/
Hist_Line_Graph_TasMIN_Yearly.py
2359 lines (2020 loc) · 141 KB
/
Hist_Line_Graph_TasMIN_Yearly.py
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"""
Created on Wednesday August 2 2017
@author: s0899345
"""
import matplotlib.pyplot as plt
import iris
import iris.coord_categorisation as iriscc
import iris.plot as iplt
import iris.quickplot as qplt
import iris.analysis.cartography
import numpy as np
from cf_units import Unit
#this file is split into parts as follows:
#PART 1: load and format all models
#PART 2: load and format observed data
#PART 3: format files to be plot specific
#PART 4: plot data
def main():
#-------------------------------------------------------------------------
#PART 1: LOAD and FORMAT ALL MODELS
#bring in all the ERAINT models we need and give them a name
CCCma = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/ERAINT/1979-2012/tasmin_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_CCCma-CanRCM4_r2_mon_198901-200912.nc'
CLMcom = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/ERAINT/1979-2012/tasmin_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_CLMcom-CCLM4-8-17_v1_mon_198901-200812.nc'
DMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/ERAINT/1979-2012/tasmin_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_DMI-HIRHAM5_v2_mon_198901-201012.nc'
KNMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/ERAINT/1979-2012/tasmin_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_KNMI-RACMO22T_v1_mon_197901-201212.nc'
MPIE = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/ERAINT/1979-2012/tasmin_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_MPI-CSC-REMO2009_v1_mon_198902-200812.nc'
SMHI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/ERAINT/1979-2012/tasmin_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_SMHI-RCA4_v1_mon_198001-201012.nc'
#bring in all the CORDEX RCM models we need and give them a name
CCCmaCanRCM= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_CCCma-CanESM2_historical_r1i1p1_CCCma-CanRCM4_r2_mon_195001-200512.nc'
CCCmaSMHI= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_CCCma-CanESM2_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
CNRM= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_CNRM-CERFACS-CNRM-CM5_historical_r1i1p1_CLMcom-CCLM4-8-17_v1_mon_195001-200512.nc'
CNRMSMHI= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_CNRM-CERFACS-CNRM-CM5_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
CSIRO = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_CSIRO-QCCCE-CSIRO-Mk3-6-0_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
ICHECDMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_ICHEC-EC-EARTH_historical_r3i1p1_DMI-HIRHAM5_v2_mon_195101-200512.nc'
ICHECCCLM = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_ICHEC-EC-EARTH_historical_r12i1p1_CLMcom-CCLM4-8-17_v1_mon_194912-200512.nc'
ICHECKNMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_ICHEC-EC-EARTH_historical_r12i1p1_KNMI-RACMO22T_v1_mon_195001-200512.nc'
ICHECMPI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_ICHEC-EC-EARTH_historical_r12i1p1_MPI-CSC-REMO2009_v1_mon_195001-200512.nc'
ICHECSMHI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_ICHEC-EC-EARTH_historical_r12i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
IPSL = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_IPSL-IPSL-CM5A-MR_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
MIROC = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MIROC-MIROC5_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
MOHCCCLM = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MOHC-HadGEM2-ES_historical_r1i1p1_CLMcom-CCLM4-8-17_v1_mon_194912-200512.nc'
MOHCKNMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MOHC-HadGEM2-ES_historical_r1i1p1_KNMI-RACMO22T_v2_mon_195001-200512.nc'
MOHCSMHI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MOHC-HadGEM2-ES_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
MPICCLM = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MPI-M-MPI-ESM-LR_historical_r1i1p1_CLMcom-CCLM4-8-17_v1_mon_194912-200512.nc'
MPIREMO = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MPI-M-MPI-ESM-LR_historical_r1i1p1_MPI-CSC-REMO2009_v1_mon_195001-200512.nc'
MPISMHI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_MPI-M-MPI-ESM-LR_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
NCCDMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_NCC-NorESM1-M_historical_r1i1p1_DMI-HIRHAM5_v1_mon_195101-200512.nc'
NCCSMHI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_NCC-NorESM1-M_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
NOAA = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_tasmin/Historical/1950-2005/tasmin_AFR-44_NOAA-GFDL-GFDL-ESM2M_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
#bring in all the GCM models we need and give them a name
CanESM2= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_CanESM2_historical_r1i1p1_185001-200512.nc'
CNRMG= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_CNRM-CM5-2_historical_r1i1p1_195001-200512.nc'
MK3 = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_CSIRO-Mk3-6-0_historical_r1i1p1_185001-200512.nc'
EARTH= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_EC-EARTH_historical_r12i1p1_195001-201212.nc'
EARTH3= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_EC-EARTH_historical+r3i1p1_1961-2005.nc'
GFDL='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_GFDL-ESM2M_historical_r1i1p1_194601-200512.nc'
HadGEM2='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_HadGEM2-ES_historical_r1i1p1_193412-200511.nc'
IPSLG='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_IPSL-CM5B-LR_historical_r1i1p1_185001-200512.nc'
