def run_task(self): # {{{
"""
Performs analysis of the time-series output of Antarctic sub-ice-shelf
melt rates.
"""
# Authors
# -------
# Xylar Asay-Davis, Stephen Price
self.logger.info("\nPlotting Antarctic melt rate time series...")
self.logger.info(' Load melt rate data...')
config = self.config
calendar = self.calendar
totalMeltFlux, meltRates = self._compute_ice_shelf_fluxes()
plotRef = self.refConfig is not None
if plotRef:
refRunName = self.refConfig.get('runs', 'mainRunName')
refTotalMeltFlux, refMeltRates = \
self._load_ice_shelf_fluxes(self.refConfig)
# Load observations from multiple files and put in dictionary based
# on shelf keyname
observationsDirectory = build_config_full_path(config,
'oceanObservations',
'meltSubdirectory')
obsFileNameDict = {
'Rignot et al. (2013)': 'Rignot_2013_melt_rates.csv',
'Rignot et al. (2013) SS': 'Rignot_2013_melt_rates_SS.csv'
}
obsDict = {} # dict for storing dict of obs data
for obsName in obsFileNameDict:
obsFileName = '{}/{}'.format(observationsDirectory,
obsFileNameDict[obsName])
obsDict[obsName] = {}
obsFile = csv.reader(open(obsFileName, 'rU'))
next(obsFile, None) # skip the header line
for line in obsFile: # some later useful values commented out
shelfName = line[0]
# surveyArea = line[1]
meltFlux = float(line[2])
meltFluxUncertainty = float(line[3])
meltRate = float(line[4])
meltRateUncertainty = float(line[5])
# actualArea = float( line[6] ) # actual area here is in sq km
# build dict of obs. keyed to filename description
# (which will be used for plotting)
obsDict[obsName][shelfName] = {
'meltFlux': meltFlux,
'meltFluxUncertainty': meltFluxUncertainty,
'meltRate': meltRate,
'meltRateUncertainty': meltRateUncertainty
}
# If areas from obs file used need to be converted from sq km to sq m
mainRunName = config.get('runs', 'mainRunName')
movingAverageMonths = config.getint('timeSeriesAntarcticMelt',
'movingAverageMonths')
nRegions = totalMeltFlux.sizes['nRegions']
outputDirectory = build_config_full_path(config, 'output',
'timeseriesSubdirectory')
make_directories(outputDirectory)
self.logger.info(' Make plots...')
for iRegion in range(nRegions):
regionName = self.iceShelvesToPlot[iRegion]
# get obs melt flux and unc. for shelf (similar for rates)
obsMeltFlux = []
obsMeltFluxUnc = []
obsMeltRate = []
obsMeltRateUnc = []
for obsName in obsDict:
if regionName in obsDict[obsName]:
obsMeltFlux.append(
obsDict[obsName][regionName]['meltFlux'])
obsMeltFluxUnc.append(
obsDict[obsName][regionName]['meltFluxUncertainty'])
obsMeltRate.append(
obsDict[obsName][regionName]['meltRate'])
obsMeltRateUnc.append(
obsDict[obsName][regionName]['meltRateUncertainty'])
else:
# append NaN so this particular obs won't plot
self.logger.warning('{} observations not available for '
'{}'.format(obsName, regionName))
obsMeltFlux.append(None)
obsMeltFluxUnc.append(None)
obsMeltRate.append(None)
obsMeltRateUnc.append(None)
title = regionName.replace('_', ' ')
regionName = regionName.replace(' ', '_')
xLabel = 'Time (yr)'
yLabel = 'Melt Flux (GT/yr)'
timeSeries = totalMeltFlux.isel(nRegions=iRegion)
filePrefix = 'melt_flux_{}'.format(regionName)
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
fields = [timeSeries]
lineColors = ['k']
lineWidths = [2.5]
legendText = [mainRunName]
if plotRef:
fields.append(refTotalMeltFlux.isel(nRegions=iRegion))
lineColors.append('r')
lineWidths.append(1.2)
legendText.append(refRunName)
timeseries_analysis_plot(config,
fields,
movingAverageMonths,
title,
xLabel,
yLabel,
figureName,
calendar=calendar,
lineColors=lineColors,
lineWidths=lineWidths,
legendText=legendText,
obsMean=obsMeltFlux,
obsUncertainty=obsMeltFluxUnc,
obsLegend=list(obsDict.keys()))
caption = 'Running Mean of Total Melt Flux under Ice ' \
'Shelves in the {} Region'.format(title)
write_image_xml(config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Antarctic Melt Time Series',
