.. _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/