outfile = ''.join([
derived_output_location, 'CloudTopv4_', model_prefix,
'.cam.h1.', year, '-', mo_date, '-', date, '-', time, '.nc'
])
f_out = cdm.open(outfile, 'w')
att_keys = f_in1.attributes.keys()
att_dic = {}
for i in range(len(att_keys)):
att_dic[i] = att_keys[i], f_in1.attributes[att_keys[i]]
to_out = att_dic[i]
setattr(f_out, to_out[0], to_out[1])
setattr(
f_out, 'comments2',
'Used create_variable.CLDTOP_NdTCLDTOT_CAM5 to create cloud output'
)
setattr(
f_out, 'comments3',
'Updated create_variable.CLDTOP_NdTCLDTOT_CAM5 to use hightest elevation with CLOUD>0.2 below ~350hPa as the cltop, rather than CLDTOP output'
)
globalAttWrite(f_out, options=None)
# Use function to write standard global atts to output file
f_out.write(cldtopspnc)
f_out.write(cldtopz3)
f_out.write(cldtopt)
f_out.write(cldtot)
f_out.write(tgcldlwp)
f_in1.close()
f_in2.close()
f_out.close()
else:
data = fIn(varRead)
data.id = varWrite
print "".join(['** Writing variable: ', varRead, ' to ', varWrite, ' **'])
# e.g. outfile = 'ACME-CAM5-SE_v0.0.1/tas_ACME-CAM5-SE_v0.0.1_Amon_01-12-clim.nc'
outfile = os.path.join(
outPath, modelId, "_".join([varWrite, modelId, tableId, '01-12-clim.nc']))
print "".join(['** Writing file: ', outfile])
# Create output directory and purge if exists
if not os.path.isdir(os.path.join(outPath, modelId)) and count2 == 0:
os.makedirs(modelId)
elif count2 == 0:
shutil.rmtree(
os.path.join(
outPath,
modelId)) # shutil removes directory and files
os.makedirs(os.path.join(outPath, modelId))
# Test for existing outfile
if os.path.isfile(outfile):
os.remove(outfile) # purge existing file
# Open file and write data
fOut = cdm.open(outfile, 'w')
fOut.write(data)
globalAttWrite(fOut, options=None)
fOut.close()
fIn.close()
# Execute shell command
# source /export/durack1/141126_metrics/PCMDI_METRICS/bin/setup_runtime.csh
# > pcmdi_metrics_driver.py -p pcmdi_input_parameters_test.py
for count1, actId in enumerate(activityId):
exps = actExpPair[actId]['exps']
time = actExpPair[actId]['time'][0]
varList = ['sos', 'tos']
for count2, exp in enumerate(exps):
for count3, var in enumerate(varList):
fileName = '_'.join([var, 'CMIP6', exp, time, 'mean'])
outFile = '_'.join([infile.split(
'/')[-1].split('.')[0].replace('_CMIP6', ''), fileName])
print('fileName:', fileName)
vars()[exp] = mat[fileName]
# Create output file and write
outFile = '.'.join([os.path.join(targetDir, outFile), 'nc'])
print('outFile:', outFile)
cdVar = cdm.createVariable(eval(exp), id='sos')
cdVar.setAxis(0, lat)
cdVar.setAxis(1, lon)
# Write variables to file
if os.path.isfile(outFile):
os.remove(outFile)
fH = cdm.open(outFile, 'w')
# Global attributes
# Use function to write standard global atts
globalAttWrite(fH, options=None)
# Master variables
fH.write(cdVar.astype('float32'))
fH.close()
del(count1, actId, exps, time, count2, exp)
filePath.split('/')[-1].split('.')[8])
# Add ocn/atm to filepath
print('outPath:', outPath)
#pdb.set_trace()
if not os.path.exists(outPath):
#mkDirNoOSErr(outPath,mode=755) ; # Problems with special permissions py3
# fix issue with weird perms on final directory
os.makedirs(''.join([outPath, '/']), mode=755)
# Update from os.mkdir as makedirs is recursive
outFile = os.path.join(outPath, outFile)
print('outfile:', outFile)
print('outFileTrim: ', outFile.replace(localPath, ''))
if os.path.exists(outFile):
os.remove(outFile)
outH = cdm.open(outFile, 'w')
globalAttWrite(outH, options=None)
# Copy across global attributes from source file - do this first, then write again so new info overwrites
for i, key in enumerate(fH.attributes.keys()):
setattr(outH, key, fH.attributes.get(key))
del (i, key)
gc.collect()
outH.SourceFile = filePath
outH.write(basinmask)
outH.sync()
# Close files
outH.close()
fH.close
basinH.close()
del (filePath, var, fH, tmp, targetLats, targetLons, basinLonsCorrect,
targetGrid, basinmask, outFile, outH)
gc.collect()
print("** File exists.. removing **")
os.remove(outFModId)
if not os.path.exists(outFMod):
os.makedirs(outFMod)
# Print outfile to screen and logfile
outFModIdStr = " ".join(["outFModId:", outFModId])
print(outFModIdStr)
writeToLog(logFile, outFModIdStr)
# Open file to write
modIdH = cdm.open(outFModId, "w")
# Copy across global attributes from source file - do this first, then write again so new info overwrites
for i, key in enumerate(fH.attributes.keys()):
setattr(modIdH, key, fH.attributes.get(key))
del (i, key)
gc.collect()
globalAttWrite(modIdH, options=None)
modIdH.climStart = str(times.asComponentTime()[0])
modIdH.climEnd = str(times.asComponentTime()[-1])
modIdH.write(clim.astype("float32"))
modIdH.close()
# Check file exists
if os.path.exists(outFWoaId):
print("** File exists.. removing **")
os.remove(outFWoaId)
if not os.path.exists(outFWoa):
os.makedirs(outFWoa)
woaIdH = cdm.open(outFWoaId, "w")
# Copy across global attributes from source file - do this first, then write again so new info overwrites
for i, key in enumerate(fH.attributes.keys()):
setattr(woaIdH, key, fH.attributes.get(key))
del (i, key)
print "".join(['** File exists.. removing: ',outfile,' **'])
os.remove(outfile)
# Open outfile
f_out = cdm.open(outfile,'w')
# Write variable attributes back out to new variable
for k in d.attributes.keys():
setattr(ann,k,d.attributes[k])
# Write out file global atts
for k in f_in.attributes.keys():
setattr(f_out,k,f_in.attributes[k])
history = getattr(f_in,'history')
# Write out start and end years
f_out.an_start_year = annfirstyr
f_out.an_end_year = annlastyr
# Global attributes
globalAttWrite(f_out,options=None) ; # Use function to write standard global atts
# Write new variable atts
ann.comment = "Converted to annual from monthly mean data"
# Write data to file, if successful close infile and outfile
try:
f_out.write(ann)
f_out.close()
f_in.close() ; # Source file kept open so attributes can be copied across
nc_good = nc_good + 1 ;
except:
print "file write bombed onto next in loop"
f_out.close()
f_in.close()
nc_bad4 = nc_bad4 + 1 ;
if os.path.exists(outfile):
def makeSteric(salinity, salinityChg, temp, tempChg, outFileName, thetao,
pressure):
"""
The makeSteric() function takes 3D (not temporal) arguments and creates
heat content and steric fields which are written to a specified outfile
Author: Paul J. Durack : [email protected] : @durack1.
Created on Thu Jul 18 13:03:37 2013.
Inputs:
------
- salinity(lev,lat,lon) - 3D array for the climatological period.
- salinityChg(lev,lat,lon) - 3D array for the temporal change period.
- temp(lev,lat,lon) - 3D array for the climatological period either in-situ or potential temperature.
- tempChg(lev,lat,lon) - 3D array for the temporal change period as with temp, either in-situ or potential temperature.
- outFileName(str) - output filename with full path specified.
- thetao(bool) - boolean value specifying either in-situ or potential temperature arrays provided.
- pressure(bool) - boolean value specifying whether lev-coordinate is pressure (dbar) or depth (m).
Usage:
------
>>> from makeStericLib import makeSteric
>>> makeSteric(salinity,salinityChg,thetao,thetaoChg,'outfile.nc',True,False)
Notes:
-----
- PJD 18 Jul 2013 - Validated Ishii v6.13 data against WOA94 - checks out ok. Units: dyn decimeter compared to http://www.nodc.noaa.gov/OC5/WOA94/dyn.html uses cm (not decimeter; x 10)
- PJD 18 Jul 2013 - Added attribute scrub to incoming variables (so,so_chg,temp,temp_chg) to maintain output consistency
- PJD 22 Jul 2013 - Added name attributes to so and temp variables, added units to so_chg
- PJD 22 Jul 2013 - removed duplicated code by converting repetition to function scrubNaNAndMask
- PJD 23 Jul 2013 - Further cleaned up so,so_chg,temp,temp_chg outputs specifying id/name attributes
- PJD 5 Aug 2013 - Updated python-seawater library to version 3.3.1 from github repo, git clone http://github.com/ocefpaf/python-seawater, python setup.py install --user
- PJD 7 Aug 2013 - FIXED: thetao rather than in-situ temperature propagating throughout calculations
- PJD 7 Aug 2013 - Replaced looping with 3D gpan
- PJD 7 Aug 2013 - Further code duplication cleanup
- PJD 8 Aug 2013 - FIXED: scrubNanAndMask function type/mask/grid issue - encase sw arguments in np.array() (attempt to strip cdms fluff)
- PJD 8 Aug 2013 - FIXED: removed depth variable unit edits - not all inputs are depth (m)
- PJD 15 Aug 2013 - Increased interpolated field resolution [200,300,500,700,1000,1500,1800,2000] - [5,10,20,30,40,50,75,100,125,150,200, ...]
