Source code for mpas_analysis.ocean.climatology_map_ohc_anomaly

# 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
import numpy

from mpas_analysis.shared import AnalysisTask

from mpas_analysis.shared.climatology import RemapMpasClimatologySubtask

from mpas_analysis.ocean.plot_climatology_map_subtask import \
    PlotClimatologyMapSubtask

from mpas_analysis.ocean.utility import compute_zmid


[docs]class ClimatologyMapOHCAnomaly(AnalysisTask): # {{{ """ An analysis task for comparison of the anomaly from a reference year (typically the start of the simulation) of ocean heat content (OHC) Attributes ---------- mpasClimatologyTask : ``MpasClimatologyTask`` The task that produced the climatology to be remapped and plotted refYearClimatolgyTask : ``RefYearMpasClimatologyTask`` The task that produced the climatology from the first year to be remapped and then subtracted from the main climatology """ # Authors # ------- # Xylar Asay-Davis
[docs] def __init__(self, config, mpasClimatologyTask, refYearClimatolgyTask, controlConfig=None): # {{{ """ Construct the analysis task. Parameters ---------- config : ``MpasAnalysisConfigParser`` Configuration options mpasClimatologyTask : ``MpasClimatologyTask`` The task that produced the climatology to be remapped and plotted refYearClimatolgyTask : ``RefYearMpasClimatologyTask`` The task that produced the climatology from the first year to be remapped and then subtracted from the main climatology controlConfig : ``MpasAnalysisConfigParser``, optional Configuration options for a control run (if any) """ # Authors # ------- # Xylar Asay-Davis fieldName = 'deltaOHC' # call the constructor from the base class (AnalysisTask) super(ClimatologyMapOHCAnomaly, self).__init__( config=config, taskName='climatologyMapOHCAnomaly', componentName='ocean', tags=['climatology', 'horizontalMap', fieldName, 'publicObs']) sectionName = self.taskName mpasFieldName = 'deltaOHC' # 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)) variableList = ['timeMonthly_avg_activeTracers_temperature', 'timeMonthly_avg_layerThickness'] depthRanges = config.getExpression('climatologyMapOHCAnomaly', 'depthRanges', usenumpyfunc=True) self.mpasClimatologyTask = mpasClimatologyTask self.refYearClimatolgyTask = refYearClimatolgyTask for minDepth, maxDepth in depthRanges: depthRangeString = '{:g}-{:g}m'.format(numpy.abs(minDepth), numpy.abs(maxDepth)) remapClimatologySubtask = RemapMpasOHCClimatology( mpasClimatologyTask=mpasClimatologyTask, refYearClimatolgyTask=refYearClimatolgyTask, parentTask=self, climatologyName='{}_{}'.format(fieldName, depthRangeString), variableList=variableList, comparisonGridNames=comparisonGridNames, seasons=seasons, minDepth=minDepth, maxDepth=maxDepth) self.add_subtask(remapClimatologySubtask) outFileLabel = 'deltaOHC_{}'.format(depthRangeString) remapObservationsSubtask = None if controlConfig is None: refTitleLabel = None refFieldName = None diffTitleLabel = 'Model - Observations' else: controlRunName = controlConfig.get('runs', 'mainRunName') refTitleLabel = 'Control: {}'.format(controlRunName) refFieldName = mpasFieldName diffTitleLabel = 'Main - Control' for comparisonGridName in comparisonGridNames: for season in seasons: # make a new subtask for this season and comparison grid subtaskName = 'plot{}_{}_{}'.format( season, comparisonGridName, depthRangeString) subtask = PlotClimatologyMapSubtask( self, season, comparisonGridName, remapClimatologySubtask, remapObservationsSubtask, controlConfig=controlConfig, subtaskName=subtaskName) subtask.set_plot_info( outFileLabel=outFileLabel, fieldNameInTitle=r'$\Delta$OHC over {}'.format( depthRangeString), mpasFieldName=mpasFieldName, refFieldName=refFieldName, refTitleLabel=refTitleLabel, diffTitleLabel=diffTitleLabel, unitsLabel=r'GJ m$^{-2}$', imageCaption='Anomaly in Ocean Heat Content over ' '{}'.format(depthRangeString), galleryGroup='OHC Anomaly', groupSubtitle=None, groupLink='ohc_anom', galleryName=None) self.add_subtask(subtask)
# }}} def setup_and_check(self): # {{{ ''' Checks whether analysis is being performed only on the reference year, in which case the analysis will not be meaningful. Raises ------ ValueError: if attempting to analyze only the reference year ''' # 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(ClimatologyMapOHCAnomaly, self).setup_and_check() startYear, endYear = self.mpasClimatologyTask.get_start_and_end() refStartYear, refEndYear = \ self.refYearClimatolgyTask.get_start_and_end() if (startYear == refStartYear) and (endYear == refEndYear): raise ValueError('OHC Anomaly is not meaningful and will not work ' 'when climatology and ref year are the same.')
