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Hist_Taylor_Pr_3.py
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Hist_Taylor_Pr_3.py
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"""
Created on Wednesday August 2 2017
@author: s0899345
Taylor Diagram (Taylor, 2001) code from "Yannick Copin <[email protected]>". This code was put in to the public domain and accessed from https://gist.github.com/ycopin/3342888
with "Time-stamp: <2018-05-17 19:41:54 ycopin>"
"""
import iris
import iris.coord_categorisation as iriscc
import iris.analysis.cartography
import numpy as np
import math
import matplotlib.pyplot as PLT
from Taylor_Diagram_Template_YC3 import TaylorDiagram
import cf_units
import datetime
#this file is split into parts as follows:
#PART A: Define Necessary Maths
#PART B: Main Script
#PART 1: load and format all models
#PART 2: load and format observed data
#PART 3: format files to synthesize data temporaly and spatially
#PART 4: Calculate Standard Deviation
#PART 5: Calculate Pearson's Correlation Coefficient
#PART 6: Plot Taylor Diagram (based on Copin, 2017)
#PART A : Define Necessary Maths
def mean(x):
sum = 0.0
for i in x:
sum += i
return sum / len(x)
# calculates the sample standard deviation
def sampleStandardDeviation(x):
sumv = 0.0
for i in x:
sumv += (i - mean(x))**2
return math.sqrt(sumv/(len(x)-1))
# calculates the PCC using both the 2 functions above
def pearson(x,y):
scorex = []
scorey = []
for i in x:
scorex.append((i - mean(x))/sampleStandardDeviation(x))
for j in y:
scorey.append((j - mean(y))/sampleStandardDeviation(y))
# multiplies both lists together into 1 list (hence zip) and sums the whole list
return (sum([i*j for i,j in zip(scorex,scorey)]))/(len(x)-1)
#PART B: Main Script
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_pr/ERAINT/1979-2012/pr_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_CCCma-CanRCM4_r2_mon_198901-200912.nc'
CLMcom = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_pr/ERAINT/1979-2012/pr_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_pr/ERAINT/1979-2012/pr_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_DMI-HIRHAM5_v2_mon_198901-201012.nc'
KNMI = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_pr/ERAINT/1979-2012/pr_AFR-44_ECMWF-ERAINT_evaluation_r1i1p1_KNMI-RACMO22T_v1_mon_197901-201212.nc'
MPIE = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_pr/ERAINT/1979-2012/pr_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_pr/ERAINT/1979-2012/pr_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_pr/Historical/1950-2005/pr_AFR-44_CCCma-CanESM2_historical_r1i1p1_CCCma-CanRCM4_r2_mon_195101-200512.nc'
CCCmaSMHI= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_pr/Historical/1950-2005/pr_AFR-44_CCCma-CanESM2_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
CNRM= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_AFR-44_MIROC-MIROC5_historical_r1i1p1_SMHI-RCA4_v1_mon_195101-200512.nc'
MOHCCCLM = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/AFR_44_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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_pr/Historical/1950-2005/pr_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/pr_Amon_CanESM2_historical_r1i1p1_185001-200512.nc'
CNRMG= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_CNRM-CM5-2_historical_r1i1p1_195001-200512.nc'
MK3 = '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_CSIRO-Mk3-6-0_historical_r1i1p1_185001-200512.nc'
EARTH= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_EC-EARTH_historical_r12i1p1_195001-201212.nc'
EARTH3= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_EC-EARTH_historical_r3i1p1_1850-2009.nc'
GFDL='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_GFDL-ESM2M_historical_r1i1p1_194601-200512.nc'
HadGEM2='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_HadGEM2-ES_historical_r1i1p1_193412-200511.nc'
IPSLG='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_IPSL-CM5B-LR_historical_r1i1p1_185001-200512.nc'
