psdModifiedGammaMassXmean

Workspace.psdModifiedGammaMassXmean(self: pyarts.arts._Workspace, psd_data: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Matrix]] = self.psd_data, dpsd_data_dx: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Tensor3]] = self.dpsd_data_dx, psd_size_grid: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Vector]] = self.psd_size_grid, pnd_agenda_input_t: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Vector]] = self.pnd_agenda_input_t, pnd_agenda_input: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Matrix]] = self.pnd_agenda_input, pnd_agenda_input_names: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.ArrayOfString]] = self.pnd_agenda_input_names, dpnd_data_dx_names: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.ArrayOfString]] = self.dpnd_data_dx_names, scat_species_a: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric]] = self.scat_species_a, scat_species_b: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric]] = self.scat_species_b, n0: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric]] = std::numeric_limits<Numeric>::quiet_NaN(), mu: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric]] = std::numeric_limits<Numeric>::quiet_NaN(), la: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric]] = std::numeric_limits<Numeric>::quiet_NaN(), ga: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric]] = std::numeric_limits<Numeric>::quiet_NaN(), t_min: Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric], t_max: Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Numeric], picky: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Index]] = 0, verbosity: Optional[Union[pyarts.arts.WorkspaceVariable, pyarts.arts.Verbosity]] = self.verbosity) → None

Modified gamma distribution PSD, with mass content and mean size (Xmean) as inputs.

“Mean size” is here defined as mass weighted size. Remembering that mass is a*x^b, this mean size can be expressed as M_b+1/M_b where M_b is b:th moment of the PSD (see e.g. Eq. 17 in Petty&Huang, JAS, 2011).

This version of MGD PSD works as psdModifiedGammaMass(), but takes mass content and mass size as first two arguments. This means that the first and second column of pnd_agenda_input shall hold mass content and Xmean, respectively. Accordingly, the number of dependent parameters is two.

These requirements apply to the MGD parameters:

  1. mu + scat_species_b + 1 > 0

  2. la > 0

  3. ga > 0

  4. Xmean must be > 0.

Author(s): Patrick Eriksson

Parameters:

  • psd_data (Matrix, optional) – Particle size distribution values for a set of points. See psd_data, defaults to self.psd_data [OUT]

  • dpsd_data_dx (Tensor3, optional) – Partial derivates of psd_data. See dpsd_data_dx, defaults to self.dpsd_data_dx [OUT]

  • psd_size_grid (Vector, optional) – The particle sizes associated with psd_data. See psd_size_grid, defaults to self.psd_size_grid [IN]

  • pnd_agenda_input_t (Vector, optional) – Temperature input to one element of pnd_agenda_array. See pnd_agenda_input_t, defaults to self.pnd_agenda_input_t [IN]

  • pnd_agenda_input (Matrix, optional) – The variable input to one element of pnd_agenda_array. See pnd_agenda_input, defaults to self.pnd_agenda_input [IN]

  • pnd_agenda_input_names (ArrayOfString, optional) – Naming of (existing or expected) data in pnd_agenda_input. See pnd_agenda_input_names, defaults to self.pnd_agenda_input_names [IN]

  • dpnd_data_dx_names (ArrayOfString, optional) – Selection of partial derivatives of pnd_data. See dpnd_data_dx_names, defaults to self.dpnd_data_dx_names [IN]

  • scat_species_a (Numeric, optional) – Mass-size relationship parameter, for one scattering species. See scat_species_a, defaults to self.scat_species_a [IN]

  • scat_species_b (Numeric, optional) – Mass-size relationship parameter, for one scattering species. See scat_species_b, defaults to self.scat_species_b [IN]

  • n0 (Numeric, optional) – n0. Defaults to NaN [IN]

  • mu (Numeric, optional) – mu. Defaults to NaN [IN]

  • la (Numeric, optional) – la. Defaults to NaN [IN]

  • ga (Numeric, optional) – ga. Defaults to NaN [IN]

  • t_min (Numeric) – Low temperature limit to calculate a psd. [IN]

  • t_max (Numeric) – High temperature limit to calculate a psd. [IN]

  • picky (Index, optional) – Flag whether to be strict with parametrization value checks. Defaults to 0 [IN]

  • verbosity (Verbosity) – ARTS verbosity. See verbosity, defaults to self.verbosity [IN]