target_datasets.append(local.load_file(FILE_1, varName, name="KNMI")) target_datasets.append(local.load_file(FILE_2, varName, name="REGCM")) target_datasets.append(local.load_file(FILE_3, varName, name="UCT")) """ Step 2: Fetch an OCW Dataset Object from the data_source.rcmed module """ print( "Working with the rcmed interface to get CRU3.1 Monthly Mean Precipitation" ) # the dataset_id and the parameter id were determined from # https://rcmes.jpl.nasa.gov/content/data-rcmes-database CRU31 = rcmed.parameter_dataset(10, 37, LAT_MIN, LAT_MAX, LON_MIN, LON_MAX, START, END) """ Step 3: Processing Datasets so they are the same shape """ print("Processing datasets ...") CRU31 = dsp.normalize_dataset_datetimes(CRU31, 'monthly') print("... on units") CRU31 = dsp.water_flux_unit_conversion(CRU31) for member, each_target_dataset in enumerate(target_datasets): target_datasets[member] = dsp.subset(target_datasets[member], EVAL_BOUNDS) target_datasets[member] = dsp.water_flux_unit_conversion( target_datasets[member]) target_datasets[member] = dsp.normalize_dataset_datetimes( target_datasets[member], 'monthly') print("... spatial regridding") new_lats = np.arange(LAT_MIN, LAT_MAX, gridLatStep) new_lons = np.arange(LON_MIN, LON_MAX, gridLonStep) CRU31 = dsp.spatial_regrid(CRU31, new_lats, new_lons) for member, each_target_dataset in enumerate(target_datasets): target_datasets[member] = dsp.spatial_regrid(target_datasets[member],
target_datasets.append(local.load_file(FILE_1, varName, name="KNMI")) target_datasets.append(local.load_file(FILE_2, varName, name="REGCM")) target_datasets.append(local.load_file(FILE_3, varName, name="UCT")) """ Step 2: Fetch an OCW Dataset Object from the data_source.rcmed module """ print("Working with the rcmed interface to get CRU3.1 Daily Precipitation") # the dataset_id and the parameter id were determined from # https://rcmes.jpl.nasa.gov/content/data-rcmes-database CRU31 = rcmed.parameter_dataset( 10, 37, LAT_MIN, LAT_MAX, LON_MIN, LON_MAX, START, END) """ Step 3: Processing datasets so they are the same shape ... """ print("Processing datasets so they are the same shape") CRU31 = dsp.water_flux_unit_conversion(CRU31) CRU31 = dsp.normalize_dataset_datetimes(CRU31, 'monthly') for member, each_target_dataset in enumerate(target_datasets): target_datasets[member] = dsp.subset(target_datasets[member], EVAL_BOUNDS) target_datasets[member] = dsp.water_flux_unit_conversion(target_datasets[ member]) target_datasets[member] = dsp.normalize_dataset_datetimes( target_datasets[member], 'monthly') print("... spatial regridding") new_lats = np.arange(LAT_MIN, LAT_MAX, gridLatStep) new_lons = np.arange(LON_MIN, LON_MAX, gridLonStep) CRU31 = dsp.spatial_regrid(CRU31, new_lats, new_lons)