improver.psychrometric_calculations.significant_phase_mask module
Module for calculating the significant phase mask.
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class SignificantPhaseMask(model_id_attr=None)[source]
Bases: BasePlugin
Derives a categorical field for the specified precipitation phase indicating whether
that phase is the dominant phase at each point (1 where true, else 0) based on input
snow-fraction data.
The decision is: snow-fraction <= 0.01: Rain; snow-fraction >= 0.99: Snow; Sleet
in between.
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__init__(model_id_attr=None)[source]
Initialise the class
- Parameters:
model_id_attr (Optional[str]) – Name of the attribute used to identify the source model for
blending.
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_abc_impl = <_abc._abc_data object>
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_rain_phase(snow_fraction_data)[source]
Calculates the rain_phase data
- Return type:
ndarray
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_sleet_phase(snow_fraction_data)[source]
Calculates the sleet_phase data
- Return type:
ndarray
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_snow_phase(snow_fraction_data)[source]
Calculates the snow_phase data
- Return type:
ndarray
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static _validate_snow_fraction(snow_fraction)[source]
Ensures that the input snow-fraction field has appropriate name
(snow_fraction), units (1) and data (between 0 and 1 inclusive).
- Parameters:
snow_fraction (Cube)
- Return type:
None
- Raises
- ValueError:
If any of the above are not True.
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process(snow_fraction, phase)[source]
Make significant-phase-mask cube for the specified phase.
- Parameters:
snow_fraction (Cube) – The input snow-fraction data to derive the phase mask from.
phase (str) – One of “rain”, “sleet” or “snow”. This is the phase mask that will be
returned.
- Return type:
Cube
- Returns:
The requested phase mask containing 1 where that phase is dominant
and 0 elsewhere. Dimensions will be identical to snow-fraction.