groupLink='antmelttime',
gallery='Total Melt Flux',
thumbnailDescription=title,
imageDescription=caption,
imageCaption=caption)
xLabel = 'Time (yr)'
yLabel = 'Melt Rate (m/yr)'
timeSeries = meltRates.isel(nRegions=iRegion)
filePrefix = 'melt_rate_{}'.format(regionName)
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
fields = [timeSeries]
lineColors = ['k']
lineWidths = [2.5]
legendText = [mainRunName]
if plotRef:
fields.append(refMeltRates.isel(nRegions=iRegion))
lineColors.append('r')
lineWidths.append(1.2)
legendText.append(refRunName)
if config.has_option(self.taskName, 'firstYearXTicks'):
firstYearXTicks = config.getint(self.taskName,
'firstYearXTicks')
else:
firstYearXTicks = None
if config.has_option(self.taskName, 'yearStrideXTicks'):
yearStrideXTicks = config.getint(self.taskName,
'yearStrideXTicks')
else:
yearStrideXTicks = None
timeseries_analysis_plot(config,
fields,
movingAverageMonths,
title,
xLabel,
yLabel,
figureName,
calendar=calendar,
lineColors=lineColors,
lineWidths=lineWidths,
legendText=legendText,
obsMean=obsMeltRate,
obsUncertainty=obsMeltRateUnc,
obsLegend=list(obsDict.keys()),
firstYearXTicks=firstYearXTicks,
yearStrideXTicks=yearStrideXTicks)
caption = 'Running Mean of Area-averaged Melt Rate under Ice ' \
'Shelves in the {} Region'.format(title)
write_image_xml(config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Antarctic Melt Time Series',
groupLink='antmelttime',
gallery='Area-averaged Melt Rate',
thumbnailDescription=title,
imageDescription=caption,
imageCaption=caption)
def run_task(self): # {{{
'''
Process MOC analysis member data if available, or compute MOC at
post-processing if not. Plots streamfunction climatolgoical sections
as well as time series of max Atlantic MOC at 26.5N (latitude of
RAPID MOC Array).
'''
# Authors
# -------
# Milena Veneziani, Mark Petersen, Phillip J. Wolfram, Xylar Asay-Davis
self.logger.info("\nPlotting streamfunction of Meridional Overturning "
"Circulation (MOC)...")
config = self.config
# **** Compute MOC ****
if not self.usePostprocessing and self.mocAnalysisMemberEnabled:
self._compute_moc_climo_analysismember()
dsMOCTimeSeries = self._compute_moc_time_series_analysismember()
else:
self._compute_moc_climo_postprocess()
dsMOCTimeSeries = self._compute_moc_time_series_postprocess()
# **** Plot MOC ****
# Define plotting variables
mainRunName = config.get('runs', 'mainRunName')
movingAveragePoints = config.getint(self.sectionName,
'movingAveragePoints')
movingAveragePointsClimatological = config.getint(
self.sectionName, 'movingAveragePointsClimatological')
colorbarLabel = '[Sv]'
xLabel = 'latitude [deg]'
yLabel = 'depth [m]'
for region in self.regionNames:
self.logger.info(' Plot climatological {} MOC...'.format(region))
title = '{} MOC (ANN, years {:04d}-{:04d})\n {}'.format(
region, self.startYearClimo, self.endYearClimo, mainRunName)
filePrefix = self.filePrefixes[region]
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
x = self.lat[region]
y = self.depth
z = self.moc[region]
# Subset lat range
minLat = config.getExpression(self.sectionName,
'latBinMin{}'.format(region))
maxLat = config.getExpression(self.sectionName,
'latBinMax{}'.format(region))
indLat = np.logical_and(x >= minLat, x <= maxLat)
x = x[indLat]
z = z[:, indLat]
plot_vertical_section(config,
x,
y,
z,
self.sectionName,
suffix=region,
colorbarLabel=colorbarLabel,
title=title,
xlabel=xLabel,
ylabel=yLabel,
fileout=figureName,
N=movingAveragePointsClimatological)
caption = '{} Meridional Overturning Streamfunction'.format(region)
write_image_xml(
config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Meridional Overturning Streamfunction',
groupLink='moc',
thumbnailDescription=region,
imageDescription=caption,
imageCaption=caption) # }}}
# Plot time series
self.logger.info(' Plot time series of max Atlantic MOC at 26.5N...')
