simple code for loading CCiA CMIP5 data

load_specific_CCiA_data.py

# this is specific to needs outlined in this repo:
# https://github.com/Thomas-Moore-Creative/NCI-CCiA-ARD
import xarray as xr
import numpy as np
import datetime
import intake
NCI_catalog = intake.open_catalog('/g/data/hh5/public/apps/nci-intake-catalogue/catalogue.yaml')
# build CCiA catalog subset
CCiA_catalog = NCI_catalog.esgf.cmip5.search(variable=['psl','pr'],
            realm=['atmos'],
            time_frequency='mon',
            experiment=['rcp85','historical'],
            ensemble=['r1i1p1'],
            model=['ACCESS1.0',
                   'CESM1(CAM5)',
                   'CNRM-CM5',
                   'GFDL-ESM2M',
                   'HadGEM2-CC',
                   'CanESM2',
                   'MIROC5',
                   'NorESM1-M']\
            )
# let's check the models included
CCiA_catalog.unique('model')
# create the dataset dict
CCiA_dataset_dict = CCiA_catalog.to_dataset_dict()
# make a list of all the keys
CCiA_key_list = list(CCiA_dataset_dict.keys())
CCiA_key_list
# define a function to return a CCiA_data_object based on model & experiment & variable
# crudely handle datetime issue across models
def load_CCiA_data(model,experiment,variable):
    key_string_list = [i for i in CCiA_key_list if model in i]
    key_string_list = [i for i in key_string_list if experiment in i]
    key_string = [i for i in key_string_list if variable in i]
    CCiA_data_object = CCiA_dataset_dict[key_string.pop()]
    #check if datetime64 object?
    if not np.issubdtype(CCiA_data_object.time.dtype, np.datetime64):
        CCiA_data_object
        datetimeindex = CCiA_data_object.indexes['time'].to_datetimeindex()
        CCiA_data_object['time'] = datetimeindex
    return CCiA_data_object
# use the function
MIROC5_rcp85_psl_data = load_CCiA_data('MIROC5','rcp85','psl')
MIROC5_rcp85_psl_data