- PJD 18 Aug 2013 - AR5 hard coded rho=1020,cp=4187 == 4.3e6 vs Ishii 1970 rho.mean=1024,cp.mean=3922 == 4.1e6 ~5% too high
- PJD 13 Jan 2014 - Corrected steric_height_anom and steric_height_thermo_anom to true anomaly fields, needed to remove climatology
- PJD 3 May 2014 - Turned off thetao conversion, although convert to numpy array rather than cdms2 transient variable
- PJD 13 Oct 2014 - Added seawater_library_version as a global attribute
- PJD 13 Oct 2014 - FIXED: bug with calculation of rho_halo variable was calculating gpan
- PJD 13 Oct 2014 - Added alternate calculation of halosteric anomaly (direct salinity anomaly calculation, rather than total-thermosteric)
- PJD 13 Oct 2014 - Added makeSteric_version as a global attribute
- TODO: Better deal with insitu vs thetao variables
- TODO: Query Charles on why *.name attributes are propagating
- TODO: validate outputs and compare to matlab versions - 10e-7 errors.
"""
# Remap all variables to short names
so = salinity
so_chg = salinityChg
temp = temp
temp_chg = tempChg
del (salinity, salinityChg, tempChg)
gc.collect()
# Strip attributes to maintain consistency between datasets
for count, x in enumerate(so.attributes.keys()):
delattr(so, x)
#print so.listattributes() ; # Print remaining attributes
for count, x in enumerate(so_chg.attributes.keys()):
delattr(so_chg, x)
for count, x in enumerate(temp.attributes.keys()):
delattr(temp, x)
for count, x in enumerate(temp_chg.attributes.keys()):
delattr(temp_chg, x)
del (count, x)
# Create z-coordinate from salinity input
if not pressure:
z_coord = so.getAxis(0)
y_coord = so.getAxis(1)
y_coord = tile(y_coord, (so.shape[2], 1)).transpose()
depth_levels = tile(z_coord.getValue(),
(so.shape[2], so.shape[1], 1)).transpose()
pressure_levels = sw.pres(np.array(depth_levels), np.array(y_coord))
del (z_coord, y_coord, depth_levels)
gc.collect()
else:
pressure_levels = so.getAxis(0)
pressure_levels = transpose(
tile(pressure_levels, (so.shape[2], so.shape[1], 1)))
pressure_levels = cdm.createVariable(pressure_levels, id='pressure_levels')
pressure_levels.setAxis(0, so.getAxis(0))
pressure_levels.setAxis(1, so.getAxis(1))
pressure_levels.setAxis(2, so.getAxis(2))
pressure_levels.id = 'pressure_levels'
pressure_levels.units_long = 'decibar (pressure)'
pressure_levels.positive = 'down'
pressure_levels.long_name = 'sea_water_pressure'
pressure_levels.standard_name = 'sea_water_pressure'
pressure_levels.units = 'decibar'
pressure_levels.axis = 'Z'
# Cleanup depth axis attributes
depth = so.getAxis(0)
depth.id = 'depth'
depth.name = 'depth'
depth.long_name = 'depth'
depth.standard_name = 'depth'
depth.axis = 'Z'
so.setAxis(0, depth)
so_chg.setAxis(0, depth)
temp.setAxis(0, depth)
temp_chg.setAxis(0, depth)
del (depth)
# Convert using python-seawater library (v3.3.1 - 130807)
if thetao:
# Process potential temperature to in-situ - default conversion sets reference pressure to 0 (surface)
#temp_chg = sw.temp(np.array(so),np.array(temp_chg),np.array(pressure_levels)); # units degrees C
#temp = sw.temp(np.array(so),np.array(temp),np.array(pressure_levels)); # units degrees C
#temp_chg = sw.ptmp(np.array(so),np.array(temp_chg),np.array(pressure_levels),np.array(pressure_levels)); # units degrees C
#temp = sw.ptmp(np.array(so),np.array(temp),np.array(pressure_levels),np.array(pressure_levels)); # units degrees C
temp_chg = np.array(temp_chg)
# units degrees C
temp = np.array(temp)
# units degrees C
# Climatologies - rho,cp,steric_height
rho = sw.dens(np.array(so), np.array(temp), np.array(pressure_levels))
# units kg m-3
cp = sw.cp(np.array(so), np.array(temp), np.array(pressure_levels))
# units J kg-1 C-1
steric_height = sw.gpan(np.array(so), np.array(temp),
np.array(pressure_levels))
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
# Halosteric - rho,cp
ss = map(array, (so + so_chg))
rho_halo = sw.dens(np.array(ss), np.array(temp), np.array(pressure_levels))
# units kg m-3
cp_halo = sw.cp(np.array(ss), np.array(temp), np.array(pressure_levels))
# units J kg-1 C-1
tmp = sw.gpan(np.array(ss), np.array(temp), np.array(pressure_levels))
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
steric_height_halo_anom2 = tmp - steric_height
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
# Full steric - steric_height
tt = map(array, (temp + temp_chg))
tmp = sw.gpan(np.array(ss), np.array(tt), np.array(pressure_levels))
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
steric_height_anom = tmp - steric_height
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
del (ss, tmp)
gc.collect()
# Thermosteric - rho,cp,steric_height
rho_thermo = sw.dens(np.array(so), np.array(tt), np.array(pressure_levels))
# units kg m-3
cp_thermo = sw.cp(np.array(so), np.array(tt), np.array(pressure_levels))
# units J kg-1 C-1
tmp = sw.gpan(np.array(so), np.array(tt), np.array(pressure_levels))
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
steric_height_thermo_anom = tmp - steric_height
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
del (tt, tmp)
gc.collect()
# Halosteric - steric_height
steric_height_halo_anom = steric_height_anom - steric_height_thermo_anom
# units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
# Create heat content
heat_content = np.array(temp) * np.array(rho) * np.array(cp)
# units J
heat_content_sanom = np.array(temp) * np.array(rho_halo) * np.array(
cp_halo)
# units J
heat_content_tanom = np.array(temp_chg) * np.array(rho) * np.array(cp)
# units J
#heat_content_tanom = np.array(temp_chg)*np.array(1020)*np.array(4187) ; # units J - try hard-coded - AR5 numbers
heat_content_tsanom = np.array(temp_chg) * np.array(rho_halo) * np.array(
cp_halo)
# units J
# Correct all instances of NaN values and fix masks - applied before cdms variables are created otherwise names/ids/attributes are reset
temp = scrubNaNAndMask(temp, so)
temp_chg = scrubNaNAndMask(temp_chg, so)
rho = scrubNaNAndMask(rho, so)
cp = scrubNaNAndMask(cp, so)
rho_halo = scrubNaNAndMask(rho_halo, so)
cp_halo = scrubNaNAndMask(cp_halo, so)
rho_thermo = scrubNaNAndMask(rho_thermo, so)
cp_thermo = scrubNaNAndMask(cp_thermo, so)
steric_height = scrubNaNAndMask(steric_height, so)
steric_height_anom = scrubNaNAndMask(steric_height_anom, so)
steric_height_thermo_anom = scrubNaNAndMask(steric_height_thermo_anom, so)
steric_height_halo_anom = scrubNaNAndMask(steric_height_halo_anom, so)
steric_height_halo_anom2 = scrubNaNAndMask(steric_height_halo_anom2, so)
heat_content = scrubNaNAndMask(heat_content, so)
heat_content_sanom = scrubNaNAndMask(heat_content_sanom, so)
heat_content_tanom = scrubNaNAndMask(heat_content_tanom, so)
heat_content_tsanom = scrubNaNAndMask(heat_content_tsanom, so)
# Recreate and redress variables
so.id = 'so_mean'
so.units = '1e-3'
so_chg.id = 'so_chg'
so_chg.units = '1e-3'
temp = cdm.createVariable(temp, id='temp_mean')
temp.setAxis(0, so.getAxis(0))
temp.setAxis(1, so.getAxis(1))
temp.setAxis(2, so.getAxis(2))
temp.units = 'degrees_C'
temp_chg = cdm.createVariable(temp_chg, id='temp_chg')
temp_chg.setAxis(0, so.getAxis(0))
temp_chg.setAxis(1, so.getAxis(1))
temp_chg.setAxis(2, so.getAxis(2))
temp_chg.units = 'degrees_C'
rho = cdm.createVariable(rho, id='rho')
rho.setAxis(0, so.getAxis(0))
rho.setAxis(1, so.getAxis(1))
rho.setAxis(2, so.getAxis(2))
rho.name = 'density_mean'
rho.units = 'kg m^-3'
cp = cdm.createVariable(cp, id='cp')
cp.setAxis(0, so.getAxis(0))
cp.setAxis(1, so.getAxis(1))
cp.setAxis(2, so.getAxis(2))