xLabel = 'Time [years]'
yLabel = '[Sv]'
title = 'Max Atlantic MOC at $26.5\degree$N\n {}'.format(mainRunName)
filePrefix = self.filePrefixes['timeSeries']
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
if config.has_option(self.taskName, 'firstYearXTicks'):
firstYearXTicks = config.getint(self.taskName, 'firstYearXTicks')
else:
firstYearXTicks = None
if config.has_option(self.taskName, 'yearStrideXTicks'):
yearStrideXTicks = config.getint(self.taskName, 'yearStrideXTicks')
else:
yearStrideXTicks = None
fields = [dsMOCTimeSeries.mocAtlantic26]
lineColors = ['k']
lineWidths = [2]
legendText = [mainRunName]
if self.refConfig is not None:
refDirectory = build_config_full_path(self.refConfig, 'output',
'timeseriesSubdirectory')
refStartYear = self.refConfig.getint('timeSeries', 'startYear')
refEndYear = self.refConfig.getint('timeSeries', 'endYear')
refStartDate = '{:04d}-01-01_00:00:00'.format(refStartYear)
refEndDate = '{:04d}-12-31_23:59:59'.format(refEndYear)
refFileName = '{}/mocTimeSeries.nc'.format(refDirectory)
self.logger.info(' Read in reference run MOC time series')
dsRefMOC = open_mpas_dataset(fileName=refFileName,
calendar=self.calendar,
timeVariableNames=None,
variableList=['mocAtlantic26'],
startDate=refStartDate,
endDate=refEndDate)
fields.append(dsRefMOC.mocAtlantic26)
lineColors.append('r')
lineWidths.append(2)
refRunName = self.refConfig.get('runs', 'mainRunName')
legendText.append(refRunName)
timeseries_analysis_plot(config,
fields,
movingAveragePoints,
title,
xLabel,
yLabel,
figureName,
calendar=self.calendar,
lineColors=lineColors,
lineWidths=lineWidths,
legendText=legendText,
firstYearXTicks=firstYearXTicks,
yearStrideXTicks=yearStrideXTicks)
caption = u'Time Series of maximum Meridional Overturning ' \
u'Circulation at 26.5°N'
write_image_xml(config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Meridional Overturning Streamfunction',
groupLink='moc',
thumbnailDescription='Time Series',
imageDescription=caption,
imageCaption=caption) # }}}
def run_task(self): # {{{
"""
Performs analysis of time series of sea-ice properties.
"""
# Authors
# -------
# Xylar Asay-Davis, Milena Veneziani
self.logger.info("\nPlotting sea-ice area and volume time series...")
config = self.config
calendar = self.calendar
sectionName = self.taskName
plotTitles = {
'iceArea': 'Sea-ice area',
'iceVolume': 'Sea-ice volume',
'iceThickness': 'Sea-ice mean thickness'
}
units = {
'iceArea': '[km$^2$]',
'iceVolume': '[10$^3$ km$^3$]',
'iceThickness': '[m]'
}
obsFileNames = {
'iceArea': {
'NH':
build_config_full_path(config=config,
section='seaIceObservations',
relativePathOption='areaNH',
relativePathSection=sectionName),
'SH':
build_config_full_path(config=config,
section='seaIceObservations',
relativePathOption='areaSH',
relativePathSection=sectionName)
},
'iceVolume': {
'NH':
build_config_full_path(config=config,
section='seaIceObservations',
relativePathOption='volNH',
relativePathSection=sectionName),
'SH':
build_config_full_path(config=config,
section='seaIceObservations',
relativePathOption='volSH',
relativePathSection=sectionName)
}
}
# Some plotting rules
titleFontSize = config.get('timeSeriesSeaIceAreaVol', 'titleFontSize')
mainRunName = config.get('runs', 'mainRunName')
preprocessedReferenceRunName = \
config.get('runs', 'preprocessedReferenceRunName')
preprocessedReferenceDirectory = \
config.get('seaIcePreprocessedReference', 'baseDirectory')
compareWithObservations = config.getboolean('timeSeriesSeaIceAreaVol',
'compareWithObservations')
movingAveragePoints = config.getint('timeSeriesSeaIceAreaVol',
'movingAveragePoints')
polarPlot = config.getboolean('timeSeriesSeaIceAreaVol', 'polarPlot')
outputDirectory = build_config_full_path(config, 'output',
'timeseriesSubdirectory')
make_directories(outputDirectory)
self.logger.info(' Load sea-ice data...')
# Load mesh
dsTimeSeries = self._compute_area_vol()
yearStart = days_to_datetime(dsTimeSeries['NH'].Time.min(),
calendar=calendar).year
yearEnd = days_to_datetime(dsTimeSeries['NH'].Time.max(),
calendar=calendar).year
timeStart = date_to_days(year=yearStart,
month=1,
day=1,
calendar=calendar)
timeEnd = date_to_days(year=yearEnd,
month=12,
day=31,
calendar=calendar)
if preprocessedReferenceRunName != 'None':
# determine if we're beyond the end of the preprocessed data
# (and go ahead and cache the data set while we're checking)
outFolder = '{}/preprocessed'.format(outputDirectory)
make_directories(outFolder)
inFilesPreprocessed = '{}/icevol.{}.year*.nc'.format(
preprocessedReferenceDirectory, preprocessedReferenceRunName)
outFileName = '{}/iceVolume.nc'.format(outFolder)
combine_time_series_with_ncrcat(inFilesPreprocessed,
outFileName,
logger=self.logger)
dsPreprocessed = open_mpas_dataset(fileName=outFileName,
calendar=calendar,
timeVariableNames='xtime')
preprocessedYearEnd = days_to_datetime(dsPreprocessed.Time.max(),
calendar=calendar).year
if yearStart <= preprocessedYearEnd:
dsPreprocessedTimeSlice = \
dsPreprocessed.sel(Time=slice(timeStart, timeEnd))
else:
self.logger.warning('Preprocessed time series ends before the '
'timeSeries startYear and will not be '
'plotted.')
preprocessedReferenceRunName = 'None'
if self.refConfig is not None:
dsTimeSeriesRef = {}
baseDirectory = build_config_full_path(self.refConfig, 'output',
'timeSeriesSubdirectory')
refRunName = self.refConfig.get('runs', 'mainRunName')
for hemisphere in ['NH', 'SH']:
inFileName = '{}/seaIceAreaVol{}.nc'.format(
baseDirectory, hemisphere)
dsTimeSeriesRef[hemisphere] = xr.open_dataset(inFileName)
norm = {
'iceArea': 1e-6, # m^2 to km^2
'iceVolume': 1e-12, # m^3 to 10^3 km^3
'iceThickness': 1.
