| """Init-source plumbing for GraphCast. |
| |
| CRE's pipeline calls ``fetch_era5_for_graphcast(init_date)`` in |
| ``src/prediction/graphcast_inference.py`` with ``init_date = today - 5`` |
| to work around ARCO ERA5T's publication lag. That lag means the "5-day |
| forecast" actually covers ``today-5`` through ``today-1`` — retroactive, |
| not forward-looking. Alert SMS to workers can't warn before a heat event |
| when the forecast is already in the past. |
| |
| This package provides an alternative: GFS (NOAA Global Forecast System) |
| analysis at ~3h lag. A GFS-sourced ``xarray.Dataset`` is shape-compatible |
| with the ERA5 Zarr ``full_ds`` used inside ``fetch_era5_for_graphcast``, |
| so the integration in Phase 2 is a one-line source swap behind a config |
| toggle. |
| |
| Phase 1 status: this package is reachable only from tests. Nothing in the |
| production pipeline imports it. Wiring is deferred to Phase 2 so we can |
| validate the module in isolation before deploying. |
| |
| Public entry point: |
| fetch_gfs_as_era5(target_date: str) -> xarray.Dataset |
| |
| Sister module in Weather AI 2 (``~/weather AI 2/src/init_sources/``) is the |
| canonical copy; this CRE copy is identical code and keeps pace via manual |
| sync. If/when init_sources grows a third user, extract to a shared pip- |
| installable package. |
| """ |
|
|
| from __future__ import annotations |
|
|
| from src.init_sources.gfs import fetch_gfs_as_era5 |
|
|
