backend/drift_check.py quantifies the migration's data impact by fetching both
live history sources (NASA POWER primary + the Open-Meteo/ERA5 fallback) for a
sample of cells and reporting, per variable: mean-absolute-difference / bias / max
(raw drift) and grade-band divergence (the share of days whose graded band actually
changes). Since Open-Meteo is ERA5, this doubles as a fidelity check for the ERA5
seed.
Because grades are percentiles within each source's own distribution, a uniform
bias moves MAD but not grades — so the two numbers are read together. Open-Meteo is
kept as a dormant fallback (not deleted), so both sources stay fetchable for this
comparison. The comparison logic is unit-tested; the per-cell fetch runs on a
networked box (python drift_check.py [--limit N] [--days N]).