cp.name = 'heat_capacity_mean'
cp.units = 'J kg^-1 C^-1'
rho_halo = cdm.createVariable(rho_halo, id='rho_halo')
rho_halo.setAxis(0, so.getAxis(0))
rho_halo.setAxis(1, so.getAxis(1))
rho_halo.setAxis(2, so.getAxis(2))
rho_halo.name = 'density_mean_halo'
rho_halo.units = 'kg m^-3'
cp_halo = cdm.createVariable(cp_halo, id='cp_halo')
cp_halo.setAxis(0, so.getAxis(0))
cp_halo.setAxis(1, so.getAxis(1))
cp_halo.setAxis(2, so.getAxis(2))
cp_halo.name = 'heat_capacity_mean_halo'
cp_halo.units = 'J kg^-1 C^-1'
rho_thermo = cdm.createVariable(rho_thermo, id='rho_thermo')
rho_thermo.setAxis(0, so.getAxis(0))
rho_thermo.setAxis(1, so.getAxis(1))
rho_thermo.setAxis(2, so.getAxis(2))
rho_thermo.name = 'density_mean_thermo'
rho_thermo.units = 'kg m^-3'
cp_thermo = cdm.createVariable(cp_thermo, id='cp_thermo')
cp_thermo.setAxis(0, so.getAxis(0))
cp_thermo.setAxis(1, so.getAxis(1))
cp_thermo.setAxis(2, so.getAxis(2))
cp_thermo.name = 'heat_capacity_mean_thermo'
cp_thermo.units = 'J kg^-1 C^-1'
steric_height = cdm.createVariable(steric_height, id='steric_height')
steric_height.setAxis(0, so.getAxis(0))
steric_height.setAxis(1, so.getAxis(1))
steric_height.setAxis(2, so.getAxis(2))
steric_height.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_anom = cdm.createVariable(steric_height_anom,
id='steric_height_anom')
steric_height_anom.setAxis(0, so.getAxis(0))
steric_height_anom.setAxis(1, so.getAxis(1))
steric_height_anom.setAxis(2, so.getAxis(2))
steric_height_anom.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_thermo_anom = cdm.createVariable(
steric_height_thermo_anom, id='steric_height_thermo_anom')
steric_height_thermo_anom.setAxis(0, so.getAxis(0))
steric_height_thermo_anom.setAxis(1, so.getAxis(1))
steric_height_thermo_anom.setAxis(2, so.getAxis(2))
steric_height_thermo_anom.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom = cdm.createVariable(steric_height_halo_anom,
id='steric_height_halo_anom')
steric_height_halo_anom.setAxis(0, so.getAxis(0))
steric_height_halo_anom.setAxis(1, so.getAxis(1))
steric_height_halo_anom.setAxis(2, so.getAxis(2))
steric_height_halo_anom.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom2 = cdm.createVariable(
steric_height_halo_anom2, id='steric_height_halo_anom2')
steric_height_halo_anom2.setAxis(0, so.getAxis(0))
steric_height_halo_anom2.setAxis(1, so.getAxis(1))
steric_height_halo_anom2.setAxis(2, so.getAxis(2))
steric_height_halo_anom2.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
heat_content = cdm.createVariable(heat_content, id='heat_content')
heat_content.setAxis(0, so.getAxis(0))
heat_content.setAxis(1, so.getAxis(1))
heat_content.setAxis(2, so.getAxis(2))
heat_content.units = 'J'
heat_content_sanom = cdm.createVariable(heat_content_sanom,
id='heat_content_sanom')
heat_content_sanom.setAxis(0, so.getAxis(0))
heat_content_sanom.setAxis(1, so.getAxis(1))
heat_content_sanom.setAxis(2, so.getAxis(2))
heat_content_sanom.units = 'J'
heat_content_tanom = cdm.createVariable(heat_content_tanom,
id='heat_content_tanom')
heat_content_tanom.setAxis(0, so.getAxis(0))
heat_content_tanom.setAxis(1, so.getAxis(1))
heat_content_tanom.setAxis(2, so.getAxis(2))
heat_content_tanom.units = 'J'
heat_content_tsanom = cdm.createVariable(heat_content_tsanom,
id='heat_content_tsanom')
heat_content_tsanom.setAxis(0, so.getAxis(0))
heat_content_tsanom.setAxis(1, so.getAxis(1))
heat_content_tsanom.setAxis(2, so.getAxis(2))
heat_content_tsanom.units = 'J'
# Create model-based depth index for subset target levels
newdepth = np.array([
5, 10, 20, 30, 40, 50, 75, 100, 125, 150, 200, 300, 500, 700, 1000,
1500, 1800, 2000
]).astype('f')
newdepth_bounds = np.array([[0, 5], [5, 10], [10, 20], [20, 30], [30, 40],
[40, 50], [50, 75], [75, 100], [100, 125],
[125, 150], [150, 200], [200, 300], [300, 500],
[500, 700], [700, 1000], [1000, 1500],
[1500, 1800], [1800, 2000]]).astype('f')
#newdepth = np.array([200,300,500,700,1000,1500,1800,2000]).astype('f');
#newdepth_bounds = np.array([[0,200],[200,300],[300,500],[500,700],[700,1000],[1000,1500],[1500,1800],[1800,2000]]).astype('f')
# Interpolate to depths
so_depthInterp = cdu.linearInterpolation(so,
pressure_levels,
levels=newdepth)
temp_depthInterp = cdu.linearInterpolation(temp,
pressure_levels,
levels=newdepth)
steric_height_depthInterp = cdu.linearInterpolation(steric_height,
pressure_levels,
levels=newdepth)
steric_height_anom_depthInterp = cdu.linearInterpolation(
steric_height_anom, pressure_levels, levels=newdepth)
steric_height_thermo_anom_depthInterp = cdu.linearInterpolation(
steric_height_thermo_anom, pressure_levels, levels=newdepth)
steric_height_halo_anom_depthInterp = cdu.linearInterpolation(
steric_height_halo_anom, pressure_levels, levels=newdepth)
steric_height_halo_anom2_depthInterp = cdu.linearInterpolation(
steric_height_halo_anom2, pressure_levels, levels=newdepth)
heat_content_sanom_depthInterp = cdu.linearInterpolation(
heat_content_sanom, pressure_levels, levels=newdepth)
heat_content_tanom_depthInterp = cdu.linearInterpolation(
heat_content_tanom, pressure_levels, levels=newdepth)
heat_content_tsanom_depthInterp = cdu.linearInterpolation(
heat_content_tanom, pressure_levels, levels=newdepth)
# Fix masks - applied before cdms variables are created otherwise names/ids/attributes are reset
temp_depthInterp = scrubNaNAndMask(temp_depthInterp, so_depthInterp)
steric_height_depthInterp = scrubNaNAndMask(steric_height_depthInterp,
so_depthInterp)
steric_height_anom_depthInterp = scrubNaNAndMask(
steric_height_anom_depthInterp, so_depthInterp)
steric_height_thermo_anom_depthInterp = scrubNaNAndMask(
steric_height_thermo_anom_depthInterp, so_depthInterp)
steric_height_halo_anom_depthInterp = scrubNaNAndMask(
steric_height_halo_anom_depthInterp, so_depthInterp)
steric_height_halo_anom2_depthInterp = scrubNaNAndMask(
steric_height_halo_anom2_depthInterp, so_depthInterp)
heat_content_sanom_depthInterp = scrubNaNAndMask(
heat_content_sanom_depthInterp, so_depthInterp)
heat_content_tanom_depthInterp = scrubNaNAndMask(
heat_content_tanom_depthInterp, so_depthInterp)
heat_content_tsanom_depthInterp = scrubNaNAndMask(
heat_content_tsanom_depthInterp, so_depthInterp)
# Fix bounds
newdepth = so_depthInterp.getAxis(0)
newdepth.setBounds(newdepth_bounds)
del (newdepth_bounds)
newdepth.id = 'depth2'
newdepth.units_long = 'decibar (pressure)'
newdepth.positive = 'down'
newdepth.long_name = 'sea_water_pressure'
newdepth.standard_name = 'sea_water_pressure'
newdepth.units = 'decibar'
newdepth.axis = 'Z'
# Assign corrected bounds
so_depthInterp.setAxis(0, newdepth)
temp_depthInterp.setAxis(0, newdepth)
steric_height_depthInterp.setAxis(0, newdepth)
steric_height_anom_depthInterp.setAxis(0, newdepth)
steric_height_thermo_anom_depthInterp.setAxis(0, newdepth)
steric_height_halo_anom_depthInterp.setAxis(0, newdepth)
steric_height_halo_anom2_depthInterp.setAxis(0, newdepth)
heat_content_sanom_depthInterp.setAxis(0, newdepth)
heat_content_tanom_depthInterp.setAxis(0, newdepth)
heat_content_tsanom_depthInterp.setAxis(0, newdepth)
# Average/integrate to surface - configure bounds
# Preallocate arrays
so_depthAve = np.ma.zeros([len(newdepth), shape(so)[1], shape(so)[2]])
temp_depthAve = so_depthAve.copy()
heat_content_sanom_depthInteg = so_depthAve.copy()
heat_content_tanom_depthInteg = so_depthAve.copy()
heat_content_tsanom_depthInteg = so_depthAve.copy()
for count, depth in enumerate(newdepth):