}
xLabel = 'Time [years]'
galleryGroup = 'Time Series'
groupLink = 'timeseries'
obs = {}
preprocessed = {}
figureNameStd = {}
figureNamePolar = {}
title = {}
plotVars = {}
obsLegend = {}
plotVarsRef = {}
for hemisphere in ['NH', 'SH']:
self.logger.info(' Make {} plots...'.format(hemisphere))
for variableName in ['iceArea', 'iceVolume']:
key = (hemisphere, variableName)
# apply the norm to each variable
plotVars[key] = (norm[variableName] *
dsTimeSeries[hemisphere][variableName])
if self.refConfig is not None:
plotVarsRef[key] = norm[variableName] * \
dsTimeSeriesRef[hemisphere][variableName]
prefix = '{}/{}{}_{}'.format(self.plotsDirectory, variableName,
hemisphere, mainRunName)
figureNameStd[key] = '{}.png'.format(prefix)
figureNamePolar[key] = '{}_polar.png'.format(prefix)
title[key] = '{} ({})'.format(plotTitles[variableName],
hemisphere)
if compareWithObservations:
key = (hemisphere, 'iceArea')
obsLegend[key] = 'SSM/I observations, annual cycle '
if hemisphere == 'NH':
key = (hemisphere, 'iceVolume')
obsLegend[key] = 'PIOMAS, annual cycle (blue)'
if preprocessedReferenceRunName != 'None':
for variableName in ['iceArea', 'iceVolume']:
key = (hemisphere, variableName)
if compareWithObservations:
outFolder = '{}/obs'.format(outputDirectory)
make_directories(outFolder)
outFileName = '{}/iceArea{}.nc'.format(outFolder, hemisphere)
combine_time_series_with_ncrcat(
obsFileNames['iceArea'][hemisphere],
outFileName,
logger=self.logger)
dsObs = open_mpas_dataset(fileName=outFileName,
calendar=calendar,
timeVariableNames='xtime')
key = (hemisphere, 'iceArea')
obs[key] = self._replicate_cycle(plotVars[key], dsObs.IceArea,
calendar)
key = (hemisphere, 'iceVolume')
if hemisphere == 'NH':
outFileName = '{}/iceVolume{}.nc'.format(
outFolder, hemisphere)
combine_time_series_with_ncrcat(
obsFileNames['iceVolume'][hemisphere],
outFileName,
logger=self.logger)
dsObs = open_mpas_dataset(fileName=outFileName,
calendar=calendar,
timeVariableNames='xtime')
obs[key] = self._replicate_cycle(plotVars[key],
dsObs.IceVol, calendar)
else:
obs[key] = None
if preprocessedReferenceRunName != 'None':
outFolder = '{}/preprocessed'.format(outputDirectory)
inFilesPreprocessed = '{}/icearea.{}.year*.nc'.format(
preprocessedReferenceDirectory,
preprocessedReferenceRunName)
outFileName = '{}/iceArea.nc'.format(outFolder)
combine_time_series_with_ncrcat(inFilesPreprocessed,
outFileName,
logger=self.logger)
dsPreprocessed = open_mpas_dataset(fileName=outFileName,
calendar=calendar,
timeVariableNames='xtime')
dsPreprocessedTimeSlice = dsPreprocessed.sel(
Time=slice(timeStart, timeEnd))
key = (hemisphere, 'iceArea')
preprocessed[key] = dsPreprocessedTimeSlice[
'icearea_{}'.format(hemisphere.lower())]
inFilesPreprocessed = '{}/icevol.{}.year*.nc'.format(
preprocessedReferenceDirectory,
preprocessedReferenceRunName)
outFileName = '{}/iceVolume.nc'.format(outFolder)
combine_time_series_with_ncrcat(inFilesPreprocessed,
outFileName,
logger=self.logger)
dsPreprocessed = open_mpas_dataset(fileName=outFileName,
calendar=calendar,
timeVariableNames='xtime')
dsPreprocessedTimeSlice = dsPreprocessed.sel(
Time=slice(timeStart, timeEnd))
key = (hemisphere, 'iceVolume')
preprocessed[key] = dsPreprocessedTimeSlice[
'icevolume_{}'.format(hemisphere.lower())]
for variableName in ['iceArea', 'iceVolume']:
key = (hemisphere, variableName)
dsvalues = [plotVars[key]]
legendText = [mainRunName]
lineColors = ['k']
lineWidths = [3]
if compareWithObservations and key in obsLegend.keys():
dsvalues.append(obs[key])
legendText.append(obsLegend[key])
lineColors.append('b')
lineWidths.append(1.2)
if preprocessedReferenceRunName != 'None':
dsvalues.append(preprocessed[key])
legendText.append(preprocessedReferenceRunName)
lineColors.append('purple')
lineWidths.append(1.2)
if self.refConfig is not None:
dsvalues.append(plotVarsRef[key])
legendText.append(refRunName)
lineColors.append('r')
lineWidths.append(1.2)
if config.has_option(sectionName, 'firstYearXTicks'):
