Open danangmassandy opened 1 month ago
Proposed dimensions for zarr structure:
Dimensions: (forecast_date: 1, forecast_day_idx: 91, lat: 67, lon: 54, ensemble: 50)
Coordinates:
* forecast_date (forecast_date) datetime64[ns] 2024-08-01
* forecast_day_idx (forecast_day_idx) int64 728B 0 1 2 3 4 ... 86 87 88 89 90
* lat (lat) float64 ...
* lon (lon) float64 ...
Dimensions without coordinates: ensemble
Data variables: (12/19)
rh_clim (forecast_date, forecast_day_idx, lat, lon) float32 5MB ...
tmax_clim (forecast_date, forecast_day_idx, lat, lon) float32 5MB ...
tsi_clim (forecast_date, forecast_day_idx, lat, lon) float32 5MB ...
wspd_clim (forecast_date, forecast_day_idx, lat, lon) float32 5MB ...
temp_clim (forecast_date, forecast_day_idx, lat, lon) float32 5MB ...
precip_clim (forecast_date, forecast_day_idx, lat, lon) float32 5MB ...
... ...
rh (forecast_date, ensemble, forecast_day_idx, lat, lon) float32 265MB ...
tmax (forecast_date, ensemble, forecast_day_idx, lat, lon) float32 265MB ...
tsi (forecast_date, ensemble, forecast_day_idx, lat, lon) float32 265MB ...
wspd (forecast_date, ensemble, forecast_day_idx, lat, lon) float32 265MB ...
precip (forecast_date, ensemble, forecast_day_idx, lat, lon) float32 265MB ...
tmin (forecast_date, ensemble, forecast_day_idx, lat, lon) float32 265MB ...
When there is a new forecast data, the forecast_date will be expanded. Forecast_day_idx is days from the forecast_date, the values would be 91 days which today's forecast + next 3 months forecast data.