MIROCG='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_MIROC5_historical_r1i1p1_185001-201212.nc'
MPI='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_MPI-ESM-MR_historical_r1i1p1_185001-200512.nc'
NorESM1='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/tasmin_Amon_NorESM1-M_historical_r1i1p1_185001-200512.nc'
#Load exactly one cube from given file
CCCma = iris.load_cube(CCCma)
CLMcom = iris.load_cube(CLMcom)
DMI = iris.load_cube(DMI, 'air_temperature')
KNMI = iris.load_cube(KNMI)
MPIE = iris.load_cube(MPIE)
SMHI = iris.load_cube(SMHI)
CCCmaCanRCM = iris.load_cube(CCCmaCanRCM)
CCCmaSMHI = iris.load_cube(CCCmaSMHI)
CNRM = iris.load_cube(CNRM)
CNRMSMHI = iris.load_cube(CNRMSMHI)
CSIRO = iris.load_cube(CSIRO)
ICHECDMI = iris.load_cube(ICHECDMI, 'air_temperature')
ICHECCCLM = iris.load_cube(ICHECCCLM)
ICHECKNMI = iris.load_cube(ICHECKNMI)
ICHECMPI = iris.load_cube(ICHECMPI)
ICHECSMHI = iris.load_cube(ICHECSMHI)
IPSL = iris.load_cube(IPSL)
MIROC = iris.load_cube(MIROC)
MOHCCCLM = iris.load_cube(MOHCCCLM)
MOHCKNMI = iris.load_cube(MOHCKNMI)
MOHCSMHI = iris.load_cube(MOHCSMHI)
MPICCLM = iris.load_cube(MPICCLM)
MPIREMO = iris.load_cube(MPIREMO)
MPISMHI = iris.load_cube(MPISMHI)
NCCDMI = iris.load_cube(NCCDMI, 'air_temperature')
NCCSMHI = iris.load_cube(NCCSMHI)
NOAA = iris.load_cube(NOAA)
CanESM2 = iris.load_cube(CanESM2)
CNRMG = iris.load_cube(CNRMG)
MK3 = iris.load_cube(MK3)
EARTH = iris.load_cube(EARTH)
EARTH3 = iris.load_cube(EARTH3)
GFDL = iris.load_cube(GFDL, 'air_temperature')
HadGEM2 = iris.load_cube(HadGEM2)
IPSLG = iris.load_cube(IPSLG)
MIROCG = iris.load_cube(MIROCG)
MPI = iris.load_cube(MPI)
NorESM1 = iris.load_cube(NorESM1)
#remove flat latitude and longitude and only use grid latitude and grid longitude to make consistent with the observed data, also make sure all of the longitudes are monotonic. This is only applicable to the ERAINT and CORDEX Models as the Observed data and GCMs are already in standard linear format.
lats = iris.coords.DimCoord(CCCma.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CCCma.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CCCma.remove_coord('latitude')
CCCma.remove_coord('longitude')
CCCma.remove_coord('grid_latitude')
CCCma.remove_coord('grid_longitude')
CCCma.add_dim_coord(lats, 1)
CCCma.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(CLMcom.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CLMcom.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CLMcom.remove_coord('latitude')
CLMcom.remove_coord('longitude')
CLMcom.remove_coord('grid_latitude')
CLMcom.remove_coord('grid_longitude')
CLMcom.add_dim_coord(lats, 1)
CLMcom.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(DMI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = DMI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
DMI.remove_coord('latitude')
DMI.remove_coord('longitude')
DMI.remove_coord('grid_latitude')
DMI.remove_coord('grid_longitude')
DMI.add_dim_coord(lats, 1)
DMI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(KNMI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = KNMI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
KNMI.remove_coord('latitude')
KNMI.remove_coord('longitude')
KNMI.remove_coord('grid_latitude')
KNMI.remove_coord('grid_longitude')
KNMI.add_dim_coord(lats, 1)
KNMI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MPIE.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MPIE.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MPIE.remove_coord('latitude')
MPIE.remove_coord('longitude')
MPIE.remove_coord('grid_latitude')
MPIE.remove_coord('grid_longitude')
MPIE.add_dim_coord(lats, 1)
MPIE.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(SMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = SMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
SMHI.remove_coord('latitude')
SMHI.remove_coord('longitude')
SMHI.remove_coord('grid_latitude')
SMHI.remove_coord('grid_longitude')
SMHI.add_dim_coord(lats, 1)
SMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(CCCmaCanRCM.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CCCmaCanRCM.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CCCmaCanRCM.remove_coord('latitude')
CCCmaCanRCM.remove_coord('longitude')
CCCmaCanRCM.remove_coord('grid_latitude')
CCCmaCanRCM.remove_coord('grid_longitude')
CCCmaCanRCM.add_dim_coord(lats, 1)
CCCmaCanRCM.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(CCCmaSMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CCCmaSMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CCCmaSMHI.remove_coord('latitude')
CCCmaSMHI.remove_coord('longitude')
CCCmaSMHI.remove_coord('grid_latitude')
CCCmaSMHI.remove_coord('grid_longitude')
CCCmaSMHI.add_dim_coord(lats, 1)
CCCmaSMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(CNRM.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CNRM.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CNRM.remove_coord('latitude')
CNRM.remove_coord('longitude')
CNRM.remove_coord('grid_latitude')
CNRM.remove_coord('grid_longitude')
CNRM.add_dim_coord(lats, 1)
CNRM.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(CNRMSMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CNRMSMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CNRMSMHI.remove_coord('latitude')
CNRMSMHI.remove_coord('longitude')
CNRMSMHI.remove_coord('grid_latitude')
CNRMSMHI.remove_coord('grid_longitude')
CNRMSMHI.add_dim_coord(lats, 1)
CNRMSMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(CSIRO.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = CSIRO.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
CSIRO.remove_coord('latitude')
CSIRO.remove_coord('longitude')
CSIRO.remove_coord('grid_latitude')