firstYearXTicks = config.getint(sectionName,
'firstYearXTicks')
else:
firstYearXTicks = None
if config.has_option(sectionName, 'yearStrideXTicks'):
yearStrideXTicks = config.getint(sectionName,
'yearStrideXTicks')
else:
yearStrideXTicks = None
# separate plots for nothern and southern hemispheres
timeseries_analysis_plot(config,
dsvalues,
movingAveragePoints,
title[key],
xLabel,
units[variableName],
figureNameStd[key],
calendar=calendar,
lineColors=lineColors,
lineWidths=lineWidths,
legendText=legendText,
titleFontSize=titleFontSize,
firstYearXTicks=firstYearXTicks,
yearStrideXTicks=yearStrideXTicks)
filePrefix = '{}{}_{}'.format(variableName, hemisphere,
mainRunName)
thumbnailDescription = '{} {}'.format(hemisphere,
plotTitles[variableName])
caption = 'Running mean of {}'.format(thumbnailDescription)
write_image_xml(config,
filePrefix,
componentName='Sea Ice',
componentSubdirectory='sea_ice',
galleryGroup=galleryGroup,
groupLink=groupLink,
thumbnailDescription=thumbnailDescription,
imageDescription=caption,
imageCaption=caption)
if (polarPlot):
timeseries_analysis_plot_polar(config,
dsvalues,
movingAveragePoints,
title[key],
figureNamePolar[key],
lineColors=lineColors,
lineWidths=lineWidths,
legendText=legendText,
titleFontSize=titleFontSize)
filePrefix = '{}{}_{}_polar'.format(
variableName, hemisphere, mainRunName)
write_image_xml(config,
filePrefix,
componentName='Sea Ice',
componentSubdirectory='sea_ice',
galleryGroup=galleryGroup,
groupLink=groupLink,
thumbnailDescription=thumbnailDescription,
imageDescription=caption,
imageCaption=caption)
def run_task(self): # {{{
'''
Process MOC analysis member data if available, or compute MOC at
post-processing if not. Plots streamfunction climatolgoical sections
as well as time series of max Atlantic MOC at 26.5N (latitude of
RAPID MOC Array).
'''
# Authors
# -------
# Milena Veneziani, Mark Petersen, Phillip J. Wolfram, Xylar Asay-Davis
self.logger.info("\nPlotting streamfunction of Meridional Overturning "
"Circulation (MOC)...")
config = self.config
# **** Compute MOC ****
# Check whether MOC Analysis Member is enabled
if self.mocAnalysisMemberEnabled:
# Add a moc_analisysMember_processing
self.logger.info('*** MOC Analysis Member is on ***')
# (mocDictClimo, mocDictTseries) = \
# self._compute_moc_analysismember(config, streams, calendar,
# sectionName, dictClimo,
# dictTseries)
# delete the following 3 lines after analysis of the MOC AM is
# supported
self.logger.info('...but not yet supported. Using offline MOC')
self._compute_moc_climo_postprocess()
dsMOCTimeSeries = self._compute_moc_time_series_postprocess()
else:
self._compute_moc_climo_postprocess()
dsMOCTimeSeries = self._compute_moc_time_series_postprocess()
# **** Plot MOC ****
# Define plotting variables
mainRunName = config.get('runs', 'mainRunName')
movingAveragePoints = config.getint(self.sectionName,
'movingAveragePoints')
movingAveragePointsClimatological = config.getint(
self.sectionName, 'movingAveragePointsClimatological')
colorbarLabel = '[Sv]'
xLabel = 'latitude [deg]'
yLabel = 'depth [m]'
for region in self.regionNames:
self.logger.info(' Plot climatological {} MOC...'.format(region))
title = '{} MOC (ANN, years {:04d}-{:04d})\n {}'.format(
region, self.startYearClimo, self.endYearClimo, mainRunName)
filePrefix = self.filePrefixes[region]
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
x = self.lat[region]
y = self.depth
z = self.moc[region]
plot_vertical_section(config,
x,
y,
z,
self.sectionName,
suffix=region,
colorbarLabel=colorbarLabel,
title=title,
xlabel=xLabel,
ylabel=yLabel,
fileout=figureName,
N=movingAveragePointsClimatological)
caption = '{} Meridional Overturning Streamfunction'.format(region)
write_image_xml(
config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Meridional Overturning Streamfunction',
groupLink='moc',
thumbnailDescription=region,
imageDescription=caption,
imageCaption=caption) # }}}
# Plot time series
self.logger.info(' Plot time series of max Atlantic MOC at 26.5N...')
