# 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