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plotBCs.py
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plotBCs.py
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""" plotBCs.py
5/13/2014: taken from compareOBS.py, which was a mess. Just want to
plot BCs
3/7/2014
compare HadISST, Hurrell blended hadISST/NOAA, NSIDC (and CanESM2)
"""
import numpy as np
import numpy.ma as ma
import matplotlib.pyplot as plt
import platform as platform
import cccmaplots as cplt
import constants as con
import cccmautils as cutl
import cccmaNC as cnc
import cccmacmaps
cplt = reload(cplt)
con = reload(con)
cutl = reload(cutl)
cnc = reload(cnc)
plt.close("all")
plt.ion()
printtofile=1
testsic=0
mtype='nh' # map type (nh,sh,sq)
plotallmos=0
plotseacyc=0
plotseacycmag=0 # only for SST
diffobs=1 # difference canesm and hadisst bcs
had=0
hurr=0
canesm=1 # assume pert2 if "doBCs"
#else NSIDC
# @@ something is way wrong with CanESM2 SST files and/or figures @@
# @@ OR is is HadISST? basically the comparison for ssts north of 60N is horrible.
# there is no seasonal cycle in HadISST but there is one that looks ok in CanESM2.
# what's the seasonal cycle in actual observed ssts? it's only about 3-4 degrees
# so something is wrong w/ my CanESM calc. Potentially it's just related to masking
# and/or polar average function.
field = 'gt' # gt, sicn, sic
#sic=1
#sicn=0
#else SST
#doBCs=0 # use the actual BC files @@so far only hadisst sst
latlim=50
flipmask=0 # flip the landmask (for HURRELL)
deni = 913 # density of ice
bcstr = ''
# BCs for runs that are actually done: HadISST, CanESM
# set up based on actual casenames
casenamec = 'kemctl1'
casenamep = 'kem1rcp85a'
timeperc='1979-1989'
timeperp='2002-2012' # CanESM2 (or HadISST)
if field == 'sicn':
# SICN caxis info
cminm=-.25; cmaxm=.25
cminm=-.15; cmaxm=.15 # @@
cmind=-.15; cmaxd=.15 # for differencing canesm and hadisst
cmap = 'red2blue_w20'
elif field == 'sic':
cminm=-.5*deni
cmaxm = .5*deni
cmind=cminm; cmaxd=cmaxm
cmap = 'red2blue_w20'
elif field == 'gt': # sst
cminm=-2
cmaxm=2
cmind=-2; cmaxd=2
cmap = 'blue2red_w20'
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/DATA/' # @@@
basepath = '/Volumes/MyPassport1TB/DATA/'
basepath2 = '/Users/kelly/CCCma/CanSISE/BoundaryConditionFiles/'
temppath = '/Users/kelly/CCCma/CanSISE/matlab/'
else: # on linux workstation in Vic
basepath = '/home/rkm/work/BCs/'
basepath2 = basepath
temppath = basepath
print 'NOT FINISHED AT ALL' # left off here @@@
# ===========================
if sicn:
field = 'sicn'
# @@ check what the units are: are they all fraction?
fhadsic = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sicn_' + timeper + 'climo.nc' #SICN, 129x64
fhadsicts = basepath2 + 'HadISST/SICN_BC_HadISST_' + timeper + '_1870010100-2011020100.nc' #0000120100-0125120100.nc' # test matlab generated BC file
fhurrsic = basepath + 'HURRELL/MODEL_ICE.T42_' + timeper + 'climo.nc' #SEAICE (%), 128x64
fnsidcsic = basepath + 'NSIDC/nsidc_bt_128x64_1978m11_2011m12_sicn_' + timeper + 'climo.nc' #SICN, 129x64
fhadsicp = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sicn_' + timeperp2 + 'climo.nc' #SICN, 129x64
fhadsicpts = basepath2 + 'HadISST/SICN_BC_HadISST_' + timeperp2 + '_1870010100-2011020100.nc' #0000120100-0125120100.nc' # test matlab generated BC file
fhurrsicp = basepath + 'HURRELL/MODEL_ICE.T42_' + timeperp2 + 'climo.nc' #SEAICE (%), 128x64
fnsidcsicp = basepath + 'NSIDC/nsidc_bt_128x64_1978m11_2011m12_sicn_' + timeperp2 + 'climo.nc' #SICN, 129x64
hadsicc = cnc.getNCvar(fhadsic,'SICN')
hadsiccts = cnc.getNCvar(fhadsicts,'SICN')
hadsiccclimo,junk = cutl.climatologize3d(hadsiccts)
hurrsicc = cnc.getNCvar(fhurrsic,'SEAICE')/100
hurrtimes = cnc.getNCvar(fhurrsic,'time')
#hurrsicc.resize(hadsicc.shape) # can't resize like this. ??