tmp = cdu.averager(so_depthInterp[0:(count + 1), ...],
axis=0,
weights='weighted',
action='average')
so_depthAve[count, ] = tmp
tmp = cdu.averager(temp_depthInterp[0:(count + 1), ...],
axis=0,
weights='weighted',
action='average')
temp_depthAve[count, ] = tmp
tmp = cdu.averager(heat_content_sanom_depthInterp[0:(count + 1), ...],
axis=0,
weights='weighted',
action='sum')
heat_content_sanom_depthInteg[count, ] = tmp
tmp = cdu.averager(heat_content_tanom_depthInterp[0:(count + 1), ...],
axis=0,
weights='weighted',
action='sum')
heat_content_tanom_depthInteg[count, ] = tmp
tmp = cdu.averager(heat_content_tsanom_depthInterp[0:(count + 1), ...],
axis=0,
weights='weighted',
action='sum')
heat_content_tsanom_depthInteg[count, ] = tmp
del (heat_content_tanom_depthInterp, heat_content_tsanom_depthInterp)
gc.collect()
# Fix masks - applied before cdms variables are created otherwise names/ids/attributes are reset
so_depthAve = scrubNaNAndMask(so_depthAve, so_depthInterp)
temp_depthAve = scrubNaNAndMask(temp_depthAve, so_depthInterp)
heat_content_sanom_depthInteg = scrubNaNAndMask(
heat_content_sanom_depthInteg, so_depthInterp)
heat_content_tanom_depthInteg = scrubNaNAndMask(
heat_content_tanom_depthInteg, so_depthInterp)
heat_content_tsanom_depthInteg = scrubNaNAndMask(
heat_content_tsanom_depthInteg, so_depthInterp)
del (so_depthInterp)
# Convert numpy arrays to cdms objects
heat_content_sanom_depthInteg = cdm.createVariable(
heat_content_sanom_depthInteg, id='heat_content_sanom_depthInteg')
heat_content_sanom_depthInteg.id = 'heat_content_sanom_depthInteg'
heat_content_sanom_depthInteg.setAxis(0, newdepth)
heat_content_sanom_depthInteg.setAxis(1, so.getAxis(1))
heat_content_sanom_depthInteg.setAxis(2, so.getAxis(2))
heat_content_sanom_depthInteg.units = 'J'
heat_content_tanom_depthInteg = cdm.createVariable(
heat_content_tanom_depthInteg, id='heat_content_tanom_depthInteg')
heat_content_tanom_depthInteg.id = 'heat_content_tanom_depthInteg'
heat_content_tanom_depthInteg.setAxis(0, newdepth)
heat_content_tanom_depthInteg.setAxis(1, so.getAxis(1))
heat_content_tanom_depthInteg.setAxis(2, so.getAxis(2))
heat_content_tanom_depthInteg.units = 'J'
heat_content_tsanom_depthInteg = cdm.createVariable(
heat_content_tsanom_depthInteg, id='heat_content_tsanom_depthInteg')
heat_content_tsanom_depthInteg.id = 'heat_content_tsanom_depthInteg'
heat_content_tsanom_depthInteg.setAxis(0, newdepth)
heat_content_tsanom_depthInteg.setAxis(1, so.getAxis(1))
heat_content_tsanom_depthInteg.setAxis(2, so.getAxis(2))
heat_content_tsanom_depthInteg.units = 'J'
so_depthAve = cdm.createVariable(so_depthAve, id='so_depthAve')
so_depthAve.id = 'so_depthAve'
so_depthAve.setAxis(0, newdepth)
so_depthAve.setAxis(1, so.getAxis(1))
so_depthAve.setAxis(2, so.getAxis(2))
so_depthAve.units = '1e-3'
temp_depthAve = cdm.createVariable(temp_depthAve, id='temp_depthAve')
temp_depthAve.id = 'temp_depthAve'
temp_depthAve.setAxis(0, newdepth)
temp_depthAve.setAxis(1, so.getAxis(1))
temp_depthAve.setAxis(2, so.getAxis(2))
temp_depthAve.units = 'degrees_C'
steric_height_depthInterp = cdm.createVariable(
steric_height_depthInterp, id='steric_height_depthInterp')
steric_height_depthInterp.setAxis(0, newdepth)
steric_height_depthInterp.setAxis(1, so.getAxis(1))
steric_height_depthInterp.setAxis(2, so.getAxis(2))
steric_height_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_anom_depthInterp = cdm.createVariable(
steric_height_anom_depthInterp, id='steric_height_anom_depthInterp')
steric_height_anom_depthInterp.setAxis(0, newdepth)
steric_height_anom_depthInterp.setAxis(1, so.getAxis(1))
steric_height_anom_depthInterp.setAxis(2, rho.getAxis(2))
steric_height_anom_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_thermo_anom_depthInterp = cdm.createVariable(
steric_height_thermo_anom_depthInterp,
id='steric_height_thermo_anom_depthInterp')
steric_height_thermo_anom_depthInterp.setAxis(0, newdepth)
steric_height_thermo_anom_depthInterp.setAxis(1, so.getAxis(1))
steric_height_thermo_anom_depthInterp.setAxis(2, so.getAxis(2))
steric_height_thermo_anom_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom_depthInterp = cdm.createVariable(
steric_height_halo_anom_depthInterp,
id='steric_height_halo_anom_depthInterp')
steric_height_halo_anom_depthInterp.setAxis(0, newdepth)
steric_height_halo_anom_depthInterp.setAxis(1, so.getAxis(1))
steric_height_halo_anom_depthInterp.setAxis(2, so.getAxis(2))
steric_height_halo_anom_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom2_depthInterp = cdm.createVariable(
steric_height_halo_anom2_depthInterp,
id='steric_height_halo_anom2_depthInterp')
steric_height_halo_anom2_depthInterp.setAxis(0, newdepth)
steric_height_halo_anom2_depthInterp.setAxis(1, so.getAxis(1))
steric_height_halo_anom2_depthInterp.setAxis(2, so.getAxis(2))
steric_height_halo_anom2_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
# Cleanup workspace
del (newdepth)
gc.collect()
# Write variables to file
if os.path.isfile(outFileName):
os.remove(outFileName)
filehandle = cdm.open(outFileName, 'w')
# Global attributes
globalAttWrite(filehandle, options=None)
# Use function to write standard global atts
# Write seawater version
filehandle.seawater_library_version = sw.__version__
# Write makeSteric version
makeStericPath = str(makeSteric.__code__).split(' ')[6]
makeStericPath = replace(replace(makeStericPath, '"', ''), ',', '')
# Clean scraped path
filehandle.makeSteric_version = ' '.join(getGitInfo(makeStericPath)[0:3])
# Master variables
filehandle.write(so.astype('float32'))
filehandle.write(so_chg.astype('float32'))
filehandle.write(so_depthAve.astype('float32'))
filehandle.write(temp.astype('float32'))
filehandle.write(temp_chg.astype('float32'))
filehandle.write(temp_depthAve.astype('float32'))
# Derived variables
filehandle.write(cp.astype('float32'))
filehandle.write(cp_halo.astype('float32'))
filehandle.write(cp_thermo.astype('float32'))
filehandle.write(rho.astype('float32'))
filehandle.write(rho_halo.astype('float32'))
filehandle.write(rho_thermo.astype('float32'))
filehandle.write(heat_content.astype('float32'))
filehandle.write(heat_content_sanom.astype('float32'))
filehandle.write(heat_content_sanom_depthInteg.astype('float32'))
filehandle.write(heat_content_tanom.astype('float32'))
filehandle.write(heat_content_tanom_depthInteg.astype('float32'))
filehandle.write(heat_content_tsanom.astype('float32'))
filehandle.write(heat_content_tsanom_depthInteg.astype('float32'))
filehandle.write(steric_height.astype('float32'))
filehandle.write(steric_height_depthInterp.astype('float32'))
filehandle.write(steric_height_anom.astype('float32'))
filehandle.write(steric_height_anom_depthInterp.astype('float32'))
filehandle.write(steric_height_halo_anom.astype('float32'))
filehandle.write(steric_height_halo_anom2.astype('float32'))
filehandle.write(steric_height_halo_anom_depthInterp.astype('float32'))
filehandle.write(steric_height_halo_anom2_depthInterp.astype('float32'))
filehandle.write(steric_height_thermo_anom.astype('float32'))
filehandle.write(steric_height_thermo_anom_depthInterp.astype('float32'))
filehandle.close()
# Cleanup workspace
del (outFileName)
gc.collect()
def makeSteric(salinity,salinityChg,temp,tempChg,outFileName,thetao,pressure):
"""
The makeSteric() function takes 3D (not temporal) arguments and creates
heat content and steric fields which are written to a specified outfile
Author: Paul J. Durack : [email protected] : @durack1.
