Source code for improver.wind_calculations.wind_gust_diagnostic
# (C) Crown Copyright, Met Office. All rights reserved.
#
# This file is part of 'IMPROVER' and is released under the BSD 3-Clause license.
# See LICENSE in the root of the repository for full licensing details.
"""Module containing plugin for WindGustDiagnostic."""
import warnings
from typing import Tuple
import iris
import numpy as np
from iris.coords import Coord
from iris.cube import Cube
from improver import PostProcessingPlugin
from improver.metadata.probabilistic import find_percentile_coordinate
[docs]
class WindGustDiagnostic(PostProcessingPlugin):
"""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: float, percentile_windspeed: float) -> None:
"""
Create a WindGustDiagnostic plugin for a given set of percentiles.
Args:
percentile_gust:
Percentile value required from wind-gust cube.
percentile_windspeed:
Percentile value required from wind-speed cube.
"""
self.percentile_gust = percentile_gust
self.percentile_windspeed = percentile_windspeed
def __repr__(self) -> str:
"""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, cube_ws: Cube) -> Cube:
"""
Create a cube containing the wind_gust diagnostic.
Args:
cube_gust:
Cube contain one or more percentiles of wind_gust data.
cube_ws:
Cube contain one or more percentiles of wind_speed data.
Returns:
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.remove_coord(perc_coord_gust.name())
return result