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Merge pull request #1102 from xylar/add-wind-stress-curl
Add task for plotting maps of wind stress curl
2 parents 29b3fa0 + 8cfeb05 commit 239549b

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‎docs/developers_guide/api.rst‎

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@@ -78,6 +78,7 @@ Ocean tasks
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ClimatologyMapArgoSalinity
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ClimatologyMapWaves
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ClimatologyMapCustom
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ClimatologyMapWindStressCurl
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GeojsonNetcdfTransects
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IndexNino34
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MeridionalHeatTransport
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add_standard_regions_and_subset
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get_standard_region_names
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compute_zmid
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compute_zinterface
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vector_cell_to_edge_isotropic
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Sea ice tasks

‎docs/users_guide/analysis_tasks.rst‎

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tasks/climatologyMapSSH
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tasks/climatologyMapVel
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tasks/climatologyMapWaves
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tasks/climatologyMapWindStressCurl
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tasks/climatologyMapWoa
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tasks/antshipTransects

‎docs/users_guide/tasks/climatologyMapWindStressCurl.rst‎

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.. _task_climatologyMapWindStressCurl:
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climatologyMapWindStressCurl
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============================
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An analysis task for plotting maps of wind stress curl.
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Component and Tags::
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component: ocean
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tags: climatology, horizontalMap, windStressCurl, publicObs
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Configuration Options
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---------------------
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The following configuration options are available for this task::
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[climatologyMapWindStressCurl]
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## options related to plotting horizontally remapped climatologies of
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## wind stress curl against control model results
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# colormap for model/observations
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colormapNameResult = cmo.curl
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# whether the colormap is indexed or continuous
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colormapTypeResult = continuous
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# color indices into colormapName for filled contours
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# the type of norm used in the colormap
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normTypeResult = linear
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# A dictionary with keywords for the norm
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normArgsResult = {'vmin': -1e-6, 'vmax': 1e-6}
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# colormap for differences
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colormapNameDifference = cmo.balance
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# whether the colormap is indexed or continuous
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colormapTypeDifference = continuous
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# the type of norm used in the colormap
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normTypeDifference = linear
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# A dictionary with keywords for the norm
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normArgsDifference = {'vmin': -2e-7, 'vmax': 2e-7}
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# Months or seasons to plot (Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct,
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# Nov, Dec, JFM, AMJ, JAS, OND, ANN)
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seasons = ['ANN']
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# comparison grid(s) on which to plot analysis
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comparisonGrids = ['latlon']
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For analysis focused on polar regions (using the ``--polar_regions`` flag),
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the following config options add Arctic and Antarctic comparison grids::
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[climatologyMapWindStressCurl]
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## options related to plotting horizontally remapped climatologies of
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## wind stress curl against control model results
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# comparison grid(s) on which to plot analysis
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comparisonGrids = ['latlon', 'arctic_extended', 'antarctic_extended']
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For more details, see:
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* :ref:`config_colormaps`
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* :ref:`config_seasons`
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* :ref:`config_comparison_grids`
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Example Result
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--------------
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.. image:: examples/wind_stress_curl.png
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:width: 500 px
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:align: center

‎docs/users_guide/tasks/examples/wind_stress_curl.png‎

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‎mpas_analysis/__main__.py‎

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@@ -189,6 +189,11 @@ def build_analysis_list(config, controlConfig):
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analyses.append(ocean.ClimatologyMapCustom(
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config, oceanClimatologyTasks['avg'], controlConfig))
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analyses.append(ocean.ClimatologyMapWindStressCurl(
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config, oceanClimatologyTasks['avg'], controlConfig)
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)
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analyses.append(ocean.ConservationTask(
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config, controlConfig))
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‎mpas_analysis/default.cfg‎

