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plot3dvarmap_canam4sims.py
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plot3dvarmap_canam4sims.py
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""" plot3dvarmap_canam4sims.py
# 4/8/2014
# Taken from plotvert_canam4sims2.py
# This script will plot a map of a level of a 3d atmos var
#
# 2/19/2014
# Vertical plots for CanAM4 sea ice simulations
# 3/3/2014: taken from first version. Try and use new
# cccmaNC module to read and average netcdf data
"""
#import numpy as np # for array handling
#import scipy as sp # scientific python
import scipy.stats
#import matplotlib.pyplot as plt # for basic plotting
import matplotlib.cm as cm
from subprocess import call # for doing system calls - not really needed
#from netCDF4 import Dataset
#from mpl_toolkits.basemap import Basemap # for maps
import datetime as datetime
import matplotlib.colors as col
import platform as platform
#import cccmaplots as cplt # in startup now: ~/.config/ipython/profile_default/startup/00-startup.py
import constants as con
import cccmautils as cutl
import matplotlib.font_manager as fm
#import cccmaNC as cnc # in startup
#import cccmacmaps # in startup
#import cdo as cdo; cdo = cdo.Cdo()
#import os
# https://code.zmaw.de/projects/cdo/wiki/Cdo%7Brbpy%7D
# while I'm still creating these modules, have to reload to get changes
# don't need to do anymore b/c added to configuration (autoreload)
#cplt = reload(cplt)
#con = reload(con)
#cutl = reload(cutl)
#cnc = reload(cnc)
plt.close("all")
plt.ion()
printtofile=1
allmos=1 # make monthly figures
bimos=0 # bi-monthly figures. not implemented yet 4/29/14
seasonal=1 # seasonal figures
singleplots=1 # seasonal climo and mean diff
obssims=0 # this will overrule the simulation settings and set to kemhad*
thickness=0; level2=70000 # calc thickness between level and level2 for GZ only, typically 1000-700hPa
#level = 100000 # for thickness calc
#level = 30000
#level = 50000 # 500hPa
level = 70000
sigtype = 'cont' # significance: 'cont' or 'hatch' which is default
""" plev = 100, 200, 300, 500, 700, 1000, 2000, 3000, 5000, 7000, 10000, 12500,
15000, 17500, 20000, 22500, 25000, 30000, 35000, 40000, 45000, 50000,
55000, 60000, 65000, 70000, 75000, 77500, 80000, 82500, 85000, 87500,
90000, 92500, 95000, 97500, 100000 ;
"""
#seasons = 'DJF','MAM','JJA','SON'
seasons = 'SON','DJF','MAM','JJA'
model = 'CanAM4'
ftype = 'ts' # timeseries
## @@ really shouldn't use anymore now that code is all worked out #ftype = 'climo' # 12-month climatology
season = 'ANN'
# # # ########### set Simulations #############
# Control run
casename = 'kemctl1'
timstr = '001-061'
timstr2 = '062-121'
# Pert run
casenamep1 = 'kem1pert1' # 2002-2012 sic and sit
casenamep2 = 'kem1pert2' # 2002-2012 sic, sit, adjusted sst
casenamep3 = 'kem1pert3' # 2002-2012 sic, adjusted sst. control sit
timstrp = '001-061'
timstrp2 = '062-121'
casenamepra = 'kem1rcp85a' # 2022-2032 sic, adjusted sst, sit from RCP8.5
######## set pert run ############
casenamep = casenamepra
########### OR SET OTHER RUNS ##############
if obssims:
casename = 'kemhadctl'
casenamep = 'kemhadpert'
timstr2 = '062-121'
timstrp2 = '062-121'
if casenamep == casenamepra:
timstrp2 = '062-121'