xLabel = 'Time [years]'
yLabel = '[Sv]'
title = 'Max Atlantic MOC at $26.5^\circ$N\n {}'.format(mainRunName)
filePrefix = self.filePrefixes['timeSeries']
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
if config.has_option(self.taskName, 'firstYearXTicks'):
firstYearXTicks = config.getint(self.taskName, 'firstYearXTicks')
else:
firstYearXTicks = None
if config.has_option(self.taskName, 'yearStrideXTicks'):
yearStrideXTicks = config.getint(self.taskName, 'yearStrideXTicks')
else:
yearStrideXTicks = None
timeseries_analysis_plot(config, [dsMOCTimeSeries.mocAtlantic26],
movingAveragePoints,
title,
xLabel,
yLabel,
figureName,
lineStyles=['k-'],
lineWidths=[2],
legendText=[None],
calendar=self.calendar,
firstYearXTicks=firstYearXTicks,
yearStrideXTicks=yearStrideXTicks)
caption = u'Time Series of maximum Meridional Overturning ' \
u'Circulation at 26.5°N'
write_image_xml(config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Meridional Overturning Streamfunction',
groupLink='moc',
thumbnailDescription='Time Series',
imageDescription=caption,
imageCaption=caption) # }}}
def run_task(self): # {{{
"""
Performs analysis of the time-series output of sea-surface temperature
(SST).
"""
# Authors
# -------
# Xylar Asay-Davis, Milena Veneziani
self.logger.info("\nPlotting SST time series...")
self.logger.info(' Load SST data...')
config = self.config
calendar = self.calendar
mainRunName = config.get('runs', 'mainRunName')
preprocessedReferenceRunName = \
config.get('runs', 'preprocessedReferenceRunName')
preprocessedInputDirectory = config.get('oceanPreprocessedReference',
'baseDirectory')
movingAveragePoints = config.getint('timeSeriesSST',
'movingAveragePoints')
regions = config.getExpression('regions', 'regions')
plotTitles = config.getExpression('regions', 'plotTitles')
regionsToPlot = config.getExpression('timeSeriesSST', 'regions')
regionIndicesToPlot = [
regions.index(region) for region in regionsToPlot
]
outputDirectory = build_config_full_path(config, 'output',
'timeseriesSubdirectory')
make_directories(outputDirectory)
dsSST = open_mpas_dataset(fileName=self.inputFile,
calendar=calendar,
variableList=self.variableList,
startDate=self.startDate,
endDate=self.endDate)
yearStart = days_to_datetime(dsSST.Time.min(), calendar=calendar).year
yearEnd = days_to_datetime(dsSST.Time.max(), calendar=calendar).year
timeStart = date_to_days(year=yearStart,
month=1,
day=1,
calendar=calendar)
timeEnd = date_to_days(year=yearEnd,
month=12,
day=31,
calendar=calendar)
if self.refConfig is not None:
baseDirectory = build_config_full_path(self.refConfig, 'output',
'timeSeriesSubdirectory')
refFileName = '{}/{}.nc'.format(
baseDirectory, self.mpasTimeSeriesTask.fullTaskName)
refStartYear = self.refConfig.getint('timeSeries', 'startYear')
refEndYear = self.refConfig.getint('timeSeries', 'endYear')
refStartDate = '{:04d}-01-01_00:00:00'.format(refStartYear)
refEndDate = '{:04d}-12-31_23:59:59'.format(refEndYear)
dsRefSST = open_mpas_dataset(fileName=refFileName,
calendar=calendar,
variableList=self.variableList,
startDate=refStartDate,
endDate=refEndDate)
else:
dsRefSST = None
if preprocessedReferenceRunName != 'None':
self.logger.info(' Load in SST for a preprocesses reference '
'run...')
inFilesPreprocessed = '{}/SST.{}.year*.nc'.format(
preprocessedInputDirectory, preprocessedReferenceRunName)
outFolder = '{}/preprocessed'.format(outputDirectory)
make_directories(outFolder)
outFileName = '{}/sst.nc'.format(outFolder)
combine_time_series_with_ncrcat(inFilesPreprocessed,
outFileName,
logger=self.logger)
dsPreprocessed = open_mpas_dataset(fileName=outFileName,
calendar=calendar,
timeVariableNames='xtime')
yearEndPreprocessed = days_to_datetime(dsPreprocessed.Time.max(),
calendar=calendar).year
if yearStart <= yearEndPreprocessed:
dsPreprocessedTimeSlice = \
dsPreprocessed.sel(Time=slice(timeStart, timeEnd))
else:
self.logger.warning('Preprocessed time series ends before the '
'timeSeries startYear and will not be '
'plotted.')
preprocessedReferenceRunName = 'None'
self.logger.info(' Make plots...')
