def SH_kgkg_sur(self, ni=10):
'''
Specific humidity [kg/kg]
https://crudata.uea.ac.uk/cru/pubs/thesis/2007-willett/2INTRO.pdf
'''
# temporary variable, interpolate station by station
dewp = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.getValues(self.nc_sa, 'd2m',
ni) # self.nc_sa.variables['d2m'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
dewp[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n] - 273.15)
# compute
SH = spec_hum_kgkg(dewp[:, :], self.rg.variables['PRESS_pl'][:, :])
# add variable to ncdf file
vn = 'SH_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Specific humidity ERA-5 surface only'
var.units = '1'
var.standard_name = 'specific_humidity'
self.rg.variables[vn][:, :] = SH
def WIND_sur(self):
"""
Wind speed and direction at 10 metre derived from surface data,
exclusively.
"""
# temporary variable, interpolate station by station
U = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.nc_sa.variables['U10M'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
U[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n])
# temporary variable, interpolate station by station
V = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.nc_sa.variables['V10M'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
V[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n])
# add variable to ncdf file
vn = 'WSPD_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = '10 metre wind speed {} surface only'.format(self.NAME)
var.units = 'm s-1'
var.standard_name = 'wind_speed'
# add variable to ncdf file
vn = 'WDIR_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = '10 metre wind direction {} surface only'.format(
self.NAME)
var.units = 'degree'
var.standard_name = 'wind_from_direction'
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
WS = np.sqrt(np.power(V[:, n], 2) + np.power(U[:, n], 2))
WD = [
atan2(V[i, n], U[i, n]) * (180 / pi) + 180
for i in np.arange(V.shape[0])
]
self.rg.variables['WSPD_sur'][:, n] = WS
self.rg.variables['WDIR_sur'][:, n] = WD
def WIND_sur(self, ni=10):
"""
Wind speed and direction temperature derived from surface data,
exclusively.
"""
# temporary variable, interpolate station by station
U = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.getValues(self.nc_sa, 'u10',
ni) # self.nc_sa.variables['u10'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
U[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n])
# temporary variable, interpolate station by station
V = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.getValues(self.nc_sa, 'v10',
ni) # self.nc_sa.variables['v10'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
V[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n])
# wind speed, add variable to ncdf file, convert
vn_spd = 'WSPD_sur' # variable name
var = self.rg.createVariable(vn_spd, 'f4', ('time', 'station'))
var.long_name = '10 wind speed ERA-5 surface only'
var.units = 'm s-1'
var.standard_name = 'wind_speed'
# wind direction, add variable to ncdf file, convert, relative to North
vn_dir = 'WDIR_sur' # variable name
var = self.rg.createVariable(vn_dir, 'f4', ('time', 'station'))
var.long_name = '10 wind direction ERA-5 surface only'
var.units = 'degree'
var.standard_name = 'wind_from_direction'
WS = np.sqrt(np.power(V, 2) + np.power(U, 2))
self.rg.variables[vn_spd][:, :] = WS
# Wind direction:
# U - easterly component V - northerly component
# convert to "clockwise from north" from "anti-clockwise from x-axis" : 90 - angle
# convert "from direction" : + 180
WD = 90 - (np.arctan2(V, U) * (180 / np.pi)) + 180
self.rg.variables[vn_dir][:, :] = WD
def AIRT_C_sur(self):
"""
Air temperature derived from surface data, exclusively.
"""
# add variable to ncdf file
vn = 'AIRT_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = '2_metre_temperature {} surface only'.format(self.NAME)
var.units = self.nc_sa.variables['t2m'].units.encode('UTF8')
# interpolate station by station
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.nc_sa.variables['t2m'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
self.rg.variables[vn][:, n] = series_interpolate(
self.times_out_nc, time_in * 3600, values[:, n] - 273.15)
def AIRT_C_pl(self):
"""
Air temperature derived from pressure levels, exclusively.
"""
vn = 'AIRT_pl' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'air_temperature {} pressure levels only'.format(
self.NAME)
var.units = 'degrees_C'
var.standard_name = 'air_temperature'
# interpolate station by station
time_in = self.nc_pl.variables['time'][:].astype(np.int64)
values = self.nc_pl.variables['T'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
self.rg.variables[vn][:, n] = series_interpolate(
self.times_out_nc, time_in * 3600, values[:, n] - 273.15)
def PRESS_Pa_pl(self, ni=10):
"""
Surface air pressure from pressure levels.
"""
# add variable to ncdf file
vn = 'PRESS_pl' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'air_pressure ERA-5 pressure levels only'
var.units = 'Pa'
var.standard_name = 'surface_air_pressure'
# interpolate station by station
time_in = self.nc_pl.variables['time'][:].astype(np.int64)
values = self.getValues(self.nc_pl, 'air_pressure', ni)
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
# scale from hPa to Pa
self.rg.variables[vn][:, n] = series_interpolate(
self.times_out_nc, time_in * 3600, values[:, n]) * 100
def SH_kgkg_sur(self):
'''
Specific humidity [kg/kg] derived from surface data, exclusively.