CSIRO.remove_coord('grid_longitude')
CSIRO.add_dim_coord(lats, 1)
CSIRO.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(ICHECDMI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = ICHECDMI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
ICHECDMI.remove_coord('latitude')
ICHECDMI.remove_coord('longitude')
ICHECDMI.remove_coord('grid_latitude')
ICHECDMI.remove_coord('grid_longitude')
ICHECDMI.add_dim_coord(lats, 1)
ICHECDMI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(ICHECCCLM.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = ICHECCCLM.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
ICHECCCLM.remove_coord('latitude')
ICHECCCLM.remove_coord('longitude')
ICHECCCLM.remove_coord('grid_latitude')
ICHECCCLM.remove_coord('grid_longitude')
ICHECCCLM.add_dim_coord(lats, 1)
ICHECCCLM.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(ICHECKNMI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = ICHECKNMI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
ICHECKNMI.remove_coord('latitude')
ICHECKNMI.remove_coord('longitude')
ICHECKNMI.remove_coord('grid_latitude')
ICHECKNMI.remove_coord('grid_longitude')
ICHECKNMI.add_dim_coord(lats, 1)
ICHECKNMI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(ICHECMPI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = ICHECMPI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
ICHECMPI.remove_coord('latitude')
ICHECMPI.remove_coord('longitude')
ICHECMPI.remove_coord('grid_latitude')
ICHECMPI.remove_coord('grid_longitude')
ICHECMPI.add_dim_coord(lats, 1)
ICHECMPI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(ICHECSMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = ICHECSMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
ICHECSMHI.remove_coord('latitude')
ICHECSMHI.remove_coord('longitude')
ICHECSMHI.remove_coord('grid_latitude')
ICHECSMHI.remove_coord('grid_longitude')
ICHECSMHI.add_dim_coord(lats, 1)
ICHECSMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(IPSL.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = IPSL.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
IPSL.remove_coord('latitude')
IPSL.remove_coord('longitude')
IPSL.remove_coord('grid_latitude')
IPSL.remove_coord('grid_longitude')
IPSL.add_dim_coord(lats, 1)
IPSL.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MIROC.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MIROC.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MIROC.remove_coord('latitude')
MIROC.remove_coord('longitude')
MIROC.remove_coord('grid_latitude')
MIROC.remove_coord('grid_longitude')
MIROC.add_dim_coord(lats, 1)
MIROC.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MOHCCCLM.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MOHCCCLM.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MOHCCCLM.remove_coord('latitude')
MOHCCCLM.remove_coord('longitude')
MOHCCCLM.remove_coord('grid_latitude')
MOHCCCLM.remove_coord('grid_longitude')
MOHCCCLM.add_dim_coord(lats, 1)
MOHCCCLM.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MOHCKNMI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MOHCKNMI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MOHCKNMI.remove_coord('latitude')
MOHCKNMI.remove_coord('longitude')
MOHCKNMI.remove_coord('grid_latitude')
MOHCKNMI.remove_coord('grid_longitude')
MOHCKNMI.add_dim_coord(lats, 1)
MOHCKNMI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MOHCSMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MOHCSMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MOHCSMHI.remove_coord('latitude')
MOHCSMHI.remove_coord('longitude')
MOHCSMHI.remove_coord('grid_latitude')
MOHCSMHI.remove_coord('grid_longitude')
MOHCSMHI.add_dim_coord(lats, 1)
MOHCSMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MPICCLM.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MPICCLM.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MPICCLM.remove_coord('latitude')
MPICCLM.remove_coord('longitude')
MPICCLM.remove_coord('grid_latitude')
MPICCLM.remove_coord('grid_longitude')
MPICCLM.add_dim_coord(lats, 1)
MPICCLM.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MPIREMO.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MPIREMO.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MPIREMO.remove_coord('latitude')
MPIREMO.remove_coord('longitude')
MPIREMO.remove_coord('grid_latitude')
MPIREMO.remove_coord('grid_longitude')
MPIREMO.add_dim_coord(lats, 1)
MPIREMO.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(MPISMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = MPISMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
MPISMHI.remove_coord('latitude')
MPISMHI.remove_coord('longitude')
MPISMHI.remove_coord('grid_latitude')
MPISMHI.remove_coord('grid_longitude')
MPISMHI.add_dim_coord(lats, 1)
MPISMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(NCCDMI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = NCCDMI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
NCCDMI.remove_coord('latitude')
NCCDMI.remove_coord('longitude')
NCCDMI.remove_coord('grid_latitude')
NCCDMI.remove_coord('grid_longitude')
NCCDMI.add_dim_coord(lats, 1)
NCCDMI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(NCCSMHI.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = NCCSMHI.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
NCCSMHI.remove_coord('latitude')
NCCSMHI.remove_coord('longitude')
NCCSMHI.remove_coord('grid_latitude')
NCCSMHI.remove_coord('grid_longitude')
NCCSMHI.add_dim_coord(lats, 1)
NCCSMHI.add_dim_coord(lons, 2)
lats = iris.coords.DimCoord(NOAA.coord('latitude').points[:,0], standard_name='latitude', units='degrees')
lons = NOAA.coord('longitude').points[0]
for i in range(len(lons)):
if lons[i]>100.:
lons[i] = lons[i]-360.