MIROCG='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_MIROC5_historical_r1i1p1_185001-201212.nc'
MPI='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_Amon_MPI-ESM-MR_historical_r1i1p1_185001-200512.nc'
NorESM1='/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/GCM_data/pr_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, 'precipitation_flux')
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, 'precipitation_flux')
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, 'precipitation_flux')
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, 'precipitation_flux')
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_ts4.00.1901.2015.pre.dat.nc'
UDel= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/Actual_Data/UDel_precip.mon.total.v401.nc'
GPCC= '/exports/csce/datastore/geos/users/s0899345/Climate_Modelling/Actual_Data/ESRL_PSD_GPCC_precip.mon.combined.total.v7.nc'
#Load exactly one cube from given file
CRU = iris.load_cube(CRU, 'precipitation')
UDel = iris.load_cube(UDel)
GPCC = iris.load_cube(GPCC)
#-------------------------------------------------------------------------
#PART 3: FORMAT DATA TO BE PLOT SPECIFIC
#fix EARTH3 time units as they differ from all other models
t_coord=EARTH3.coord('time')
t_unit = t_coord.attributes['invalid_units']
timestep, _, t_fmt_str = t_unit.split(' ')
new_t_unit_str= '{} since 1850-01-01 00:00:00'.format(timestep)
new_t_unit = cf_units.Unit(new_t_unit_str, calendar=cf_units.CALENDAR_STANDARD)
new_datetimes = [datetime.datetime.strptime(str(dt), t_fmt_str) for dt in t_coord.points]
new_dt_points = [new_t_unit.date2num(new_dt) for new_dt in new_datetimes]
new_t_coord = iris.coords.DimCoord(new_dt_points, standard_name='time', units=new_t_unit)
t_coord_dim = EARTH3.coord_dims('time')
EARTH3.remove_coord('time')
EARTH3.add_dim_coord(new_t_coord,t_coord_dim)
#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())
UDel = UDel.regrid(CanESM2, iris.analysis.Linear())
GPCC = GPCC.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)
UDel = UDel.extract(Malawi)
GPCC = GPCC.extract(Malawi)
#time constraignt to make all series the same, the common perios between all three is 1990-2005
iris.FUTURE.cell_datetime_objects = True
t_constraint_ERAINT = iris.Constraint(time=lambda cell: 1990 <= cell.point.year <= 2005)
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)
CCCmaCanRCM = CCCmaCanRCM.extract(t_constraint_ERAINT)
CCCmaSMHI = CCCmaSMHI.extract(t_constraint_ERAINT)
CNRM =CNRM.extract(t_constraint_ERAINT)
CNRMSMHI =CNRMSMHI.extract(t_constraint_ERAINT)
CSIRO=CSIRO.extract(t_constraint_ERAINT)
ICHECDMI=ICHECDMI.extract(t_constraint_ERAINT)
ICHECCCLM=ICHECCCLM.extract(t_constraint_ERAINT)
ICHECKNMI=ICHECKNMI.extract(t_constraint_ERAINT)
ICHECMPI=ICHECMPI.extract(t_constraint_ERAINT)
ICHECSMHI=ICHECSMHI.extract(t_constraint_ERAINT)
IPSL=IPSL.extract(t_constraint_ERAINT)
MIROC=MIROC.extract(t_constraint_ERAINT)
MOHCCCLM=MOHCCCLM.extract(t_constraint_ERAINT)
MOHCKNMI=MOHCKNMI.extract(t_constraint_ERAINT)
MOHCSMHI=MOHCSMHI.extract(t_constraint_ERAINT)
MPICCLM=MPICCLM.extract(t_constraint_ERAINT)
MPIREMO=MPIREMO.extract(t_constraint_ERAINT)
MPISMHI=MPISMHI.extract(t_constraint_ERAINT)
NCCDMI=NCCDMI.extract(t_constraint_ERAINT)
NCCSMHI=NCCSMHI.extract(t_constraint_ERAINT)
NOAA=NOAA.extract(t_constraint_ERAINT)
CanESM2 = CanESM2.extract(t_constraint_ERAINT)
CNRMG =CNRMG.extract(t_constraint_ERAINT)
MK3 =MK3.extract(t_constraint_ERAINT)
EARTH =EARTH.extract(t_constraint_ERAINT)
EARTH3 =EARTH3.extract(t_constraint_ERAINT)
GFDL=GFDL.extract(t_constraint_ERAINT)
HadGEM2=HadGEM2.extract(t_constraint_ERAINT)
IPSLG=IPSLG.extract(t_constraint_ERAINT)
MIROCG=MIROCG.extract(t_constraint_ERAINT)
MPI=MPI.extract(t_constraint_ERAINT)
NorESM1=NorESM1.extract(t_constraint_ERAINT)
CRU = CRU.extract(t_constraint_ERAINT)
UDel = UDel.extract(t_constraint_ERAINT)
GPCC = GPCC.extract(t_constraint_ERAINT)
#Convert units to match, CORDEX data in precipitation_flux (kg m-2 s-1) but want all data in precipitation rate (mm month-1).
