wrf.cape_2d

wrf.cape_2d(pres_hpa, tkel, qv, height, terrain, psfc_hpa, ter_follow, missingval=9.969209968386869e+36, meta=True)

Return the two-dimensional CAPE, CIN, LCL, and LFC.

This function calculates the maximum convective available potential energy (CAPE), maximum convective inhibition (CIN), lifted condensation level (LCL), and level of free convection (LFC). This function uses the RIP [Read/Interpolate/plot] code to calculate potential energy (CAPE) and convective inhibition (CIN) [J kg-1] only for the parcel with max theta-e in the column (i.e. something akin to Colman’s MCAPE). CAPE is defined as the accumulated buoyant energy from the level of free convection (LFC) to the equilibrium level (EL). CIN is defined as the accumulated negative buoyant energy from the parcel starting point to the LFC. The word ‘parcel’ here refers to a 500 meter deep parcel, with actual temperature and moisture averaged over that depth.

The leftmost dimension of the returned array represents four different quantities:

  • return_val[0,...] will contain CAPE [J kg-1]
  • return_val[1,...] will contain CIN [J kg-1]
  • return_val[2,...] will contain LCL [m]
  • return_val[3,...] will contain LFC [m]

This is the raw computational algorithm and does not extract any variables from WRF output files. Use wrf.getvar() to both extract and compute diagnostic variables.

Parameters:
  • pres_hpa (xarray.DataArray or numpy.ndarray) –

    Full pressure (perturbation + base state pressure) in [hPa] with at least three dimensions. The rightmost dimensions can be top_bottom x south_north x west_east or bottom_top x south_north x west_east.

    Note

    The units for pres_hpa are [hPa].

    Note

    This variable must be supplied as a xarray.DataArray in order to copy the dimension names to the output. Otherwise, default names will be used.

  • tkel (xarray.DataArray or numpy.ndarray) – Temperature in [K] with same dimensionality as pres_hpa.
  • qv (xarray.DataArray or numpy.ndarray) – Water vapor mixing ratio in [kg/kg] with the same dimensionality as pres_hpa.
  • height (xarray.DataArray or numpy.ndarray) – Geopotential height in [m] with the same dimensionality as pres_hpa.
  • terrain (xarray.DataArray or numpy.ndarray) – Terrain height in [m]. This is at least a two-dimensional array with the same dimensionality as pres_hpa, excluding the vertical (bottom_top/top_bottom) dimension.
  • psfc_hpa (xarray.DataArray or numpy.ndarray) –

    The surface pressure in [hPa]. This is at least a two-dimensional array with the same dimensionality as pres_hpa, excluding the vertical (bottom_top/top_bottom) dimension.

    Note

    The units for psfc_hpa are [hPa].

  • ter_follow (bool) – A boolean that should be set to True if the data uses terrain following coordinates (WRF data). Set to False for pressure level data.
  • missingval (float, optional) – The fill value to use for the output. Default is wrf.Constants.DEFAULT_FILL.
  • meta (bool) – Set to False to disable metadata and return numpy.ndarray instead of xarray.DataArray. Default is True.

Warning

The input arrays must not contain any missing/fill values or numpy.nan values.

Returns:The cape, cin, lcl, and lfc values as an array whose leftmost dimension is 4 (0=CAPE, 1=CIN, 2=LCL, 3=LFC) . If xarray is enabled and the meta parameter is True, then the result will be an xarray.DataArray object. Otherwise, the result will be a numpy.ndarray object with no metadata.
Return type:xarray.DataArray or numpy.ndarray

See also

wrf.getvar(), wrf.cape_3d()