StormFusion-MT & TrackFormer — tropical-cyclone forecasting
Two research checkpoints for tropical-cyclone forecasting. Each predicts, at 20 six-hourly lead times (6–120 h), a 17-dim state per lead: east/north storm motion (km), max wind (kt), central pressure (hPa), radius of max wind (km), and 34/50/64-kt wind radii in four quadrants.
Research models — not an operational warning system. Do not use for evacuation, aviation, maritime, or emergency decisions.
| model | params | inputs | training data |
|---|---|---|---|
| TrackFormer v9 | 17M (fp16, 33MB) | track history + IBTrACS environment, protected triple-stream | all basins, 1980+, 193k partial-lead windows |
| TrackFormer v8 | 15M (fp16, 30MB) | track history only, protected dual-stream | all basins, 1980+, 193k partial-lead windows |
| StormFusion-MT v2 | 3.3M (fp16, 6.7MB) | ERA5 patches + track history | WP, 2000+, 1,337 storm-centered windows |
| TrackFormer (v1) | 21M (fp16, 43MB) | track history only (single-stream) | all basins, 1980+, 84,150 windows |
Weights and full reproducible code (dataset builders, training, eval) are in the GitHub repo:
https://github.com/yu314-coder/typhoon-predict (models/).
Results — WP 2020+ held-out test (lower is better)
| model | track km | vmax kt | pres hPa | rmw km | radius km |
|---|---|---|---|---|---|
| StormFusion-MT v2 (3.3M, ERA5) | 729 | 24.2 | 21.6 | 16.2 | 31.8 |
| TrackFormer v1 (21M, single-stream) | 720 | 22.1 | 21.2 | 11.8 | 31.5 |
| TrackFormer v3 (15M, dual-stream) | 659 | 21.6 | 18.1 | 11.8 | 28.8 |
| TrackFormer v8 (15M, +partial-lead data) | 649 | 20.7 | 15.9 | 11.3 | 27.8 |
| TrackFormer v9 (17M, +IBTrACS environment) | 618 | 18.6 | 15.8 | 11.5 | 27.2 |
Key findings. (1) A track-only model that never sees ERA5 matches or beats the full ERA5
model, so data diversity > engineered features > parameters (a 17.7M ERA5 model overfit and did
worse than the 3.3M one). (2) Naively adding motion-dynamics features to a single-stream model
improves intensity but hurts track through negative transfer; TrackFormer v3 fixes this with a
protected dual-stream architecture (separate kinematic/thermodynamic encoders, gradient routing, a
zero-init gated thermo→track adapter, and a persistence-residual track head), cutting WP-2020+ track
error to 659 km (−61, storm-bootstrap 95% CI [−103, −16] km, p≈0.995) while keeping the intensity
gains. Full architecture and derivation (incl. a random-matrix block-covariance uncertainty head) in
paper/trackformer.pdf in the GitHub repo.
Architectures
- StormFusion-MT v2 — separate inner/outer ERA5 conv encoders keeping a 3×3 grid of spatial tokens, track/environment token encoders, a temporal Transformer context, learned + sinusoidal lead-time queries, cross-attention decoding, and multi-task state / log-scale heads.
- TrackFormer — the same decoder design, track-only: a 40-dim track-history projection → Transformer context (d_model 384, 8 heads, 4+6 layers) → lead queries → dual heads. No atmospheric inputs.
Usage
See the GitHub repo for model_v2.py / train_track.py, the checkpoints, and normalization
stats. Inputs are per-feature standardized (stats saved with each checkpoint / dataset);
multiply predictions by TARGET_SCALE = [100,100,35,20,50] + [50]*12 for physical units.
Data
IBTrACS v04r01 best tracks (NOAA NCEI) and ERA5 reanalysis (Copernicus/ECMWF). Obtain the source data under its own access and licensing terms.
Limitations
- Absolute track error (~720 km averaged over 6–120 h) is far from operational quality.
- The real ceiling is storm diversity (~13k storms have ever existed); larger models overfit.
- Wind-radius labels are sparse; no calibration or comparison against official agency forecasts.
- Pre-satellite track/intensity labels are lower quality.