#np.append(hurrsicc,hurrsicc[:,:,0])#,axis=2) # could not get append to work
#hurrsicc[:,:,len(lon)-1] = hurrsicc[:,:,0] # add a wraparound. nope.
hurrsicc = np.flipud(hurrsicc) # the lats are flipped compared to hadisst and nsidc
nsidcsicc = cnc.getNCvar(fnsidcsic,'SICN')
hadsicp = cnc.getNCvar(fhadsicp,'SICN')
hadsicpts = cnc.getNCvar(fhadsicpts,'SICN')
hadsicpclimo,junk = cutl.climatologize3d(hadsicpts)
hadsicc = hadsicc[...,:-1]
hadsicp = hadsicp[...,:-1]
hadsicd = hadsicp - hadsicc
hurrsicp = cnc.getNCvar(fhurrsicp,'SEAICE')/100
#hurrsicc.resize(hadsicc.shape) # other datasets have extra lon.
#hurrsicp[:,:,len(lon)-1] = hurrsicp[:,:,0] # add a wraparound
hurrsicp = np.flipud(hurrsicp) # the lats are flipped compared to hadisst and nsidc
nsidcsicp = cnc.getNCvar(fnsidcsicp,'SICN')
nsidcsicc = nsidcsicc[:,:,0:-1]
nsidcsicp = nsidcsicp[:,:,0:-1]
nsidcsicd = nsidcsicp-nsidcsicc
# add CanESM2 boundary conditions too
fcansic = basepath2 + 'CanESM2/SICN_BC_CanESM2_historical' + timeper + '_climo.nc'
fcansicp = basepath2 + 'CanESM2/SICN_BC_CanESM2_historical' + timeperp + '_climo.nc'
cansicc = cnc.getNCvar(fcansic,'SICN')
cansicp = cnc.getNCvar(fcansicp,'SICN')
cansicc = cansicc[:,:,0:-1]
cansicp = cansicp[:,:,0:-1]
cansicd = cansicp - cansicc
elif sic:
field = 'sic'
fhadsic = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sic_' + timeper + 'climo.nc' #SIC, 129x64
fhadsicp = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sic_' + timeperp2 + 'climo.nc' #SIC, 129x64
fhadsicts = basepath2 + 'HadISST/SIC_BC_HadISST_' + timeper + '_1870010100-2011020100.nc' # test matlab generated BC file
fhadsicpts = basepath2 + 'HadISST/SIC_BC_HadISST_' + timeperp2 + '_1870010100-2011020100.nc' # test matlab generated BC file
fhadsicorig = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sic_1870010100-2013030100.nc'
fhadsicnorig = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sicn_1870010100-2013030100.nc'
hadsicc = cnc.getNCvar(fhadsic,'SIC')
hadsicp = cnc.getNCvar(fhadsicp,'SIC')
hadsiccts = cnc.getNCvar(fhadsicts,'SIC')
hadsiccclimo,junk = cutl.climatologize3d(hadsiccts)
hadsicpts = cnc.getNCvar(fhadsicpts,'SIC')
hadsicpclimo,junk = cutl.climatologize3d(hadsicpts)
hadsicc = hadsicc[...,:-1]
hadsicp = hadsicp[...,:-1]
hadsicd = hadsicp - hadsicc
# also need sicn for averaging
fhadsicn = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sicn_' + timeper + 'climo.nc' #SICN, 129x64
fhadsicnp = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_sicn_' + timeperp2 + 'climo.nc' #SICN, 129x64
hadsicnc = cnc.getNCvar(fhadsicn,'SICN')
hadsicnp = cnc.getNCvar(fhadsicnp,'SICN')
# add CanESM2 boundary conditions too
fcansic = basepath2 + 'CanESM2/SIC_BC_CanESM2_historical' + timeper + '_climo.nc'
fcansicp = basepath2 + 'CanESM2/SIC_BC_CanESM2_historical' + timeperp + '_climo.nc'
cansicc = cnc.getNCvar(fcansic,'SIC')
cansicp = cnc.getNCvar(fcansicp,'SIC')
cansicc = cansicc[:,:,0:-1]
cansicp = cansicp[:,:,0:-1]
cansicd = cansicp - cansicc
# add CanESM2 boundary conditions too
fcansicn = basepath2 + 'CanESM2/SICN_BC_CanESM2_historical' + timeper + '_climo.nc'
fcansicnp = basepath2 + 'CanESM2/SICN_BC_CanESM2_historical' + timeperp + '_climo.nc'
cansicnc = cnc.getNCvar(fcansicn,'SICN')
cansicnp = cnc.getNCvar(fcansicnp,'SICN')
cansicnc = cansicnc[:,:,0:-1]
cansicnp = cansicnp[:,:,0:-1]
cansicnd = cansicnp - cansicnc
else:
# SST (var names are sic still...)
field = 'gt'
if doBCs:
bcstr='BC'
# use the actual BC files for the simulations
fhadsic = basepath + 'HadISST/hadisst_kemhadctl_128x64_0001_0125_gt.nc'
fhadsicp = basepath + 'HadISST/hadisst_kemhadpert_128x64_0001_0125_gt.nc'
# or GTadjusted_BC_HadISST_2002-2011_0000120100-0125120100_abs10thresh.nc
hadsicc,hadsiccstd = cutl.climatologize(cnc.getNCvar(fhadsic,'GT')) # I think, K?
hadsicp,hadsicpstd = cutl.climatologize(cnc.getNCvar(fhadsicp,'GT'))
# @@ Hurrell files are same as not doBCs
fhurrsic = basepath + 'HURRELL/MODEL_SST.T42_' + timeper + 'climo.nc' #SST, degC, 128x64
fhurrsicp = basepath + 'HURRELL/MODEL_SST.T42_' + timeperp2 + 'climo.nc' #SST, degC, 128x64
else:
fhadsic = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_gt_' + timeper + 'climo.nc' #GT, K, 129x64
fhurrsic = basepath + 'HURRELL/MODEL_SST.T42_' + timeper + 'climo.nc' #SST, degC, 128x64
fhadsicp = basepath + 'HadISST/hadisst1.1_bc_128_64_1870_2013m03_gt_' + timeperp + 'climo.nc' #GT, K, 129x64
fhurrsicp = basepath + 'HURRELL/MODEL_SST.T42_' + timeperp2 + 'climo.nc' #SST, degC, 128x64
hadsicc = cnc.getNCvar(fhadsic,'GT') # I think, K?
hadsicp = cnc.getNCvar(fhadsicp,'GT')
# CanESM2 uses BC files regardless of doBCs flag
fcansic = basepath2 + 'CanESM2/GT_BC_CanESM2_historical1979-1989_1870010100-2011020100.nc'
fcansicp = basepath2 + 'CanESM2/GTadjusted_BC_CanESM2_historical2002-2012_1870010100-2011020100_abs10thresh.nc'
# fcansicp = basepath + 'CanESM2/canesm2_kem1pert2_128x64_0001_0120_gt_0000120100-0120120100.nc' # adjusted ssts, shifted one month from above file
cansicc,cansiccstd = cutl.climatologize(cnc.getNCvar(fcansic,'GT'))
cansicp,cansicpstd = cutl.climatologize(cnc.getNCvar(fcansicp,'GT'))
hurrsicc = cnc.getNCvar(fhurrsic,'SST')+273
#hurrsicc.resize(hadsicc.shape) # can't resize like this. ??
#np.append(hurrsicc,hurrsicc[:,:,0])#,axis=2) # could not get append to work
#hurrsicc[:,:,len(lon)-1] = hurrsicc[:,:,0] # add a wraparound. nope.
#hurrsicc = np.flipud(hurrsicc) # the lats are flipped compared to hadisst and nsidc
hurrsicp = cnc.getNCvar(fhurrsicp,'SST')+273
#hurrsicc.resize(hadsicc.shape) # other datasets have extra lon.
