""" createallmonthBCsclimo.py

4/16/2014

taken from createallmonthsBCsclimo.m, which was on macbook pro

"""

import copy

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 as ccm

cplt = reload(cplt)

con = reload(con)

cutl = reload(cutl)

ccm = reload(ccm)

cnc = reload(cnc)

plt.close("all")

plt.ion()

# # # ########## Read NC data ###############

plat = platform.system()

months = con.get_mon()

writefiles = True

skipcontrolwrite=False # skip writing control BC files

testplots = False

doobs=True # 7/8/2014. if True, do obs data

dset='NSIDC'; dtype='bootstrap' # or HadISST,''

field = 'sit' # 'ts', 'sic', 'sit' # these are the model output CMIP names

adjustsst=True # for field='ts'

threshtype = 'abs' # when field='ts' and adjustsst=1. absolute or relative threshold for sea ice conc change

thresh = 10 #when field='ts' and adjustsst=1. threshold for where to change SST

controlsit=0 # for field='sit'. set to 1 if want to keep the control sit.

usesictest=1 # for field='sit' and controlsit=1. use pert sea ice conc to check where sit=0

ensmembers = 0; eindex=4 # make BC files for specified CanESM ensemble member

casenamec = 'historical'; timeperc = '1979-1989'

#casename = 'rcp85';

#timeper = '2022-2032'

#timeper = '2042-2052'

casename = 'historicalrcp45'; timeper='2002-2012' # test against matlab-generated BCs

deni = 913. # kg/m3 density of ice

if field == 'ts': # Surface Temperature (K)

units = 'K';

clims=[236.2, 306.2]

if casename == 'rcp85':

climsdiff=[-4, 4]

else:

climsdiff=[-2, 2]

cmap='kem_w20'; cmapclimo='blue2red_20'; # actually only 18 colors...

bcfield='GT'

bcdescrip='ground temperature (K)'

bcunits='K'

elif field == 'sic': # Sea Ice Fraction (%)

timeres = 'OImon'

lmaskflag='lmaskon'

units = '%'

clims=[0, 1]

climsdiff=[-.15, .15]

cmap='red2blue_w20'

cmapclimo='Spectral' #'sicclimo_12' # @@ don't think i have in python yet

bcfield='SICN'

bcdescrip='sea ice fraction'

bcunits='frac'# '%' # I think this is an error, should be frac. changed 7/8/2014 but not in bc files up through kem1pert2r4ct

elif field == 'sit':

timeres='OImon'

lmaskflag='lmaskon'

units = 'm'

clims=[-2.5*deni, 2.5*deni] # for now set clims like this until have a better cmap

climsdiff=[-.5*deni, .5*deni] # @@@

cmap='red2blue_w20'

cmapclimo= 'Spectral'# @@ don't have yet? 'sitclimo_12'

bcfield='SIC'

bcdescrip='sea ice thickness*density'

bcunits='kg/m2'

else:

'No such field: ' + field

# set up filenames

if doobs:

# do observational data

if plat == 'Darwin': # means I'm on my mac

basepath = '/Volumes/MyPassport1TB/DATA/CanSISE/'

basepath2 = '/Users/kelly/CCCma/CanSISE/BoundaryConditionFiles/'

else: # on linux workstation in Vic

basepath = '/home/rkm/work/BCs/'

basepath2 = '/home/rkm/work/BCs/'

timeper = '2002-2011'

# ########### from matlab

if dset=='HadISST': # grid 64 x 129

if field=='ts':

prfield='gt'

#ncfield='GT'

bcfield='GT'

bcdescrip='ground temperature (K)'

bcunits='K'

units='K'

#climsdiff=[-1, 1]

climsdiff=[-2, 2]

clims=[236.2, 306.2]

lmaskflag='lmaskon'

#conv=1

cmap='kem_w20'; cmapclimo='blue2red_20'; # actually only 18 colors...

elif field=='sic':

prfield='sicn'

