if variable == 'pr':
# truncate to whole number
rounder = np.rint
downscaling_operation = 'mult'
aoi_mask = aoi_mask_fn
# make AOI_Mask input resolution for computing 95th percentiles...
if aoi_mask_fn is not None:
aoi_mask = Mask( aoi_mask_fn, historical, 1, 0 )
else:
aoi_mask = None
else:
# round to 2 decimals
rounder = partial( np.round, decimals=1 )
downscaling_operation = 'add'
aoi_mask = None
def round_it( x, mask ):
arr = np.ma.masked_array( data=x, mask=mask )
return rounder( arr )
round_data = partial( round_it, mask=( mask==0 ) )
ar5 = downscale.DeltaDownscale( baseline, clim_begin, clim_end, historical, future,
downscaling_operation=downscaling_operation, mask=mask, mask_value=0, ncpus=32,
src_crs={'init':'epsg:4326'}, src_nodata=None, dst_nodata=None,
post_downscale_function=round_data, varname=variable, modelname=modelname, anom=anom,
fix_clim=fix_clim, aoi_mask=aoi_mask )
ar5.downscale( output_dir=output_path )
# SETUP DATASET output_dir = '/workspace/Shared/Tech_Projects/EPSCoR_Southcentral/project_data/test' future_fn = '/workspace/Shared/Tech_Projects/ESGF_Data_Access/project_data/snap_prepped_data/IPSL-CM5A-LR/hur/hur_Amon_IPSL-CM5A-LR_rcp26_r1i1p1_200601_210012.nc' historical_fn = '/workspace/Shared/Tech_Projects/ESGF_Data_Access/project_data/snap_prepped_data/IPSL-CM5A-LR/hur/hur_Amon_IPSL-CM5A-LR_historical_r1i1p1_185001_200512.nc' variable = 'hur' model = 'IPSL-CM5A-LR' scenario = 'rcp26' historical = downscale.Dataset( historical_fn, variable, model, scenario, units=None ) future = downscale.Dataset( future_fn, variable, model, scenario, units=None ) # DOWNSCALE mask = rasterio.open(baseline.filelist[0]).read_masks(1) clim_begin = '1961' clim_end = '1990' ar5 = downscale.DeltaDownscale( baseline, clim_begin, clim_end, historical, future, \ metric='mean', ds_type='absolute', level=1000, level_name='plev' )# add in the mask! ar5.downscale( output_dir=output_dir ) # CRU historical output_dir = '/workspace/Shared/Tech_Projects/ESGF_Data_Access/project_data/test' historical_fn = '/Data/Base_Data/Climate/World/CRU_grids/CRU_TS323/cru_ts3.23.1901.2014.cld.dat.nc' historical = downscale.Dataset( historical_fn, 'cld', 'cru_ts31', 'observed', units=None, interp=True ) clim_begin = '1961' clim_end = '1990' cru = downscale.DeltaDownscale( baseline, clim_begin, clim_end, historical, metric='mean', ds_type='relative' ) cru.downscale( output_dir=output_dir ) # filelist = [ os.path.join(root, fn) for root, subs, files in os.walk(base_dir) if len(files) > 0 for fn in files if variable in fn and scenario in fn and model in fn ]
historical_fn = '/workspace/Shared/Tech_Projects/ESGF_Data_Access/project_data/snap_prepped_data/IPSL-CM5A-LR/hur/hur_Amon_IPSL-CM5A-LR_historical_r1i1p1_185001_200512.nc'
variable = 'hur'
model = 'IPSL-CM5A-LR'
scenario = 'rcp26'
historical = downscale.Dataset(historical_fn,
variable,
model,
scenario,
units=None)
future = downscale.Dataset(future_fn, variable, model, scenario, units=None)
# DOWNSCALE
mask = rasterio.open(baseline.filelist[0]).read_masks(1)
clim_begin = '1961'
clim_end = '1990'
ar5 = downscale.DeltaDownscale( baseline, clim_begin, clim_end, historical, future, \
metric='mean', ds_type='absolute', level=1000, level_name='plev' )# add in the mask!
ar5.downscale(output_dir=output_dir)
# CRU historical
output_dir = '/workspace/Shared/Tech_Projects/ESGF_Data_Access/project_data/test'
historical_fn = '/Data/Base_Data/Climate/World/CRU_grids/CRU_TS323/cru_ts3.23.1901.2014.cld.dat.nc'
historical = downscale.Dataset(historical_fn,
'cld',
'cru_ts31',
'observed',
units=None,
interp=True)
clim_begin = '1961'
clim_end = '1990'
cru = downscale.DeltaDownscale(baseline,
clim_begin,
scenario,
project=project,
units=units)
future = downscale.Dataset(fn,
variable,
model,
scenario,
project=project,
units=units)
# convert from Kelvin to Celcius
if historical:
historical.ds[variable] = historical.ds[variable] - 273.15
historical.ds[variable]['units'] = units
if future:
future.ds[variable] = future.ds[variable] - 273.15
future.ds[variable]['units'] = units
# DOWNSCALE
mask = rasterio.open(baseline.filelist[0]).read_masks(1)
clim_begin = '1961'
clim_end = '1990'
ar5 = downscale.DeltaDownscale( baseline, clim_begin, clim_end, historical, future, \
metric=metric, downscaling_operation='add', mask=mask, mask_value=0, ncpus=32, \
src_crs={'init':'epsg:4326'}, src_nodata=None, dst_nodata=None,
post_downscale_function=None, modelname=modelname ) # -9999.0
ar5.downscale(output_dir=output_path)