'''
# add variable to ncdf file
vn = 'SH_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Specific humidity {} surface only'.format(self.NAME)
var.units = '1'
var.standard_name = 'specific_humidity'
# interpolate station by station
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.nc_sa.variables['QV2M'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
self.rg.variables[vn][:, n] = series_interpolate(
self.times_out_nc, time_in * 3600, values[:, n])
def LW_Wm2_sur(self):
"""
Long-wave radiation downwards derived from surface data, exclusively.
"""
# add variable to ncdf file
vn = 'LW_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Surface thermal radiation downwards {} surface only'.format(
self.NAME)
var.units = 'W m-2'
var.standard_name = 'surface_downwelling_longwave_flux'
# interpolate station by station
time_in = self.nc_sf.variables['time'][:].astype(np.int64)
values = self.nc_sf.variables['LWGDN'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
self.rg.variables[vn][:, n] = series_interpolate(
self.times_out_nc, time_in * 3600, values[:, n])
def RH_per_pl(self, ni=10):
"""
Relative humdity derived from pressure-level.
"""
# temporary variable, interpolate station by station
rh = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.getValues(self.nc_pl, 'r', ni)
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
rh[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n])
# add variable to ncdf file
vn = 'RH_pl' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Relative humidity ERA-5 pressure-levels'
var.units = 'percent'
var.standard_name = 'relative_humidity'
self.rg.variables[vn][:, :] = rh
def PRECCORR_mm_sur(self):
"""
Corrected Precipitation derived from surface data, exclusively.
Convert units: kg/m2/s to mm/time_step (hours)
1 kg/m2 = 1mm
"""
# add variable to ncdf file
vn = 'PRECCORR_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Corrected Total precipitation {} surface only'.format(
self.NAME)
var.units = 'kg m-2 s-1'
var.comment = "units [kg m-2 s-1] corresponds to [mm/s] for water (density 1000 [kg m-3])"
var.standard_name = 'precipitation_flux'
# interpolate station by station
time_in = self.nc_sf.variables['time'][:].astype(np.int64)
values = self.nc_sf.variables['PRECTOTCORR'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
self.rg.variables[vn][:, n] = series_interpolate(
self.times_out_nc, time_in * 3600, values[:, n]) * self.scf
def RH_per_pl(self):
"""
Relative Humdity derived from pressure level data, exclusively.Clipped to
range [0.1,99.9].
"""
# temporary variable, interpolate station by station
time_in = self.nc_pl.variables['time'][:].astype(np.int64)
values = self.nc_pl.variables['RH'][:]
# add variable to ncdf file
vn = 'RH_pl' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Relative humidity {} surface only'.format(self.NAME)
var.units = 'percent'
var.standard_name = 'relative_humidity'
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
rh = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n])
rh *= 100 # Convert to %
self.rg.variables[vn][:, n] = rh
def RH_per_sur(self):
"""
Relative Humdity derived from surface data, exclusively.Clipped to
range [0.1,99.9].
"""
# temporary variable, interpolate station by station
time_in = self.nc_sf.variables['time'][:].astype(np.int64)
dewp = self.nc_sf.variables['T2MDEW'][:]
t = self.nc_sa.variables['T2M'][:]
relhu = relhu_approx_lawrence(t, dewp)
# add variable to ncdf file
vn = 'RH_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Relative humidity {} surface only'.format(self.NAME)
var.units = 'percent'
var.standard_name = 'relative_humidity'
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
rh = series_interpolate(self.times_out_nc, time_in * 3600,
relhu[:, n])
self.rg.variables[vn][:, n] = rh
def RH_per_sur(self):
"""
Relative humdity derived from surface data, exclusively. Clipped to
range [0.001, 0.999]. Kernel AIRT_ERAI_C_sur must be run before.
"""
# temporary variable, interpolate station by station
dewp = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.nc_sa.variables['d2m'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
dewp[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n] - 273.15)
# add variable to ncdf file
vn = 'RH_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Relative humidity {} surface only'.format(self.NAME)
var.units = 'percent'
var.standard_name = 'relative_humidity'
# simple: https://doi.org/10.1175/BAMS-86-2-225
RH = 100 - 5 * (self.rg.variables['AIRT_sur'][:, :] - dewp[:, :])
self.rg.variables[vn][:, :] = RH.clip(min=0.1, max=99.9) / 100
def RH_per_sur(self, ni=10):
"""
Relative humdity derived from surface data, exclusively. Clipped to
range [0.1,99.9]. Kernel AIRT_C_sur must be run before.
"""
# temporary variable, interpolate station by station
dewp = np.zeros((self.nt, self.nstation), dtype=np.float32)
time_in = self.nc_sa.variables['time'][:].astype(np.int64)
values = self.getValues(self.nc_sa, 'd2m',
ni) # self.nc_sa.variables['d2m'][:]
for n, s in enumerate(self.rg.variables['station'][:].tolist()):
dewp[:, n] = series_interpolate(self.times_out_nc, time_in * 3600,
values[:, n] - 273.15)
# add variable to ncdf file
vn = 'RH_sur' # variable name
var = self.rg.createVariable(vn, 'f4', ('time', 'station'))
var.long_name = 'Relative humidity ERA-5 surface only'
var.units = 'percent'
var.standard_name = 'relative_humidity'
RH = relhu_approx_lawrence(self.rg.variables['AIRT_sur'][:, :],
dewp[:, :])
self.rg.variables[vn][:, :] = RH.clip(min=0.1, max=99.9)