Created on Thu Jul 18 13:03:37 2013.
Inputs:
------
- salinity(lev,lat,lon) - 3D array for the climatological period.
- salinityChg(lev,lat,lon) - 3D array for the temporal change period.
- temp(lev,lat,lon) - 3D array for the climatological period either in-situ or potential temperature.
- tempChg(lev,lat,lon) - 3D array for the temporal change period as with temp, either in-situ or potential temperature.
- outFileName(str) - output filename with full path specified.
- thetao(bool) - boolean value specifying either in-situ or potential temperature arrays provided.
- pressure(bool) - boolean value specifying whether lev-coordinate is pressure (dbar) or depth (m).
Usage:
------
>>> from makeStericLib import makeSteric
>>> makeSteric(salinity,salinityChg,thetao,thetaoChg,'outfile.nc',True,False)
Notes:
-----
- PJD 18 Jul 2013 - Validated Ishii v6.13 data against WOA94 - checks out ok. Units: dyn decimeter compared to http://www.nodc.noaa.gov/OC5/WOA94/dyn.html uses cm (not decimeter; x 10)
- PJD 18 Jul 2013 - Added attribute scrub to incoming variables (so,so_chg,temp,temp_chg) to maintain output consistency
- PJD 22 Jul 2013 - Added name attributes to so and temp variables, added units to so_chg
- PJD 22 Jul 2013 - removed duplicated code by converting repetition to function scrubNaNAndMask
- PJD 23 Jul 2013 - Further cleaned up so,so_chg,temp,temp_chg outputs specifying id/name attributes
- PJD 5 Aug 2013 - Updated python-seawater library to version 3.3.1 from github repo, git clone http://github.com/ocefpaf/python-seawater, python setup.py install --user
- PJD 7 Aug 2013 - FIXED: thetao rather than in-situ temperature propagating throughout calculations
- PJD 7 Aug 2013 - Replaced looping with 3D gpan
- PJD 7 Aug 2013 - Further code duplication cleanup
- PJD 8 Aug 2013 - FIXED: scrubNanAndMask function type/mask/grid issue - encase sw arguments in np.array() (attempt to strip cdms fluff)
- PJD 8 Aug 2013 - FIXED: removed depth variable unit edits - not all inputs are depth (m)
- PJD 15 Aug 2013 - Increased interpolated field resolution [200,300,500,700,1000,1500,1800,2000] - [5,10,20,30,40,50,75,100,125,150,200, ...]
- PJD 18 Aug 2013 - AR5 hard coded rho=1020,cp=4187 == 4.3e6 vs Ishii 1970 rho.mean=1024,cp.mean=3922 == 4.1e6 ~5% too high
- PJD 13 Jan 2014 - Corrected steric_height_anom and steric_height_thermo_anom to true anomaly fields, needed to remove climatology
- PJD 3 May 2014 - Turned off thetao conversion, although convert to numpy array rather than cdms2 transient variable
- PJD 13 Oct 2014 - Added seawater_library_version as a global attribute
- PJD 13 Oct 2014 - FIXED: bug with calculation of rho_halo variable was calculating gpan
- PJD 13 Oct 2014 - Added alternate calculation of halosteric anomaly (direct salinity anomaly calculation, rather than total-thermosteric)
- PJD 13 Oct 2014 - Added makeSteric_version as a global attribute
- TODO: Better deal with insitu vs thetao variables
- TODO: Query Charles on why *.name attributes are propagating
- TODO: validate outputs and compare to matlab versions - 10e-7 errors.
"""
# Remap all variables to short names
so = salinity
so_chg = salinityChg
temp = temp
temp_chg = tempChg
del(salinity,salinityChg,tempChg) ; gc.collect()
# Strip attributes to maintain consistency between datasets
for count,x in enumerate(so.attributes.keys()):
delattr(so,x)
#print so.listattributes() ; # Print remaining attributes
for count,x in enumerate(so_chg.attributes.keys()):
delattr(so_chg,x)
for count,x in enumerate(temp.attributes.keys()):
delattr(temp,x)
for count,x in enumerate(temp_chg.attributes.keys()):
delattr(temp_chg,x)
del(count,x)
# Create z-coordinate from salinity input
if not pressure:
z_coord = so.getAxis(0)
y_coord = so.getAxis(1)
y_coord = tile(y_coord,(so.shape[2],1)).transpose()
depth_levels = tile(z_coord.getValue(),(so.shape[2],so.shape[1],1)).transpose()
pressure_levels = sw.pres(np.array(depth_levels),np.array(y_coord))
del(z_coord,y_coord,depth_levels) ; gc.collect()
else:
pressure_levels = so.getAxis(0)
pressure_levels = transpose(tile(pressure_levels,(so.shape[2],so.shape[1],1)))
pressure_levels = cdm.createVariable(pressure_levels,id='pressure_levels')
pressure_levels.setAxis(0,so.getAxis(0))
pressure_levels.setAxis(1,so.getAxis(1))
pressure_levels.setAxis(2,so.getAxis(2))
pressure_levels.id = 'pressure_levels'
pressure_levels.units_long = 'decibar (pressure)'
pressure_levels.positive = 'down'
pressure_levels.long_name = 'sea_water_pressure'
pressure_levels.standard_name = 'sea_water_pressure'
pressure_levels.units = 'decibar'
pressure_levels.axis = 'Z'
# Cleanup depth axis attributes
depth = so.getAxis(0)
depth.id = 'depth'
depth.name = 'depth'
depth.long_name = 'depth'
depth.standard_name = 'depth'
depth.axis = 'Z'
so.setAxis(0,depth)
so_chg.setAxis(0,depth)
temp.setAxis(0,depth)
temp_chg.setAxis(0,depth)
del(depth)
# Convert using python-seawater library (v3.3.1 - 130807)
if thetao:
# Process potential temperature to in-situ - default conversion sets reference pressure to 0 (surface)
#temp_chg = sw.temp(np.array(so),np.array(temp_chg),np.array(pressure_levels)); # units degrees C
#temp = sw.temp(np.array(so),np.array(temp),np.array(pressure_levels)); # units degrees C
#temp_chg = sw.ptmp(np.array(so),np.array(temp_chg),np.array(pressure_levels),np.array(pressure_levels)); # units degrees C
#temp = sw.ptmp(np.array(so),np.array(temp),np.array(pressure_levels),np.array(pressure_levels)); # units degrees C
temp_chg = np.array(temp_chg); # units degrees C
temp = np.array(temp); # units degrees C
# Climatologies - rho,cp,steric_height
rho = sw.dens(np.array(so),np.array(temp),np.array(pressure_levels)) ; # units kg m-3
cp = sw.cp(np.array(so),np.array(temp),np.array(pressure_levels)) ; # units J kg-1 C-1
steric_height = sw.gpan(np.array(so),np.array(temp),np.array(pressure_levels)) ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
# Halosteric - rho,cp
ss = map(array,(so+so_chg))
rho_halo = sw.dens(np.array(ss),np.array(temp),np.array(pressure_levels)) ; # units kg m-3
cp_halo = sw.cp(np.array(ss),np.array(temp),np.array(pressure_levels)) ; # units J kg-1 C-1
tmp = sw.gpan(np.array(ss),np.array(temp),np.array(pressure_levels)) ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
steric_height_halo_anom2 = tmp-steric_height ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
# Full steric - steric_height
tt = map(array,(temp+temp_chg))
tmp = sw.gpan(np.array(ss),np.array(tt),np.array(pressure_levels)) ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
steric_height_anom = tmp-steric_height ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
del(ss,tmp) ; gc.collect()
# Thermosteric - rho,cp,steric_height
rho_thermo = sw.dens(np.array(so),np.array(tt),np.array(pressure_levels)) ; # units kg m-3
cp_thermo = sw.cp(np.array(so),np.array(tt),np.array(pressure_levels)) ; # units J kg-1 C-1
tmp = sw.gpan(np.array(so),np.array(tt),np.array(pressure_levels)) ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
steric_height_thermo_anom = tmp-steric_height ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
del(tt,tmp) ; gc.collect()
# Halosteric - steric_height
steric_height_halo_anom = steric_height_anom-steric_height_thermo_anom ; # units m3 kg-1 Pa == m2 s-2 == J kg-1 (dynamic decimeter)