#hurrsicp[:,:,len(lon)-1] = hurrsicp[:,:,0] # add a wraparound
#hurrsicp = np.flipud(hurrsicp) # the lats are flipped compared to hadisst and nsidc
# MASK out land & inland lakes
lsmask=con.get_t63landmask()
lsmask = np.tile(lsmask,(12,1,1))
## if flipmask:
## lsmask=np.flipud(lsmask)
hadsicc = ma.masked_where(lsmask!=0,hadsicc) # 0 is ocean
hadsicp = ma.masked_where(lsmask!=0,hadsicp) # 0 is ocean
hadsicc = hadsicc[:,:,0:-1]
hadsicp = hadsicp[:,:,0:-1]
#hurrsicc = ma.masked_where(lsmask!=0,hurrsicc) # 0 is ocean # @@ BOGUS
cansicc = ma.masked_where(lsmask!=0,cansicc) # 0 is ocean
cansicp = ma.masked_where(lsmask!=0,cansicp) # 0 is ocean
cansicc = cansicc[:,:,0:-1]
cansicp = cansicp[:,:,0:-1]
hadsicd = hadsicp-hadsicc
hurrsicd = hurrsicp-hurrsicc
cansicd = cansicp-cansicc
lat = cnc.getNCvar(fhadsic,'lat') # just adjust Hurrell data, which is flipped
lon = cnc.getNCvar(fhadsic,'lon') # same for all datasets
lon = lon[0:-1]
if testsic==0:
if had:
## hadsicc = hadsicc[:,:,0:-1]
## hadsicp = hadsicp[:,:,0:-1]
## #hadsiccclimo = hadsiccclimo[:,:,0:-1] # @@ shouldn't need anymore? already tested
## #hadsicpclimo = hadsicpclimo[:,:,0:-1]
## hadsicd = hadsicp-hadsicc
#hadsicclimod = hadsicpclimo-hadsiccclimo
plotflds=hadsicd
dset = 'HadISST'
title = dset + ' (' + timeperp2 + ')-(' + timeper + ')'
savstr=timeperp2 + 'min' + timeper
elif hurr:
lathurr = cnc.getNCvar(fhurrsic,'lat')
hurrsicd = hurrsicp-hurrsicc
plotflds=hurrsicd
lat=lathurr
flipmask=1
dset = 'HURRELL'
title = dset + ' (' + timeperp2 + ')-(' + timeper + ')'
savstr=timeperp2 + 'min' + timeper
elif canesm:
dset = 'CanESM2'
if plotseacycmag:
# get ground cover, GC
#testcase = 'kemctl1'; plotflds = cansicc # ?? @@
#testcase = 'kem1pert2'; plotflds = cansicp
testcase = 'kem1pert1'; plotflds = cansicc # same SSTs as control, will use the GC from this run
filen = '/home/rkm/work/DATA/CanAM4/' + testcase + '/ts/' + testcase + '_gc_001-111_ts.nc'
gcts = cnc.getNCvar(filen,'GC',timesel='0002-01-01,0111-12-31')
filen = '/home/rkm/work/DATA/CanAM4/' + testcase + '/ts/' + testcase + '_gc_001-111_climo.nc'
gcclimo = cnc.getNCvar(filen,'GC') # -1 land/sea ice>.15, 0 sea
# to test for sea (0), have to use np.isclose() with tolerance 1e-9
# because the numbers are actually very close to zero but not exactly.
gctsoneyr = gcts[0:12,:,:-1]
cminscm = -40; cmaxscm = 40
title = dset + ' ' + testcase + ' SEACYC Magnitude (' + timeper + ')'
savstr=timeper + 'seacycmag'
else:
plotflds=cansicd
title = dset + ' (' + timeperp + ')-(' + timeper + ')'
savstr=timeperp + 'min' + timeper
else:
#nsidc
if sicn==0:
print 'No SST or SIC dataset for NSIDC!'