#Since 1 kg of rain spread over 1 m of surface is 1mm in thickness, and there are 60*60*24*365.25=31557600 seconds in a year, the conversion is:
Convert=31557600
CCCma = CCCma*Convert
CLMcom=CLMcom*Convert
DMI=DMI*Convert
KNMI=KNMI*Convert
MPIE=MPIE*Convert
SMHI=SMHI*Convert
CCCmaCanRCM = CCCmaCanRCM*Convert
CCCmaSMHI = CCCmaSMHI*Convert
CNRM = CNRM*Convert
CNRMSMHI = CNRMSMHI*Convert
CSIRO = CSIRO*Convert
ICHECDMI = ICHECDMI*Convert
ICHECCCLM = ICHECCCLM*Convert
ICHECKNMI = ICHECKNMI*Convert
ICHECMPI = ICHECMPI*Convert
ICHECSMHI = ICHECSMHI*Convert
IPSL = IPSL*Convert
MIROC = MIROC*Convert
MOHCCCLM = MOHCCCLM*Convert
MOHCKNMI = MOHCKNMI*Convert
MOHCSMHI = MOHCSMHI*Convert
MPICCLM = MPICCLM*Convert
MPIREMO = MPIREMO*Convert
MPISMHI = MPISMHI*Convert
NCCDMI = NCCDMI*Convert
NCCSMHI = NCCSMHI*Convert
NOAA = NOAA*Convert
CanESM2 = CanESM2*Convert
CNRMG = CNRMG*Convert
MK3=MK3*Convert
EARTH=EARTH*Convert
EARTH3=EARTH3*Convert
GFDL=GFDL*Convert
HadGEM2=HadGEM2*Convert
IPSLG = IPSLG*Convert
MIROCG = MIROCG*Convert
MPI=MPI*Convert
NorESM1=NorESM1*Convert
#Convert units to match, CRU and GPCC data is in mm per month but want precipitation rate in mm per year.
#Since there are 12 months in the year, the conversion is:
Convert=12
CRU = CRU*Convert
GPCC = GPCC*Convert
#Convert units to match, UDel data in cm per month but want precipitation rate in mm per year.
#Since there are 12 months in the year and 10mm in a cm, the conversion is:
Convert=12*10
UDel = UDel*Convert
#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(CRU, 'time')
iriscc.add_season(UDel, 'time')
iriscc.add_season(GPCC, '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(CRU, 'time')
iriscc.add_year(UDel, 'time')
iriscc.add_year(GPCC, '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)
NorESM1SON = NorESM1.extract(SON)
CRUSON = CRU.extract(SON)
UDelSON = UDel.extract(SON)
GPCCSON = GPCC.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)
CRUDJF = CRU.extract(DJF)
UDelDJF = UDel.extract(DJF)
GPCCDJF = GPCC.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)
CRUMAM = CRU.extract(MAM)
UDelMAM = UDel.extract(MAM)
GPCCMAM = GPCC.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)