cmap = 'blue2red_w20'
cmapclimo = 'Spectral_r'
conv = 1 # conversion factor to convert units, etc
# # # ######## set Field info ###############
field = 'u' # t, u, gz
if sigtype=='cont':
suff='pdf'
else:
suff='png'
if field == 't':
ncfield = 'TEMP'
units = 'K' # @@
if level == 30000:
cminc = 215; cmaxc = 245
elif level == 70000:
cminc = 245; cmaxc = 285
if level == 30000:
cmin = -.3; cmax = .3
cminm = -.8; cmaxm = .8 # for monthly
cminsea = -.5; cmaxsea = .5
elif level == 70000:
cmin = -.3; cmax = .3
cminm = -1; cmaxm = 1 # for monthly
cminsea = -.5; cmaxsea = .5
elif field == 'u':
ncfield = 'U'
units = 'm/s' #@@
if level==50000:
cminc=-25; cmaxc=25
elif level==70000:
cminc=-15; cmaxc=15
elif level == 30000:
cminc=-40; cmaxc=40
if level == 30000:
cmin = -2; cmax = 2
cminm = -5; cmaxm = 5
cminsea = -3; cmaxsea = 3
else:
cmin = -1; cmax = 1
cminm = -3; cmaxm = 3
cminsea = -1; cmaxsea = 1
cmapclimo='blue2red_20'
elif field == 'gz':
ncfield = 'PHI'
units = 'm' # @@
conv = 1/con.get_g()
if level==50000:
cminc = 5200; cmaxc = 5900 # climo 500hPa
elif level==70000:
cminc=2800; cmaxc = 3200
elif level==30000:
cminc=8600; cmaxc = 9800
elif level==100000: # use this for thickness calc 1000-700
cminc=2650; cmaxc = 3050
cmin = -8 # annual mean
cmax = 8 # annual mean
if level==30000:
cmin = -15; cmax = 15
cminsea=-20; cmaxsea = 20
cminm = -30; cmaxm = 30 # for monthly
else:
cminsea = -15; cmaxsea = 15
cminm = -20; cmaxm = 20 # for monthly
else:
print 'no such field: ' + field
# # # ########## Read NC data ###############
plat = platform.system()
if plat == 'Darwin': # means I'm on my mac
basepath = '/Users/kelly/CCCma/CanSISE/RUNS/'
subdir = '/'
else: # on linux workstation in Vic
basepath = '/home/rkm/work/DATA/' + model + '/'
subdir = '/ts/'
# The 3D data is split into 2 timeseries
fnamec = basepath + casename + subdir + casename + '_' + field + '_' + timstr + '_' + ftype + '.nc'
fnamep = basepath + casenamep + subdir + casenamep + '_' + field + '_' + timstrp + '_' + ftype + '.nc'
## fnamep2 = basepath + casenamep2 + subdir + casenamep2 + '_' + field + '_' + timstrp + '_' + ftype + '.nc'
## fnamep3 = basepath + casenamep3 + subdir + casenamep3 + '_' + field + '_' + timstrp + '_' + ftype + '.nc'
fnamec2 = basepath + casename + subdir + casename + '_' + field + '_' + timstr2 + '_' + ftype + '.nc'
fnamep2 = basepath + casenamep + subdir + casenamep + '_' + field + '_' + timstrp2 + '_' + ftype + '.nc'
## fnamep22 = basepath + casenamep2 + subdir + casenamep2 + '_' + field + '_' + timstrp2 + '_' + ftype + '.nc'
## fnamep32 = basepath + casenamep3 + subdir + casenamep3 + '_' + field + '_' + timstrp2 + '_' + ftype + '.nc'
print field + ' level ' + str(level/100)
if field=='gz' and thickness==1: print ' to level ' + str(level2/100)
print 'CONTROL: ' + casename
print 'PERT: ' + casenamep
lat = cnc.getNCvar(fnamec,'lat')
lon = cnc.getNCvar(fnamec,'lon')
seasfldc = np.append(cnc.getNCvar(fnamec,ncfield,timesel='0002-01-01,0061-12-31',levsel=level,seas=season)*conv,
cnc.getNCvar(fnamec2,ncfield,levsel=level,seas=season)*conv,
axis=0)
seasfldp = np.append(cnc.getNCvar(fnamep,ncfield,timesel='0002-01-01,0061-12-31',levsel=level,seas=season)*conv,
cnc.getNCvar(fnamep2,ncfield,levsel=level,seas=season)*conv,