exit()
plotflds=nsidcsicd
dset = 'NSIDCbootstrap'
title = ' (' + timeperp2 + ')-(' + timeper + ')'
savstr=timeperp2 + 'min' + timeper
cmlen = float(15)
if diffobs: # difference CanESM and HadISST
plotfld = cansicd - hadsicd
cplt.map_allmonths(plotfld,lat,lon,cmin=cmind,cmax=cmaxd,title='CanESM-HadISST ' + field,type='nh',cmap=cmap)
if printtofile==1:
plt.savefig('CanESM-HadISST_' + field + 'diffs_abt' + savstr + '_allmos_nh.pdf')
cplt.map_allmonths(plotfld,lat,lon,cmin=cmind,cmax=cmaxd,title='CanESM-HadISST ' + field,cmap=cmap)
if printtofile==1:
plt.savefig('CanESM-HadISST_' + field + 'diffs_abt' + savstr + '_allmos_sq.pdf')
if plotseacycmag: # only for CanESM2 SST
maxfld = np.max(plotflds,axis=0)
maxidx = np.argmax(plotflds,axis=0)
minfld = np.min(plotflds,axis=0)
minfld2 = np.min(ma.masked_where(gctsoneyr==1,plotflds),axis=0)
minidx = np.argmin(plotflds,axis=0)
janfld = plotflds[0,:,:]
julfld = plotflds[6,:,:]
seacycmon = julfld - janfld
seacycmag = maxfld - minfld
# PLOT SEASONAL CYCLE MAG as a map
figa,axs = plt.subplots(1,2)
bm,pc = cplt.kemmap(seacycmon,lat,lon,cmin=cminscm,cmax=cmaxscm,cmap=cmap,
type=mtype,axis=axs[0],suppcb=1,lmask=1,flipmask=flipmask)
axs[0].set_title('Jul - Jan')
bm,pc = cplt.kemmap(seacycmag,lat,lon,cmin=cminscm,cmax=cmaxscm,cmap=cmap,
type=mtype,axis=axs[1],suppcb=1,lmask=1,flipmask=flipmask)
axs[1].set_title('Max - Min')
cbar_ax = figa.add_axes([.91,.25,.02,.5])
figa.colorbar(pc,cax=cbar_ax)
lons, lats = np.meshgrid(lon,lat)
## # PLOT MINIMUM GT: shouldn't get below freezing in the sea (GC=0)
## figb,axs = plt.subplots(1,1)
## bm,pc = cplt.kemmap(minfld2,lat,lon,cmin=238,cmax=308,cmap='blue2red_20',
## type=mtype,axis=axs,lmask=1,flipmask=flipmask)
## bm.contour(lons,lats,minfld2,levels=[273, 273],colors='k',linewidths='2',latlon=True)
## axs.set_title('Min GT')
plotfldsm = ma.masked_where(np.logical_or(gctsoneyr==-1,gctsoneyr==1),plotflds)
# PLOT MAP FOR ALL MONTHS
months = con.get_mon()
midx=0
fig,axx = plt.subplots(2,6)
fig.set_size_inches(12,6)
fig.subplots_adjust(hspace=.05,wspace=.05)
# These figures look good: where colder than 271.2, the surface isn't SEA (0), for kemctl1
for ax in axx.flat:
plotfld = plotfldsm[midx,:,:];
bm,pc = cplt.kemmap(plotfld,lat,lon,cmin=236.2,cmax=306.2,cmap='blue2red_20',
type=mtype,axis=ax,suppcb=1,lmask=1,flipmask=flipmask)
bm.contour(lons,lats,plotfld,levels=[271.2, 271.2],colors='k',linewidths='2',latlon=True)
ax.set_title(months[midx])
midx=midx+1
cbar_ax = fig.add_axes([.91,.25,.02,.5])
fig.colorbar(pc,cax=cbar_ax)
plt.suptitle(testcase + ' SST masked')
if printtofile:
fig.savefig('SSTfreezecont_' + testcase + '_allmos_nh.png')
cellareas = cutl.calc_cellareas(lat,lon)
cellareasall = ma.zeros((12,) + cellareas.shape)
polcellareas = ma.zeros((12,) + cellareas.shape)
polplotfldsm = ma.zeros((12,) + cellareas.shape)
totalarea = np.zeros((12,))
plotfldsmNth = np.zeros((12,))
for moidx in range(0,12):
cellareasall[moidx,:,:] = ma.masked_where(np.logical_or(gctsoneyr[moidx,:,:]==-1,gctsoneyr[moidx,:,:]==1),cellareas)
polcellareas[moidx,:,:] = ma.masked_where(lats>=latlim,cellareasall[moidx,:,:])
polplotfldsm[moidx,:,:] = ma.masked_where(lats>=latlim,plotfldsm[moidx,:,:])
totalarea[moidx] = np.sum(polplotfldsm[moidx,:,:])