lons = iris.coords.DimCoord(lons, standard_name='longitude', units='degrees')
NOAA.remove_coord('latitude')
NOAA.remove_coord('longitude')
NOAA.remove_coord('grid_latitude')
NOAA.remove_coord('grid_longitude')
NOAA.add_dim_coord(lats, 1)
NOAA.add_dim_coord(lons, 2)
#-------------------------------------------------------------------------
#PART 2: OBSERVED DATA
#bring in all the files we need and give them a name
CRU= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/Actual_Data/cru_ts4.01.1901.2016.tmn.dat.nc'
#Load exactly one cube from given file
CRU = iris.load_cube(CRU, 'near-surface temperature minimum')
#-------------------------------------------------------------------------
#PART 3: FORMAT DATA TO BE PLOT SPECIFIC
#regrid all models to have same latitude and longitude system, all regridded to model with lowest resolution
CCCma = CCCma.regrid(CanESM2, iris.analysis.Linear())
CLMcom =CLMcom.regrid(CanESM2, iris.analysis.Linear())
DMI=DMI.regrid(CanESM2, iris.analysis.Linear())
KNMI=KNMI.regrid(CanESM2, iris.analysis.Linear())
MPIE=MPIE.regrid(CanESM2, iris.analysis.Linear())
SMHI=SMHI.regrid(CanESM2, iris.analysis.Linear())
CCCmaCanRCM = CCCmaCanRCM.regrid(CanESM2, iris.analysis.Linear())
CCCmaSMHI = CCCmaSMHI.regrid(CanESM2, iris.analysis.Linear())
CNRM =CNRM.regrid(CanESM2, iris.analysis.Linear())
CNRMSMHI =CNRMSMHI.regrid(CanESM2, iris.analysis.Linear())
CSIRO=CSIRO.regrid(CanESM2, iris.analysis.Linear())
ICHECDMI=ICHECDMI.regrid(CanESM2, iris.analysis.Linear())
ICHECCCLM=ICHECCCLM.regrid(CanESM2, iris.analysis.Linear())
ICHECKNMI=ICHECKNMI.regrid(CanESM2, iris.analysis.Linear())
ICHECMPI=ICHECMPI.regrid(CanESM2, iris.analysis.Linear())
ICHECSMHI=ICHECSMHI.regrid(CanESM2, iris.analysis.Linear())
IPSL=IPSL.regrid(CanESM2, iris.analysis.Linear())
MIROC=MIROC.regrid(CanESM2, iris.analysis.Linear())
MOHCCCLM=MOHCCCLM.regrid(CanESM2, iris.analysis.Linear())
MOHCKNMI=MOHCKNMI.regrid(CanESM2, iris.analysis.Linear())
MOHCSMHI=MOHCSMHI.regrid(CanESM2, iris.analysis.Linear())
MPICCLM=MPICCLM.regrid(CanESM2, iris.analysis.Linear())
MPIREMO=MPIREMO.regrid(CanESM2, iris.analysis.Linear())
MPISMHI=MPISMHI.regrid(CanESM2, iris.analysis.Linear())
NCCDMI=NCCDMI.regrid(CanESM2, iris.analysis.Linear())
NCCSMHI=NCCSMHI.regrid(CanESM2, iris.analysis.Linear())
NOAA=NOAA.regrid(CanESM2, iris.analysis.Linear())
#CanESM2 = CanESM2.regrid(CanESM2, iris.analysis.Linear())
CNRMG =CNRMG.regrid(CanESM2, iris.analysis.Linear())
MK3 =MK3.regrid(CanESM2, iris.analysis.Linear())
EARTH =EARTH.regrid(CanESM2, iris.analysis.Linear())
EARTH3 =EARTH3.regrid(CanESM2, iris.analysis.Linear())
GFDL=GFDL.regrid(CanESM2, iris.analysis.Linear())
HadGEM2=HadGEM2.regrid(CanESM2, iris.analysis.Linear())
IPSLG=IPSLG.regrid(CanESM2, iris.analysis.Linear())
MIROCG=MIROCG.regrid(CanESM2, iris.analysis.Linear())
MPI=MPI.regrid(CanESM2, iris.analysis.Linear())
NorESM1=NorESM1.regrid(CanESM2, iris.analysis.Linear())
CRU = CRU.regrid(CanESM2, iris.analysis.Linear())
#we are only interested in the latitude and longitude relevant to Malawi (has to be slightly larger than country boundary to take into account resolution of GCMs)
Malawi = iris.Constraint(longitude=lambda v: 32.0 <= v <= 36., latitude=lambda v: -17. <= v <= -8.)
CCCma = CCCma.extract(Malawi)
CLMcom =CLMcom.extract(Malawi)
DMI=DMI.extract(Malawi)
KNMI=KNMI.extract(Malawi)
MPIE=MPIE.extract(Malawi)
SMHI=SMHI.extract(Malawi)
CCCmaCanRCM = CCCmaCanRCM.extract(Malawi)
CCCmaSMHI = CCCmaSMHI.extract(Malawi)
CNRM =CNRM.extract(Malawi)
CNRMSMHI =CNRMSMHI.extract(Malawi)
CSIRO=CSIRO.extract(Malawi)
ICHECDMI=ICHECDMI.extract(Malawi)
ICHECCCLM=ICHECCCLM.extract(Malawi)
ICHECKNMI=ICHECKNMI.extract(Malawi)
