgumentParser(description = \ | |
| 'Script to plot the SST and sea ice concentration used as lower boundary conditions by the GCM') | |
| p.add_argument('-data_path', type=str, help= 'path to the data', default='/discover/nobackup/sakella/lake_mask/') | |
| p.add_argument('-year', type=int, help= 'year', default=2006) | |
| p.add_argument('-month', type=int, help= 'month', default=4) | |
| p.add_argument('-day', type=int, help= 'day', default=1) | |
| return vars(p.parse_args()) | |
| #----------------------------------------------------------------- | |
| if __name__ == '__main__': | |
| main() | |
| #----------------------------------------------------------------- |
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