Merge pull request #353 from MetOffice/352_inflow_properties_additon

Adds inflow layer properties diagnostic

cset-workflow/includes/deterministic_plot_inflow_properties.cylc

@@ -0,0 +1,12 @@
+{% if DETERMINISTIC_PLOT_INFLOW_PROPERTIES %}
+[runtime]
+    [[parallel_inflow_layer_properties]]
+    inherit = PARALLEL
+        [[[environment]]]
+        CSET_RECIPE_NAME = "inflow_layer_properties_plot.yaml"
+
+    [[collate_inflow_layer_properties]]
+    inherit = COLLATE
+        [[[environment]]]
+        CSET_RECIPE_NAME = "inflow_layer_properties_plot.yaml"
+{% endif %}

cset-workflow/meta/rose-meta.conf

@@ -523,3 +523,11 @@ help=Recommend looking at the input data to get these values. Uses the grid's na
 type=real
 sort-key=subsection2
 compulsory=true
+
+[template variables=DETERMINISTIC_PLOT_INFLOW_PROPERTIES]
+ns=Diagnostics
+description=Extracts data required for, and calculates the inflow properties diagnostic, plotting on a map.
+            Required STASH m01s20i119, m01s00i025, m01s00i033.
+help=See includes/deterministic_plot_inflow_properties.cylc
+type=python_boolean
+compulsory=true

src/CSET/operators/convection.py

@@ -20,8 +20,11 @@
 """
 
 import copy
+import logging
 import warnings
 
+import iris
+import iris.cube
 import numpy as np
 
 
@@ -32,16 +35,14 @@ def cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-75.0):
     ----------
     SBCAPE: Cube
         Surface-based convective available potential energy as calculated by the
-        model.
-        Stash: m01s20i114
+        model. If using the UM please use STASH ``m01s20i114``
     MUCAPE: Cube
         Most-unstable convective available potential energy as calculated by the
-        model.
-        Stash: m01s20i112
+        model. If using the UM please use STASH ``m01s20i112``
     MUCIN: Cube
         Most-unstable convective inhibition associated with the most-unstable
-        ascent as calculated by the model.
-        Stash: m01s20i113
+        ascent as calculated by the model. If using the UM please use STASH
+        ``m01s20i113``
     MUCIN_thresh: float, optional, default is -75. J/kg.
         Threshold to filter the MUCAPE by values are realistically realisable.
 
@@ -51,13 +52,14 @@ def cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-75.0):
 
     Notes
     -----
-    This diagnostic is based on Clark et al. (2012) [1]_. It is based around the idea
-    that for elevated convection the convective instability is not based at the
-    surface. This utilises two flavours of CAPE: the surface-based CAPE (SBCAPE)
-    and the most-unstable CAPE (MUCAPE). The MUCAPE is filtered by the MUCIN
-    associated with that parcel's ascent to ensure that any CAPE can at least
-    theoretically be released. The default value is set at -75 J/kg but it can
-    be changes depending on location and users requirements.
+    This diagnostic is based on Clark et al. (2012) [Clarketal2012]_. It is
+    based around the idea that for elevated convection the convective
+    instability is not based at the surface. This utilises two flavours of CAPE:
+    the surface-based CAPE (SBCAPE) and the most-unstable CAPE (MUCAPE). The
+    MUCAPE is filtered by the MUCIN associated with that parcel's ascent to
+    ensure that any CAPE can at least theoretically be released. The default
+    value is set at -75 J/kg but it can be changes depending on location and
+    users requirements.
 
     .. math:: 1 - (\frac{SBCAPE}{MUCAPE})
 
@@ -73,29 +75,29 @@ def cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-75.0):
     surface-based convection is more likely.
 
     Further details about this diagnostic for elevated convection identification
-    can be found in Flack et al. (2023) [2]_.
+    can be found in Flack et al. (2023) [FlackCAPE2023]_.
 
     Expected applicability ranges: Convective-scale models will be noisier than
     parametrized models as they are more responsive to the convection, and thus
-    it may be more sensible to view as a larger spatial average rather than
-    on the native resolution.
+    it may be more sensible to view as a larger spatial average rather than on
+    the native resolution.
 
