end_date = "%02d" % target_month + "%02d" % (int(start_date[-2:]) + 13)
#Define the domain for display
lat_down = config.getint('Plot', 'lat_down')
lat_up = config.getint('Plot', 'lat_up')
lon_left = config.getint('Plot', 'lon_left')
lon_right = config.getint('Plot', 'lon_right')
grid_lat = config.getint('Plot', 'grid_lat')
grid_lon = config.getint('Plot', 'grid_lon')
data_range = [0, days]
title_str = 'TRMM Number of Dry Days Climatology' + '\n' + start_date + '-' + end_date
name_str = plot_dir + 'TRMM_' + start_date + '-' + end_date + '_threshold' + str(
threshold) + '_Climatology_BiWeekly_' + version + '.png'
s2s.plot_processing(trmm_climatology[target_week, :, :], new_lat, new_lon,
lat_down, lat_up, lon_left, lon_right, grid_lat,
grid_lon, data_range, title_str, name_str,
'Climatology')
data_range = [0, days]
title_str = 'TRMM Number of Dry Days Total' + '\n' + str(
target_year) + ' ' + start_date + '-' + end_date
name_str = plot_dir + 'TRMM_' + str(
target_year) + '_' + start_date + '-' + end_date + '_threshold' + str(
threshold) + '_Total_BiWeekly_' + version + '.png'
s2s.plot_processing(
trmm_total[target_week, target_year - start_year, :, :], new_lat,
new_lon, lat_down, lat_up, lon_left, lon_right, grid_lat, grid_lon,
data_range, title_str, name_str, 'Total')
data_range = [-1 * days, days]
title_str = 'TRMM Number of Dry Days Anomaly' + '\n' + str(
#Define the domain for display
lat_down = config.getint('Plot','lat_down')
lat_up = config.getint('Plot','lat_up')
lon_left = config.getint('Plot','lon_left')
lon_right = config.getint('Plot','lon_right')
grid_lat = config.getint('Plot','grid_lat')
grid_lon = config.getint('Plot','grid_lon')
#Plot ECMWF NDD climatology/total/anomaly
for i_step in range(0,lead_times):
start_date = week_initial_date[target_week]
end_date = "%02d"%target_month + "%02d"%(int(start_date[-2:])+6)
data_range = [0,days]
title_str = 'ECMWF NDD Weekly Climatology' + '\n' + start_date + '-' + end_date + ' (LT' + str(i_step+1) + ')'
name_str = plot_dir + 'ECMWF_' + start_date + '-' + end_date + '_' + 'LT' + str(i_step+1) + '_threshold' + str(threshold) + '_Climatology_Weekly.png'
s2s_utility_prec.plot_processing(ec_climatology[i_step,target_week,:,:],ec_lat_weekly,ec_lon_weekly,lat_down,lat_up,lon_left,lon_right,grid_lat,grid_lon,data_range,title_str,name_str,'Climatology')
data_range = [0,days]
title_str = 'ECMWF NDD Weekly Total' + '\n' + str(target_year) + ' ' + start_date + '-' + end_date + ' (LT' + str(i_step+1) + ')'
name_str = plot_dir + 'ECMWF_' + str(target_year) + '_' + start_date + '-' + end_date + '_' + 'LT' + str(i_step+1) + '_threshold' + str(threshold) + '_Total_Weekly.png'
s2s_utility_prec.plot_processing(ec_total_ens_avg[i_step,target_week,target_year-start_year,:,:],ec_lat_weekly,ec_lon_weekly,lat_down,lat_up,lon_left,lon_right,grid_lat,grid_lon,data_range,title_str,name_str,'Total')
data_range = [-1*days,days]
title_str = 'ECMWF NDD Weekly Anomaly' + '\n' + str(target_year) + ' ' + start_date + '-' + end_date + ' (LT' + str(i_step+1) + ')'
name_str = plot_dir + 'ECMWF_' + str(target_year) + '_' + start_date + '-' + end_date + '_' + 'LT' + str(i_step+1) + '_threshold' + str(threshold) + '_Anomaly_Weekly.png'
s2s_utility_prec.plot_processing(ec_anomaly[i_step,target_week,target_year-start_year,:,:],ec_lat_weekly,ec_lon_weekly,lat_down,lat_up,lon_left,lon_right,grid_lat,grid_lon,data_range,title_str,name_str,'Anomaly')
print('Finished!')