ICHECMPI=ICHECMPI.extract(Malawi)
ICHECSMHI=ICHECSMHI.extract(Malawi)
IPSL=IPSL.extract(Malawi)
MIROC=MIROC.extract(Malawi)
MOHCCCLM=MOHCCCLM.extract(Malawi)
MOHCKNMI=MOHCKNMI.extract(Malawi)
MOHCSMHI=MOHCSMHI.extract(Malawi)
MPICCLM=MPICCLM.extract(Malawi)
MPIREMO=MPIREMO.extract(Malawi)
MPISMHI=MPISMHI.extract(Malawi)
NCCDMI=NCCDMI.extract(Malawi)
NCCSMHI=NCCSMHI.extract(Malawi)
NOAA=NOAA.extract(Malawi)
CanESM2 = CanESM2.extract(Malawi)
CNRMG =CNRMG.extract(Malawi)
MK3 =MK3.extract(Malawi)
EARTH =EARTH.extract(Malawi)
EARTH3 =EARTH3.extract(Malawi)
GFDL=GFDL.extract(Malawi)
HadGEM2=HadGEM2.extract(Malawi)
IPSLG=IPSLG.extract(Malawi)
MIROCG=MIROCG.extract(Malawi)
MPI=MPI.extract(Malawi)
NorESM1=NorESM1.extract(Malawi)
CRU = CRU.extract(Malawi)
#time constraignt to make all series the same, for ERAINT this is 1990-2008 and for RCMs and GCMs this is 1961-2005
iris.FUTURE.cell_datetime_objects = True
t_constraint_ERAINT = iris.Constraint(time=lambda cell: 1990 <= cell.point.year <= 2008)
CCCma = CCCma.extract(t_constraint_ERAINT)
CLMcom =CLMcom.extract(t_constraint_ERAINT)
DMI=DMI.extract(t_constraint_ERAINT)
KNMI=KNMI.extract(t_constraint_ERAINT)
MPIE=MPIE.extract(t_constraint_ERAINT)
SMHI=SMHI.extract(t_constraint_ERAINT)
CRUE = CRU.extract(t_constraint_ERAINT)
t_constraint = iris.Constraint(time=lambda cell: 1961 <= cell.point.year <= 2005)
CCCmaCanRCM = CCCmaCanRCM.extract(t_constraint)
CCCmaSMHI = CCCmaSMHI.extract(t_constraint)
CNRM =CNRM.extract(t_constraint)
CNRMSMHI =CNRMSMHI.extract(t_constraint)
CSIRO=CSIRO.extract(t_constraint)
ICHECDMI=ICHECDMI.extract(t_constraint)
ICHECCCLM=ICHECCCLM.extract(t_constraint)
ICHECKNMI=ICHECKNMI.extract(t_constraint)
ICHECMPI=ICHECMPI.extract(t_constraint)
ICHECSMHI=ICHECSMHI.extract(t_constraint)
IPSL=IPSL.extract(t_constraint)
MIROC=MIROC.extract(t_constraint)
MOHCCCLM=MOHCCCLM.extract(t_constraint)
MOHCKNMI=MOHCKNMI.extract(t_constraint)
MOHCSMHI=MOHCSMHI.extract(t_constraint)
MPICCLM=MPICCLM.extract(t_constraint)
MPIREMO=MPIREMO.extract(t_constraint)
MPISMHI=MPISMHI.extract(t_constraint)
NCCDMI=NCCDMI.extract(t_constraint)
NCCSMHI=NCCSMHI.extract(t_constraint)
NOAA=NOAA.extract(t_constraint)
CanESM2 = CanESM2.extract(t_constraint)
CNRMG =CNRMG.extract(t_constraint)
MK3 =MK3.extract(t_constraint)
EARTH =EARTH.extract(t_constraint)
EARTH3 =EARTH3.extract(t_constraint)
GFDL=GFDL.extract(t_constraint)
HadGEM2=HadGEM2.extract(t_constraint)
IPSLG=IPSLG.extract(t_constraint)
MIROCG=MIROCG.extract(t_constraint)
MPI=MPI.extract(t_constraint)
NorESM1=NorESM1.extract(t_constraint)
CRU = CRU.extract(t_constraint)
#Convert units to match, CORDEX data is in Kelvin but Observed data in Celsius, we would like to show all data in Celsius
CCCma.convert_units('Celsius')
CLMcom.convert_units('Celsius')
DMI.convert_units('Celsius')
KNMI.convert_units('Celsius')
MPIE.convert_units('Celsius')
SMHI.convert_units('Celsius')
CCCmaCanRCM.convert_units('Celsius')
CCCmaSMHI.convert_units('Celsius')
CNRM.convert_units('Celsius')
CNRMSMHI.convert_units('Celsius')
CSIRO.convert_units('Celsius')
ICHECDMI.convert_units('Celsius')
ICHECCCLM.convert_units('Celsius')
ICHECKNMI.convert_units('Celsius')
ICHECMPI.convert_units('Celsius')
ICHECSMHI.convert_units('Celsius')
IPSL.convert_units('Celsius')
MIROC.convert_units('Celsius')
MOHCCCLM.convert_units('Celsius')
MOHCKNMI.convert_units('Celsius')
MOHCSMHI.convert_units('Celsius')
MPICCLM.convert_units('Celsius')
MPIREMO.convert_units('Celsius')
MPISMHI.convert_units('Celsius')
NCCDMI.convert_units('Celsius')
NCCSMHI.convert_units('Celsius')
NOAA.convert_units('Celsius')
CanESM2.convert_units('Celsius')
CNRMG.convert_units('Celsius')
MK3.convert_units('Celsius')