     Interpretation notes: UM stash for CAPE and CIN are calculated at the end of
-    the timestep. Therefore this diagnostic is applicable after precipitation has
-    occurred, not before as is the usual interpretation of CAPE related diagnostics.
+    the timestep. Therefore this diagnostic is applicable after precipitation
+    has occurred, not before as is the usual interpretation of CAPE related
+    diagnostics.
 
     References
     ----------
-    .. [1] Clark, A. J., Kain J. S., Marsh P. T., Correia J., Xue M., and Kong
-       F., (2012) "Forecasting tornado pathlengths using a three-dimensional
-       object identification algorithm applied to convection-allowing
-       forecasts." Weather and Forecasting, vol. 27, 1090–1113, doi:
-       10.1175/WAF-D-11-00147.1
-    .. [2] Flack, D.L.A., Lehnert, M., Lean, H.W., and Willington, S. (2023)
-       "Characteristics of Diagnostics for Identifying Elevated
+    .. [Clarketal2012] Clark, A. J., Kain J. S., Marsh P. T., Correia J., Xue
+       M., and Kong F., (2012) "Forecasting tornado pathlengths using a
+       three-dimensional object identification algorithm applied to
+       convection-allowing forecasts." Weather and Forecasting, vol. 27,
+       1090–1113, doi: 10.1175/WAF-D-11-00147.1
+    .. [FlackCAPE2023] Flack, D.L.A., Lehnert, M., Lean, H.W., and Willington,
+       S. (2023) "Characteristics of Diagnostics for Identifying Elevated
        Convection over the British Isles in a Convection-Allowing Model."
-       Weather and Forecasting, vol. 30, 1079-1094, doi:
-       10.1175/WAF-D-22-0219.1
+       Weather and Forecasting, vol. 30, 1079-1094, doi: 10.1175/WAF-D-22-0219.1
 