lat_up = 30
lon_left = 80
lon_right = 150
grid_lat = 10
grid_lon = 10
#Plot TRMM climatology/average/anomaly
start_date = week_initial_date[target_week]
end_date = start_date[:2] + "%02d" % (int(start_date[-2:]) + 6)
data_range = [0, 18] #change data range for plotting accordingly
title_str = 'TRMM Rainfall Climatology' + '\n' + start_date + '-' + end_date
name_str = 'TRMM_' + start_date + '-' + end_date + '_Climatology.png'
s2s_utility_prec.plot_processing(trmm_climatology[target_week, :, :],
trmm_lat, trmm_lon, lat_down, lat_up,
lon_left, lon_right, grid_lat, grid_lon,
data_range, title_str, name_str,
'Climatology')
data_range = [0, 36]
title_str = 'TRMM Rainfall Average' + '\n' + str(
target_year) + ' ' + start_date + '-' + end_date
name_str = 'TRMM_' + str(
target_year) + '_' + start_date + '-' + end_date + '_Average.png'
s2s_utility_prec.plot_processing(
trmm_average[target_week, target_year - start_year, :, :], trmm_lat,
trmm_lon, lat_down, lat_up, lon_left, lon_right, grid_lat, grid_lon,
data_range, title_str, name_str, 'Average')
data_range = [-10, 10]
title_str = 'TRMM Rainfall Anomaly' + '\n' + str(
s2s_utility_prec.write_ec_data(ec_output,ec_filename,ec_daily,ec_step,ec_week,ec_year,ec_day,ec_member,prec_lat,prec_lon,'Total')
print('File saved! ' + ec_filename + ' to directory ' + ec_output)
ec_filename = 'ECMWF_' + calendar.month_abbr[target_month] + '_threshold' + str(threshold) + '_Climatology_Mask_Weekly.nc'
s2s_utility_prec.write_ec(ec_output,ec_filename,ec_climatology_mask,ec_step,ec_week,ec_year,prec_lat,prec_lon,'Climatology')
print('File saved! ' + ec_filename + ' to directory ' + ec_output)
#---------------------------------------------------------------
# This part is to output and display ECMWF Rainfall percentile mask
#---------------------------------------------------------------
if plot_figure:
#Define the domain for display
lat_down = config.getint('Plot','lat_down')
lat_up = config.getint('Plot','lat_up')
lon_left = config.getint('Plot','lon_left')
lon_right = config.getint('Plot','lon_right')
grid_lat = config.getint('Plot','grid_lat')
grid_lon = config.getint('Plot','grid_lon')
#Plot ECMWF daily Rainfall XXth percentile climatology mask
for i_step in range(0,lead_times):
start_date = week_initial_date[target_week]
end_date = "%02d"%target_month + "%02d"%(int(start_date[-2:])+6)
data_range = [0,10]
title_str = 'ECMWF Daily Rainfall ' + str(threshold) + 'th Percentile' + '\n' + str(start_date) + '-' + str(end_date) + ' (LT' + str(i_step+1) + ')'
name_str = plot_dir + 'ECMWF_' + str(start_date) + '-' + str(end_date) + '_' + 'LT' + str(i_step+1) + '_threshold' + str(threshold) + '_climatology_mask.png'
s2s_utility_prec.plot_processing(ec_climatology_mask[i_step,target_week,:,:],prec_lat,prec_lon,lat_down,lat_up,lon_left,lon_right,grid_lat,grid_lon,data_range,title_str,name_str,'Climatology_Mask')
print('Finished!')