#ncfield='SICN'

bcfield='SICN'

bcdescrip='sea ice fraction (frac)'

bcunits='frac'

units='frac'

climsdiff=[-.15, .15]

clims=[0, 1]

lmaskflag='lmaskon'

#conv=1

cmap='red2blue_w20'

cmapclimo='Spectral' #'sicclimo_12' # @@ don't think i have in python yet

elif field=='sit':

prfield='sic'

lmaskflag='lmaskon'

units = 'm'

clims=[-2.5*deni, 2.5*deni]

climsdiff=[-.5*deni, .5*deni]

cmap='red2blue_w20'

cmapclimo= 'Spectral'# @@ don't have yet? 'sitclimo_12'

bcfield='SIC'

bcdescrip='sea ice thickness*density'

bcunits='kg/m2'

filename = basepath + dset + '/hadisst1.1_bc_128_64_1870_2013m03_' + prfield + '_' + timeper + 'climo.nc'

filenamec = basepath + dset + '/hadisst1.1_bc_128_64_1870_2013m03_' + prfield + '_' + timeperc + 'climo.nc'

sicfnamep = basepath + dset + '/hadisst1.1_bc_128_64_1870_2013m03_sicn_' + timeper + 'climo.nc'

sicfnamec = basepath + dset + '/hadisst1.1_bc_128_64_1870_2013m03_sicn_' + timeperc + 'climo.nc'

elif dset == 'NSIDC': # grid 64 x 129

if field=='ts':

# @@ READ HadISST sst

prfield='gt'

#ncfield='GT'

bcfield='GT'

bcdescrip='ground temperature (K)'

bcunits='K'

units='K'

#climsdiff=[-1, 1]

climsdiff=[-2, 2]

clims=[236.2, 306.2]

lmaskflag='lmaskon'

#conv=1

cmap='kem_w20'; cmapclimo='blue2red_20'; # actually only 18 colors...

elif field=='sic':

prfield='sicn'

#ncfield='SICN'

bcfield='SICN'

bcdescrip='sea ice fraction (frac)'

bcunits='frac'

units='frac'

climsdiff=[-.15, .15]

clims=[0, 1]

lmaskflag='lmaskon'

#conv=1

cmap='red2blue_w20'

cmapclimo='Spectral' #'sicclimo_12' # @@ don't think i have in python yet

fbase='nsidc_bt_128x64_1978m11_2011m12'

elif field=='sit':

prfield='sic'

lmaskflag='lmaskon'

units = 'm'

clims=[-2.5*deni, 2.5*deni]

climsdiff=[-.5*deni, .5*deni]

cmap='red2blue_w20'

cmapclimo= 'Spectral'# @@ don't have yet? 'sitclimo_12'

bcfield='SIC'

bcdescrip='sea ice thickness*density'

bcunits='kg/m2'

filename = basepath + dset + '/nsidc_bt_128x64_1978m11_2011m12_' + prfield + '_' + timeper + 'climo.nc'

filenamec = basepath + dset + '/nsidc_bt_128x64_1978m11_2011m12_' + prfield + '_' + timeperc + 'climo.nc'

sicfnamep = basepath + dset + '/nsidc_bt_128x64_1978m11_2011m12_sicn_' + timeper + 'climo.nc'

sicfnamec = basepath + dset + '/nsidc_bt_128x64_1978m11_2011m12_sicn_' + timeperc + 'climo.nc'

# ############ end from matlab

# end if doobs

else:

model = 'CanESM2'

timeres = 'Amon'

# Read in CanESM2 data, "pert" first

if plat == 'Darwin': # means I'm on my mac

#basepath = '/Users/kelly/CCCma/CanSISE/DATA/' # @@@

basepath = '/Volumes/MyPassport1TB/DATA/CanSISE/'

basepath2 = '/Users/kelly/CCCma/CanSISE/BoundaryConditionFiles/'

else: # on linux workstation in Vic

basepath = '/home/rkm/work/DATA/'

basepath2 = '/home/rkm/work/BCs/'

enstype = 'ens'

if ensmembers:

enstype = 'r' + str(eindex) + 'i1p1'

filename = basepath + model + '/' + casename + '/' + field + '/' + \

field + '_' + timeres + '_' + model + '_' + casename + \

'_' + enstype + '_' + timeper + 'climo.nc'

