metadata¶

Manage GRIB metadata.

Functions

`compute_origin`(ref_grid, field)	Compute horizontal components of the origin dict.
`extract`(metadata)
`extract_hcoords`(metadata)	Extract horizontal coordinates.
`extract_pv`(metadata)	Extract hybrid level coefficients.
`is_staggered_horizontal`(field)	Determine if the field is on a staggered horizontal grid.
`load_grid_reference`(metadata)	Construct a grid from a reference parameter.
`override`(metadata, **kwargs)	Override GRIB metadata.
`set_origin_xy`(ds, ref_param)	Set horizontal components of the origin attribute.

Classes

Grid(lon_first_grid_point, lat_first_grid_point)

Coordinates of the reference grid.

class meteodatalab.metadata.Grid(lon_first_grid_point: float, lat_first_grid_point: float)[source]¶

Coordinates of the reference grid.

lon_first_grid_point¶

longitude of first grid point in rotated lat-lon CRS

Type:: float

lat_first_grid_point¶

latitude of first grid point in rotated lat-lon CRS

Type:: float

meteodatalab.metadata.compute_origin(ref_grid: Grid, field: DataArray) → dict[str, float][source]¶

Compute horizontal components of the origin dict.

Parameters:

ref_grid (Grid) – reference grid
field (xarray.DataArray) – field for which to compute the origin

Returns:

Horizontal components of the origin

Return type:

dict[str, float]

meteodatalab.metadata.extract_hcoords(metadata: Metadata) → dict[str, DataArray][source]¶

Extract horizontal coordinates.

Parameters:: metadata (Metadata) – GRIB metadata containing the grid definition.
Returns:: Horizontal coordinates in geolatlon.
Return type:: dict[str, xarray.DataArray]

meteodatalab.metadata.extract_pv(metadata: Metadata) → dict[str, DataArray][source]¶

Extract hybrid level coefficients.

Parameters:: metadata (Metadata) – GRIB metadata containing the pv metadata.
Returns:: Hybrid level coefficients.
Return type:: dict[str, xarray.DataArray]

meteodatalab.metadata.is_staggered_horizontal(field: DataArray) → bool[source]¶

Determine if the field is on a staggered horizontal grid.

Parameters:: field (xr.DataArray) – Field containing the grid definition.
Raises:: ValueError – if the field is a on regular grid without origin_x and origin_y set.
Returns:: True if the field is on a staggered horizontal grid.
Return type:: bool

meteodatalab.metadata.load_grid_reference(metadata: Metadata) → Grid[source]¶

Construct a grid from a reference parameter.

Parameters:: metadata (Metadata) – GRIB metadata defining the reference grid.
Returns:: reference grid
Return type:: Grid

meteodatalab.metadata.override(metadata: Metadata, **kwargs: Any) → dict[str, Any][source]¶

Override GRIB metadata.

Note that no special consideration is made for maintaining consistency when overriding template definition keys such as productDefinitionTemplateNumber. Note that the origin components in x and y are left untouched.

Parameters:

metadata (Metadata) – Metadata of the input GRIB metadata
kwargs (Any) – Keyword arguments forwarded to earthkit-data GribMetadata override method

Returns:

Updated metadata along with the geography and parameter namespaces

Return type:

dict[str, Any]

meteodatalab.metadata.set_origin_xy(ds: dict[str, DataArray], ref_param: str) → None[source]¶

Set horizontal components of the origin attribute.

Parameters:

ds (dict[str, xarray.DataArray]) – Dataset of fields to update.
ref_param (str) – Name of the parameter field to use as a reference. Must be a key of ds.

Raises:

KeyError – if the ref_param key is not found in the input dataset