#!/usr/bin/env python
# -*- coding: utf-8 -*-
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"""Script to calculate a probability of precipitation being showery if present."""
from improver import cli
[docs]@cli.clizefy
@cli.with_output
def process(
*cubes: cli.inputcube,
cloud_threshold: float,
convection_threshold: float,
model_id_attr: str = None,
):
"""
Create a shower condition diagnostic that provides the probability that
precipitation, if present, should be classified as showery. This shower
condition is created from cloud area fraction and convective ratio fields.
Args:
cubes (iris.cube.CubeList):
Cubes of cloud area fraction and convective ratio that are used
to calculate a proxy probability that conditions are suitable for
showery precipitation.
cloud_threshold (float):
The cloud area fraction value at which to threshold the input cube.
This sets the amount of cloud coverage below which conditions are
likely to be considered showery (i.e. precipitation between sunny
spells).
convection_threshold (float):
The convective ratio value above which, despite the cloud conditions
not suggesting showers, the precipitation is so clearly derived
from convection that it should be classified as showery.
model_id_attr (str):
Name of the attribute used to identify the source model for
blending (optional).
Returns:
iris.cube.Cube:
Probability of any precipitation, if present, being classified as
showery.
"""
from iris.cube import CubeList
from improver.precipitation_type.shower_condition_probability import (
ShowerConditionProbability,
)
return ShowerConditionProbability(
cloud_threshold=cloud_threshold,
convection_threshold=convection_threshold,
model_id_attr=model_id_attr,
)(CubeList(cubes))