def get_land_ice_mask(fname):
fland = cdms.open(cmip5.landfrac(fname))
fglac = cdms.open(cmip5.glacierfrac(fname))
land = fland("sftlf")
glacier=fglac("sftgif")
#mask ocean and ice sheets
totmask = np.logical_or(land==0,glacier==100.)
# totmask =np.repeat(totmask.asma()[np.newaxis],12,axis=0)
fland.close()
fglac.close()
return totmask
def get_tas_and_precip_from_file(fname):
f = cdms.open(fname)
tas = cdutil.ANNUALCYCLE.climatology(f("tas",time=('1979-1-1','2005-12-31')))-273.15 #convert from K to C
fpr = cdms.open(get_corresponding_pr(fname))
pr = cdutil.ANNUALCYCLE.climatology(fpr("pr",time=('1979-1-1','2005-12-31')))*(86400 * 30) #convert to mm
fland = cdms.open(cmip5.landfrac(fname))
fglac = cdms.open(cmip5.glacierfrac(fname))
land = fland("sftlf")
glacier=fglac("sftgif")
#mask ocean and ice sheets
totmask = np.logical_or(land==0,glacier==100.)
totmask =np.repeat(totmask.asma()[np.newaxis],12,axis=0)
tasmask = MV.masked_where(totmask,tas)
prmask = MV.masked_where(totmask,pr)
f.close()
fpr.close()
fland.close()
fglac.close()
return tasmask,prmask
def PET_from_cmip(fname):
"""
fname must be a temperature file
Calculate PET from cmip5 data on crunchy
#Ta = temperature, degrees K = tas
# Rnet = surface net radiation, W/m2 = (hfls+hfss)
# u = wind speed at 2 meters, m/s = sfcWind (??)
# q = specific humidity, kg/kg = huss
# press = surface pressure, Pascals = ps
"""
#Get land and ice masks
temp_variable = fname.split(".")[-4]
f_ta = cdms.open(fname)
Ta = f_ta(temp_variable)
f_ta.close()
fland = cdms.open(cmip5.landfrac(fname))
land = fland("sftlf")
fland.close()
try:
fglac = cdms.open(cmip5.glacierfrac(fname))
glacier = fglac("sftgif")
fglac.close()
except:
glacier = MV.zeros(land.shape)
#mask ocean and ice sheets
totmask = np.logical_or(land == 0, glacier == 100.)
nt = len(Ta.getTime())
totmask = np.repeat(totmask.asma()[np.newaxis], nt, axis=0)
if cmip5.get_corresponding_file(fname, "sfcWind") is None:
#if no surface wind is available, use NCEP reanalyis
f_wind = cdms.open("wspd.mon.ltm.nc")
wspd = f_wind("wspd")
ny = nt / 12
u = np.repeat(wspd, ny, axis=0) #Repeat monthly climatologies
u.setAxisList([Ta.getTime()] + wspd.getAxisList()[1:])
u.id = "sfcWind"
f_wind.close()
else:
f_wind = cdms.open(cmip5.get_corresponding_file(fname, "sfcWind"))
u = f_wind("sfcWind")
f_wind.close()
f_hfls = cdms.open(cmip5.get_corresponding_file(fname, "hfls"))
hfls = f_hfls("hfls")
f_hfls.close()
# Some models put sfcWind on a different grid to calculate surface fluxes
if u.shape != hfls.shape:
u = u.regrid(hfls.getGrid(), regridTool='regrid2')
f_hfss = cdms.open(cmip5.get_corresponding_file(fname, "hfss"))
hfss = f_hfss("hfss")
f_hfss.close()
Rnet = hfss + hfls
f_huss = cdms.open(cmip5.get_corresponding_file(fname, "huss"))
q = f_huss("huss")
f_huss.close()
f_ps = cdms.open(cmip5.get_corresponding_file(fname, "ps"))
press = f_ps("ps")
f_ps.close()
corresponding_files = [
cmip5.get_corresponding_file(fname, var)
for var in ["hfss", temp_variable, "huss", "ps", "hfls"]
]
L = cmip5.get_common_timeax(corresponding_files)
if type(L) == type(()):
PET, VPD, RH = penmont_vpd_SH(Ta(time=L), Rnet(time=L), q(time=L),
press(time=L), u(time=L))
else:
PET, VPD, RH = penmont_vpd_SH(Ta[:L], Rnet[:L], q[:L], press[:L],
u[:L])
PET = MV.masked_where(totmask, PET)
PET.setAxisList(Ta.getAxisList())
PET.id = "PET"
VPD = MV.masked_where(totmask, VPD)
VPD.setAxisList(Ta.getAxisList())
VPD.id = "VPD"
RH = MV.masked_where(totmask, RH)
RH.setAxisList(Ta.getAxisList())
RH.id = "RH"
return PET, VPD, RH
def PET_from_cmip(fname, temp_variable="tas"):
#Ta = temperature, degrees K = tas
# Rnet = surface net radiation, W/m2 = (hfls+hfss)
# u = wind speed at 2 meters, m/s = sfcWind (??)
# q = specific humidity, kg/kg = huss
# press = surface pressure, Pascals = ps
#Get land and ice masks
fland = cdms.open(cmip5.landfrac(fname))
fglac = cdms.open(cmip5.glacierfrac(fname))
land = fland("sftlf")
glacier = fglac("sftgif")
#mask ocean and ice sheets
totmask = np.logical_or(land == 0, glacier == 100.)
