Functions
- mcradar.utilities.air_density(T, P)
The density of air.
- Parameters:
T – Ambient temperature [K].
P – Ambient pressure [Pa].
- Returns:
The kinematic viscosity [Pa/s].
- mcradar.utilities.air_dynamic_viscosity(T)
The kinematic viscosity of air.
- Parameters:
T – Ambient temperature [K].
- Returns:
The kinematic viscosity [Pa/s].
- mcradar.utilities.air_kinematic_viscosity(T, P)
The kinematic viscosity of air.
- Parameters:
T – Ambient temperature [K].
P – Ambient pressure [Pa].
- Returns:
The kinematic viscosity [m^2/s].
- mcradar.utilities.db2lin(data)
Convert from logarithm to linear units
- Parameters:
data (single value or an array) –
- Return type:
returns the data converted to linear
- mcradar.utilities.fall_velocity_HW(area, mass, D_max, T=273.15, P=100000.0)
The Heymsfield-Westbrook fall velocity.
- Parameters:
area – Projected area [m^2].
mass – Particle mass [kg].
D_max – Particle maximum dimension [m].
T – Ambient temperature [K].
P – Ambient pressure [Pa].
- Returns:
The fall velocity [m/s].
- mcradar.utilities.lin2db(data)
Convert from linear to logarithm units
- Parameters:
data (single value or an array) –
- Return type:
returns the data converted to dB
- mcradar.tableOperator.calcRho(mcTable)
Calculate the density of each super particles [g/cm^3].
- Parameters:
mcTable (output from getMcSnowTable()) –
- Returns:
mcTable with an additional column for the density.
The density is calculated separately for aspect ratio < 1
and for aspect ratio >= 1.
- mcradar.tableOperator.calcRhophys(mcTable)
calculate the density of the particle, using the rime mass, ice mass, water mass,… :param mcTable: :type mcTable: output from getMcSnowTable()
- Return type:
mcTable with an additional column for the density.
- mcradar.tableOperator.creatRadarCols(mcTable, dicSettings)
Create the Ze and KDP column
- Parameters:
mcTable (output from getMcSnowTable()) –
wls (wavelenght (iterable) [mm]) –
- Returns:
mcTable with a empty columns ‘sZe*_’ ‘sKDP_*’ for*
storing Ze_H and Ze_V and sKDP of one particle of a
given wavelength
- mcradar.tableOperator.getMcSnowTable(mcSnowPath)
Read McSnow output table
- Parameters:
mcSnowPath (path for the output from McSnow) –
- Returns:
Pandas DataFrame with the McSnow output variables. This DataFrame additionally includes
a column for the radii and the density [sRho]. The
velocity is negative towards the ground.
- mcradar.tableOperator.kernel_estimate(R_SP_list, Rgrid, sigma0=0.62, weight=None, space='loge')
Calculate the kernel density estimate (kde) based on the super-particle list (adapted from McSnow’s mo_output routines (f.e. write_distributions_meltdegree) :param R_SP_list: :type R_SP_list: list of the radii of the superparticle :param Rgrid: :type Rgrid: array of radii on which the kde is calculated :param sigma0: :type sigma0: bandwidth prefactor of the kde (default value from Shima et al. (2009) :param weight: :type weight: weight applied during integration (in this application the multiplicity) :param space: :type space: space in which the kde is applied (loge: logarithmix with base e, lin: linear space; D2: radii transformed by r_new=r**2)