wgts = polcellareas[moidx,:,:]/totalarea[moidx]
plotfldsmNth[moidx] = np.average(polplotfldsm[moidx,:,:],weights=wgts)
fig = plt.figure()
plt.plot(np.arange(1,13),plotfldsmNth,'k');
plt.title(testcase + ' Average SST North of ' + str(latlim) + 'N where GC=0')
plt.ylim((270,286))
plt.xlim((1,12))
if printtofile:
fig.savefig('SST' + str(latlim) + 'Nseamask_' + testcase + '_seascyc.pdf')
if plotallmos:
incr = (cmaxm-cminm) / cmlen
conts = np.arange(cminm,cmaxm+incr,incr)
months = con.get_mon()
midx=0
fig,axx = plt.subplots(2,6)
fig.set_size_inches(12,6)
fig.subplots_adjust(hspace=.05,wspace=.05)
for ax in axx.flat:
plotfld = plotflds[midx,:,:];
bm,pc = cplt.kemmap(plotfld,lat,lon,cmin=cminm,cmax=cmaxm,cmap=cmap,
type=mtype,axis=ax,suppcb=1,lmask=1,flipmask=flipmask)
ax.set_title(months[midx])
midx=midx+1
cbar_ax = fig.add_axes([.91,.25,.02,.5])
fig.colorbar(pc,cax=cbar_ax)
plt.suptitle(title)
if printtofile:
if sicn:
fig.savefig(dset + '_sicn' + bcstr + '_' + savstr + '_allmos_' + mtype + 'smclim.pdf')
elif sic:
fig.savefig(dset + '_sic' + bcstr + '_' + savstr + '_allmos_' + mtype + '.pdf')
else:
fig.savefig(dset + '_sst' + bcstr + '_' + savstr + '_allmos_' + mtype + '.pdf')
if plotseacyc:
if sicn:
# calc sea ice area
# mult fraction by grid cell area & sum
areas = cutl.calc_cellareas(lat,lon)
## plt.figure()
## plt.pcolor(areas)
## plt.colorbar()
areas = np.tile(areas,(12,1,1))
#hadsicc = ma.masked_outside(hadsicc,0,1) #@@ need this? No.
#hadsicp = ma.masked_outside(hadsicp,0,1)
hadsiac = hadsicc*areas
hadsiap = hadsicp*areas
hadsiacclimo = hadsiccclimo*areas
hadsiapclimo = hadsicpclimo*areas
hurrsiac = hurrsicc*areas
hurrsiap = hurrsicp*areas
nsidcsiac = nsidcsicc*areas
nsidcsiap = nsidcsicp*areas
cansiac = cansicc*areas
cansiap = cansicp*areas
## plt.figure()
## plt.pcolor(sia[0,:,:])
## plt.colorbar()
## plt.figure()
## plt.pcolor(hadsicc[0,:,:])
## plt.colorbar()
hadsiacnh = np.sum(np.sum(hadsiac[:,lat>0,:],2),1)
hadsiapnh = np.sum(np.sum(hadsiap[:,lat>0,:],2),1)
## Climos are exactly the same as above! good
## hadsiacclimonh = np.sum(np.sum(hadsiacclimo[:,lat>0,:],2),1)
## hadsiapclimonh = np.sum(np.sum(hadsiapclimo[:,lat>0,:],2),1)
hurrsiacnh = np.sum(np.sum(hurrsiac[:,lat>0,:],2),1)
hurrsiapnh = np.sum(np.sum(hurrsiap[:,lat>0,:],2),1)
nsidcsiacnh = np.sum(np.sum(nsidcsiac[:,lat>0,:],2),1)
nsidcsiapnh = np.sum(np.sum(nsidcsiap[:,lat>0,:],2),1)
cansiacnh = np.sum(np.sum(cansiac[:,lat>0,:],2),1)
cansiapnh = np.sum(np.sum(cansiap[:,lat>0,:],2),1)
## siash = np.sum(np.sum(sia[:,lat<0,:],2),1)
## siag = np.sum(np.sum(sia,2),1)
fig = plt.figure()
plt.plot(hadsiacnh,'k'); plt.plot(hadsiapnh,'k--')
#plt.plot(hurrsiacnh,'b'); plt.plot(hurrsiapnh,'b--') # SCREWY
plt.plot(nsidcsiacnh,'r'); plt.plot(nsidcsiapnh,'r--')
plt.plot(cansiacnh,'g'); plt.plot(cansiapnh,'g--')
plt.plot(hadsiacclimonh,'c'); plt.plot(hadsiapclimonh,'c--')
plt.legend(('HadISST 1979-89','HadISST 2002-11',
'NSIDCbt 1979-89','NSIDCbt 2002-11',
'CanESM2 1979-89','CanESM2 2002-12'),'lower left')
plt.title('Arctic SICN')
if printtofile:
fig.savefig('SICNNH_seascyc_OBS.pdf')
fig = plt.figure();
plt.plot(hadsiapnh-hadsiacnh,'k')
plt.plot(nsidcsiapnh-nsidcsiacnh,'r')
plt.plot(cansiapnh-cansiacnh,'g')
plt.legend(('HadISST DIFF','NSIDCbt DIFF','CanESM2 DIFF'),'lower left')