# Create heat content
heat_content = np.array(temp)*np.array(rho)*np.array(cp) ; # units J
heat_content_sanom = np.array(temp)*np.array(rho_halo)*np.array(cp_halo) ; # units J
heat_content_tanom = np.array(temp_chg)*np.array(rho)*np.array(cp) ; # units J
#heat_content_tanom = np.array(temp_chg)*np.array(1020)*np.array(4187) ; # units J - try hard-coded - AR5 numbers
heat_content_tsanom = np.array(temp_chg)*np.array(rho_halo)*np.array(cp_halo) ; # units J
# Correct all instances of NaN values and fix masks - applied before cdms variables are created otherwise names/ids/attributes are reset
temp = scrubNaNAndMask(temp,so)
temp_chg = scrubNaNAndMask(temp_chg,so)
rho = scrubNaNAndMask(rho,so)
cp = scrubNaNAndMask(cp,so)
rho_halo = scrubNaNAndMask(rho_halo,so)
cp_halo = scrubNaNAndMask(cp_halo,so)
rho_thermo = scrubNaNAndMask(rho_thermo,so)
cp_thermo = scrubNaNAndMask(cp_thermo,so)
steric_height = scrubNaNAndMask(steric_height,so)
steric_height_anom = scrubNaNAndMask(steric_height_anom,so)
steric_height_thermo_anom = scrubNaNAndMask(steric_height_thermo_anom,so)
steric_height_halo_anom = scrubNaNAndMask(steric_height_halo_anom,so)
steric_height_halo_anom2 = scrubNaNAndMask(steric_height_halo_anom2,so)
heat_content = scrubNaNAndMask(heat_content,so)
heat_content_sanom = scrubNaNAndMask(heat_content_sanom,so)
heat_content_tanom = scrubNaNAndMask(heat_content_tanom,so)
heat_content_tsanom = scrubNaNAndMask(heat_content_tsanom,so)
# Recreate and redress variables
so.id = 'so_mean'
so.units = '1e-3'
so_chg.id = 'so_chg'
so_chg.units = '1e-3'
temp = cdm.createVariable(temp,id='temp_mean')
temp.setAxis(0,so.getAxis(0))
temp.setAxis(1,so.getAxis(1))
temp.setAxis(2,so.getAxis(2))
temp.units = 'degrees_C'
temp_chg = cdm.createVariable(temp_chg,id='temp_chg')
temp_chg.setAxis(0,so.getAxis(0))
temp_chg.setAxis(1,so.getAxis(1))
temp_chg.setAxis(2,so.getAxis(2))
temp_chg.units = 'degrees_C'
rho = cdm.createVariable(rho,id='rho')
rho.setAxis(0,so.getAxis(0))
rho.setAxis(1,so.getAxis(1))
rho.setAxis(2,so.getAxis(2))
rho.name = 'density_mean'
rho.units = 'kg m^-3'
cp = cdm.createVariable(cp,id='cp')
cp.setAxis(0,so.getAxis(0))
cp.setAxis(1,so.getAxis(1))
cp.setAxis(2,so.getAxis(2))
cp.name = 'heat_capacity_mean'
cp.units = 'J kg^-1 C^-1'
rho_halo = cdm.createVariable(rho_halo,id='rho_halo')
rho_halo.setAxis(0,so.getAxis(0))
rho_halo.setAxis(1,so.getAxis(1))
rho_halo.setAxis(2,so.getAxis(2))
rho_halo.name = 'density_mean_halo'
rho_halo.units = 'kg m^-3'
cp_halo = cdm.createVariable(cp_halo,id='cp_halo')
cp_halo.setAxis(0,so.getAxis(0))
cp_halo.setAxis(1,so.getAxis(1))
cp_halo.setAxis(2,so.getAxis(2))
cp_halo.name = 'heat_capacity_mean_halo'
cp_halo.units = 'J kg^-1 C^-1'
rho_thermo = cdm.createVariable(rho_thermo,id='rho_thermo')
rho_thermo.setAxis(0,so.getAxis(0))
rho_thermo.setAxis(1,so.getAxis(1))
rho_thermo.setAxis(2,so.getAxis(2))
rho_thermo.name = 'density_mean_thermo'
rho_thermo.units = 'kg m^-3'
cp_thermo = cdm.createVariable(cp_thermo,id='cp_thermo')
cp_thermo.setAxis(0,so.getAxis(0))
cp_thermo.setAxis(1,so.getAxis(1))
cp_thermo.setAxis(2,so.getAxis(2))
cp_thermo.name = 'heat_capacity_mean_thermo'
cp_thermo.units = 'J kg^-1 C^-1'
steric_height = cdm.createVariable(steric_height,id='steric_height')
steric_height.setAxis(0,so.getAxis(0))
steric_height.setAxis(1,so.getAxis(1))
steric_height.setAxis(2,so.getAxis(2))
steric_height.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_anom = cdm.createVariable(steric_height_anom,id='steric_height_anom')
steric_height_anom.setAxis(0,so.getAxis(0))
steric_height_anom.setAxis(1,so.getAxis(1))
steric_height_anom.setAxis(2,so.getAxis(2))
steric_height_anom.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_thermo_anom = cdm.createVariable(steric_height_thermo_anom,id='steric_height_thermo_anom')
steric_height_thermo_anom.setAxis(0,so.getAxis(0))
steric_height_thermo_anom.setAxis(1,so.getAxis(1))
steric_height_thermo_anom.setAxis(2,so.getAxis(2))
steric_height_thermo_anom.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom = cdm.createVariable(steric_height_halo_anom,id='steric_height_halo_anom')
steric_height_halo_anom.setAxis(0,so.getAxis(0))
steric_height_halo_anom.setAxis(1,so.getAxis(1))
steric_height_halo_anom.setAxis(2,so.getAxis(2))
steric_height_halo_anom.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom2 = cdm.createVariable(steric_height_halo_anom2,id='steric_height_halo_anom2')
steric_height_halo_anom2.setAxis(0,so.getAxis(0))
steric_height_halo_anom2.setAxis(1,so.getAxis(1))
steric_height_halo_anom2.setAxis(2,so.getAxis(2))
steric_height_halo_anom2.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
heat_content = cdm.createVariable(heat_content,id='heat_content')
heat_content.setAxis(0,so.getAxis(0))
heat_content.setAxis(1,so.getAxis(1))
heat_content.setAxis(2,so.getAxis(2))
heat_content.units = 'J'
heat_content_sanom = cdm.createVariable(heat_content_sanom,id='heat_content_sanom')
heat_content_sanom.setAxis(0,so.getAxis(0))
heat_content_sanom.setAxis(1,so.getAxis(1))
heat_content_sanom.setAxis(2,so.getAxis(2))
heat_content_sanom.units = 'J'
heat_content_tanom = cdm.createVariable(heat_content_tanom,id='heat_content_tanom')
heat_content_tanom.setAxis(0,so.getAxis(0))
heat_content_tanom.setAxis(1,so.getAxis(1))
heat_content_tanom.setAxis(2,so.getAxis(2))
heat_content_tanom.units = 'J'
heat_content_tsanom = cdm.createVariable(heat_content_tsanom,id='heat_content_tsanom')
heat_content_tsanom.setAxis(0,so.getAxis(0))
heat_content_tsanom.setAxis(1,so.getAxis(1))
heat_content_tsanom.setAxis(2,so.getAxis(2))
heat_content_tsanom.units = 'J'
# Create model-based depth index for subset target levels
newdepth = np.array([5,10,20,30,40,50,75,100,125,150,200,300,500,700,1000,1500,1800,2000]).astype('f');
newdepth_bounds = np.array([[0,5],[5,10],[10,20],[20,30],[30,40],[40,50],[50,75],[75,100],[100,125],[125,150],
[150,200],[200,300],[300,500],[500,700],[700,1000],[1000,1500],[1500,1800],[1800,2000]]).astype('f')
#newdepth = np.array([200,300,500,700,1000,1500,1800,2000]).astype('f');
#newdepth_bounds = np.array([[0,200],[200,300],[300,500],[500,700],[700,1000],[1000,1500],[1500,1800],[1800,2000]]).astype('f')
# Interpolate to depths
so_depthInterp = cdu.linearInterpolation(so,pressure_levels,levels=newdepth)
temp_depthInterp = cdu.linearInterpolation(temp,pressure_levels,levels=newdepth)
steric_height_depthInterp = cdu.linearInterpolation(steric_height,pressure_levels,levels=newdepth)
steric_height_anom_depthInterp = cdu.linearInterpolation(steric_height_anom,pressure_levels,levels=newdepth)
steric_height_thermo_anom_depthInterp = cdu.linearInterpolation(steric_height_thermo_anom,pressure_levels,levels=newdepth)
steric_height_halo_anom_depthInterp = cdu.linearInterpolation(steric_height_halo_anom,pressure_levels,levels=newdepth)
steric_height_halo_anom2_depthInterp = cdu.linearInterpolation(steric_height_halo_anom2,pressure_levels,levels=newdepth)
heat_content_sanom_depthInterp = cdu.linearInterpolation(heat_content_sanom,pressure_levels,levels=newdepth)
heat_content_tanom_depthInterp = cdu.linearInterpolation(heat_content_tanom,pressure_levels,levels=newdepth)
heat_content_tsanom_depthInterp = cdu.linearInterpolation(heat_content_tanom,pressure_levels,levels=newdepth)
# Fix masks - applied before cdms variables are created otherwise names/ids/attributes are reset
temp_depthInterp = scrubNaNAndMask(temp_depthInterp,so_depthInterp)