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iceShelvesInTable = []
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[climatologyMapWindStressCurl]
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## options related to plotting horizontally remapped climatologies of
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## wind stress curl against control model results
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# colormap for model/observations
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colormapNameResult = cmo.curl
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# whether the colormap is indexed or continuous
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colormapTypeResult = continuous
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# color indices into colormapName for filled contours
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# the type of norm used in the colormap
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normTypeResult = linear
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# A dictionary with keywords for the norm
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normArgsResult = {'vmin': -1e-6, 'vmax': 1e-6}
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# colormap for differences
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colormapNameDifference = cmo.balance
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# whether the colormap is indexed or continuous
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colormapTypeDifference = continuous
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# the type of norm used in the colormap
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normTypeDifference = linear
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# A dictionary with keywords for the norm
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normArgsDifference = {'vmin': -2e-7, 'vmax': 2e-7}
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# Months or seasons to plot (Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct,
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# Nov, Dec, JFM, AMJ, JAS, OND, ANN)
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seasons = ['ANN']
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# comparison grid(s) on which to plot analysis
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comparisonGrids = ['latlon']
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[timeSeriesAntarcticMelt]
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## options related to plotting time series of melt below Antarctic ice shelves
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‎mpas_analysis/ocean/__init__.py‎

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ClimatologyMapCustom
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)
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from mpas_analysis.ocean.climatology_map_wind_stress_curl import (
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ClimatologyMapWindStressCurl
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)
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from mpas_analysis.ocean.conservation import ConservationTask
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from mpas_analysis.ocean.time_series_temperature_anomaly import \

