add UKV

src/nwp_consumer/internal/entities/coordinates.py

@@ -98,6 +98,10 @@ class NWPDimensionCoordinateMap:
     longitude: list[float] | None = None
     """The longitude coordinates of the forecast grid in degrees. """
 
+    x: list[float] | None = None
+    y: list[float] | None = None
+    # These are the x and y osgb that the UKV model uses. They are not used in the other models
+
     def __post_init__(self) -> None:
         """Rigidly set input value ordering and precision."""
         self.variable = sorted(self.variable)

src/nwp_consumer/internal/entities/modelmetadata.py

@@ -297,3 +297,30 @@ class Models:
     )
     """MetOffice's Unified Model, in the Global configuration, at a resolution of 10km."""
 
+    MO_UKV_2KM: ModelMetadata = ModelMetadata(
+        name="ukv-uk",
+        resolution="2km",
+        expected_coordinates=NWPDimensionCoordinateMap(
+            init_time=[],
+            step=list(range(0, 55)),
+            variable=sorted(
+                [
+                    Parameter.CLOUD_COVER_TOTAL,
+                    Parameter.CLOUD_COVER_HIGH,
+                    Parameter.CLOUD_COVER_MEDIUM,
+                    Parameter.CLOUD_COVER_LOW,
+                    Parameter.VISIBILITY_SL,
+                    Parameter.RELATIVE_HUMIDITY_SL,
+                    Parameter.SNOW_DEPTH_GL,
+                    Parameter.DOWNWARD_SHORTWAVE_RADIATION_FLUX_GL,
+                    Parameter.TEMPERATURE_SL,
+                    Parameter.WIND_U_COMPONENT_10m,
+                    Parameter.WIND_V_COMPONENT_10m,
+                ],
+            ),
+            x=[0, 7e5],
+            y=[0, 1.2e6],
+        ),
+    )
+    """MetOffice's UKV Mode, at a resolution of approximate 2km."""
+

src/nwp_consumer/internal/repositories/raw_repositories/mo_datahub.py

@@ -77,7 +77,7 @@ def repository() -> entities.RawRepositoryMetadata:
             name="MetOffice-Weather-Datahub",
             is_archive=False,
             is_order_based=True,
-            running_hours=[0, 12],
+            running_hours=[0, 12], # for UKV, we need to change this to every hour.
             delay_minutes=60,
             max_connections=10,
             required_env=["METOFFICE_API_KEY", "METOFFICE_ORDER_ID"],
@@ -86,6 +86,7 @@ def repository() -> entities.RawRepositoryMetadata:
             available_models={
                 "default": entities.Models.MO_UM_GLOBAL_10KM,
                 "um-global-10km": entities.Models.MO_UM_GLOBAL_10KM,
+                "ukv-uk-2km": entities.Models.MO_UKV_2KM,
             },
         )
 
@@ -286,10 +287,13 @@ def _convert(path: pathlib.Path) -> ResultE[list[xr.DataArray]]:
                     allowed_parameters=MetOfficeDatahubRawRepository.model().expected_coordinates.variable,
                 )
                 .rename(name_dict={"time": "init_time"})
-                .expand_dims(dim="init_time")
-                .expand_dims(dim="step")
-                .to_dataarray(name=MetOfficeDatahubRawRepository.model().name)
-            )
+                .expand_dims(dim="init_time"))
+
+            if "step" not in ds.dims:
+                da = da.expand_dims(dim="step")
+
+            da = da.to_dataarray(name=MetOfficeDatahubRawRepository.model().name)
+
             da = (
                 da.drop_vars(
                     names=[
@@ -299,10 +303,14 @@ def _convert(path: pathlib.Path) -> ResultE[list[xr.DataArray]]:
                     ],
                     errors="ignore",
                 )
-                .transpose(*MetOfficeDatahubRawRepository.model().expected_coordinates.dims)
-                .sortby(variables=["step", "variable", "longitude"])
-                .sortby(variables="latitude", ascending=False)
-            )
+                .transpose(*MetOfficeDatahubRawRepository.model().expected_coordinates.dims))
+
+            if "latitude" in MetOfficeDatahubRawRepository.model().expected_coordinates.dims:
+                da = da.sortby(variables=["step", "variable", "longitude"])
+                da = da.sortby(variables="latitude", ascending=False)
+            else:
+                da = da.sortby(variables=["step", "variable"])
+
         except Exception as e:
             return Failure(
                 ValueError(