def qflx_prec_2lhflx(QFLX, PRECC, PRECL, PRECSC, PRECSL):
"""computes LHFLX from QFLX and the precipitation variables PRECC, PRECL, PRECSC, PERCSL.
Assumes that the input is in compatible units, such as kg/(m^2 s) for QFLX
and m/s for PRECC, PRECL."""
QFLX = convert_units(QFLX, 'kg/(m^2 s)')
PRECC = convert_units(PRECC, 'm/s')
PRECL = convert_units(PRECL, 'm/s')
PRECSC = convert_units(PRECSC, 'm/s')
PRECSL = convert_units(PRECSL, 'm/s')
Lv = 2.501e6 # units J/kg
Lf = 3.337e5 # units J/kg
LHFLX = (Lv + Lf) * QFLX - Lf * 1.e3 * (PRECC + PRECL - PRECSC - PRECSL)
LHFLX.units = "W/m^2"
LHFLX.long_name = "Surf latent heat flux"
return LHFLX
def qflx_2lhflx(QFLX):
"""computes LHFLX from QFLX."""
# Based on get_LHFLX in the NCL code for AMWG. It may be that Susannah Burrow's qflx_lhflx_conversions.py
# does the same thing in more generality, but I've not looked at it carefully.
QFLX = convert_units(QFLX, 'kg/(m^2 s)')
Lv = 2.501e6 # units J/kg
LHFLX = Lv * QFLX
LHFLX.units = "W/m^2"
LHFLX.long_name = "Surf latent heat flux"
return LHFLX
def prect2precip( PRECT, seasonid ):
"""converts a precipitation rate PRECT (averaged over a season; typical units mm/day)
to a cumulative precipitation PRECIP (summed over the season). Thus PRECIP is PRECT multiplied
by the length of the season. PRECIP is returned. We assume a 365-day (noleap) calendar."""
lenseason = { 'ANN':365, 'JFMAMJJASOND':365, 'DJF':90, 'MAM':92, 'JJA':92, 'SON':91,
'JAN':31, 'FEB':28, 'MAR':31, 'APR':30, 'MAY':31,
'JUN':30, 'JUL':31, 'AUG':31, 'SEP':30, 'OCT':31, 'NOV':30, 'DEC':31 }
if seasonid not in lenseason:
raise DiagError( "While converting precipitation rate to cumulative, cannot identify season %s" % seasonid )
PRECIP = lenseason[seasonid] * convert_units( PRECT, 'mm/day' )
PRECIP.units = 'mm'
return PRECIP
derived_var(
vid='CLDLOW_TAU1.3-9.4_MISR', inputs=['CLMISR'], outputs=['CLDLOW_TAU1.3-9.4_MISR'],
func=(lambda clmisr, h0=0,h1=3, t0=1.3,t1=9.4: reduce_height_thickness( clmisr, h0,h1, t0,t1) ) )
#func=(lambda clmisr, h0=0,h1=6, t0=2,t1=4: reduce_height_thickness( clmisr, h0,h1, t0,t1) ) )
],
#6-MISR
'CLDLOW_TAU9.4_MISR':[
derived_var(
vid='CLDLOW_TAU9.4_MISR', inputs=['CLMISR'], outputs=['CLDLOW_TAU9.4_MISR'],
func=(lambda clmisr, h0=0,h1=3, t0=9.4,t1=379: reduce_height_thickness(
clmisr, h0,h1, t0,t1) ) )
],
#TGCLDLWP_OCEAN
'TGCLDLWP_OCN':[derived_var(
vid='TGCLDLWP', inputs=['TGCLDLWP_OCEAN'], outputs=['TGCLDLWP_OCN'],
func=(lambda x: convert_units(x, 'g/m^2')) ),
derived_var(
vid='TGCLDLWP_OCN', inputs=['TGCLDLWP', 'OCNFRAC'], outputs=['TGCLDLWP_OCN'],
func=(lambda x, y, units='g/m^2': simple_vars.ocean_only(x,y, units)) )],
#...end of clouds, Yuying Zhang
# To compare LHFLX and QFLX, need to unify these to a common variable
# e.g. LHFLX (latent heat flux in W/m^2) vs. QFLX (evaporation in mm/day).
# The conversion functions are defined in qflx_lhflx_conversions.py.
# [SMB: 25 Feb 2015]
#'LHFLX':[derived_var(
# vid='LHFLX', inputs=['QFLX'], outputs=['LHFLX'],
# func=(lambda x: x) ) ],
#'QFLX':[derived_var(
# vid='QFLX', inputs=['LHFLX'], outputs=['QFLX'],
# func=(lambda x: x) ) ],
def ocean_only(var, OCNFRAC, units=None):
if units != None:
convert_units(var, units)
return mask_by(var, OCNFRAC, lo=0.5, hi=None)