axis=0)
if field=='gz' and thickness==1:
seasfldc2 = np.append(cnc.getNCvar(fnamec,ncfield,timesel='0002-01-01,0061-12-31',levsel=level2,seas=season)*conv,
cnc.getNCvar(fnamec2,ncfield,levsel=level2,seas=season)*conv,
axis=0)
seasfldp2 = np.append(cnc.getNCvar(fnamep,ncfield,timesel='0002-01-01,0061-12-31',levsel=level2,seas=season)*conv,
cnc.getNCvar(fnamep2,ncfield,levsel=level2,seas=season)*conv,
axis=0)
seasfldc=seasfldc2 - seasfldc
seasfldp=seasfldp2 - seasfldp
#nt,nlev,nlat,nlon = fldc.shape # if nt == 12 then it's a climo
nt,nlat,nlon = seasfldc.shape
print nt
# seasonalize
#seasfldczm = cutl.seasonalize_monthlyts(fldczm,timeavg)
#seasfldpzm = cutl.seasonalize_monthlyts(fldpzm,timeavg)
if ftype=='ts':
tstat,pval = sp.stats.ttest_ind(seasfldp,seasfldc,axis=0)
# time-mean
seasfldctm=np.mean(seasfldc,0)
seasfldptm=np.mean(seasfldp,0)
############################## SEASONAL (ANN) MEAN ##########################
if singleplots:
# SEASONAL MEAN CLIMO (CONTROL)
if field=='gz' and thickness==1:
title = season + ' ' + field + ' ' + str(level2/100) + '-' + str(level/100) + ': ' + casename
else:
title = season + ' ' + field + ' ' + str(level/100) + ': ' + casename
plotfld = seasfldctm
fig1 = plt.figure()
bm,pc = cplt.kemmap(plotfld,lat,lon,cmin=cminc,cmax=cmaxc,cmap=cmapclimo,type='nh',\
title=title,units=units)
if printtofile:
if field=='gz' and thickness==1:
fig1.savefig(field + 'THK' + str(level2/100) + '-' + str(level/100) + '_' + season + \
'_' + casename + '_nh.' + suff)
else:
fig1.savefig(field + 'LEV' + str(level/100) + '_' + season + \
'_' + casename + '_nh.' + suff)
# SEASONAL MEAN DIFF
# full height of atmosphere
plotfld = seasfldptm - seasfldctm
fig = plt.figure()
bm,pc = cplt.kemmap(plotfld,lat,lon,cmin=cmin,cmax=cmax,cmap=cmap,type='nh',\
title=title,units=units)
cplt.addtsigm(bm,pval,lat,lon,type=sigtype)
if printtofile:
if field=='gz' and thickness==1:
fig.savefig(field + 'DIFFTHK' + str(level2/100) + '-' + str(level/100) + sigtype + '_' + season + \
'_' + casenamep + '_v_' + casename + '_nh.' + suff)
else:
fig.savefig(field + 'DIFFLEV' + str(level/100) + sigtype + '_' + season + \
'_' + casenamep + '_v_' + casename + '_nh.' + suff)
######################## ALL MONTHS #######################
if allmos:
fldc = np.append(cnc.getNCvar(fnamec,ncfield,timesel='0002-01-01,0061-12-31',levsel=level)*conv,
cnc.getNCvar(fnamec2,ncfield,levsel=level)*conv,
axis=0)
fldp = np.append(cnc.getNCvar(fnamep,ncfield,timesel='0002-01-01,0061-12-31',levsel=level)*conv,
cnc.getNCvar(fnamep2,ncfield,levsel=level)*conv,
axis=0)
if field == 'gz' and thickness==1:
fldc2 = np.append(cnc.getNCvar(fnamec,ncfield,timesel='0002-01-01,0061-12-31',levsel=level2)*conv,
cnc.getNCvar(fnamec2,ncfield,levsel=level2)*conv,
axis=0)
fldp2 = np.append(cnc.getNCvar(fnamep,ncfield,timesel='0002-01-01,0061-12-31',levsel=level2)*conv,
cnc.getNCvar(fnamep2,ncfield,levsel=level2)*conv,
axis=0)
fldc = fldc2 - fldc
fldp = fldp2 - fldp
# ALL MONTHS
months = con.get_mon()
# sigs = np.zeros((12,nlat,nlon))
midx=0
fig4,ax4 = plt.subplots(2,6)
fig4.set_size_inches(12,6)
fig4.subplots_adjust(hspace=.15,wspace=.05)
for ax in ax4.flat:
monfldc = fldc[midx::12,:,:]
monfldp = fldp[midx::12,:,:]
