Input datasets
datasets.input
datasets.input
This module exposes the input datasets for OceanBench challengers to produce forecast datasets to evaluate in the benchmark.
Functions
| Name | Description |
|---|---|
| glo12_nowcasts | Open weekly GLO12 nowcasts from 2023 to 2025. |
| ifs_forcings | Open weekly IFS forcings from 2023 to 2025. |
glo12_nowcasts
datasets.input.glo12_nowcasts()Open weekly GLO12 nowcasts from 2023 to 2025.
Returns
| Name | Type | Description |
|---|---|---|
| Dataset | The Dataset containing GLO12 nowcasts. |
Examples
>>> glo12_nowcasts()
<xarray.Dataset> Size: 8TB
Dimensions: (time: 1099, latitude: 2041, longitude: 4320, depth: 50)
Coordinates:
* latitude (latitude) float32 8kB -80.0 -79.92 -79.83 ... 89.83 89.92 90.0
* longitude (longitude) float32 17kB -180.0 -179.9 -179.8 ... 179.8 179.9
* time (time) datetime64[ns] 9kB 2022-12-28T12:00:00 ... 2025-12-30T1...
* depth (depth) float32 200B 0.494 1.541 2.646 ... 5.275e+03 5.728e+03
Data variables:
siconc (time, latitude, longitude) float32 39GB dask.array<chunksize=(1, 640, 1280), meta=np.ndarray>
sithick (time, latitude, longitude) float32 39GB dask.array<chunksize=(1, 640, 1280), meta=np.ndarray>
so (time, depth, latitude, longitude) float32 2TB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
thetao (time, depth, latitude, longitude) float32 2TB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
uo (time, depth, latitude, longitude) float32 2TB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
usi (time, latitude, longitude) float32 39GB dask.array<chunksize=(1, 640, 1280), meta=np.ndarray>
vo (time, depth, latitude, longitude) float32 2TB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
vsi (time, latitude, longitude) float32 39GB dask.array<chunksize=(1, 640, 1280), meta=np.ndarray>
zos (time, latitude, longitude) float32 39GB dask.array<chunksize=(1, 640, 1280), meta=np.ndarray>ifs_forcings
datasets.input.ifs_forcings()Open weekly IFS forcings from 2023 to 2025.
Returns
| Name | Type | Description |
|---|---|---|
| Dataset | The Dataset containing IFS forcings. |
Examples
>>> ifs_forcings()
<xarray.Dataset> Size: 1TB
Dimensions: (first_day_datetime: 157, lead_day_index: 10,
lat: 2560, lon: 5120)
Coordinates:
* first_day_datetime (first_day_datetime) datetime64[ns] 1kB 2023-01-03 .....
* lat (lat) float64 20kB 89.95 89.88 89.81 ... -89.88 -89.95
* lead_day_index (lead_day_index) int64 80B 0 1 2 3 4 5 6 7 8 9
* lon (lon) float64 41kB 0.0 0.07031 0.1406 ... 359.9 359.9
Data variables: (12/17)
cp (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
ewss (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
nsss (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
skt (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
sohumspe (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
somslpre (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
... ...
sowaprec (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
sowinu10 (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
sowinv10 (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
sp (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
ssr (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>
strd (first_day_datetime, lead_day_index, lat, lon) float32 82GB dask.array<chunksize=(1, 1, 640, 1280), meta=np.ndarray>