     Examples
     --------
@@ -116,15 +118,18 @@ def cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-75.0):
     >>> plt.show()
     """
     # Load in the data into the new arrays.
-    SBCAPE_data = copy.deepcopy(SBCAPE.data)
     MUCAPE_data = copy.deepcopy(MUCAPE.data)
-    # Filter MUCAPE by MUCIN to all for possible (realistic) MUCAPE.
-    MUCAPE_data[MUCIN.data <= MUCIN_thresh] = 0.0
-    # Now calculate the main diagnostic
+    if isinstance(MUCAPE_data, np.ma.MaskedArray):
+        MUCAPE_data = MUCAPE_data.filled(np.nan)
+    # Remove all MUCAPE below MUCIN threshold.
+    MUCAPE_data[MUCIN.data <= MUCIN_thresh] = np.nan
     with warnings.catch_warnings():
         # Ignore possible divide by zero warnings, as they are replaced by NaNs.
-        warnings.simplefilter("ignore", RuntimeWarning)
-        EC_Flagb = 1 - (SBCAPE_data / MUCAPE_data)
+        warnings.filterwarnings("ignore", category=RuntimeWarning)
+        # Now calculate the main diagnostic.
+        EC_Flagb = 1 - (SBCAPE.data / MUCAPE_data)
+        if isinstance(EC_Flagb, np.ma.MaskedArray):
+            EC_Flagb = EC_Flagb.filled(np.nan)
     # Filter to reduce NaN values and -inf values for plotting ease.
     # There are multiple types of NaN values so need to convert them all to same type.
     EC_Flagb[np.isnan(EC_Flagb)] = np.nan
@@ -136,3 +141,112 @@ def cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-75.0):
     cape_ratio_cube.var_name = "cape_ratio"
     cape_ratio_cube.attributes.pop("STASH", None)
     return cape_ratio_cube
+
+
+def inflow_layer_properties(EIB, BLheight, Orography):
+    r"""Filter to create a binary mask identifying elevated convection.
+
+    Parameters
+    ----------
+    EIB: Cube
+        Effective inflow layer base (precalculated or as identified by the
+        model). If using the UM please use STASH ``m01s20i119``.
+    BLheight: Cube
+        Boundary layer height (precalculated or as identified by the model). If
+        using the UM please use STASH ``m01s00i025``.
+    Orography: Cube
+        Model or actual orography, expected to be 2 dimensional. If 3 or 4
+        dimensional cube given converts to 2 dimensions assuming static
+        orography field in ensemble realization and time. If using the UM please
+        use STASH ``m01s00i033``.
+
+    Returns
+    -------
+    Cube
+
+    Notes
+    -----
+    This diagnostic is based on the concept of an effective inflow layer. This
+    concept was first introduced by Thompson et al. (2007) [Thompsonetal2007]_.
+    The inflow layer defined the region of air that is most likely to be
+    ingested into the convective event. It is defined by thresholding the CAPE
+    and CIN values: CAPE > 100 J/kg and \|CIN\| < 250 J/kg.
+
+    To turn this into a diagnostic for elevated convection the inflow layer base
+    is filtered against the boundary layer height. The model orography is added
+    to the boundary layer height to ensure reference height consistency as the
+    BL height is defined above ground level and the inflow layer base is defined
+    above sea level in the model output.
+
+    .. math:: EIB > BLheight + Orography
+
+    This is a binary diagnostic. It has a value of 0 to imply the environment is
+    suitable for surface-based convection. It has a value of 1 to indicate the
+    environment is suitable to produce elevated convection.
+
+    Further details about this diagnostic for elevated convection identification
+    can be found in Flack et al. (2023) [Flackinf2023]_.
+
+    Expected applicability ranges: Convective-scale models will be noisier than
+    parametrized models as they are more responsive to the convection, and thus
+    it may be more sensible to view as a larger spatial average rather than at
+    native resolution.
+
+    Interpretation notes: The effective inflow layer base diagnostic from UM
+    STASH is dependent upon the UM CAPE and CIN diagnostics. These diagnostics
+    are calculated at the end of the timestep. Therefore this diagnostic is
+    applicable after precipitation has occurred, not before as is the usual
+    interpretation of CAPE related diagnostics.
+
+    You might encounter warnings with the following text ``Orography assumed not
+    to vary with time or ensemble member.`` or ``Orography assumed not to vary
+    with time and ensemble member.`` these warnings are expected when the
+    orography files are not 2-dimensional, and do not cause any problems unless
+    ordering is not as expected.
+
+    References
+    ----------
+    .. [Thompsonetal2007] Thompson, R. L. Mead, C. M., and Edwards, R., (2007)
+       "Effective Storm-Relative Helicity and Bulk Shear in Supercell
+       Thunderstorm Environments." Weather and Forecasting, vol. 22, 102-115,
+       doi: 10.1175/WAF969.1
+    .. [Flackinf2023] Flack, D.L.A., Lehnert, M., Lean, H.W., and Willington, S.
+       (2023) "Characteristics of Diagnostics for Identifying Elevated
+       Convection over the British Isles in a Convection-Allowing Model."
+       Weather and Forecasting, vol. 30, 1079-1094, doi: 10.1175/WAF-D-22-0219.1
+
+    Examples
+    --------
+    >>> Inflow_properties=convection.inflow_layer_properties(EIB,BLheight,Orography)
+    >>> iplt.pcolormesh(Inflow_properties[0,:,:],cmap=mpl.cm.Purples)
+    >>> plt.gca().coastlines('10m')
+    >>> plt.colorbar()
+    >>> plt.clim(0,1)
+    >>> plt.show()
+
+    """
+    # Setup new array for output of the diagnostic.
+    EC_Flagd = np.zeros(EIB.shape)
+    # Check dimensions for Orography cube and replace with 2D array if not 2D.
+    if Orography.ndim == 3:
+        try:
+            Orography = Orography.slices_over("realization").next()
+        except iris.exceptions.CoordinateNotFoundError:
+            Orography = Orography.slices_over("time").next()
+        logging.warning("Orography assumed not to vary with time or ensemble member")
+    elif Orography.ndim == 4:
+        Orography = Orography.slices_over(("time", "realization")).next()
+        logging.warning("Orography assumed not to vary with time or ensemble member. ")
+    # Masked arrays are not respected, so convert masked values into NaNs.
+    if isinstance(EIB.data, np.ma.MaskedArray):
+        EIB.data = EIB.data.filled(np.nan)
+    # Change points where Effective inflow layer base is larger than boundary
+    # layer height to 1 implying elevated convection.
+    EC_Flagd[EIB.data > (BLheight.data + Orography.data)] = 1.0
+    # Take the coordinates from an existing cube and replace the data.
+    inflow_properties_cube = EIB.copy()
+    inflow_properties_cube.data = EC_Flagd
+    # Rename and remove STASH code.
+    inflow_properties_cube.var_name = "inflow_layer_properties"
+    inflow_properties_cube.attributes.pop("STASH", None)
+    return inflow_properties_cube