‎mpas_analysis/ocean/climatology_map_wind_stress_curl.py‎

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# This software is open source software available under the BSD-3 license.
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#
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# Copyright (c) 2022 Triad National Security, LLC. All rights reserved.
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# Copyright (c) 2022 Lawrence Livermore National Security, LLC. All rights
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# reserved.
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# Copyright (c) 2022 UT-Battelle, LLC. All rights reserved.
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#
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# Additional copyright and license information can be found in the LICENSE file
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# distributed with this code, or at
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# https://raw.githubusercontent.com/MPAS-Dev/MPAS-Analysis/main/LICENSE
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import xarray as xr
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from mpas_tools.ocean.streamfunction.vorticity import (
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compute_vertically_integrated_vorticity,
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)
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from mpas_analysis.ocean.utility import (
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vector_cell_to_edge_isotropic,
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vector_to_edge_normal,
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)
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from mpas_analysis.shared import AnalysisTask
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from mpas_analysis.shared.climatology import RemapMpasClimatologySubtask
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from mpas_analysis.shared.plot import PlotClimatologyMapSubtask
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class ClimatologyMapWindStressCurl(AnalysisTask):
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"""
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An analysis task for computing and plotting maps of the wind stress curl.
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"""
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def __init__(self, config, mpas_climatology_task, control_config=None):
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"""
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Construct the analysis task.
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Parameters
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----------
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config : mpas_tools.config.MpasConfigParser
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Configuration options
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mpas_climatology_task : mpas_analysis.shared.climatology.MpasClimatologyTask
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The task that produced the climatology to be remapped and plotted
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control_config : mpas_tools.config.MpasConfigParser, optional
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Configuration options for a control run (if any)
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""" # noqa: E501
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field_name = 'windStressCurl'
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super().__init__(
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config=config,
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taskName='climatologyMapWindStressCurl',
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componentName='ocean',
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tags=[
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'climatology', 'horizontalMap', field_name, 'publicObs'
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],
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)
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section_name = self.taskName
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# read in what seasons we want to plot
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seasons = config.getexpression(section_name, 'seasons')
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if len(seasons) == 0:
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raise ValueError(
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f'config section {section_name} does not contain '
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f'valid list of seasons'
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)
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comparison_grid_names = config.getexpression(
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section_name, 'comparisonGrids'
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)
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if len(comparison_grid_names) == 0:
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raise ValueError(
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f'config section {section_name} does not contain '
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f'valid list of comparison grids'
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)
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variable_list = list(RemapMpasWindStressCurl.VARIABLES)
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remap_climatology_subtask = RemapMpasWindStressCurl(
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mpasClimatologyTask=mpas_climatology_task,
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parentTask=self,
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climatologyName=field_name,
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variableList=variable_list,
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seasons=seasons,
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comparisonGridNames=comparison_grid_names,
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subtaskName='remapWindStressCurl',
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vertices=True,
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)
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self.add_subtask(remap_climatology_subtask)
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out_file_label = field_name
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field_title = 'Wind Stress Curl'
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remap_observations_subtask = None
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mpas_field_name = field_name
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if control_config is None:
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ref_field_name = None
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ref_title_label = None
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diff_title_label = 'Model - Observations'
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else:
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control_run_name = control_config.get('runs', 'mainRunName')
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ref_field_name = mpas_field_name
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ref_title_label = f'Control: {control_run_name}'
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diff_title_label = 'Main - Control'
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for comparison_grid_name in comparison_grid_names:
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for season in seasons:
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# make a new subtask for this season and comparison grid
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subtask_name = f'plot{season}_{comparison_grid_name}'
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subtask = PlotClimatologyMapSubtask(
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self, season, comparison_grid_name,
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remap_climatology_subtask, remap_observations_subtask,
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controlConfig=control_config, subtaskName=subtask_name)
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subtask.set_plot_info(
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outFileLabel=out_file_label,
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fieldNameInTitle=field_title,
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mpasFieldName=mpas_field_name,
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refFieldName=ref_field_name,
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refTitleLabel=ref_title_label,
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diffTitleLabel=diff_title_label,
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unitsLabel=r'N m$^{-3}$',
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imageCaption=field_title,
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galleryGroup='Wind Stress Curl',
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groupSubtitle=None,
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groupLink='wsc',
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galleryName=None,
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configSectionName=section_name)
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self.add_subtask(subtask)
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class RemapMpasWindStressCurl(RemapMpasClimatologySubtask):
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"""
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A subtask for computing climatologies of the wind stress curl before
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it gets remapped to a comparison grid.
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"""
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VARIABLES = (
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'timeMonthly_avg_windStressZonal',
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'timeMonthly_avg_windStressMeridional',
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)
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def setup_and_check(self):
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"""
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Add the variables needed for computing wind stress curl to the
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climatology task
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"""
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super().setup_and_check()
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# Add the variables and seasons, now that we have the variable list
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self.mpasClimatologyTask.add_variables(
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list(self.VARIABLES), self.seasons
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)
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def customize_masked_climatology(self, climatology, season):
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"""
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Compute the wind stress curl and add it to the climatology.
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Parameters
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----------
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climatology : xarray.Dataset
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the climatology data set
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season : str
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The name of the season to be masked
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Returns
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-------
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climatology : xarray.Dataset
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the modified climatology data set
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"""
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logger = self.logger
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ds_mesh = xr.open_dataset(self.restartFileName)
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var_list = [
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'verticesOnEdge',
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'cellsOnVertex',
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'kiteAreasOnVertex',
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'angleEdge',
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'areaTriangle',
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'dcEdge',
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'edgesOnVertex',
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'verticesOnEdge',
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'latVertex',
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]
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ds_mesh = ds_mesh[var_list]
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ws_zonal_cell = climatology['timeMonthly_avg_windStressZonal']
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ws_meridional_cell = (
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climatology['timeMonthly_avg_windStressMeridional']
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)
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ws_zonal_edge, ws_meridional_edge = vector_cell_to_edge_isotropic(
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ds_mesh, ws_zonal_cell, ws_meridional_cell
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)
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ws_normal_edge = vector_to_edge_normal(
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ds_mesh, ws_zonal_edge, ws_meridional_edge
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)
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# despite the name, this is the curl operator
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wind_sress_curl, _ = compute_vertically_integrated_vorticity(
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ds_mesh, ws_normal_edge, logger
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)
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climatology['windStressCurl'] = wind_sress_curl
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climatology['windStressCurl'].attrs['units'] = 'N m-3'
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# drop the original wind stress variables
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climatology = climatology.drop_vars(list(self.VARIABLES))
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return climatology

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