EARTH.convert_units('Celsius')
EARTH3.units = Unit('Celsius') #this fixes EARTH3 which has no units defined
EARTH3=EARTH3-273 #this converts the data manually from Kelvin to Celsius
GFDL.convert_units('Celsius')
HadGEM2.convert_units('Celsius')
IPSLG.convert_units('Celsius')
MIROCG.convert_units('Celsius')
MPI.convert_units('Celsius')
NorESM1.convert_units('Celsius')
#limit to a season
SON = iris.Constraint(season='son')
DJF = iris.Constraint(season='djf')
MAM = iris.Constraint(season='mam')
JJA = iris.Constraint(season='jja')
#add season data to files
iriscc.add_season(CCCma, 'time')
iriscc.add_season(CLMcom, 'time')
iriscc.add_season(DMI, 'time')
iriscc.add_season(KNMI, 'time')
iriscc.add_season(MPIE, 'time')
iriscc.add_season(SMHI, 'time')
iriscc.add_season(CCCmaCanRCM, 'time')
iriscc.add_season(CCCmaSMHI, 'time')
iriscc.add_season(CNRM, 'time')
iriscc.add_season(CNRMSMHI, 'time')
iriscc.add_season(CSIRO, 'time')
iriscc.add_season(ICHECDMI, 'time')
iriscc.add_season(ICHECCCLM, 'time')
iriscc.add_season(ICHECKNMI, 'time')
iriscc.add_season(ICHECMPI, 'time')
iriscc.add_season(ICHECSMHI, 'time')
iriscc.add_season(IPSL, 'time')
iriscc.add_season(MIROC, 'time')
iriscc.add_season(MOHCCCLM, 'time')
iriscc.add_season(MOHCKNMI, 'time')
iriscc.add_season(MOHCSMHI, 'time')
iriscc.add_season(MPICCLM, 'time')
iriscc.add_season(MPIREMO, 'time')
iriscc.add_season(MPISMHI, 'time')
iriscc.add_season(NCCDMI, 'time')
iriscc.add_season(NCCSMHI, 'time')
iriscc.add_season(NOAA, 'time')
iriscc.add_season(CanESM2, 'time')
iriscc.add_season(CNRMG, 'time')
iriscc.add_season(MK3, 'time')
iriscc.add_season(EARTH, 'time')
iriscc.add_season(EARTH3, 'time')
iriscc.add_season(GFDL, 'time')
iriscc.add_season(HadGEM2, 'time')
iriscc.add_season(IPSLG, 'time')
iriscc.add_season(MIROCG, 'time')
iriscc.add_season(MPI, 'time')
iriscc.add_season(NorESM1, 'time')
iriscc.add_season(CRUE, 'time')
iriscc.add_season(CRU, 'time')
#add year data to files
iriscc.add_year(CCCma, 'time')
iriscc.add_year(CLMcom, 'time')
iriscc.add_year(DMI, 'time')
iriscc.add_year(KNMI, 'time')
iriscc.add_year(MPIE, 'time')
iriscc.add_year(SMHI, 'time')
iriscc.add_year(CCCmaCanRCM, 'time')
iriscc.add_year(CCCmaSMHI, 'time')
iriscc.add_year(CNRM, 'time')
iriscc.add_year(CNRMSMHI, 'time')
iriscc.add_year(CSIRO, 'time')
iriscc.add_year(ICHECDMI, 'time')
iriscc.add_year(ICHECCCLM, 'time')
iriscc.add_year(ICHECKNMI, 'time')
iriscc.add_year(ICHECMPI, 'time')
iriscc.add_year(ICHECSMHI, 'time')
iriscc.add_year(IPSL, 'time')
iriscc.add_year(MIROC, 'time')
iriscc.add_year(MOHCCCLM, 'time')
iriscc.add_year(MOHCKNMI, 'time')
iriscc.add_year(MOHCSMHI, 'time')
iriscc.add_year(MPICCLM, 'time')
iriscc.add_year(MPIREMO, 'time')
iriscc.add_year(MPISMHI, 'time')
iriscc.add_year(NCCDMI, 'time')
iriscc.add_year(NCCSMHI, 'time')
iriscc.add_year(NOAA, 'time')
iriscc.add_year(CanESM2, 'time')
iriscc.add_year(CNRMG, 'time')
iriscc.add_year(MK3, 'time')
iriscc.add_year(EARTH, 'time')
iriscc.add_year(EARTH3, 'time')
iriscc.add_year(GFDL, 'time')
iriscc.add_year(HadGEM2, 'time')
iriscc.add_year(IPSLG, 'time')
iriscc.add_year(MIROCG, 'time')
iriscc.add_year(MPI, 'time')
iriscc.add_year(NorESM1, 'time')
iriscc.add_year(CRUE, 'time')
iriscc.add_year(CRU, 'time')
#extract only the season we are interested in
CCCmaSON = CCCma.extract(SON)
CLMcomSON = CLMcom.extract(SON)
DMISON=DMI.extract(SON)
KNMISON=KNMI.extract(SON)
MPIESON=MPIE.extract(SON)
SMHISON = SMHI.extract(SON)
CCCmaCanRCMSON = CCCmaCanRCM.extract(SON)
CCCmaSMHISON = CCCmaSMHI.extract(SON)
CNRMSON = CNRM.extract(SON)
CNRMSMHISON = CNRMSMHI.extract(SON)
CSIROSON = CSIRO.extract(SON)
ICHECDMISON = ICHECDMI.extract(SON)
ICHECCCLMSON = ICHECCCLM.extract(SON)
