Source code for mpas_analysis.ocean.climatology_map_ssh

# This software is open source software available under the BSD-3 license.
#
# Copyright (c) 2022 Triad National Security, LLC. All rights reserved.
# Copyright (c) 2022 Lawrence Livermore National Security, LLC. All rights
# reserved.
# Copyright (c) 2022 UT-Battelle, LLC. All rights reserved.
#
# Additional copyright and license information can be found in the LICENSE file
# distributed with this code, or at
# https://raw.githubusercontent.com/MPAS-Dev/MPAS-Analysis/master/LICENSE
import xarray as xr
from pyremap import LatLonGridDescriptor

from mpas_analysis.shared import AnalysisTask

from mpas_analysis.shared.io.utility import build_obs_path

from mpas_analysis.shared.climatology import RemapMpasClimatologySubtask, \
    RemapObservedClimatologySubtask

from mpas_analysis.ocean.plot_climatology_map_subtask import \
    PlotClimatologyMapSubtask

from mpas_analysis.shared.constants import constants


[docs]class ClimatologyMapSSH(AnalysisTask): """ An analysis task for comparison of sea surface height (ssh) against observations """ # Authors # ------- # Xylar Asay-Davis
[docs] def __init__(self, config, mpasClimatologyTask, controlConfig=None): """ Construct the analysis task. Parameters ---------- config : mpas_tools.config.MpasConfigParser Configuration options mpasClimatologyTask : ``MpasClimatologyTask`` The task that produced the climatology to be remapped and plotted controlconfig : mpas_tools.config.MpasConfigParser, optional Configuration options for a control run (if any) """ # Authors # ------- # Xylar Asay-Davis fieldName = 'ssh' # call the constructor from the base class (AnalysisTask) super(ClimatologyMapSSH, self).__init__( config=config, taskName='climatologyMapSSH', componentName='ocean', tags=['climatology', 'horizontalMap', fieldName, 'publicObs']) mpasFieldName = 'timeMonthly_avg_pressureAdjustedSSH' iselValues = None sectionName = self.taskName # read in what seasons we want to plot seasons = config.getexpression(sectionName, 'seasons') if len(seasons) == 0: raise ValueError('config section {} does not contain valid list ' 'of seasons'.format(sectionName)) comparisonGridNames = config.getexpression(sectionName, 'comparisonGrids') if len(comparisonGridNames) == 0: raise ValueError('config section {} does not contain valid list ' 'of comparison grids'.format(sectionName)) # the variable mpasFieldName will be added to mpasClimatologyTask # along with the seasons. remapClimatologySubtask = RemapSSHClimatology( mpasClimatologyTask=mpasClimatologyTask, parentTask=self, climatologyName=fieldName, variableList=[mpasFieldName], comparisonGridNames=comparisonGridNames, seasons=seasons, iselValues=iselValues) if controlConfig is None: refTitleLabel = 'Observations (AVISO Dynamic ' \ 'Topography, 1993-2010)' observationsDirectory = build_obs_path( config, 'ocean', '{}Subdirectory'.format(fieldName)) obsFileName = \ "{}/zos_AVISO_L4_199210-201012_20180710.nc".format( observationsDirectory) refFieldName = 'zos' outFileLabel = 'sshAVISO' galleryName = 'Observations: AVISO' remapObservationsSubtask = RemapObservedSSHClimatology( parentTask=self, seasons=seasons, fileName=obsFileName, outFilePrefix=refFieldName, comparisonGridNames=comparisonGridNames) self.add_subtask(remapObservationsSubtask) diffTitleLabel = 'Model - Observations' else: remapObservationsSubtask = None controlRunName = controlConfig.get('runs', 'mainRunName') galleryName = None refTitleLabel = 'Control: {}'.format(controlRunName) refFieldName = mpasFieldName outFileLabel = 'ssh' diffTitleLabel = 'Main - Control' for comparisonGridName in comparisonGridNames: for season in seasons: # make a new subtask for this season and comparison grid subtask = PlotClimatologyMapSubtask( self, season, comparisonGridName, remapClimatologySubtask, remapObservationsSubtask, controlConfig=controlConfig, removeMean=True) subtask.set_plot_info( outFileLabel=outFileLabel, fieldNameInTitle='Zero-mean SSH', mpasFieldName=mpasFieldName, refFieldName=refFieldName, refTitleLabel=refTitleLabel, diffTitleLabel=diffTitleLabel, unitsLabel=r'cm', imageCaption='Mean Sea Surface Height', galleryGroup='Sea Surface Height', groupSubtitle=None, groupLink='ssh', galleryName=galleryName) self.add_subtask(subtask)
class RemapSSHClimatology(RemapMpasClimatologySubtask): """ Change units from m to cm """ # Authors # ------- # Xylar Asay-Davis def customize_masked_climatology(self, climatology, season): """ Mask the melt rates using ``landIceMask`` and rescale it to m/yr Parameters ---------- climatology : ``xarray.Dataset``` The MPAS climatology data set that has had a mask added but has not yet been remapped season : str The name of the season to be masked Returns ------- climatology : ``xarray.Dataset`` object the modified climatology data set """ # Authors # ------- # Xylar Asay-Davis fieldName = self.variableList[0] # scale the field to cm from m climatology[fieldName] = constants.cm_per_m * climatology[fieldName] return climatology class RemapObservedSSHClimatology(RemapObservedClimatologySubtask): """ A subtask for reading and remapping SSH observations """ # Authors # ------- # Xylar Asay-Davis def get_observation_descriptor(self, fileName): """ get a MeshDescriptor for the observation grid Parameters ---------- fileName : str observation file name describing the source grid Returns ------- obsDescriptor : ``MeshDescriptor`` The descriptor for the observation grid """ # Authors # ------- # Xylar Asay-Davis # create a descriptor of the observation grid using the lat/lon # coordinates obsDescriptor = LatLonGridDescriptor.read(fileName=fileName, latVarName='lat', lonVarName='lon') return obsDescriptor def build_observational_dataset(self, fileName): """ read in the data sets for observations, and possibly rename some variables and dimensions Parameters ---------- fileName : str observation file name Returns ------- dsObs : ``xarray.Dataset`` The observational dataset """ # Authors # ------- # Xylar Asay-Davis dsObs = xr.open_dataset(fileName) dsObs = dsObs.rename({'time': 'Time'}) dsObs.coords['month'] = dsObs['Time.month'] dsObs.coords['year'] = dsObs['Time.year'] dsObs = dsObs.drop_vars(['Time', 'time_bnds']) # scale the field to cm from m dsObs['zos'] = constants.cm_per_m * dsObs['zos'] return dsObs