# }}} # }}} class RemapMpasOHCClimatology(RemapMpasClimatologySubtask): # {{{ """ A subtask for computing climatologies of ocean heat content from climatologies of temperature Attributes ---------- minDepth, maxDepth : float The minimum and maximum depths for integration """ # Authors # ------- # Xylar Asay-Davis def __init__(self, mpasClimatologyTask, refYearClimatolgyTask, parentTask, climatologyName, variableList, seasons, comparisonGridNames, minDepth, maxDepth): # {{{ ''' Construct the analysis task and adds it as a subtask of the ``parentTask``. Parameters ---------- mpasClimatologyTask : ``MpasClimatologyTask`` The task that produced the climatology to be remapped refYearClimatolgyTask : ``RefYearMpasClimatologyTask`` The task that produced the climatology from the first year to be remapped and then subtracted from the main climatology parentTask : ``AnalysisTask`` The parent task, used to get the ``taskName``, ``config`` and ``componentName`` climatologyName : str A name that describes the climatology (e.g. a short version of the important field(s) in the climatology) used to name the subdirectories for each stage of the climatology variableList : list of str A list of variable names in ``timeSeriesStatsMonthly`` to be included in the climatologies seasons : list of str, optional A list of seasons (keys in ``shared.constants.monthDictionary``) to be computed or ['none'] (not ``None``) if only monthly climatologies are needed. comparisonGridNames : list of {'latlon', 'antarctic'} The name(s) of the comparison grid to use for remapping. minDepth, maxDepth : float The minimum and maximum depths for integration ''' # Authors # ------- # Xylar Asay-Davis subtaskName = 'remapMpasClimatology_{:g}-{:g}m'.format( numpy.abs(minDepth), numpy.abs(maxDepth)) # call the constructor from the base class # (RemapMpasClimatologySubtask) super(RemapMpasOHCClimatology, self).__init__( mpasClimatologyTask, parentTask, climatologyName, variableList, seasons, comparisonGridNames, subtaskName=subtaskName) self.refYearClimatolgyTask = refYearClimatolgyTask self.run_after(refYearClimatolgyTask) self.minDepth = minDepth self.maxDepth = maxDepth # }}} def setup_and_check(self): # {{{ ''' Perform steps to set up the analysis and check for errors in the setup. Raises ------ IOError : If a restart file is not available from which to read mesh information or if no history files are available from which to compute the climatology in the desired time range. ''' # Authors # ------- # Xylar Asay-Davis # first, call setup_and_check from the base class # (RemapMpasClimatologySubtask), which will set up remappers and add # variables to mpasClimatologyTask super(RemapMpasOHCClimatology, self).setup_and_check() # don't add the variables and seasons to mpasClimatologyTask until # we're sure this subtask is supposed to run self.refYearClimatolgyTask.add_variables(self.variableList, self.seasons) # }}} def customize_masked_climatology(self, climatology, season): # {{{ """ Mask the melt rates using ``landIceMask`` and rescale it to m/yr Parameters ---------- climatology : ``xarray.Dataset`` object the climatology data set season : str The name of the season to be masked Returns ------- climatology : ``xarray.Dataset`` object the modified climatology data set """ # Authors # ------- # Xylar Asay-Davis ohc = self._compute_ohc(climatology) refFileName = self.refYearClimatolgyTask.get_file_name(season) refYearClimo = xarray.open_dataset(refFileName) if 'Time' in refYearClimo.dims: refYearClimo = refYearClimo.isel(Time=0) refOHC = self._compute_ohc(refYearClimo) climatology['deltaOHC'] = ohc - refOHC climatology.deltaOHC.attrs['units'] = 'GJ m$^{-2}$' climatology.deltaOHC.attrs['description'] = \ 'Anomaly from year {} in ocean heat content'.format( self.refYearClimatolgyTask.startYear) climatology = climatology.drop_vars(self.variableList) return climatology # }}} def _compute_ohc(self, climatology): # {{{ """ Compute the OHC from the temperature and layer thicknesses in a given climatology data sets. """ dsRestart = xarray.open_dataset(self.restartFileName) dsRestart = dsRestart.isel(Time=0) # specific heat [J/(kg*degC)] cp = self.namelist.getfloat('config_specific_heat_sea_water') # [kg/m3] rho = self.namelist.getfloat('config_density0') unitsScalefactor = 1e-9 nVertLevels = dsRestart.sizes['nVertLevels'] zMid = compute_zmid(dsRestart.bottomDepth, dsRestart.maxLevelCell, dsRestart.layerThickness) vertIndex = xarray.DataArray.from_dict( {'dims': ('nVertLevels',), 'data': numpy.arange(nVertLevels)}) temperature = climatology['timeMonthly_avg_activeTracers_temperature'] layerThickness = climatology['timeMonthly_avg_layerThickness'] masks = [vertIndex < dsRestart.maxLevelCell, zMid <= self.minDepth, zMid >= self.maxDepth] for mask in masks: temperature = temperature.where(mask) layerThickness = layerThickness.where(mask) ohc = unitsScalefactor * rho * cp * layerThickness * temperature ohc = ohc.sum(dim='nVertLevels') return ohc # }}} # }}} # vim: foldmethod=marker ai ts=4 sts=4 et sw=4 ft=python