ICHECKNMISON = ICHECKNMI.extract(SON)
ICHECMPISON = ICHECMPI.extract(SON)
ICHECSMHISON = ICHECSMHI.extract(SON)
IPSLSON = IPSL.extract(SON)
MIROCSON = MIROC.extract(SON)
MOHCCCLMSON = MOHCCCLM.extract(SON)
MOHCKNMISON = MOHCKNMI.extract(SON)
MOHCSMHISON = MOHCSMHI.extract(SON)
MPICCLMSON = MPICCLM.extract(SON)
MPIREMOSON = MPIREMO.extract(SON)
MPISMHISON = MPISMHI.extract(SON)
NCCDMISON = NCCDMI.extract(SON)
NCCSMHISON = NCCSMHI.extract(SON)
NOAASON = NOAA.extract(SON)
CanESM2SON = CanESM2.extract(SON)
CNRMGSON = CNRMG.extract(SON)
MK3SON = MK3.extract(SON)
EARTHSON = EARTH.extract(SON)
EARTH3SON = EARTH3.extract(SON)
GFDLSON = GFDL.extract(SON)
HadGEM2SON = HadGEM2.extract(SON)
IPSLGSON = IPSLG.extract(SON)
MIROCGSON = MIROCG.extract(SON)
MPISON = MPI.extract(SON)
NorESM1SON = NorESM1.extract(SON)
CRUESON = CRUE.extract(SON)
CRUSON = CRU.extract(SON)
CCCmaDJF = CCCma.extract(DJF)
CLMcomDJF=CLMcom.extract(DJF)
DMIDJF=DMI.extract(DJF)
KNMIDJF=KNMI.extract(DJF)
MPIEDJF=MPIE.extract(DJF)
SMHIDJF=SMHI.extract(DJF)
CCCmaCanRCMDJF = CCCmaCanRCM.extract(DJF)
CCCmaSMHIDJF = CCCmaSMHI.extract(DJF)
CNRMDJF = CNRM.extract(DJF)
CNRMSMHIDJF = CNRMSMHI.extract(DJF)
CSIRODJF = CSIRO.extract(DJF)
ICHECDMIDJF = ICHECDMI.extract(DJF)
ICHECCCLMDJF = ICHECCCLM.extract(DJF)
ICHECKNMIDJF = ICHECKNMI.extract(DJF)
ICHECMPIDJF = ICHECMPI.extract(DJF)
ICHECSMHIDJF = ICHECSMHI.extract(DJF)
IPSLDJF = IPSL.extract(DJF)
MIROCDJF = MIROC.extract(DJF)
MOHCCCLMDJF = MOHCCCLM.extract(DJF)
MOHCKNMIDJF = MOHCKNMI.extract(DJF)
MOHCSMHIDJF = MOHCSMHI.extract(DJF)
MPICCLMDJF = MPICCLM.extract(DJF)
MPIREMODJF = MPIREMO.extract(DJF)
MPISMHIDJF = MPISMHI.extract(DJF)
NCCDMIDJF = NCCDMI.extract(DJF)
NCCSMHIDJF = NCCSMHI.extract(DJF)
NOAADJF = NOAA.extract(DJF)
CanESM2DJF = CanESM2.extract(DJF)
CNRMGDJF = CNRMG.extract(DJF)
MK3DJF = MK3.extract(DJF)
EARTHDJF = EARTH.extract(DJF)
EARTH3DJF = EARTH3.extract(DJF)
GFDLDJF = GFDL.extract(DJF)
HadGEM2DJF = HadGEM2.extract(DJF)
IPSLGDJF = IPSLG.extract(DJF)
MIROCGDJF = MIROCG.extract(DJF)
MPIDJF = MPI.extract(DJF)
NorESM1DJF = NorESM1.extract(DJF)
CRUEDJF = CRUE.extract(DJF)
CRUDJF = CRU.extract(DJF)
CCCmaMAM = CCCma.extract(MAM)
CLMcomMAM=CLMcom.extract(MAM)
DMIMAM=DMI.extract(MAM)
KNMIMAM=KNMI.extract(MAM)
MPIEMAM=MPIE.extract(MAM)
SMHIMAM=SMHI.extract(MAM)
CCCmaCanRCMMAM = CCCmaCanRCM.extract(MAM)
CCCmaSMHIMAM = CCCmaSMHI.extract(MAM)
CNRMMAM = CNRM.extract(MAM)
CNRMSMHIMAM = CNRMSMHI.extract(MAM)
CSIROMAM = CSIRO.extract(MAM)
ICHECDMIMAM = ICHECDMI.extract(MAM)
ICHECCCLMMAM = ICHECCCLM.extract(MAM)
ICHECKNMIMAM = ICHECKNMI.extract(MAM)
ICHECMPIMAM = ICHECMPI.extract(MAM)
ICHECSMHIMAM = ICHECSMHI.extract(MAM)
IPSLMAM = IPSL.extract(MAM)
MIROCMAM = MIROC.extract(MAM)
MOHCCCLMMAM = MOHCCCLM.extract(MAM)
MOHCKNMIMAM = MOHCKNMI.extract(MAM)
MOHCSMHIMAM = MOHCSMHI.extract(MAM)
MPICCLMMAM = MPICCLM.extract(MAM)
MPIREMOMAM = MPIREMO.extract(MAM)
MPISMHIMAM = MPISMHI.extract(MAM)
NCCDMIMAM = NCCDMI.extract(MAM)
NCCSMHIMAM = NCCSMHI.extract(MAM)
NOAAMAM = NOAA.extract(MAM)
CanESM2MAM = CanESM2.extract(MAM)
CNRMGMAM = CNRMG.extract(MAM)
MK3MAM = MK3.extract(MAM)
EARTHMAM = EARTH.extract(MAM)
EARTH3MAM = EARTH3.extract(MAM)
GFDLMAM = GFDL.extract(MAM)
HadGEM2MAM = HadGEM2.extract(MAM)
IPSLGMAM = IPSLG.extract(MAM)
MIROCGMAM = MIROCG.extract(MAM)
MPIMAM = MPI.extract(MAM)
NorESM1MAM = NorESM1.extract(MAM)
CRUEMAM = CRUE.extract(MAM)
CRUMAM = CRU.extract(MAM)
CCCmaJJA = CCCma.extract(JJA)
CLMcomJJA=CLMcom.extract(JJA)
DMIJJA=DMI.extract(JJA)
KNMIJJA=KNMI.extract(JJA)
MPIEJJA=MPIE.extract(JJA)
SMHIJJA=SMHI.extract(JJA)
CCCmaCanRCMJJA = CCCmaCanRCM.extract(JJA)
CCCmaSMHIJJA = CCCmaSMHI.extract(JJA)
