.. _task_climatologyMapSose: climatologyMapSose ============================= An analysis task for comparing fields at various depths against results from the `Southern Ocean State Estimate (SOSE)`_. Component and Tags:: component: ocean tags: climatology, horizontalMap, sose, publicObs, temperature, salinity, potentialDensity, mixedLayerDepth, zonalVelocity, meridionalVelocity, velocityMagnitude Configuration Options --------------------- The following configuration options are available for this task:: [climatologyMapSose] ## options related to plotting climatology maps of Antarctic fields at various ## levels, including the sea floor against reference model results and SOSE ## reanalysis data # comparison grid(s) # only the Antarctic really makes sense but lat-lon could technically work. comparisonGrids = ['antarctic'] # Months or seasons to plot (Jan, Feb, Mar, Apr, May, Jun, Jul, Aug, Sep, Oct, # Nov, Dec, JFM, AMJ, JAS, OND, ANN) seasons = ['ANN','JFM','JAS'] # list of depths in meters (positive up) at which to analyze, 'top' for the # sea surface, 'bot' for the sea floor depths = ['top', -200, -400, -600, -800, 'bot'] # a list of fields top plot for each transect. All supported fields are listed # below fieldList = ['temperature', 'salinity', 'potentialDensity', 'mixedLayerDepth', 'zonalVelocity', 'meridionalVelocity', 'velocityMagnitude'] # set the suffix for files, e.g. if you want to use a different comparison # grid from the default fileSuffix = 6000.0x6000.0km_10.0km_Antarctic_stereo_20180710 [climatologyMapSoseTemperature] ## options related to plotting climatology maps of Antarctic ## potential temperature at various levels, including the sea floor against ## reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = RdYlBu_r # the type of norm used in the colormap normTypeResult = linear # A dictionary with keywords for the norm normArgsResult = {'vmin': -2., 'vmax': 2.} # place the ticks automatically by default # colorbarTicksResult = numpy.linspace(-2., 2., 9) # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = linear # A dictionary with keywords for the norm normArgsDifference = {'vmin': -2., 'vmax': 2.} # place the ticks automatically by default # colorbarTicksDifference = numpy.linspace(-2., 2., 9) [climatologyMapSoseSalinity] ## options related to plotting climatology maps of Antarctic ## salinity at various levels, including the sea floor against ## reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = haline # the type of norm used in the colormap normTypeResult = linear # A dictionary with keywords for the norm normArgsResult = {'vmin': 33.8, 'vmax': 35.0} # place the ticks automatically by default # colorbarTicksResult = numpy.linspace(34.2, 35.2, 9) # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = linear # A dictionary with keywords for the norm normArgsDifference = {'vmin': -0.5, 'vmax': 0.5} # place the ticks automatically by default # colorbarTicksDifference = numpy.linspace(-0.5, 0.5, 9) [climatologyMapSosePotentialDensity] ## options related to plotting climatology maps of Antarctic ## potential density at various levels, including the sea floor against ## reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = Spectral_r # the type of norm used in the colormap normTypeResult = linear # A dictionary with keywords for the norm normArgsResult = {'vmin': 1026.5, 'vmax': 1028.} # place the ticks automatically by default # colorbarTicksResult = numpy.linspace(1026., 1028., 9) # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = linear # A dictionary with keywords for the norm normArgsDifference = {'vmin': -0.3, 'vmax': 0.3} # place the ticks automatically by default # colorbarTicksDifference = numpy.linspace(-0.3, 0.3, 9) [climatologyMapSoseMixedLayerDepth] ## options related to plotting climatology maps of Antarctic ## mixed layer depth against reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = viridis # color indices into colormapName for filled contours # the type of norm used in the colormap normTypeResult = log # A dictionary with keywords for the norm normArgsResult = {'vmin': 10., 'vmax': 300.} # specify the ticks colorbarTicksResult = [10, 20, 40, 60, 80, 100, 200, 300] # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = symLog # A dictionary with keywords for the norm normArgsDifference = {'linthresh': 10., 'linscale': 0.5, 'vmin': -200., 'vmax': 200.