tstat,pval = sp.stats.ttest_ind(monfldp,monfldc,axis=0)
#sigs[midx,:,:] = ma.masked_where(pval>siglevel,pval)
plotfld = np.mean(monfldp-monfldc,0)
bm,pc = cplt.kemmap(plotfld,lat,lon,cmin=cminm,cmax=cmaxm,cmap=cmap,type='nh',\
title=months[midx],axis=ax,suppcb=1)
ax.set_title(months[midx])
cplt.addtsigm(bm,pval,lat,lon,type=sigtype)
midx = midx+1
#cbar_ax = fig4.add_axes([.2, .02, .7, .03])
#fig4.colorbar(pc,cax=cbar_ax,orientation='horizontal')
cbar_ax = fig4.add_axes([.91,.25, .02,.5])
fig4.colorbar(pc,cax=cbar_ax)
if field=='gz' and thickness==1:
plt.suptitle(ncfield + ' ' + str(level2/100) + '-' + str(level/100)+ ' (' + units + ')')
else:
plt.suptitle(ncfield + ' ' + str(level/100) + ' (' + units + ')')
if printtofile:
if field=='gz' and thickness==1:
fig4.savefig(field + 'DIFFTHK' + str(level2/100) + '-' + str(level/100) + sigtype + '_' + casenamep +\
'_v_' + casename + '_allmos_nh.' + suff)
else:
fig4.savefig(field + 'DIFFLEV' + str(level/100) + sigtype + '_' + casenamep +\
'_v_' + casename + '_allmos_nh.' + suff)
if bimos:
print 'bimos'
if seasonal:
tstat = np.zeros((len(seasons),nlat,nlon))
pval = np.zeros((len(seasons),nlat,nlon))
fldcallseas = np.zeros((len(seasons),nlat,nlon))
fldpallseas = np.zeros((len(seasons),nlat,nlon))
midx=0
fig6,ax6 = plt.subplots(1,4)
fig6.set_size_inches(12,2.5)
fig6.subplots_adjust(hspace=.15,wspace=.05)
for ax in ax6.flat:
fldcsea = np.append(cnc.getNCvar(fnamec,ncfield,timesel='0002-01-01,0061-12-31',
levsel=level,seas=seasons[midx])*conv,
cnc.getNCvar(fnamec2,ncfield,levsel=level,seas=seasons[midx])*conv,
axis=0)
fldpsea = np.append(cnc.getNCvar(fnamep,ncfield,timesel='0002-01-01,0061-12-31',
levsel=level,seas=seasons[midx])*conv,
cnc.getNCvar(fnamep2,ncfield,levsel=level,seas=seasons[midx])*conv,
axis=0)
if field == 'gz' and thickness==1:
fldcsea2 = np.append(cnc.getNCvar(fnamec,ncfield,timesel='0002-01-01,0061-12-31',levsel=level2,seas=seasons[midx])*conv,
cnc.getNCvar(fnamec2,ncfield,levsel=level2,seas=seasons[midx])*conv,
axis=0)
fldpsea2 = np.append(cnc.getNCvar(fnamep,ncfield,timesel='0002-01-01,0061-12-31',levsel=level2,seas=seasons[midx])*conv,
cnc.getNCvar(fnamep2,ncfield,levsel=level2,seas=seasons[midx])*conv,
axis=0)
fldcsea = fldcsea2 - fldcsea
fldpsea = fldpsea2 - fldpsea
tstat[midx,:,:],pval[midx,:,:] = sp.stats.ttest_ind(fldpsea,fldcsea,axis=0)
fldcallseas[midx,:,:] = np.mean(fldcsea,axis=0)
fldpallseas[midx,:,:] = np.mean(fldpsea,axis=0)
plotfld = fldpallseas[midx,:,:] - fldcallseas[midx,:,:]
bm,pc = cplt.kemmap(plotfld,lat,lon,cmin=cminsea,cmax=cmaxsea,cmap=cmap,type='nh',\
axis=ax,suppcb=1)
ax.set_title(seasons[midx])
cplt.addtsigm(bm,pval[midx,:,:],lat,lon,type=sigtype)
midx = midx+1
#cbar_ax = fig4.add_axes([.2, .02, .7, .03])
#fig4.colorbar(pc,cax=cbar_ax,orientation='horizontal')
cbar_ax = fig6.add_axes([.91,.25, .02,.5])
fig6.colorbar(pc,cax=cbar_ax)
#plt.suptitle(ncfield + ' (' + units + ')')
if printtofile:
if field=='gz' and thickness==1:
fig6.savefig(field + 'DIFFTHK' + str(level2/100) + '-' + str(level/100) + sigtype + '_' + casenamep +\
'_v_' + casename + '_seas_nh.' + suff)
else:
fig6.savefig(field + 'DIFFLEV' + str(level/100) + sigtype + '_' + casenamep +\
'_v_' + casename + '_seas_nh.' + suff)