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Merge pull request #899 from alicebarthel/add_OSNAP_TSclimtransects
Add osnap T S climtransects
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‎docs/users_guide/analysis_tasks.rst

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@@ -34,6 +34,7 @@ Analysis Tasks
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tasks/meridionalHeatTransport
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tasks/streamfunctionMOC
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tasks/indexNino34
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tasks/osnapTransects
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tasks/woceTransects
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tasks/soseTransects
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tasks/woaTransects

‎docs/users_guide/tasks/examples/osnap_transect.png

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‎docs/users_guide/tasks/osnapTransects.rst

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.. _task_osnapTransects:
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osnapTransects
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=============
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An analysis task for interpolating MPAS fields to
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`Overturning in the Subpolar North Atlantic Program (OSNAP)`_ transects
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and comparing them with ship-based observations.
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Component and Tags::
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component: ocean
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tags: climatology, transect, osnap
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Configuration Options
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---------------------
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The following configuration options are available for this task::
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[osnapTransects]
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## options related to plotting model vs. OSNAP transects.
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# Times for comparison times (JFM, JAS, ANN)
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seasons = ['ANN']
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# The approximate horizontal resolution (in km) of each transect. Latitude/
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# longitude between observation points will be subsampled at this interval.
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# Use 'obs' to indicate no subsampling.
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horizontalResolution = obs
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# The name of the vertical comparison grid. Valid values are 'mpas' for the
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# MPAS vertical grid, 'obs' to use the locations of observations or
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# any other name if the vertical grid is defined by 'verticalComparisonGrid'
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# verticalComparisonGridName = obs
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verticalComparisonGridName = uniform_0_to_4000m_at_10m
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#verticalComparisonGridName = mpas
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# The vertical comparison grid if 'verticalComparisonGridName' is not 'mpas' or
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# 'obs'. This should be numpy array of (typically negative) elevations (in m).
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verticalComparisonGrid = numpy.linspace(0, -4000, 401)
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# The minimum weight of a destination cell after remapping. Any cell with
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# weights lower than this threshold will therefore be masked out.
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renormalizationThreshold = 0.01
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[osnapTemperatureTransects]
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## options related to plotting OSNAP transects of potential temperature
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# colormap for model/observations
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colormapNameResult = RdYlBu_r
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeResult = linear
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# A dictionary with keywords for the norm
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normArgsResult = {'vmin': 0.0, 'vmax': 18.0}
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# color indices into colormapName for filled contours
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#colormapIndicesResult = [0, 40, 80, 110, 140, 170, 200, 230, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsResult = [0, 1, 2, 3, 4, 6, 8, 10, 14, 18]
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# place the ticks automatically by default
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# colorbarTicksResult = numpy.linspace(0.0, 18.0, 9)
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# contour line levels
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contourLevelsResult = np.arange(1.0, 18.0, 2.0)
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# colormap for differences
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colormapNameDifference = RdBu_r
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeDifference = linear
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# A dictionary with keywords for the norm
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normArgsDifference = {'vmin': -2.0, 'vmax': 2.0}
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# color indices into colormapName for filled contours
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#colormapIndicesDifference = [0, 28, 57, 85, 113, 128, 128, 142, 170, 198, 227, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsDifference = [-2, -1.5, -1.25, -1, -0.2, 0, 0.2, 1, 1.25, 1.5, 2]
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# place the ticks automatically by default
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# colorbarTicksDifference = numpy.linspace(-2.0, 2.0, 9)
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# contour line levels
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contourLevelsDifference = np.arange(-1.8, 2.0, 0.4)
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[osnapSalinityTransects]
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## options related to plotting OSNAP transects of salinity
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# colormap for model/observations
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colormapNameResult = BuOr
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeResult = linear
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# A dictionary with keywords for the norm
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normArgsResult = {'vmin': 33.0, 'vmax': 36.0}
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# color indices into colormapName for filled contours
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#colormapIndicesResult = [0, 40, 80, 110, 140, 170, 200, 230, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsResult = [33, 34, 34.25, 34.5, 34.6, 34.7, 34.8, 34.9, 35, 36]
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# place the ticks automatically by default
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# colorbarTicksResult = numpy.linspace(33.0, 36.0, 9)
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# contour line levels
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contourLevelsResult = np.arange(33.3, 36.0, 0.3)
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# colormap for differences
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colormapNameDifference = RdBu_r
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeDifference = linear
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# A dictionary with keywords for the norm
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normArgsDifference = {'vmin': -1.0, 'vmax': 1.0}
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# color indices into colormapName for filled contours
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#colormapIndicesDifference = [0, 28, 57, 85, 113, 128, 128, 142, 170, 198, 227, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsDifference = [-1, -0.5, -0.2, -0.05, -0.02, 0, 0.02, 0.05, 0.2, 0.5, 1]
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# place the ticks automatically by default
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# colorbarTicksDifference = numpy.linspace(-1.0, 1.0, 9)
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# contour line levels
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contourLevelsDifference = np.arange(-0.9, 1.0, 0.4)
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For details on these configuration options, see:
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* :ref:`config_transects`
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* :ref:`config_remapping`
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* :ref:`config_colormaps`
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* :ref:`config_seasons`
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Observations
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------------
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:ref:`osnap`
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Example Result
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--------------
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.. image:: examples/osnap_transect.png
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:width: 500 px
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:align: center
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.. _`Overturning in the Subpolar North Atlantic Program (OSNAP)`: http://www.o-snap.org

