geospatial_gradient#

metpy.calc.geospatial_gradient(f, *, dx=None, dy=None, x_dim=-1, y_dim=-2, parallel_scale=None, meridional_scale=None, return_only=None, latitude=None, longitude=None, crs=None)#

Calculate the projection-correct gradient of a 2D scalar field.

Parameters:

  • f ((…, M, N) xarray.DataArray or pint.Quantity) – scalar field for which the horizontal gradient should be calculated

  • return_only (str or Sequence[str], optional) – Sequence of which components of the gradient to compute and return. If none, returns the gradient tuple (‘df/dx’, ‘df/dy’). Otherwise, matches the return pattern of the given strings. Only valid strings are ‘df/dx’, ‘df/dy’.

  • dx (pint.Quantity, optional) – The grid spacing(s) in the x-direction. If an array, there should be one item less than the size of u along the applicable axis. Optional if xarray.DataArray with latitude/longitude coordinates used as input. Also optional if one-dimensional longitude and latitude arguments are given for your data on a non-projected grid. Keyword-only argument.

  • dy (pint.Quantity, optional) – The grid spacing(s) in the y-direction. If an array, there should be one item less than the size of u along the applicable axis. Optional if xarray.DataArray with latitude/longitude coordinates used as input. Also optional if one-dimensional longitude and latitude arguments are given for your data on a non-projected grid. Keyword-only argument.

  • x_dim (int, optional) – Axis number of x dimension. Defaults to -1 (implying […, Y, X] order). Automatically parsed from input if using xarray.DataArray. Keyword-only argument.

  • y_dim (int, optional) – Axis number of y dimension. Defaults to -2 (implying […, Y, X] order). Automatically parsed from input if using xarray.DataArray. Keyword-only argument.

  • parallel_scale (pint.Quantity, optional) – Parallel scale of map projection at data coordinate. Optional if xarray.DataArray with latitude/longitude coordinates and MetPy CRS used as input. Also optional if longitude, latitude, and crs are given. If otherwise omitted, calculation will be carried out on a Cartesian, rather than geospatial, grid. Keyword-only argument.

  • meridional_scale (pint.Quantity, optional) – Meridional scale of map projection at data coordinate. Optional if xarray.DataArray with latitude/longitude coordinates and MetPy CRS used as input. Also optional if longitude, latitude, and crs are given. If otherwise omitted, calculation will be carried out on a Cartesian, rather than geospatial, grid. Keyword-only argument.

  • latitude (pint.Quantity, optional) – Latitude of data. Optional if xarray.DataArray with latitude/longitude coordinates used as input. Also optional if parallel_scale and meridional_scale are given. If otherwise omitted, calculation will be carried out on a Cartesian, rather than geospatial, grid. Keyword-only argument.

  • longitude (pint.Quantity, optional) – Longitude of data. Optional if xarray.DataArray with latitude/longitude coordinates used as input. Also optional if parallel_scale and meridional_scale are given. If otherwise omitted, calculation will be carried out on a Cartesian, rather than geospatial, grid. Keyword-only argument.

  • crs (pyproj.crs.CRS, optional) – Coordinate Reference System of data. Optional if xarray.DataArray with MetPy CRS used as input. Also optional if parallel_scale and meridional_scale are given. If otherwise omitted, calculation will be carried out on a Cartesian, rather than geospatial, grid. Keyword-only argument.

Returns:

pint.Quantity, tuple of pint.Quantity, or tuple of pairs of pint.Quantity – Component(s) of vector derivative

See also

vector_derivative, gradient, geospatial_laplacian