climatemeans.py

import iris
from braceexpand import braceexpand
import iris.analysis
import os
import iris.analysis.cartography

in_dir_base='/home/williamsjh/cylc-run/'
runid='bc048'

whoami='williamsjh'

project='niwa00013'

out_dir='/nesi/nobackup/'+project+'/'+whoami+'/esmeval/user_data/'+whoami+'/model_data/u-'+runid

print('out_dir = ')
print(out_dir)

in_dir=in_dir_base+'u-'+runid+'/share/data/History_Data/'

firstyear=1960

nyears=20

if not os.path.exists(out_dir+'/supermeans'):
    os.makedirs(out_dir+'/supermeans')

if nyears == 2:
    supermeanlabel = '2'

if nyears == 10:
    supermeanlabel = 'a'

if nyears == 20:
    supermeanlabel = 'k'

if nyears == 2:
    supermeanlabel = '2'

if nyears >= 30 and nyears <40:
    supermeanlabel = 't'

if nyears >= 50 and nyears <100:
    supermeanlabel = 'l'

fnames = list(braceexpand(in_dir+'*pm*{196[0-9],197[0-9]}*{mar,apr,may}*'))

period = 'mam'

print(fnames)

_vars = iris.load(fnames)

#_varsmean = _vars.collapsed('time',iris.analysis.MEAN)

#iris.save(_varsmean,out_dir+'/supermeans'+'/'+runid+'a.m'+supermeanlabel+str(year)+period+'.pp')
        # the m in the previous line is the 'mean' indicator, not to be
        # confused with the 'm for monthly' in the input files!