plt.title('difference in Arctic SICN (2002-11/12 vs 1979-89)')
if printtofile:
fig.savefig('SICNNHDIFF_seascyc_OBS.pdf')
fig = plt.figure();
plt.plot((hadsiapnh-hadsiacnh)/hadsiacnh*100,'k')
plt.plot((nsidcsiapnh-nsidcsiacnh)/nsidcsiacnh*100,'r')
plt.plot((cansiapnh-cansiacnh)/cansiacnh*100,'g')
plt.legend(('HadISST DIFF','NSIDCbt DIFF','CanESM2 DIFF'),'lower left')
plt.title('% difference in Arctic SICN (2002-11/12 vs 1979-89)')
if printtofile:
fig.savefig('SICNNHDIFFpct_seascyc_OBS.pdf')
elif sic:
# calculate average NH sea ice thickness for each month
areas = cutl.calc_cellareas(lat,lon)
areas = np.tile(areas,(12,1,1))
# only NH sic
hadsiccnh = hadsicc[:,lat>0,:]
hadsicpnh = hadsicp[:,lat>0,:]
# need sea ice area too
hadsicnc = hadsicnc[:,:,0:-1]
hadsicnp = hadsicnp[:,:,0:-1]
hadsiac = hadsicnc*areas
hadsiap = hadsicnp*areas
# only NH
hadsiacnh = hadsiac[:,lat>0,:]
hadsiapnh = hadsiap[:,lat>0,:]
# total sea ice area for area weighting
hadtotsiacnh = np.sum(np.sum(hadsiacnh,2),1) # total for each month
hadtotsiapnh = np.sum(np.sum(hadsiapnh,2),1)
# tile totalsia to shape of grid
hadtotsiacnh = np.tile(hadtotsiacnh,(hadsiacnh.shape[1],hadsiacnh.shape[2],1))
hadtotsiacnh = np.transpose(hadtotsiacnh,(2,0,1))
hadtotsiapnh = np.tile(hadtotsiapnh,(hadsiapnh.shape[1],hadsiapnh.shape[2],1))
hadtotsiapnh = np.transpose(hadtotsiapnh,(2,0,1))
# average thickness
hadsiccnhavg = np.sum(np.sum(hadsiccnh/913*(hadsiacnh/hadtotsiacnh),2),1)
hadsicpnhavg = np.sum(np.sum(hadsicpnh/913*(hadsiapnh/hadtotsiapnh),2),1)
# total volume: thickness * SIA
hadsivcnh = np.sum(np.sum(hadsiccnh/913 * hadsiacnh,2),1)
hadsivpnh = np.sum(np.sum(hadsicpnh/913 * hadsiapnh,2),1)
# do CanESM
cansiac = cansicnc*areas
cansiap = cansicnp*areas
# only NH
cansiccnh = cansicc[:,lat>0,:]
cansicpnh = cansicp[:,lat>0,:]
cansiacnh = cansiac[:,lat>0,:]
cansiapnh = cansiap[:,lat>0,:]
# total sea ice area for area weighting
cantotsiacnh = np.sum(np.sum(cansiacnh,2),1) # total for each month
cantotsiapnh = np.sum(np.sum(cansiapnh,2),1)
# tile totalsia to shape of grid
cantotsiacnh = np.tile(cantotsiacnh,(cansiacnh.shape[1],cansiacnh.shape[2],1))
cantotsiacnh = np.transpose(cantotsiacnh,(2,0,1))
cantotsiapnh = np.tile(cantotsiapnh,(cansiapnh.shape[1],cansiapnh.shape[2],1))
cantotsiapnh = np.transpose(cantotsiapnh,(2,0,1))
# average thickness
cansiccnhavg = np.sum(np.sum(cansiccnh/913*(cansiacnh/cantotsiacnh),2),1)
cansicpnhavg = np.sum(np.sum(cansicpnh/913*(cansiapnh/cantotsiapnh),2),1)
# total volume: thickness * SIA
cansivcnh = np.sum(np.sum(cansiccnh/913 * cansiacnh,2),1)
cansivpnh = np.sum(np.sum(cansicpnh/913 * cansiapnh,2),1)
fig = plt.figure()
plt.plot(hadsiccnhavg,'k'); plt.plot(hadsicpnhavg,'k--')
plt.plot(cansiccnhavg,'g'); plt.plot(cansicpnhavg,'g--')
plt.legend(('HadISST 1979-89','HadISST 2002-11',
'CanESM2 1979-89','CanESM2 2002-12'),'lower left')
plt.title('Arctic SIC')
if printtofile:
fig.savefig('SICNH_seascyc_OBS.pdf')
fig = plt.figure()
plt.plot(hadsivcnh,'k'); plt.plot(hadsivpnh,'k--')
plt.plot(cansivcnh,'g'); plt.plot(cansivpnh,'g--')
plt.legend(('HadISST 1979-89','HadISST 2002-11',
'CanESM2 1979-89','CanESM2 2002-12'),'lower left')
plt.title('Total Arctic Sea Ice Volume')
if printtofile:
fig.savefig('SICNHTotVol_seascyc_OBS.pdf')
else:
# calc average SST near sea-ice (where exactly?)
hadsstc60N = cutl.polar_mean_areawgted3d(hadsicc,lat,lon,latlim=latlim)
hadsstp60N = cutl.polar_mean_areawgted3d(hadsicp,lat,lon,latlim=latlim)
hurrsstc60N = cutl.polar_mean_areawgted3d(hurrsicc,lat,lon,latlim=latlim)
hurrsstp60N = cutl.polar_mean_areawgted3d(hurrsicp,lat,lon,latlim=latlim)
cansstc60N = cutl.polar_mean_areawgted3d(cansicc,lat,lon,latlim=latlim)
cansstp60N = cutl.polar_mean_areawgted3d(cansicp,lat,lon,latlim=latlim)
fig = plt.figure()
plt.plot(hadsstc60N,'k'); plt.plot(hadsstp60N,'k--')
#plt.plot(hurrsstc60N,'b'); plt.plot(hurrsstp60N,'b--') # SCREWY
plt.plot(cansstc60N,'g'); plt.plot(cansstp60N,'g--')
plt.legend(('HadISST 1979-89','HadISST 2002-11',
'CanESM2 1979-89','CanESM2 2002-12'),'lower center')
plt.title('Average SST North of ' + str(latlim) + 'N')
if printtofile:
fig.savefig('SST' + str(latlim) + 'N_seascyc_OBS.pdf')
fig = plt.figure()
plt.plot(hadsstp60N-hadsstc60N,'k');
#plt.plot(hurrsstp60N-hurrsstc60N,'b');#SCREWY
plt.plot(cansstp60N-cansstc60N,'g');
plt.legend(('HadISST DIFF','CanESM2 DIFF'),'upper left')
plt.title('Average difference in SST North of ' + str(latlim) + 'N')
if printtofile:
fig.savefig('SST' + str(latlim) + 'NDIFF_seascyc_OBS.pdf')
if testsic:
lat = cnc.getNCvar(fhadsicorig,'lat')
lon = cnc.getNCvar(fhadsicorig,'lon')
sic = cnc.getNCvar(fhadsicorig,'SIC')
sicn = cnc.getNCvar(fhadsicnorig,'SICN')
sicANN = cutl.annualize_monthlyts(sic)
sicANN=sicANN[:,:,0:-1]
sicANNnh = sicANN[:,lat>0,:]
sicnANN = cutl.annualize_monthlyts(sicn)
sicnANN=sicnANN[:,:,0:-1]
sicnANNnh = sicnANN[:,lat>0,:]
areas = cutl.calc_cellareas(lat,lon)
areas = np.tile(areas,(sicANN.shape[0],1,1))
areasnh = areas[:,lat>0,0:-1]
totalareanh=np.sum(np.sum(areasnh,2),1)
siaANNnh = sicnANNnh*areasnh
totalsianh = np.sum(np.sum(siaANNnh,2),1)
totalsianh = np.tile(totalsianh,(sicANNnh.shape[1],sicANNnh.shape[2],1))
totalsianh = np.transpose(totalsianh,(2,0,1))
sicANNnhavg = np.sum(np.sum(sicANNnh/913*(areasnh/totalareanh[0]),2),1)
sicANNnhavg2 = np.sum(np.sum(sicANNnh/913*(siaANNnh/totalsianh),2),1)
years = range(1870,2013)
plt.figure()
#plt.plot(sicANNnhavg)
plt.plot(years,sicANNnhavg2,'k')
plt.title('HadISST NH average SIC (m)')
plt.xlim(1870,2012)
if printtofile:
plt.savefig('HadISST_SICnh_timeseries.pdf')