# control time period is in the historical run

filenamec = basepath + model + '/' + casenamec + '/' + field + '/' + \

field + '_' + timeres + '_' + model + '_' + casenamec + \

'_' + enstype + '_' + timeperc + 'climo.nc'

landmask = con.get_t63landmask()

if doobs:

pass # do not remove wraparound lon

else:

landmask=landmask[...,:-1]

landmask = np.tile(landmask,(12,1,1))

print filename

timefldp = cnc.getNCvar(filename,'time')

lat = cnc.getNCvar(filename,'lat')

lon = cnc.getNCvar(filename,'lon')

if doobs:

fldp = cnc.getNCvar(filename,bcfield)

fldc = cnc.getNCvar(filenamec,bcfield)

else:

fldp = cnc.getNCvar(filename,field)

fldc = cnc.getNCvar(filenamec,field) # we should only need this to set SSTs in near-future BCs

print filenamec

if field == 'ts' and adjustsst:

# assume adjustsst will always be true now

print 'TS and adjustsst'

# also need to get sea-ice concentration to know where to set pert SSTs

if doobs:

# make fraction into percent to match the model output

sicp = cnc.getNCvar(sicfnamep,'SICN')*100 # field is SICN for HadISST and NSIDC

sicc = cnc.getNCvar(sicfnamec,'SICN')*100

else:

filename = basepath + model + '/' + casename + '/sic/' + \

'sic_OImon_' + model + '_' + casename + \

'_' + enstype + '_' + timeper + 'climo.nc'

sicp = cnc.getNCvar(filename,'sic')

print filename

filename = basepath + model + '/' + casenamec + '/sic/' + \

'sic_OImon_' + model + '_' + casenamec + \

'_' + enstype + '_' + timeperc + 'climo.nc'

print filename

sicc = cnc.getNCvar(filename,'sic')

sicd = sicp - sicc

sicpctd = (sicp-sicc)/sicc*100

fldsave = copy.copy(fldp) # save original pert for comparison & calcs

fldp = copy.copy(fldc) # start off with control

# Now where sea ice change > thresh, set the pert SST

if threshtype == 'abs':

fldp[sicd<=-thresh] = fldsave[sicd<=-thresh] # @@ will this work in python?

else:

fldp[sicpctd<=-thresh] = fldsave[sicpctd<=-thresh]

# Now, also need to check that any open water is not < 271.2 @@

#print "Not done: check no open water is < 271.2"

# ideally don't want to change these vals over land though. landmask==-1

fldptmp=copy.copy(fldp)

fldptmp=ma.masked_where(np.logical_and(landmask != -1,fldptmp<271.2),fldptmp) # first mask out cold temps where not land

fldp[np.logical_and(sicp<=15,fldptmp.mask)] = 271.2 # where SIC is less than 15% (ie "no ice") and not land and it's too cold, set to freezing

#badsst = ma.masked_where(np.logical_and(sicp<=.15,fldp<=271.2),fldp)

#cplt.map_allmonths(badsst,lat,lon,cmin=238,cmax=308,cmap='blue2red_20',type='nh',lmask=1)

elif field == 'ts' and ~adjustsst:

# perturbation is just control with a check for open water < 271.2K

print 'TS and ~adjustsst'

fldp = copy.copy(fldc)

if doobs:

# make fraction into percent to match the model output

sicp = cnc.getNCvar(sicfnamep,'SICN')*100 # field is SICN for HadISST and NSIDC

else:

# also need to get pert sea-ice concentration to check open water temp against SIConc

filename = basepath + model + '/' + casename + '/sic/' + \

'sic_OImon_' + model + '_' + casename + \

'_' + enstype + '_' + timeper + 'climo.nc'

print filename

sicp = cnc.getNCvar(filename,'sic')

#print "Not done: check no open water is < 271.2"

fldptmp=copy.copy(fldp)