CNRMJJA = CNRM.extract(JJA)
CNRMSMHIJJA = CNRMSMHI.extract(JJA)
CSIROJJA = CSIRO.extract(JJA)
ICHECDMIJJA = ICHECDMI.extract(JJA)
ICHECCCLMJJA = ICHECCCLM.extract(JJA)
ICHECKNMIJJA = ICHECKNMI.extract(JJA)
ICHECMPIJJA = ICHECMPI.extract(JJA)
ICHECSMHIJJA = ICHECSMHI.extract(JJA)
IPSLJJA = IPSL.extract(JJA)
MIROCJJA = MIROC.extract(JJA)
MOHCCCLMJJA = MOHCCCLM.extract(JJA)
MOHCKNMIJJA = MOHCKNMI.extract(JJA)
MOHCSMHIJJA = MOHCSMHI.extract(JJA)
MPICCLMJJA = MPICCLM.extract(JJA)
MPIREMOJJA = MPIREMO.extract(JJA)
MPISMHIJJA = MPISMHI.extract(JJA)
NCCDMIJJA = NCCDMI.extract(JJA)
NCCSMHIJJA = NCCSMHI.extract(JJA)
NOAAJJA = NOAA.extract(JJA)
CanESM2JJA = CanESM2.extract(JJA)
CNRMGJJA = CNRMG.extract(JJA)
MK3JJA = MK3.extract(JJA)
EARTHJJA = EARTH.extract(JJA)
EARTH3JJA = EARTH3.extract(JJA)
GFDLJJA = GFDL.extract(JJA)
HadGEM2JJA = HadGEM2.extract(JJA)
IPSLGJJA = IPSLG.extract(JJA)
MIROCGJJA = MIROCG.extract(JJA)
MPIJJA = MPI.extract(JJA)
NorESM1JJA = NorESM1.extract(JJA)
CRUEJJA = CRUE.extract(JJA)
CRUJJA = CRU.extract(JJA)
#We are interested in plotting the data by year, so we need to take a mean of all the data by year
CCCmaSON = CCCmaSON.aggregated_by('year', iris.analysis.MEAN)
CLMcomSON = CLMcomSON.aggregated_by('year', iris.analysis.MEAN)
DMISON = DMISON.aggregated_by('year', iris.analysis.MEAN)
KNMISON = KNMISON.aggregated_by('year', iris.analysis.MEAN)
MPIESON = MPIESON.aggregated_by('year', iris.analysis.MEAN)
SMHISON = SMHISON.aggregated_by('year', iris.analysis.MEAN)
CCCmaCanRCMSON = CCCmaCanRCMSON.aggregated_by('year', iris.analysis.MEAN)
CCCmaSMHISON = CCCmaSMHISON.aggregated_by('year', iris.analysis.MEAN)
CNRMSON = CNRMSON.aggregated_by('year', iris.analysis.MEAN)
CNRMSMHISON = CNRMSMHISON.aggregated_by('year', iris.analysis.MEAN)
CSIROSON = CSIROSON.aggregated_by('year', iris.analysis.MEAN)
ICHECDMISON = ICHECDMISON.aggregated_by('year', iris.analysis.MEAN)
ICHECCCLMSON = ICHECCCLMSON.aggregated_by('year', iris.analysis.MEAN)
ICHECKNMISON = ICHECKNMISON.aggregated_by('year', iris.analysis.MEAN)
ICHECMPISON = ICHECMPISON.aggregated_by('year', iris.analysis.MEAN)
ICHECSMHISON = ICHECSMHISON.aggregated_by('year', iris.analysis.MEAN)
IPSLSON = IPSLSON.aggregated_by('year', iris.analysis.MEAN)
MIROCSON = MIROCSON.aggregated_by('year', iris.analysis.MEAN)
MOHCCCLMSON = MOHCCCLMSON.aggregated_by('year', iris.analysis.MEAN)
MOHCKNMISON = MOHCKNMISON.aggregated_by('year', iris.analysis.MEAN)
MOHCSMHISON = MOHCSMHISON.aggregated_by('year', iris.analysis.MEAN)
MPICCLMSON = MPICCLMSON.aggregated_by('year', iris.analysis.MEAN)
MPIREMOSON = MPIREMOSON.aggregated_by('year', iris.analysis.MEAN)
MPISMHISON = MPISMHISON.aggregated_by('year', iris.analysis.MEAN)
NCCDMISON = NCCDMISON.aggregated_by('year', iris.analysis.MEAN)
NCCSMHISON = NCCSMHISON.aggregated_by('year', iris.analysis.MEAN)
NOAASON = NOAASON.aggregated_by('year', iris.analysis.MEAN)
CanESM2SON = CanESM2SON.aggregated_by('year', iris.analysis.MEAN)
CNRMGSON = CNRMGSON.aggregated_by('year', iris.analysis.MEAN)
MK3SON = MK3SON.aggregated_by('year', iris.analysis.MEAN)
EARTHSON = EARTHSON.aggregated_by('year', iris.analysis.MEAN)
EARTH3SON = EARTH3SON.aggregated_by('year', iris.analysis.MEAN)
GFDLSON = GFDLSON.aggregated_by('year', iris.analysis.MEAN)
HadGEM2SON = HadGEM2SON.aggregated_by('year', iris.analysis.MEAN)
IPSLGSON = IPSLGSON.aggregated_by('year', iris.analysis.MEAN)
MIROCGSON = MIROCGSON.aggregated_by('year', iris.analysis.MEAN)
MPISON = MPISON.aggregated_by('year', iris.analysis.MEAN)
NorESM1SON = NorESM1SON.aggregated_by('year', iris.analysis.MEAN)
CRUESON = CRUESON.aggregated_by('year', iris.analysis.MEAN)
CRUSON = CRUSON.aggregated_by('year', iris.analysis.MEAN)