steric_height_depthInterp = scrubNaNAndMask(steric_height_depthInterp,so_depthInterp)
steric_height_anom_depthInterp = scrubNaNAndMask(steric_height_anom_depthInterp,so_depthInterp)
steric_height_thermo_anom_depthInterp = scrubNaNAndMask(steric_height_thermo_anom_depthInterp,so_depthInterp)
steric_height_halo_anom_depthInterp = scrubNaNAndMask(steric_height_halo_anom_depthInterp,so_depthInterp)
steric_height_halo_anom2_depthInterp = scrubNaNAndMask(steric_height_halo_anom2_depthInterp,so_depthInterp)
heat_content_sanom_depthInterp = scrubNaNAndMask(heat_content_sanom_depthInterp,so_depthInterp)
heat_content_tanom_depthInterp = scrubNaNAndMask(heat_content_tanom_depthInterp,so_depthInterp)
heat_content_tsanom_depthInterp = scrubNaNAndMask(heat_content_tsanom_depthInterp,so_depthInterp)
# Fix bounds
newdepth = so_depthInterp.getAxis(0)
newdepth.setBounds(newdepth_bounds)
del(newdepth_bounds)
newdepth.id = 'depth2'
newdepth.units_long = 'decibar (pressure)'
newdepth.positive = 'down'
newdepth.long_name = 'sea_water_pressure'
newdepth.standard_name = 'sea_water_pressure'
newdepth.units = 'decibar'
newdepth.axis = 'Z'
# Assign corrected bounds
so_depthInterp.setAxis(0,newdepth)
temp_depthInterp.setAxis(0,newdepth)
steric_height_depthInterp.setAxis(0,newdepth)
steric_height_anom_depthInterp.setAxis(0,newdepth)
steric_height_thermo_anom_depthInterp.setAxis(0,newdepth)
steric_height_halo_anom_depthInterp.setAxis(0,newdepth)
steric_height_halo_anom2_depthInterp.setAxis(0,newdepth)
heat_content_sanom_depthInterp.setAxis(0,newdepth)
heat_content_tanom_depthInterp.setAxis(0,newdepth)
heat_content_tsanom_depthInterp.setAxis(0,newdepth)
# Average/integrate to surface - configure bounds
# Preallocate arrays
so_depthAve = np.ma.zeros([len(newdepth),shape(so)[1],shape(so)[2]])
temp_depthAve = so_depthAve.copy()
heat_content_sanom_depthInteg = so_depthAve.copy()
heat_content_tanom_depthInteg = so_depthAve.copy()
heat_content_tsanom_depthInteg = so_depthAve.copy()
for count,depth in enumerate(newdepth):
tmp = cdu.averager(so_depthInterp[0:(count+1),...],axis=0,weights='weighted',action='average')
so_depthAve[count,] = tmp;
tmp = cdu.averager(temp_depthInterp[0:(count+1),...],axis=0,weights='weighted',action='average')
temp_depthAve[count,] = tmp;
tmp = cdu.averager(heat_content_sanom_depthInterp[0:(count+1),...],axis=0,weights='weighted',action='sum')
heat_content_sanom_depthInteg[count,] = tmp
tmp = cdu.averager(heat_content_tanom_depthInterp[0:(count+1),...],axis=0,weights='weighted',action='sum')
heat_content_tanom_depthInteg[count,] = tmp
tmp = cdu.averager(heat_content_tsanom_depthInterp[0:(count+1),...],axis=0,weights='weighted',action='sum')
heat_content_tsanom_depthInteg[count,] = tmp
del(heat_content_tanom_depthInterp,heat_content_tsanom_depthInterp); gc.collect()
# Fix masks - applied before cdms variables are created otherwise names/ids/attributes are reset
so_depthAve = scrubNaNAndMask(so_depthAve,so_depthInterp)
temp_depthAve = scrubNaNAndMask(temp_depthAve,so_depthInterp)
heat_content_sanom_depthInteg = scrubNaNAndMask(heat_content_sanom_depthInteg,so_depthInterp)
heat_content_tanom_depthInteg = scrubNaNAndMask(heat_content_tanom_depthInteg,so_depthInterp)
heat_content_tsanom_depthInteg = scrubNaNAndMask(heat_content_tsanom_depthInteg,so_depthInterp)
del(so_depthInterp)
# Convert numpy arrays to cdms objects
heat_content_sanom_depthInteg = cdm.createVariable(heat_content_sanom_depthInteg,id='heat_content_sanom_depthInteg')
heat_content_sanom_depthInteg.id = 'heat_content_sanom_depthInteg'
heat_content_sanom_depthInteg.setAxis(0,newdepth)
heat_content_sanom_depthInteg.setAxis(1,so.getAxis(1))
heat_content_sanom_depthInteg.setAxis(2,so.getAxis(2))
heat_content_sanom_depthInteg.units = 'J'
heat_content_tanom_depthInteg = cdm.createVariable(heat_content_tanom_depthInteg,id='heat_content_tanom_depthInteg')
heat_content_tanom_depthInteg.id = 'heat_content_tanom_depthInteg'
heat_content_tanom_depthInteg.setAxis(0,newdepth)
heat_content_tanom_depthInteg.setAxis(1,so.getAxis(1))
heat_content_tanom_depthInteg.setAxis(2,so.getAxis(2))
heat_content_tanom_depthInteg.units = 'J'
heat_content_tsanom_depthInteg = cdm.createVariable(heat_content_tsanom_depthInteg,id='heat_content_tsanom_depthInteg')
heat_content_tsanom_depthInteg.id = 'heat_content_tsanom_depthInteg'
heat_content_tsanom_depthInteg.setAxis(0,newdepth)
heat_content_tsanom_depthInteg.setAxis(1,so.getAxis(1))
heat_content_tsanom_depthInteg.setAxis(2,so.getAxis(2))
heat_content_tsanom_depthInteg.units = 'J'
so_depthAve = cdm.createVariable(so_depthAve,id='so_depthAve')
so_depthAve.id = 'so_depthAve'
so_depthAve.setAxis(0,newdepth)
so_depthAve.setAxis(1,so.getAxis(1))
so_depthAve.setAxis(2,so.getAxis(2))
so_depthAve.units = '1e-3'
temp_depthAve = cdm.createVariable(temp_depthAve,id='temp_depthAve')
temp_depthAve.id = 'temp_depthAve'
temp_depthAve.setAxis(0,newdepth)
temp_depthAve.setAxis(1,so.getAxis(1))
temp_depthAve.setAxis(2,so.getAxis(2))
temp_depthAve.units = 'degrees_C'
steric_height_depthInterp = cdm.createVariable(steric_height_depthInterp,id='steric_height_depthInterp')
steric_height_depthInterp.setAxis(0,newdepth)
steric_height_depthInterp.setAxis(1,so.getAxis(1))
steric_height_depthInterp.setAxis(2,so.getAxis(2))
steric_height_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_anom_depthInterp = cdm.createVariable(steric_height_anom_depthInterp,id='steric_height_anom_depthInterp')
steric_height_anom_depthInterp.setAxis(0,newdepth)
steric_height_anom_depthInterp.setAxis(1,so.getAxis(1))
steric_height_anom_depthInterp.setAxis(2,rho.getAxis(2))
steric_height_anom_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_thermo_anom_depthInterp = cdm.createVariable(steric_height_thermo_anom_depthInterp,id='steric_height_thermo_anom_depthInterp')
steric_height_thermo_anom_depthInterp.setAxis(0,newdepth)
steric_height_thermo_anom_depthInterp.setAxis(1,so.getAxis(1))
steric_height_thermo_anom_depthInterp.setAxis(2,so.getAxis(2))
steric_height_thermo_anom_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom_depthInterp = cdm.createVariable(steric_height_halo_anom_depthInterp,id='steric_height_halo_anom_depthInterp')
steric_height_halo_anom_depthInterp.setAxis(0,newdepth)
steric_height_halo_anom_depthInterp.setAxis(1,so.getAxis(1))
steric_height_halo_anom_depthInterp.setAxis(2,so.getAxis(2))
steric_height_halo_anom_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
steric_height_halo_anom2_depthInterp = cdm.createVariable(steric_height_halo_anom2_depthInterp,id='steric_height_halo_anom2_depthInterp')
steric_height_halo_anom2_depthInterp.setAxis(0,newdepth)
steric_height_halo_anom2_depthInterp.setAxis(1,so.getAxis(1))
steric_height_halo_anom2_depthInterp.setAxis(2,so.getAxis(2))
steric_height_halo_anom2_depthInterp.units = 'm^3 kg^-1 Pa (dynamic decimeter)'
# Cleanup workspace
del(newdepth) ; gc.collect()
# Write variables to file
if os.path.isfile(outFileName):
os.remove(outFileName)
filehandle = cdm.open(outFileName,'w')
# Global attributes
globalAttWrite(filehandle,options=None) ; # Use function to write standard global atts
# Write seawater version
filehandle.seawater_library_version = sw.__version__
# Write makeSteric version
makeStericPath = str(makeSteric.__code__).split(' ')[6]
