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"""Module containing plugin for WindGustDiagnostic."""
import warnings
import iris
import numpy as np
from improver import BasePlugin
from improver.metadata.probabilistic import find_percentile_coordinate
[docs]class WindGustDiagnostic(BasePlugin):
"""Plugin for calculating wind-gust diagnostic.
In the model a shear-driven turbulence parameterization is used to
estimate wind gusts but in convective situations this can over-estimate the
convective gust.
This diagnostic takes the Maximum of the values at each grid point of
* a chosen percentile of the wind-gust forecast and
* a chosen percentile of the wind-speed forecast
to produce a better estimate of wind-gust.
For example a typical wind-gust could be MAX(gust(50%),windspeed(95%))
an extreme wind-gust forecast could be MAX(gust(95%), windspeed(100%))
Scientific Reference: *Roberts N., Mylne K.*
Poster - European Meteorological Society Conference 2017.
See
https://github.com/metoppv/improver/files/1244828/WindGustChallenge_v2.pdf
for a discussion of the problem and proposed solutions.
"""
[docs] def __init__(self, percentile_gust, percentile_windspeed):
"""
Create a WindGustDiagnostic plugin for a given set of percentiles.
Args:
percentile_gust (float):
Percentile value required from wind-gust cube.
percentile_windspeed (float):
Percentile value required from wind-speed cube.
"""
self.percentile_gust = percentile_gust
self.percentile_windspeed = percentile_windspeed
def __repr__(self):
"""Represent the configured plugin instance as a string."""
desc = ('<WindGustDiagnostic: wind-gust perc='
'{0:3.1f}, wind-speed perc={1:3.1f}>'
.format(self.percentile_gust, self.percentile_windspeed))
return desc
[docs] def process(self, cube_gust, cube_ws):
"""
Create a cube containing the wind_gust diagnostic.
Args:
cube_gust (iris.cube.Cube):
Cube contain one or more percentiles of wind_gust data.
cube_ws (iris.cube.Cube):
Cube contain one or more percentiles of wind_speed data.
Returns:
iris.cube.Cube:
Cube containing the wind-gust diagnostic data.
"""
# Extract wind-gust data
(req_cube_gust,
perc_coord_gust) = self.extract_percentile_data(cube_gust,
self.percentile_gust,
"wind_speed_of_gust")
# Extract wind-speed data
(req_cube_ws,
perc_coord_ws) = (
self.extract_percentile_data(cube_ws,
self.percentile_windspeed,
"wind_speed"))
if perc_coord_gust.name() != perc_coord_ws.name():
msg = ('Percentile coord of wind-gust data'
'does not match coord of wind-speed data'
' {0:s} {1:s}.'.format(perc_coord_gust.name(),
perc_coord_ws.name()))
raise ValueError(msg)
# Check times are compatible.
msg = ('Could not match time coordinate')
wg_time = req_cube_gust.coords('time')
ws_time = req_cube_ws.coords('time')
if len(wg_time) == 0 or len(ws_time) == 0:
raise ValueError(msg)
if not all(wg_point == ws_point for wg_point, ws_point
in zip(wg_time[0].points, ws_time[0].points)):
if wg_time[0].bounds is None:
raise ValueError(msg)
if not all((point >= bounds[0] and point <= bounds[1])
for point, bounds in zip(ws_time[0].points,
wg_time[0].bounds)):
raise ValueError(msg)
# Add metadata to gust cube
req_cube_gust = self.add_metadata(req_cube_gust)
# Calculate wind-gust diagnostic
result = req_cube_gust.copy(
data=np.maximum(req_cube_gust.data, req_cube_ws.data))
# Update metadata
result = self.update_metadata_after_max(result,
perc_coord_gust.name())
return result