f_wind = cdms.open(fname)
u = f_wind("sfcWind")
f_wind.close()
nt = len(u.getTime())
totmask = np.repeat(totmask.asma()[np.newaxis], nt, axis=0)
f_hfls = cdms.open(cmip5.get_corresponding_file(fname, "hfls"))
hfls = f_hfls("hfls")
f_hfls.close()
f_hfss = cdms.open(cmip5.get_corresponding_file(fname, "hfss"))
hfss = f_hfss("hfss")
f_hfss.close()
Rnet = hfss + hfls
f_ta = cdms.open(cmip5.get_corresponding_file(fname, temp_variable))
Ta = f_ta(temp_variable)
f_ta.close()
f_huss = cdms.open(cmip5.get_corresponding_file(fname, "huss"))
q = f_huss("huss")
f_huss.close()
f_ps = cdms.open(cmip5.get_corresponding_file(fname, "ps"))
press = f_ps("ps")
f_ps.close()
PET, VPD, RH = penmont_vpd_SH(Ta, Rnet, q, press, u)
PET = MV.masked_where(totmask, PET)
PET.setAxisList(u.getAxisList())
PET.id = "PET"
VPD = MV.masked_where(totmask, VPD)
VPD.setAxisList(u.getAxisList())
VPD.id = "VPD"
RH = MV.masked_where(totmask, RH)
RH.setAxisList(u.getAxisList())
RH.id = "RH"
return PET, VPD, RH
def PET_from_cmip(fname, temp_variable="tas"):
#Ta = temperature, degrees K = tas
# Rnet = surface net radiation, W/m2 = (hfls+hfss)
# u = wind speed at 2 meters, m/s = sfcWind (??)
# q = specific humidity, kg/kg = huss
# press = surface pressure, Pascals = ps
#Get land and ice masks
fland = cdms.open(cmip5.landfrac(fname))
land = fland("sftlf")
fland.close()
try:
fglac = cdms.open(cmip5.glacierfrac(fname))
glacier = fglac("sftgif")
fglac.close()
except:
glacier = MV.zeros(land.shape)
#mask ocean and ice sheets
totmask = np.logical_or(land == 0, glacier == 100.)
f_wind = cdms.open(fname)
u = f_wind("sfcWind")
f_wind.close()
nt = len(u.getTime())
totmask = np.repeat(totmask.asma()[np.newaxis], nt, axis=0)
f_hfls = cdms.open(cmip5.get_corresponding_file(fname, "hfls"))
hfls = f_hfls("hfls")
f_hfls.close()
# Some models put sfcWind on a different grid to calculate surface fluxes
if u.shape != hfls.shape:
u = u.regrid(hfls.getGrid(), regridTool='regrid2')
f_hfss = cdms.open(cmip5.get_corresponding_file(fname, "hfss"))
hfss = f_hfss("hfss")
f_hfss.close()
Rnet = hfss + hfls
f_ta = cdms.open(cmip5.get_corresponding_file(fname, temp_variable))
Ta = f_ta(temp_variable)
f_ta.close()
f_huss = cdms.open(cmip5.get_corresponding_file(fname, "huss"))
q = f_huss("huss")
f_huss.close()
f_ps = cdms.open(cmip5.get_corresponding_file(fname, "ps"))
press = f_ps("ps")
f_ps.close()
corresponding_files = [
cmip5.get_corresponding_file(fname, var)
for var in ["hfss", temp_variable, "huss", "ps", "hfls"]
]
L = cmip5.get_common_timeax(corresponding_files)
PET, VPD, RH = penmont_vpd_SH(Ta[:L], Rnet[:L], q[:L], press[:L], u[:L])
PET = MV.masked_where(totmask, PET)
PET.setAxisList(Ta.getAxisList())
PET.id = "PET"
VPD = MV.masked_where(totmask, VPD)
VPD.setAxisList(Ta.getAxisList())
VPD.id = "VPD"
RH = MV.masked_where(totmask, RH)
RH.setAxisList(Ta.getAxisList())
RH.id = "RH"
return PET, VPD, RH