NatureV1

A probabilistic weather and hurricane-track model that treats satellite imagery as geolocated samples on a sphere, not a rectangle of pixels.

pip install "naturev1[all]"

Why not a ViT or CNN over the image

Three things break when you crop a GOES scene, divide by 255 and hand it to a vision backbone:

1. A GOES pixel is not a fixed size. ABI scans in fixed angular steps from geostationary orbit. Measured off a real scene, the limb pixel covers 64× the ground area of the nadir pixel. A convolution weights them equally and silently over-counts the stretched edge of the disk.
2. An array index is not a place. Nothing in image[400, 1200] says 24.7°N 81.3°W.
3. Normalizing to 0–1 destroys the physics. Channel 13 is a brightness temperature: 180 K is an overshooting top, 300 K is warm ocean. Per-image rescaling erases exactly what was measured.

NatureV1 solves the fixed-grid projection for every pixel's latitude/longitude (validated against the file's own metadata — it recovers 2.07 km at nadir where nominal C13 resolution is 2 km), computes each pixel's true ground footprint and uses it as a quadrature weight, and keeps brightness temperature in kelvin. Satellite and analysis data then fuse without either being resampled onto the other's grid.

Every output is a distribution

Track comes out as weighted scenarios, each a full trajectory with a tilting uncertainty ellipse. Collapsing them to one line scores 116 under the mixture likelihood where keeping both branches scores 8.2 — because the average of "recurves offshore" and "hits the coast" is a track through somewhere the storm was never going. Fields carry per-point variance, landfall a probability per lead time, intensity a Saffir-Simpson category with an interval.

Built for a runtime that dies

Checkpoints go down on a wall-clock interval, written to a temp file and renamed into place, so a killed cell leaves the previous checkpoint intact. Resume restores optimizer moments, LR schedule, scaler and RNG state — not just weights.

Not trained

No weights here have seen real data. The architecture, losses, ingest and training loop are complete and exercised end to end on real GOES-19 imagery, but nothing here should inform a decision about a real storm. The National Hurricane Center is the authoritative source for tropical cyclone forecasts.

Made by Nathan.