‎mpas_analysis/__main__.py

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analyses.append(ocean.WoceTransects(config, oceanClimatologyTasks['avg'],
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controlConfig))
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analyses.append(ocean.AntshipTransects(config, oceanClimatologyTasks['avg'],
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controlConfig))
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analyses.append(ocean.AntshipTransects(config,
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oceanClimatologyTasks['avg'],
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controlConfig))
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analyses.append(ocean.OsnapTransects(config, oceanClimatologyTasks['avg'],
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controlConfig))
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analyses.append(ocean.SoseTransects(config, oceanClimatologyTasks['avg'],
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controlConfig))

‎mpas_analysis/default.cfg

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@@ -529,6 +529,7 @@ woa23Subdirectory = WOA23
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schmidtkoSubdirectory = Schmidtko
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woceSubdirectory = WOCE
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antshipSubdirectory = AntShip
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osnapSubdirectory = OSNAP
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no3Subdirectory = BGC/NO3
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po4Subdirectory = BGC/PO4
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sio3Subdirectory = BGC/SiO3
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contourLevelsResult = [1027.2, 1027.4, 1027.6, 1027.7, 1027.8, 1027.85, 1027.9, 1027.95, 1028.0]
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[osnapTransects]
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## options related to plotting model vs. Overturning in the Subpolar North Atlantic Program
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## (OSNAP) transects.
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# Times for comparison times (valid values: JFM, JAS, ANN)
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seasons = ['ANN']
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# The approximate horizontal resolution (in km) of each transect. Latitude/
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# longitude between observation points will be subsampled at this interval.
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# Use 'obs' to indicate no subsampling. Use 'mpas' to indicate plotting of
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# model data on the native grid, in which case comparison with observations
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# will take place on the observation grid.
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horizontalResolution = mpas
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#horizontalResolution = obs
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#horizontalResolution = 5
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# Horizontal bounds of the plot (in km), or an empty list for automatic bounds
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# The bounds are a 2-element list of the minimum and maximum distance along the
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# transect. Note: only East and West are valid transects
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horizontalBounds = {'OSNAP_East': [],
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'OSNAP_West': []}
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# The name of the vertical comparison grid. Valid values are 'mpas' for the
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# MPAS vertical grid, 'obs' to use the locations of observations or
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# any other name if the vertical grid is defined by 'verticalComparisonGrid'.
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# If horizontalResolution is 'mpas', model data (both main and control) will be
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# plotted on the MPAS vertical grid, regardless of the comparison grid.
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verticalComparisonGridName = mpas
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#verticalComparisonGridName = obs
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#verticalComparisonGridName = uniform_0_to_4000m_at_10m
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# The vertical comparison grid if 'verticalComparisonGridName' is not 'mpas' or
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# 'obs'. This should be numpy array of (typically negative) elevations (in m).
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# The first and last entries are used as axis bounds for 'mpas' and 'obs'
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# vertical comparison grids
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verticalComparisonGrid = numpy.linspace(0, -4000, 401)
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# A range for the y axis (if any)
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verticalBounds = [-4000., 0.]
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# The minimum weight of a destination cell after remapping. Any cell with
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# weights lower than this threshold will therefore be masked out.
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renormalizationThreshold = 0.01
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[osnapTemperatureTransects]
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## options related to plotting OSNAP transects of potential temperature
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# colormap for model/observations
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colormapNameResult = RdYlBu_r
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# whether the colormap is indexed or continuous
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colormapTypeResult = continuous