src/CSET/recipes/inflow_layer_properties_plot.yaml

@@ -0,0 +1,38 @@
+title: Inflow layer properties plot
+description: |
+  Extracts data required for, and calculates the Inflow properties diagnostic, plotting on a map.
+
+parallel:
+  - operator: read.read_cubes
+    constraint:
+        operator: constraints.generate_time_constraint
+        time_start: $VALIDITY_TIME
+
+  - operator: convection.inflow_layer_properties
+    EIB:
+        operator: filters.filter_cubes
+        constraint:
+            operator: constraints.generate_stash_constraint
+            stash: m01s20i119
+    BLheight:
+        operator: filters.filter_cubes
+        constraint:
+            operator: constraints.generate_stash_constraint
+            stash: m01s00i025
+    Orography:
+        operator: filters.filter_cubes
+        constraint:
+            operator: constraints.generate_stash_constraint
+            stash: m01s00i033
+
+  - operator: write.write_cube_to_nc
+    filename: intermediate/inflow_layer
+
+collate:
+  - operator: read.read_cube
+    filename: intermediate/*.nc
+
+  - operator: write.write_cube_to_nc
+    overwrite: True
+
+  - operator: plot.postage_stamp_contour_plot

tests/operators/test_convection.py

@@ -15,22 +15,32 @@
 """Tests for convection diagnostics."""
 
 import iris
+import numpy as np
 
 import CSET.operators.convection as convection
 
 
 def test_cape_ratio():
     """Compare with precalculated ratio."""
-    precalculated = iris.load_cube("tests/test_data/convection/ECFlagB.nc")
-    precalculated_2 = iris.load_cube("tests/test_data/convection/ECFlagB_2.nc")
     SBCAPE = iris.load_cube("tests/test_data/convection/SBCAPE.nc")
     MUCAPE = iris.load_cube("tests/test_data/convection/MUCAPE.nc")
     MUCIN = iris.load_cube("tests/test_data/convection/MUCIN.nc")
-    assert (
-        convection.cape_ratio(SBCAPE, MUCAPE, MUCIN).data.all()
-        == precalculated.data.all()
-    )
-    assert (
-        convection.cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-1.5).data.all()
-        == precalculated_2.data.all()
+    cape_75 = convection.cape_ratio(SBCAPE, MUCAPE, MUCIN)
+    precalculated_75 = iris.load_cube("tests/test_data/convection/ECFlagB.nc")
+    assert np.allclose(cape_75.data, precalculated_75.data, atol=1e-5, equal_nan=True)
+
+    cape_1p5 = convection.cape_ratio(SBCAPE, MUCAPE, MUCIN, MUCIN_thresh=-1.5)
+    precalculated_1p5 = iris.load_cube("tests/test_data/convection/ECFlagB_2.nc")
+    assert np.allclose(cape_1p5.data, precalculated_1p5.data, atol=1e-5, equal_nan=True)
+
+
+def test_inflow_layer_properties():
+    """Compare with precalculated properties."""
+    EIB = iris.load_cube("tests/test_data/convection/EIB.nc")
+    BLheight = iris.load_cube("tests/test_data/convection/BLheight.nc")
+    Orography = iris.load_cube("tests/test_data/convection/Orography.nc")
+    inflow_layer_properties = convection.inflow_layer_properties(
+        EIB, BLheight, Orography
     )
+    precalculated = iris.load_cube("tests/test_data/convection/ECFlagD.nc")
+    assert np.allclose(inflow_layer_properties.data, precalculated.data)