makeStericPath = replace(replace(makeStericPath,'"',''),',','') ; # Clean scraped path
filehandle.makeSteric_version = ' '.join(getGitInfo(makeStericPath)[0:3])
# Master variables
filehandle.write(so.astype('float32'))
filehandle.write(so_chg.astype('float32'))
filehandle.write(so_depthAve.astype('float32'))
filehandle.write(temp.astype('float32'))
filehandle.write(temp_chg.astype('float32'))
filehandle.write(temp_depthAve.astype('float32'))
# Derived variables
filehandle.write(cp.astype('float32'))
filehandle.write(cp_halo.astype('float32'))
filehandle.write(cp_thermo.astype('float32'))
filehandle.write(rho.astype('float32'))
filehandle.write(rho_halo.astype('float32'))
filehandle.write(rho_thermo.astype('float32'))
filehandle.write(heat_content.astype('float32'))
filehandle.write(heat_content_sanom.astype('float32'))
filehandle.write(heat_content_sanom_depthInteg.astype('float32'))
filehandle.write(heat_content_tanom.astype('float32'))
filehandle.write(heat_content_tanom_depthInteg.astype('float32'))
filehandle.write(heat_content_tsanom.astype('float32'))
filehandle.write(heat_content_tsanom_depthInteg.astype('float32'))
filehandle.write(steric_height.astype('float32'))
filehandle.write(steric_height_depthInterp.astype('float32'))
filehandle.write(steric_height_anom.astype('float32'))
filehandle.write(steric_height_anom_depthInterp.astype('float32'))
filehandle.write(steric_height_halo_anom.astype('float32'))
filehandle.write(steric_height_halo_anom2.astype('float32'))
filehandle.write(steric_height_halo_anom_depthInterp.astype('float32'))
filehandle.write(steric_height_halo_anom2_depthInterp.astype('float32'))
filehandle.write(steric_height_thermo_anom.astype('float32'))
filehandle.write(steric_height_thermo_anom_depthInterp.astype('float32'))
filehandle.close()
# Cleanup workspace
del(outFileName) ; gc.collect()
# Open outfile to write
g = cdm.open(os.path.join(outdir, mod, run, ver, fout), 'w+')
# Copy across attributes
# Write variable attributes back out to new variable
for k in d.attributes.keys():
setattr(dan, k, d.attributes[k])
# Write out file global atts
for k in f.attributes.keys():
setattr(g, k, f.attributes[k])
history = getattr(f, 'history')
# Write out start and end years
dt = dan.getTime().asComponentTime()
g.an_start_year = dt[0].year
g.an_end_year = dt[-1].year
# Write new outfile global atts
globalAttWrite(g, options=None)
# Use function to write standard global atts to output file
# Write new variable atts
dan.comment = "Converted to annual from monthly mean data"
g.write(dan)
# Deal with eta and depth variables in sigma-coord files
if 'eta' in f.variables.keys():
if ub == yrsX[-1]:
d = f('eta', time=(cdt.comptime(lb), cdt.comptime(ub)))
# Include last year
else:
d = f('eta',
time=(cdt.comptime(lb), cdt.comptime(ub), 'co'))
# Exclude last year
etaan = cdu.YEAR(d)
etaan = etaan.astype('float32')
sftof.id = 'sftof'
# Create output files
for counter,output in enumerate(fxFiles):
outFileA = os.path.join(sanPath,filePath.split('/')[-1])
outFileA = outFileA.replace('_'.join(['',last_year]),'')
#outFileA = outFileA.replace('sst',output)
outFileA = outFileA.replace('sic',output)
print 'Processing: ',outFileA
if not os.path.exists(sanPath):
mkDirNoOSErr(sanPath)
if os.path.exists(outFileA):
os.remove(outFileA)
fO = cdm.open(outFileA,'w')
# global atts
globalAttWrite(fO,options='noid'); # 'noid' option prevents data_contact and institution being written
fO.Conventions = 'CF-1.6' ; fO.sync()
fxVar = eval(output)
fO.title = fxVar.long_name
fO.activity_id = activity_id
fO.further_info_url = further_info_url
fO.comment = comment ; fO.sync()
fO.contact = contact ; fO.sync() ; # Overwritten globalAttWrite
utcNow = datetime.datetime.utcnow();
utcNow = utcNow.replace(tzinfo=pytz.utc)
timeFormat = utcNow.strftime("%Y-%m-%dT%H:%M:%SZ")
fO.creation_date = timeFormat
fO.data_structure = data_structure
fO.institute_id = institute_id ; fO.sync()
fO.institution = institution ; fO.sync()
fO.license = license_txt
clim.id = "".join([var,'_mean'])
# Check path exists
if not os.path.exists(os.sep.join(outfile.split('/')[0:-1])):
os.makedirs(os.sep.join(outfile.split('/')[0:-1]))
# Check file exists
if os.path.exists(outfile):
print "** File exists.. removing **"
os.remove(outfile)
f_out = cdm.open(outfile,'w')
# Copy across global attributes from source file - do this first, then write again so new info overwrites
for i,key in enumerate(f_in.attributes.keys()):
setattr(f_out,key,f_in.attributes.get(key))
del(i,key) ; gc.collect()
# Write new outfile global atts
globalAttWrite(f_out,options=None) ; # Use function to write standard global atts to output file
# Write to output file
f_out.write(clim) ; # Write clim first as it has all grid stuff
if 'slope_drift1' in locals():
f_out.write(clim_drift1)
#f_out.write(clim_drift2)
f_out.write(slope)
f_out.write(slope_err)
if 'slope_drift1' in locals():
f_out.write(slope_drift1)
f_out.write(slope_err_drift1)
#f_out.write(slope_drift2)
#f_out.write(slope_err_drift2)
# Close all files
f_in.close()
f_out.close()
# Open outfile to write
g = cdm.open(os.path.join(outdir,mod,run,ver,fout),'w+')
# Copy across attributes
# Write variable attributes back out to new variable
for k in d.attributes.keys():
setattr(dan,k,d.attributes[k])
# Write out file global atts
for k in f.attributes.keys():
setattr(g,k,f.attributes[k])
history = getattr(f,'history')
# Write out start and end years
dt = dan.getTime().asComponentTime()
g.an_start_year = dt[0].year
g.an_end_year = dt[-1].year
# Write new outfile global atts
globalAttWrite(g,options=None) ; # Use function to write standard global atts to output file
# Write new variable atts
dan.comment = "Converted to annual from monthly mean data"
g.write(dan)
# Deal with eta and depth variables in sigma-coord files
if 'eta' in f.variables.keys():
if ub == yrsX[-1]:
d = f('eta',time=(cdt.comptime(lb),cdt.comptime(ub))) ; # Include last year
else:
d = f('eta',time=(cdt.comptime(lb),cdt.comptime(ub),'co')) ; # Exclude last year
etaan = cdu.YEAR(d)
etaan = etaan.astype('float32') ; # Recast from float64 back to float32 precision - half output file sizes
# Write variable attributes back out to new variable
for k in d.attributes.keys():
setattr(etaan,k,d.attributes[k])
# Write new variable atts
print('Check oceanAreaM2:',earthWaterAreaKm2*1e6)
#areacello = areacello.squeeze() ; # Loses grid info
areacello = areacello*earthAreaM2 ; # Multiply by Earth area
areacello.id = 'areacello'
areacello.units = 'm2'
areacello.earthSurfaceAreaM2 = earthAreaM2
areacello.earthWaterAreaM2 = earthWaterAreaKm2*1e6
areacello.earthLandAreaM2 = earthLandAreaKm2*1e6
areacello.oceanSurfaceAreaM2 = areacello.sum()
# Redress variable
print('shape(areacello) 0:',areacello.shape)
#areacello = areacello[:,mv.newaxis]
areacello = np.expand_dims(areacello,axis=0)
print('shape(areacello) 1:',areacello.shape)
areacello = np.expand_dims(areacello,axis=0)
print('shape(areacello) 2:',areacello.shape)
areacello.setAxis(0,tmp1.getAxis(0))
areacello.setAxis(1,tmp1.getAxis(1))
del(tmp,tmp1) ; gc.collect()
#continue
# Create outfile handle
outFile = replace(replace(inFile,'thetao','areacello'),'.xml','.nc')
if os.path.isfile(outFile):
print 'purge'
os.remove(outFile)
fHo = cdm.open(outFile,'w')
fHo.write(areacello)
globalAttWrite(fHo,options=None) ; # Use function to write standard global atts
fHo.close()
fH.close()
