/
cly_bry.py
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/
cly_bry.py
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#!/usr/bin/env python
import iris
import json
import os
import global_attrs
import convert_pp2nc
import numpy as np
import argparse
import datetime
import glob
import cf_units
global entries
global var
# construct input filename
def construct_filename(ens_member,spec):
sfile=indir+'/r'+ens_member+'i1p1f2/v'+global_attrs.data_version+'/'+spec+'/'+spec+'_AmonZ_UKESM1-StratTrop_refD1_r'+ens_member+'i1p1f2_grz_19600101-20190101.nc'
print("reading from "+sfile)
return sfile
ens_member_list=['1','2','3']
var_list=['cly','bry']
stream='AmonZ'
indir='/gws/nopw/j04/ukca_vol2/nlabraham/CCMI2022/upload/CCMI2022/model-output/NCAS-CAMBRIDGE/UKESM1-StratTrop/refD1/mon/atmos/monthly'
odir='/gws/nopw/j04/ukca_vol2/nlabraham/CCMI2022/upload'
json_dir='/home/users/nlabraham/git/ccmi-2022/Tables'
# delete existing attributes to be filled from here
keys=['activity_id','contact','creation_date','data_specs_version','data_version','experiment','experiment_id','forcing_index','frequency','grid','grid_label','initialization_index','institution_id','institution','license','mip_era','nominal_resolution','physics_index','product','realization_index','realm','source','source_id','source_type','sub_experiment','sub_experiment_id','table_id','tracking_id','history','variable_id','variant_label']
# read-in JSON information
json_file='CCMI2022_'+stream+'.json'
with open(json_dir+'/'+json_file) as json_file:
entries=json.load(json_file)
# read-in JSON CV information
json_file='CCMI2022_CV.json'
with open(json_dir+'/'+json_file) as json_file:
CV=json.load(json_file)
for var in var_list:
species=[]
if var == 'cly':
# Cly: do cl2o2 twice as contains 2x Cl
species=['cl','clo','cl2o2','cl2o2','oclo','brcl','hocl','clono2','hcl']
history=' cly='
elif var == 'bry':
# Bry:
species=['br','brcl','brono2','hbr','hobr','bro']
history=' bry='
for ens_member in ens_member_list:
# read-in initial cube
spec=species[0]
print(spec)
cube=iris.load_cube(construct_filename(ens_member,spec))
history=history+spec
cube.attributes['STASH']=str(cube.attributes['STASH'])
for spec in species[1:]:
print(spec)
tcube=iris.load_cube(construct_filename(ens_member,spec))
cube.data=cube.data + tcube.data
history=history+'+'+spec
cube.attributes['STASH']=cube.attributes['STASH']+', '+str(tcube.attributes['STASH'])
# construct suite-id from history attribute
suiteid=[]
for x in cube.attributes['history'].split():
if "u-" in x:
x = [''.join(c for c in s if c not in ",.") for s in x]
x = [s for s in x if s]
x = ''.join(x)
suiteid.append(str(x))
# rename cube information for the required summed field
cube.attributes['in_units']=str(cube.units)
cube.attributes['conversion_factor']=1
# The following should apply to all cubes read-in, take values from json
cube.rename(name=str(entries['variable_entry'][var]['out_name']))
cube.units=str(entries['variable_entry'][var]['units'])
# set standard name, but cope if this won't work so just set long name
try:
cube.standard_name=str(entries['variable_entry'][var]['standard_name'])
except:
pass
cube.long_name=str(entries['variable_entry'][var]['long_name'])
cube.var_name=str(entries['variable_entry'][var]['out_name'])
cube.attributes['missing_value']=cube.data.fill_value
# determine start and end time of data in easy to read format
start_time=str(cube.coord('time').units.num2date(cube.coord('time').bounds[0,0])).split(' ')[0].replace('-','')
end_time=str(cube.coord('time').units.num2date(cube.coord('time').bounds[-1,-1])).split(' ')[0].replace('-','')
# required for metadata
iris_version=str(iris.__version__)
# define global attributes for output file
ga=global_attrs.global_attrs(suiteid, str(cube.var_name), iris_version, CV, member=int(ens_member), table=stream, expt_id=cube.attributes['experiment_id'], grid_label=cube.attributes['grid_label'], source_type=cube.attributes['source_type'], model_name=cube.attributes['source_id'])
# comment that we've summed-up fields and which ones
ga.attrs['history']=ga.attrs['history']+history
for key in keys:
del cube.attributes[key]
# save variable to NetCDF in correct directory
convert_pp2nc.save_field(cube, ga, odir, start_time, end_time)