# mask anywhere that is not land and below icefreeze

fldptmp=ma.masked_where(np.logical_and(landmask!=-1,fldptmp<271.2),fldptmp)

# anywhere that is not land, below icefreeze AND has sea-ice conc<.15, set to 271.2

# flddum = fldp[np.logical_and(sicp<=15,fldptmp.mask)]

fldp[np.logical_and(sicp<=15,fldptmp.mask)] = 271.2

#badsstnoadj = ma.masked_where(np.logical_and(sicp<=.15,fldp<=271.2),fldp)

#cplt.map_allmonths(badsst,lat,lon,cmin=238,cmax=308,cmap='blue2red_20',type='nh',lmask=1)

fldsave=copy.copy(fldc)

elif field == 'sic':

if doobs:

pass # already fractional

else:

fldc = fldc/100 # should be fractional

fldp = fldp/100

fldsave=copy.copy(fldp) # dummy

elif field == 'sit' and controlsit:

# keep control sit

if doobs:

pass # already a mass

else:

fldc = fldc*deni

fldp = fldp*deni

if usesictest==1: #use pert sea ice concentration as the check

# this is the one we use for kem1pert3

# need to get pert sea-ice concentration to check thickness against SIConc

if doobs:

# make fraction into percent to match the model output

sicp = cnc.getNCvar(sicfnamep,'SICN')*100 # field is SICN for HadISST and NSIDC

else:

filename = basepath + model + '/' + casename + '/sic/' + \

'sic_OImon_' + model + '_' + casename + \

'_' + enstype + '_' + timeper + 'climo.nc'

print filename

sicp = cnc.getNCvar(filename,'sic')

fldtmp = copy.copy(fldc) # start with control thickness

# @@@ should this actually be, anywhere pert sic is <0.15? since the model apparently considers it open water if conc<0.15

fldtmp[sicp<0.01] = 0 # anywhere pert sic (concentration) is 0, make thickness 0

fldsave=copy.copy(fldp) # dummy, save orig pert

fldp = copy.copy(fldtmp)

print fldtmp.shape # @@

else:

#use pert sea ice thickness as the check

print 'Keep control SIT with usesittest is not implemented. Do not need it anymore?' #@@

elif field == 'sit':

if doobs:

pass # already a mass

else:

fldc = fldc*deni

fldp = fldp*deni

fldsave = copy.copy(fldp) # dummy

# put SH back to control since only want to mod NH!

fldp[:,lat<=0,:] = fldc[:,lat<=0,:] # not even sure I need to do this, already started w/ control

# add wraparound lon @@

if doobs:

pass # already has wraparound lon

else:

fldc = np.dstack((fldc,fldc[...,0]))

fldp = np.dstack((fldp,fldp[...,0]))

fldsave = np.dstack((fldsave,fldsave[...,0]))

# # end setting up the BC data itself ####

# Now on to dates

# for now just get original dates

if plat == 'Darwin':

file = basepath + 'CanSISE/CanAM4/amip/uninflatedBCs/temp_gt_1870010100-2011020100.nc'

else:

file = basepath2 + 'temp_gt_1870010100-2011020100.nc'

timeoutall = cnc.getNCvar(file,'time')

datestr = '1870010100-2010120100'

repfld = len(timeoutall)/12 # want integer division

rem = np.mod(len(timeoutall),12)

# shorten timeoutall by remainder

timeoutall = timeoutall[:-rem]

fldcall = np.tile(fldc,(repfld,1,1))

fldpall = np.tile(fldp,(repfld,1,1))

# in matlab code, I add on the remainder as well (ie 2 months or something).

# @@ necessary here? it's harder to add this in python. why do I need it?

bclat = cnc.getNCvar(file,'lat')

bclon = cnc.getNCvar(file,'lon')

#timepers = '1979-1989', '2022-2032', # '2042-2052'

outflds = {}

outflds[timeperc] = fldcall

outflds[timeper] = fldpall

casenames = {}

casenames[timeperc] = casenamec

casenames[timeper] = casename

############### TEST PLOTS ###############################

if testplots:

## This was to test the selmon operation in CDO

## fldtest = np.zeros((12,len(lat),len(lon)))

## midx=1

## for mon in months:

## fldtest[midx-1,...] = cnc.getNCvar(filenamec,field,monsel=midx)# climo file

## midx=midx+1

## fig1 = cplt.map_allmonths(fldtest,lat,lon,title='CDO selmon',cmin=clims[0],cmax=clims[1],type='nh',climo=1)

if field == 'sic' or field == 'sit':

plotfldp = ma.masked_where(fldp<=0,fldp)

plotfldc = ma.masked_where(fldc<=0,fldc)

else:

plotfldc = fldc

plotfldp = fldp

pparams = dict(type='nh',cmin=clims[0],cmax=clims[1],cmap=cmapclimo)

if field == 'ts':

pparams['conts'] = 271.2

figp = cplt.map_allmonths(plotfldp,bclat,bclon, title='pert ' + field,**pparams)

figc = cplt.map_allmonths(plotfldc,bclat,bclon, title='ctrl ' + field,**pparams)

figd = cplt.map_allmonths(fldp-fldc,bclat,bclon, title='diff',type='nh',cmin=climsdiff[0],cmax=climsdiff[1],cmap=cmap)

if field == 'ts':

figd2 = cplt.map_allmonths(fldp-fldsave,bclat,bclon, title='pert - originalpert',type='nh',cmin=climsdiff[0],cmax=climsdiff[1],cmap=cmap)

figd3 = cplt.map_allmonths(fldsave-fldc,bclat,bclon, title='originalpert - control',type='nh',cmin=climsdiff[0],cmax=climsdiff[1],cmap=cmap)

figcsq = cplt.map_allmonths(plotfldc,bclat,bclon, title='ctrl ' + field,type='sq',cmin=clims[0],cmax=clims[1],cmap=cmapclimo)

figdsq = cplt.map_allmonths(plotfldp-plotfldc,bclat,bclon, title='diff',type='sq',cmin=climsdiff[0],cmax=climsdiff[1],cmap=cmap)

############### Write the NetCDF file ####################

from netCDF4 import Dataset

if writefiles:

for thetimeper in outflds.keys():

if thetimeper==timeperc and skipcontrolwrite:

pass

else:

print thetimeper

fldout = outflds[thetimeper]

casenameout = casenames[thetimeper]

if ensmembers:

casenameout = casenameout + 'r' + str(eindex)

print fldout.shape

# note that timeper is the perturbed time period

# casenameout is the current casenames element

# If pert time period and adjusted SST:

if thetimeper==timeper and field == 'ts' and adjustsst:

if doobs:

outfile=bcfield + 'adjusted_BC_' + dset + dtype + '_' + thetimeper + '_' +\

datestr + '_' + threshtype + str(thresh) + 'threshnc3.nc'

nctitle = 'Boundary condition dataset generated from ' + dset + dtype +\

' ' + thetimeper + ' adjusted with ' + outflds.keys()[1] +\

' where SIC ' + threshtype + ' change is >=10%'

if dset=='NSIDC':

nctitle = nctitle + '. Original SSTs from HadISST1.1'

else:

outfile= bcfield + 'adjusted_BC_CanESM2_' + casenameout + '_' + thetimeper + '_' +\

datestr + '_' + threshtype + str(thresh) + 'threshnc3.nc'

nctitle = 'Boundary condition dataset generated from CanESM2 ' +\

casenamec + ' ' + outflds.keys()[0] + ', adjusted with ' +\

casename + ' ' + outflds.keys()[1] + ' where SIC ' + threshtype + ' change is >=10%'

# If pert time period and unadjusted SST:

elif thetimeper==timeper and field == 'ts' and ~adjustsst:

if ensmembers:

outfile = bcfield + 'frzchk' + casename + 'r' + str(eindex) + timeper + '_BC_CanESM2_' +\

casenamec + 'r' + str(eindex) + '_' + timeperc + '_' + datestr + 'nc3.nc'

else:

if doobs:

print 'not planning on needing to make these! @@ No filename'

