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celinelee
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python_fn_calls

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list(temperature.shape)
np.broadcast_to(isentlevels[slices], shape)
mpconsts.kappa.m_as('dimensionless')
potential_temperature(levs, tmpk)
np.max(pres_theta.m)
np.max(levels)
ValueError('Input theta level out of data bounds')
ln(p)
np.log(levs.m)
np.isnan(a)
np.exp(log_p_solved)
_less_or_close(isentprs, np.max(pres.m)
ret.append((isentlevs_nd / ((mpconsts.P0.m / isentprs)
interpolate_1d(isentlevels, pres_theta.m, *(arr[sorter] for arr in args)
ret.extend(others)
check_units('[pressure]', '[temperature]', '[temperature]')
surface_based_cape_cin(pressure, temperature, dewpoint)
energy (CAPE)
inhibition (CIN)
starting (surface)
Energy (CAPE)
INhibition (CIN)
_remove_nans(pressure, temperature, dewpoint)
parcel_profile_with_lcl(pressure, temperature, dewpoint)
cape_cin(p, t, td, profile)
check_units('[pressure]', '[temperature]', '[temperature]')
most_unstable_cape_cin(pressure, temperature, dewpoint, **kwargs)
energy (CAPE)
inhibition (CIN)
EL (or top of sounding)
Energy (CAPE)
INhibition (CIN)
_remove_nans(pressure, temperature, dewpoint)
most_unstable_parcel(pressure, temperature, dewpoint, **kwargs)
cape_cin(p, t, td, mu_profile)
check_units('[pressure]', '[temperature]', '[temperature]')
mixed_layer_cape_cin(pressure, temperature, dewpoint, **kwargs)
energy (CAPE)
inhibition (CIN)
EL (or top of sounding)
Energy (CAPE)
INhibition (CIN)
kwargs.get('depth', 100 * units.hPa)
concatenate([parcel_pressure, pressure_prof])
concatenate([parcel_temp, temp_prof])
concatenate([parcel_dewpoint, dew_prof])
parcel_profile_with_lcl(pressure_prof, temp_prof, dew_prof)
cape_cin(p, t, td, ml_profile)
check_units('[pressure]', '[temperature]', '[temperature]')
begin (default None)
pressures (default None)
pressure (default None)
layer (default 100 hPa)
potential_temperature(pressure, temperature)
saturation_mixing_ratio(pressure, dewpoint)
exner_function(parcel_start_pressure)
vapor_pressure(parcel_start_pressure, mean_mixing_ratio)
globals()
globals()
return (parcel_start_pressure, mean_temperature.to(temperature.units)
mean_dewpoint.to(dewpoint.units)
check_units('[pressure]')
variable(s)
pressures (default None)
pressure (default None)
layer (default 100 hPa)
data (default True)
abs(p_layer[0] - p_layer[-1])
ret.append((-1. / actual_depth.m)
np.trapz(datavar_layer.m, p_layer.m)
check_units('[length]', '[temperature]')
dry_static_energy(height, temperature)
return (mpconsts.g * height + mpconsts.Cp_d * temperature)
to('kJ/kg')
check_units('[length]', '[temperature]', '[dimensionless]')
moist_static_energy(height, temperature, specific_humidity)
return (dry_static_energy(height, temperature)
specific_humidity.to('dimensionless')
to('kJ/kg')
check_units('[pressure]', '[temperature]')
air. (:math:`\epsilon\approx0.622`)
virtual_temperature(layer_temp, layer_w, molecular_weight_ratio)
integral (with unit handling)
layer_virttemp.m_as('K')
np.log(layer_p.m_as('hPa')
to('m')
check_units('[pressure]', '[temperature]')
mixing_ratio_from_relative_humidity(pressure, temperature, relative_humidity)
check_units('[length]', '[temperature]')
brunt_vaisala_frequency_squared(height, potential_temperature, axis=0)
squared (a measure of atmospheric stability)
potential_temperature.to('K')
check_units('[length]', '[temperature]')
brunt_vaisala_frequency(height, potential_temperature, axis=0)
left( \frac{g}{\theta} \frac{d\theta}{dz} \right)
negative (unstable)
np.sqrt(bv_freq_squared)
check_units('[length]', '[temperature]')
brunt_vaisala_period(height, potential_temperature, axis=0)
np.sqrt(bv_freq_squared)