particle_fieldCleanup

Workspace.particle_fieldCleanup(self: pyarts.arts._Workspace, particle_field_out: pyarts.arts.WorkspaceVariable | pyarts.arts.Tensor4, particle_field_in: pyarts.arts.WorkspaceVariable | pyarts.arts.Tensor4, threshold: pyarts.arts.WorkspaceVariable | pyarts.arts.Numeric, verbosity: pyarts.arts.WorkspaceVariable | pyarts.arts.Verbosity | None = self.verbosity) → None

Removes unrealistically small or erroneous data from particle fields.

This WSM checks if the input particle field (e.g. particle_bulkprop_field) contains values smaller than the given threshold. In this case, these values will be set to zero.

The method should be applied if the particle fields contain unrealistically small or erroneous data (NWP/GCM model data, e.g. from the Chevallierl_91l sets, often contain very small or even negative values, which are numerical artefacts rather than physical values.) For the scat_species_XXX_fields, it needs to be applied separately per Tensor4 type field collection. This allows to use different thresholds for the different types of fields (not for the different scattering species, though).

particle_fieldCleanup() shall be called after generation of the atmopheric fields.

Author(s): Daniel Kreyling

Parameters:

• particle_field_out (Tensor4) – A particle property field, e.g. particle_bulkprop_field. [OUT]

• particle_field_in (Tensor4) – A particle property field, e.g. particle_bulkprop_field. [IN]

• threshold (Numeric) – Threshold below which the particle_field values are set to zero. [IN]

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