# really should throw exception or something @@

else:

outfile = bcfield + 'frzchk' + casename + timeper + '_BC_CanESM2_' +\

casenamec + '_' + timeperc + '_' + datestr + 'nc3.nc'

# the data is the control, but open water temps are checked for below freezing where no pert ice

nctitle = 'Boundary condition dataset generated from CanESM2 ' +\

casenamec + ' ' + outflds.keys()[0] + ', but open water <271.2K in ' +\

casename + ' ' + outflds.keys()[1] + ' is set to 271.2 (where SIC<15)'

# If pert time period and control SIT:

elif thetimeper==timeper and field == 'sit' and controlsit:

if usesictest:

teststr='usesictest'

else:

teststr='usesittest'

if ensmembers:

outfile=bcfield + '_BC_CanESM2_' + casenamec + 'r' + str(eindex) + '_' + timeperc + 'forpert_' +\

datestr + '_' + teststr + 'nc3.nc'

else:

if doobs:

print 'not planning on needing to make these! @@ No filename!'

# really should throw exception or something @@

else:

outfile=bcfield + '_BC_CanESM2_' + casenamec + '_' + timeperc + 'forpert_' +\

datestr + '_' + teststr + 'nc3.nc'

nctitle = 'Boundary condition dataset generated from CanESM2 ' +\

casenamec + ' ' + outflds.keys()[0] +\

', except set to zero where no ice in ' + casename + ' ' + outflds.keys()[1]

# All other cases have a "regular" outfile name

else:

if doobs:

outfile = bcfield + '_BC_' + dset + dtype + '_' + thetimeper + '_' + datestr + 'nc3.nc'

nctitle = 'Boundary condition dataset generated from ' + dset + dtype +\

' ' + thetimeper + ' climo'

if dset == 'NSIDC' and bcfield=='SIC':

nctitle = nctitle + '. Original data from HadISST thickness (originally from old Can model output)'

else:

outfile=bcfield + '_BC_CanESM2_' + casenameout + '_' + thetimeper + '_' + datestr + 'nc3.nc'

nctitle = 'Boundary condition dataset generated from CanESM2 ' +\

casenameout + ' ' + thetimeper + ' climo'

outnc = Dataset(outfile,'w',format='NETCDF3_CLASSIC')

# create the dimensions

# not sure why these need python variables, they are never used@@

# I guess they are the keys in the dict of Dimensions...

outtime = outnc.createDimension('time', None) # len(timeoutall))

outlat = outnc.createDimension('lat',len(bclat))

outlon = outnc.createDimension('lon',len(bclon))

# create variables

outtimes = outnc.createVariable('time','f8',('time',)) # f8 and d are the same dtype

outlats = outnc.createVariable('lat','d',('lat',))

outlons = outnc.createVariable('lon','d',('lon',))

outfld = outnc.createVariable(bcfield,'f4',('time','lat','lon',),fill_value=1.0e38)

# add attributes to variables

#outfld._FillValue = np.float(1.0e38) # do in variable creation step

outfld.units = bcunits

outfld.long_name = bcdescrip

outtimes.long_name = 'time'

outtimes.units = 'days since 1850-1-1'

outtimes.calendar = '365_day'

outlats.units = 'degrees_north'

outlats.long_name = 'Latitude'

outlats.standard_name = 'latitude'

outlons.units = 'degrees_east'

outlons.long_name = 'Longitude'

outlons.standard_name = 'longitude'

# global attributes

import time

outnc.title = nctitle

if ensmembers:

outnc.title = outnc.title + '. Ensemble member r' + str(eindex) + 'i1p1'

outnc.creation_date = time.ctime(time.time())

outnc.created_by = 'Kelly E. McCusker, CCCma / U. of Victoria'

# set the data to the variables: important to have [:]!

outtimes[:] = timeoutall

outlats[:] = bclat

outlons[:] = bclon

outfld[:] = fldout

outnc.close()