} colorbarTicksDifference = [-200., -100., -50., -20., -10., 0., 10., 20., 50., 100., 200.] [climatologyMapSoseZonalVelocity] ## options related to plotting climatology maps of Antarctic ## zonal velocity against reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = delta # color indices into colormapName for filled contours # the type of norm used in the colormap normTypeResult = linear # A dictionary with keywords for the norm normArgsResult = {'vmin': -0.2, 'vmax': 0.2} # determine the ticks automatically by default, uncomment to specify # colorbarTicksResult = numpy.linspace(-0.2, 0.2, 9) # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = linear # A dictionary with keywords for the norm normArgsDifference = {'vmin': -0.2, 'vmax': 0.2} # determine the ticks automatically by default, uncomment to specify # colorbarTicksDifference = numpy.linspace(-0.2, 0.2, 9) [climatologyMapSoseMeridionalVelocity] ## options related to plotting climatology maps of Antarctic ## meridional against reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = delta # color indices into colormapName for filled contours # the type of norm used in the colormap normTypeResult = linear # A dictionary with keywords for the norm normArgsResult = {'vmin': -0.2, 'vmax': 0.2} # determine the ticks automatically by default, uncomment to specify # colorbarTicksResult = numpy.linspace(-0.2, 0.2, 9) # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = linear # A dictionary with keywords for the norm normArgsDifference = {'vmin': -0.2, 'vmax': 0.2} # determine the ticks automatically by default, uncomment to specify # colorbarTicksDifference = numpy.linspace(-0.2, 0.2, 9) [climatologyMapSoseVelocityMagnitude] ## options related to plotting climatology maps of Antarctic ## meridional against reference model results and SOSE reanalysis data # colormap for model/observations colormapNameResult = ice # color indices into colormapName for filled contours # the type of norm used in the colormap normTypeResult = linear # A dictionary with keywords for the norm normArgsResult = {'vmin': 0, 'vmax': 0.2} # determine the ticks automatically by default, uncomment to specify # colorbarTicksResult = numpy.linspace(0, 0.2, 9) # colormap for differences colormapNameDifference = balance # the type of norm used in the colormap normTypeDifference = linear # A dictionary with keywords for the norm normArgsDifference = {'vmin': -0.2, 'vmax': 0.2} # determine the ticks automatically by default, uncomment to specify # colorbarTicksDifference = numpy.linspace(-0.2, 0.2, 9) There is a section for options that apply to all SOSE climatology maps and one for each field supported for specifying the color map. The option ``depths`` is a list of (approximate) depths at which to sample the potential temperature field. A value of ``'top'`` indicates the sea surface (or the ice-ocean interface under ice shelves) while a value of ``'bot'`` indicates the seafloor. The user can select only to plot a subset of the supported fields by adding only the desired field names to ``fieldList``. The default value shows the list of all available fields. SOSE data for the full Southern Ocean ------------------------------------- The default SOSE data is on a 6,000 x 6,000 km grid focused on the Antarctic continental shelf. An alternative data set is available on a 10,000 x 10,000 km grid. These data can be downloaded directly from the `data repository`_ or by calling:: download_analysis_data -o /output/path/for/diagnostics -d sose_10000km where the output path is the ``baseDirectory`` given in the ``diagnostics`` section of the config file (see :ref:`config_diagnostics`). The data set is not included in the default download because of its large size (~27 GB). Climatologies can be plotted with these data by setting:: fileSuffix = 10000.0x10000.0km_10.0km_Antarctic_stereo_20190603 For more details, see: * :ref:`config_colormaps` * :ref:`config_seasons` * :ref:`config_comparison_grids` State Estimate -------------- :ref:`sose` Example Result -------------- .. image:: examples/clim_sose_temp.png :width: 720 px :align: center .. _`Southern Ocean State Estimate (SOSE)`: http://sose.ucsd.edu/sose_stateestimation_data_05to10.html .. _`data repository`: https://web.lcrc.anl.gov/public/e3sm/diagnostics/observations/Ocean/SOSE/