for regionIndex in regionIndicesToPlot:
region = regions[regionIndex]
title = '{} SST'.format(plotTitles[regionIndex])
xLabel = 'Time [years]'
yLabel = '[$\degree$C]'
varName = self.variableList[0]
SST = dsSST[varName].isel(nOceanRegions=regionIndex)
filePrefix = self.filePrefixes[region]
figureName = '{}/{}.png'.format(self.plotsDirectory, filePrefix)
lineColors = ['k']
lineWidths = [3]
fields = [SST]
legendText = [mainRunName]
if dsRefSST is not None:
refSST = dsRefSST[varName].isel(nOceanRegions=regionIndex)
fields.append(refSST)
lineColors.append('r')
lineWidths.append(1.5)
refRunName = self.refConfig.get('runs', 'mainRunName')
legendText.append(refRunName)
if preprocessedReferenceRunName != 'None':
SST_v0 = dsPreprocessedTimeSlice.SST
fields.append(SST_v0)
lineColors.append('purple')
lineWidths.append(1.5)
legendText.append(preprocessedReferenceRunName)
if config.has_option(self.taskName, 'firstYearXTicks'):
firstYearXTicks = config.getint(self.taskName,
'firstYearXTicks')
else:
firstYearXTicks = None
if config.has_option(self.taskName, 'yearStrideXTicks'):
yearStrideXTicks = config.getint(self.taskName,
'yearStrideXTicks')
else:
yearStrideXTicks = None
timeseries_analysis_plot(config,
fields,
movingAveragePoints,
title,
xLabel,
yLabel,
figureName,
calendar=calendar,
lineColors=lineColors,
lineWidths=lineWidths,
legendText=legendText,
firstYearXTicks=firstYearXTicks,
yearStrideXTicks=yearStrideXTicks)
caption = 'Running Mean of {} Sea Surface Temperature'.format(
region)
write_image_xml(config=config,
filePrefix=filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup='Time Series',
groupLink='timeseries',
thumbnailDescription='{} SST'.format(region),
imageDescription=caption,
imageCaption=caption)
def run_task(self): # {{{
"""
Compute vertical agregates of the data and plot the time series
"""
# Authors
# -------
# Xylar Asay-Davis, Milena Veneziani, Greg Streletz
self.logger.info("\nPlotting depth-integrated time series of "
"{}...".format(self.fieldNameInTitle))
config = self.config
calendar = self.calendar
mainRunName = config.get('runs', 'mainRunName')
plotTitles = config.getExpression('regions', 'plotTitles')
allRegionNames = config.getExpression('regions', 'regions')
regionIndex = allRegionNames.index(self.regionName)
regionNameInTitle = plotTitles[regionIndex]
startDate = config.get('timeSeries', 'startDate')
endDate = config.get('timeSeries', 'endDate')
# Load data
self.logger.info(' Load ocean data...')
ds = open_mpas_dataset(fileName=self.inFileName,
calendar=calendar,
variableList=[self.mpasFieldName, 'depth'],
timeVariableNames=None,
startDate=startDate,
endDate=endDate)
ds = ds.isel(nOceanRegionsTmp=regionIndex)
depths = ds.depth.values
divisionDepths = config.getExpression(self.sectionName, 'depths')
# for each depth interval to plot, determine the top and bottom depth
topDepths = [0, 0] + divisionDepths
bottomDepths = [depths[-1]] + divisionDepths + [depths[-1]]
legends = []
for top, bottom in zip(topDepths, bottomDepths):
if bottom == depths[-1]:
legends.append('{}m-bottom'.format(top))
else:
legends.append('{}m-{}m'.format(top, bottom))
# more possible symbols than we typically use
lines = ['-', '-', '--', '+', 'o', '^', 'v']
widths = [5, 3, 3, 3, 3, 3, 3]
points = [None, None, None, 300, 300, 300, 300]
color = 'k'
xLabel = 'Time [years]'
yLabel = self.yAxisLabel
title = '{}, {} \n {} (black)'.format(self.fieldNameInTitle,
regionNameInTitle, mainRunName)
figureName = '{}/{}.png'.format(self.plotsDirectory, self.filePrefix)
timeSeries = []
lineStyles = []
lineWidths = []
maxPoints = []
legendText = []
for rangeIndex in range(len(topDepths)):
top = topDepths[rangeIndex]
bottom = bottomDepths[rangeIndex]
field = ds[self.mpasFieldName].where(ds.depth > top)
field = field.where(ds.depth <= bottom)
timeSeries.append(field.sum('nVertLevels'))
lineStyles.append('{}{}'.format(color, lines[rangeIndex]))
lineWidths.append(widths[rangeIndex])
maxPoints.append(points[rangeIndex])
legendText.append(legends[rangeIndex])
preprocessedReferenceRunName = config.get(
'runs', 'preprocessedReferenceRunName')
if preprocessedReferenceRunName != 'None':
preprocessedInputDirectory = config.get(
'oceanPreprocessedReference', 'baseDirectory')
self.logger.info(' Load in OHC from preprocessed reference '
'run...')