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeResult = linear
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# A dictionary with keywords for the norm
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normArgsResult = {'vmin': 0.0, 'vmax': 18.0}
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# color indices into colormapName for filled contours
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#colormapIndicesResult = [0, 40, 80, 110, 140, 170, 200, 230, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsResult = [0, 1, 2, 3, 4, 6, 8, 10, 14, 18]
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# place the ticks automatically by default
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# colorbarTicksResult = numpy.linspace(0.0, 18.0, 9)
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# contour line levels (use [] for automatic contour selection, 'none' for no
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# contour lines)
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contourLevelsResult = np.arange(1.0, 18.0, 2.0)
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# colormap for differences
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colormapNameDifference = balance
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# whether the colormap is indexed or continuous
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colormapTypeDifference = continuous
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeDifference = linear
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# A dictionary with keywords for the norm
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normArgsDifference = {'vmin': -3.0, 'vmax': 3.0}
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# color indices into colormapName for filled contours
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#colormapIndicesDifference = [0, 28, 57, 85, 113, 128, 128, 142, 170, 198, 227, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsDifference = [-2, -1.5, -1.25, -1, -0.2, 0, 0.2, 1, 1.25, 1.5, 2]
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# place the ticks automatically by default
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# colorbarTicksDifference = numpy.linspace(-2.0, 2.0, 9)
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# contour line levels (use [] for automatic contour selection, 'none' for no
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# contour lines)
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contourLevelsDifference = np.arange(-1.8, 2.0, 0.4)
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[osnapSalinityTransects]
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## options related to plotting OSNAP transects of salinity
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# colormap for model/observations
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colormapNameResult = haline
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# whether the colormap is indexed or continuous
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colormapTypeResult = continuous
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeResult = linear
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# A dictionary with keywords for the norm
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normArgsResult = {'vmin': 33.0, 'vmax': 36.0}
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# color indices into colormapName for filled contours
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#colormapIndicesResult = [0, 40, 80, 110, 140, 170, 200, 230, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsResult = [33, 34, 34.25, 34.5, 34.6, 34.7, 34.8, 34.9, 35, 36]
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# place the ticks automatically by default
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# colorbarTicksResult = numpy.linspace(33.0, 36.0, 9)
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# contour line levels (use [] for automatic contour selection, 'none' for no
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# contour lines)
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contourLevelsResult = np.arange(33.3, 36.0, 0.3)
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# colormap for differences
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colormapNameDifference = balance
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# whether the colormap is indexed or continuous
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colormapTypeDifference = continuous
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# the type of norm used in the colormap (linear, log, or symLog)
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normTypeDifference = linear
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# A dictionary with keywords for the norm
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normArgsDifference = {'vmin': -1.0, 'vmax': 1.0}
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# color indices into colormapName for filled contours
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#colormapIndicesDifference = [0, 28, 57, 85, 113, 128, 128, 142, 170, 198, 227, 255]
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# colormap levels/values for contour boundaries
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#colorbarLevelsDifference = [-1, -0.5, -0.2, -0.05, -0.02, 0, 0.02, 0.05, 0.2, 0.5, 1]
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# place the ticks automatically by default
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# colorbarTicksDifference = numpy.linspace(-1.0, 1.0, 9)
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# contour line levels (use [] for automatic contour selection, 'none' for no
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# contour lines)
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contourLevelsDifference = np.arange(-0.9, 1.0, 0.4)
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[geojsonTransects]
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## options related to plotting model transects at points determined by a
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## geojson file. To generate your own geojson file, go to:

‎mpas_analysis/obs/observational_datasets.xml

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</nameInDocs>
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</observation>
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<observation>
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<name>
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OSNAP Temperature Salinity and Velocity Climatology
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</name>
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<component>
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ocean
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</component>
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<description>
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OSNAP is designed to provide a continuous record of the full-water
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column, trans-basin fluxes of heat, mass and freshwater in the subpolar
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North Atlantic. It consists of two legs: one extending from southern
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Labrador to the southwestern tip of Greenland across the mouth of the
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Labrador Sea (OSNAP West), and the second from the southeastern tip of
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Greenland to Scotland (OSNAP East). The observing system also includes
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subsurface floats (OSNAP Floats) in order to trace the pathways of
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overflow waters in the basin and to assess the connectivity of currents
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crossing the OSNAP line. The location of the OSNAP East and West legs
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purposefully melds with a number of long-term observational efforts in
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the North Atlantic: the Canadian repeat AR7W program in the Labrador
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Sea; the German Labrador Sea western boundary array at 53°N; the
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global Ocean Observatories Initiative node to be placed in the
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southwestern Irminger Sea; the repeat A1E/AR7E hydrographic sections
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across the Irminger and Iceland basins; and the Ellett line in the
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Rockall region. Importantly, this observing system, in conjunction with
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the RAPID/MOCHA array at 26ºN and the EU THOR/NACLIM program, will
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provide a comprehensive measure of the Atlantic Meridional Overturning
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Circulation (AMOC) and provide a means to evaluate intergyre
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connectivity in the North Atlantic. OSNAP is a collaborative effort,
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which includes several countries including US, Canada, China, France,
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Germany, Netherlands and the UK.
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</description>
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<source>
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[Overturning in the Subpolar North Atlantic Program (OSNAP) website]
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(https://www.o-snap.org/data-access/)
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</source>
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<releasePolicy>
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Acknowledgment: OSNAP data were collected and made freely available by the OSNAP (Overturning in the Subpolar North Atlantic Program) project and all the national programs that contribute to it (www.o-snap.org).
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</releasePolicy>
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<references>
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</references>
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<bibtex>
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</bibtex>
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<dataUrls>
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- https://duke.app.box.com/s/4qbi9ocpvmxdv44wnx2g5rgoyy85jmz6
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</dataUrls>
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<preprocessing>
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- preprocess_observations/preprocessingOSNAP30day.ipynb
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</preprocessing>
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<tasks>
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- climatologyMapOSNAP
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</tasks>
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<subdirectory>
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Ocean/OSNAP
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</subdirectory>
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<nameInDocs>
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osnap_t_s
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</nameInDocs>
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</observation>
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<!--
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<observation>
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<name>

‎mpas_analysis/ocean/__init__.py

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from mpas_analysis.ocean.woce_transects import WoceTransects
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from mpas_analysis.ocean.antship_transects import AntshipTransects
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from mpas_analysis.ocean.osnap_transects import OsnapTransects
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from mpas_analysis.ocean.sose_transects import SoseTransects
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from mpas_analysis.ocean.woa_transects import WoaTransects
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from mpas_analysis.ocean.geojson_transects import GeojsonTransects

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