Source code for mpas_analysis.ocean.climatology_map_mld

# This software is open source software available under the BSD-3 license.
#
# Copyright (c) 2020 Triad National Security, LLC. All rights reserved.
# Copyright (c) 2020 Lawrence Livermore National Security, LLC. All rights
# reserved.
# Copyright (c) 2020 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
from __future__ import absolute_import, division, print_function, \
    unicode_literals

import xarray as xr
import numpy as np
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


[docs]class ClimatologyMapMLD(AnalysisTask): # {{{ """ An analysis task for comparison of mixed layer depth (mld) against observations """ # Authors # ------- # Luke Van Roekel, Xylar Asay-Davis, Milena Veneziani
[docs] def __init__(self, config, mpasClimatologyTask, controlConfig=None): # {{{ """ Construct the analysis task. Parameters ---------- config : ``MpasAnalysisConfigParser`` Configuration options mpasClimatologyTask : ``MpasClimatologyTask`` The task that produced the climatology to be remapped and plotted controlConfig : ``MpasAnalysisConfigParser``, optional Configuration options for a control run (if any) """ # Authors # ------- # Xylar Asay-Davis fieldName = 'mld' # call the constructor from the base class (AnalysisTask) super(ClimatologyMapMLD, self).__init__( config=config, taskName='climatologyMapMLD', componentName='ocean', tags=['climatology', 'horizontalMap', fieldName, 'publicObs']) sectionName = self.taskName mpasFieldName = 'timeMonthly_avg_dThreshMLD' iselValues = None # 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 'timeMonthly_avg_dThreshMLD' will be added to # mpasClimatologyTask along with the seasons. remapClimatologySubtask = RemapMpasClimatologySubtask( mpasClimatologyTask=mpasClimatologyTask, parentTask=self, climatologyName=fieldName, variableList=[mpasFieldName], comparisonGridNames=comparisonGridNames, seasons=seasons, iselValues=iselValues) if controlConfig is None: observationsDirectory = build_obs_path( config, 'ocean', '{}Subdirectory'.format(fieldName)) obsFileName = "{}/holtetalley_mld_climatology_20180710.nc".format( observationsDirectory) refFieldName = 'mld' outFileLabel = 'mldHolteTalleyARGO' remapObservationsSubtask = RemapObservedMLDClimatology( parentTask=self, seasons=seasons, fileName=obsFileName, outFilePrefix=refFieldName, comparisonGridNames=comparisonGridNames) self.add_subtask(remapObservationsSubtask) galleryName = 'Observations: Holte-Talley ARGO' refTitleLabel = \ 'Observations (HolteTalley density threshold MLD)' diffTitleLabel = 'Model - Observations' else: remapObservationsSubtask = None controlRunName = controlConfig.get('runs', 'mainRunName') galleryName = None refTitleLabel = 'Control: {}'.format(controlRunName) refFieldName = mpasFieldName outFileLabel = 'mld' 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) subtask.set_plot_info( outFileLabel=outFileLabel, fieldNameInTitle='MLD', mpasFieldName=mpasFieldName, refFieldName=refFieldName, refTitleLabel=refTitleLabel, diffTitleLabel=diffTitleLabel, unitsLabel=r'm', imageCaption='Mean Mixed-Layer Depth', galleryGroup='Mixed-Layer Depth', groupSubtitle=None, groupLink='mld', galleryName=galleryName) self.add_subtask(subtask)
# }}} def setup_and_check(self): # {{{ ''' Check if MLD capability was turned on in the run. ''' # Authors # ------- # Xylar Asay-Davis # first, call setup_and_check from the base class (AnalysisTask), # which will perform some common setup, including storing: # self.runDirectory , self.historyDirectory, self.plotsDirectory, # self.namelist, self.runStreams, self.historyStreams, # self.calendar super(ClimatologyMapMLD, self).setup_and_check() self.check_analysis_enabled( analysisOptionName='config_am_mixedlayerdepths_enable', raiseException=True)
# }}} # }}} class RemapObservedMLDClimatology(RemapObservedClimatologySubtask): # {{{ """ A subtask for reading and remapping MLD observations """ # Authors # ------- # Luke Van Roekel, Xylar Asay-Davis, Milena Veneziani 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 # Load MLD observational data dsObs = self.build_observational_dataset(fileName) # create a descriptor of the observation grid using the lat/lon # coordinates obsDescriptor = LatLonGridDescriptor.read(ds=dsObs, latVarName='lat', lonVarName='lon') dsObs.close() 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 # Load MLD observational data dsObs = xr.open_dataset(fileName) # Increment month value to be consistent with the model output dsObs.assign_coords(iMONTH=dsObs.iMONTH+1) # Rename the dimensions to be consistent with other obs. data sets dsObs = dsObs.rename({'month': 'calmonth', 'lat': 'latCoord', 'lon': 'lonCoord', 'mld_dt_mean': 'mld'}) dsObs = dsObs.rename({'iMONTH': 'Time', 'iLAT': 'lat', 'iLON': 'lon'}) # set the coordinates now that the dimensions have the same names dsObs.coords['lat'] = dsObs['latCoord'] dsObs.coords['lon'] = dsObs['lonCoord'] dsObs.coords['Time'] = dsObs['calmonth'] dsObs.coords['month'] = ('Time', np.array(dsObs['calmonth'], int)) # no meaningful year since this is already a climatology dsObs.coords['year'] = ('Time', np.ones(dsObs.dims['Time'], int)) dsObs = dsObs[['mld', 'month']] return dsObs # }}} # }}} # vim: foldmethod=marker ai ts=4 sts=4 et sw=4 ft=python