preprocessedFilePrefix = config.get(self.sectionName,
'preprocessedFilePrefix')
inFilesPreprocessed = '{}/{}.{}.year*.nc'.format(
preprocessedInputDirectory, preprocessedFilePrefix,
preprocessedReferenceRunName)
dsPreprocessed = open_multifile_dataset(
fileNames=inFilesPreprocessed,
calendar=calendar,
config=config,
timeVariableName='xtime')
yearStart = days_to_datetime(ds.Time.min(), calendar=calendar).year
yearEnd = days_to_datetime(ds.Time.max(), calendar=calendar).year
timeStart = date_to_days(year=yearStart,
month=1,
day=1,
calendar=calendar)
timeEnd = date_to_days(year=yearEnd,
month=12,
day=31,
calendar=calendar)
yearEndPreprocessed = days_to_datetime(dsPreprocessed.Time.max(),
calendar=calendar).year
if yearStart <= yearEndPreprocessed:
dsPreprocessed = dsPreprocessed.sel(
Time=slice(timeStart, timeEnd))
else:
self.logger.warning('Warning: Preprocessed time series ends '
'before the timeSeries startYear and will '
'not be plotted.')
preprocessedReferenceRunName = 'None'
# rolling mean seems to have trouble with dask data sets so we
# write out the data set and read it back as a single-file data set
# (without dask)
dsPreprocessed = dsPreprocessed.drop('xtime')
write_netcdf(dsPreprocessed, self.preprocessedFileName)
dsPreprocessed = xarray.open_dataset(self.preprocessedFileName)
if preprocessedReferenceRunName != 'None':
color = 'r'
title = '{} \n {} (red)'.format(title,
preprocessedReferenceRunName)
preprocessedFieldPrefix = config.get(self.sectionName,
'preprocessedFieldPrefix')
movingAveragePoints = config.getint(self.sectionName,
'movingAveragePoints')
suffixes = ['tot'
] + ['{}m'.format(depth)
for depth in divisionDepths] + ['btm']
# these preprocessed data are OHC *anomalies*
dsPreprocessed = compute_moving_avg(dsPreprocessed,
movingAveragePoints)
for rangeIndex in range(len(suffixes)):
variableName = '{}_{}'.format(preprocessedFieldPrefix,
suffixes[rangeIndex])
if variableName in list(dsPreprocessed.data_vars.keys()):
timeSeries.append(dsPreprocessed[variableName])
else:
self.logger.warning(
'Warning: Preprocessed variable {} '
'not found. Skipping.'.format(variableName))
timeSeries.extend(None)
lineStyles.append('{}{}'.format(color, lines[rangeIndex]))
lineWidths.append(widths[rangeIndex])
maxPoints.append(points[rangeIndex])
legendText.append(None)
if self.refConfig is not None:
refRunName = self.refConfig.get('runs', 'mainRunName')
title = '{} \n {} (blue)'.format(title, refRunName)
self.logger.info(' Load ocean data from reference run...')
refStartYear = self.refConfig.getint('timeSeries', 'startYear')
refEndYear = self.refConfig.getint('timeSeries', 'endYear')
refStartDate = '{:04d}-01-01_00:00:00'.format(refStartYear)
refEndDate = '{:04d}-12-31_23:59:59'.format(refEndYear)
dsRef = open_mpas_dataset(
fileName=self.refFileName,
calendar=calendar,
variableList=[self.mpasFieldName, 'depth'],
timeVariableNames=None,
startDate=refStartDate,
endDate=refEndDate)
dsRef = dsRef.isel(nOceanRegionsTmp=regionIndex)
color = 'b'
for rangeIndex in range(len(topDepths)):
top = topDepths[rangeIndex]
bottom = bottomDepths[rangeIndex]
field = dsRef[self.mpasFieldName].where(dsRef.depth > top)
field = field.where(dsRef.depth <= bottom)
timeSeries.append(field.sum('nVertLevels'))
lineStyles.append('{}{}'.format(color, lines[rangeIndex]))
lineWidths.append(widths[rangeIndex])
maxPoints.append(points[rangeIndex])
legendText.append(None)
if config.has_option(self.taskName, 'firstYearXTicks'):
firstYearXTicks = config.getint(self.taskName, 'firstYearXTicks')
else:
firstYearXTicks = None
if config.has_option(self.taskName, 'yearStrideXTicks'):
yearStrideXTicks = config.getint(self.taskName, 'yearStrideXTicks')
else:
yearStrideXTicks = None
timeseries_analysis_plot(config=config,
dsvalues=timeSeries,
N=None,
title=title,
xlabel=xLabel,
ylabel=yLabel,
fileout=figureName,
lineStyles=lineStyles,
lineWidths=lineWidths,
maxPoints=maxPoints,
legendText=legendText,
calendar=calendar,
firstYearXTicks=firstYearXTicks,
yearStrideXTicks=yearStrideXTicks)
write_image_xml(config=config,
filePrefix=self.filePrefix,
componentName='Ocean',
componentSubdirectory='ocean',
galleryGroup=self.galleryGroup,
groupLink=self.groupLink,
galleryName=self.galleryName,
thumbnailDescription='{} {}'.format(
self.regionName, self.thumbnailSuffix),
imageDescription=self.imageCaption,
imageCaption=self.imageCaption)