Wind-driven coastal hazard — sustained wind above 50 km/h, with the rain it carries.
The classifier reads the same drivers; the coastal districts concentrate the high scores because the drivers there are genuinely stronger, not because a coastal prior is applied.
Uncalibrated softmax, as above. A high confidence in Tropical Cyclone means the drivers resemble that class, not that a cyclone has been detected.
Nothing above the WATCH level can be published automatically while no calibration map exists, and nothing at all can be published while the pipeline stamps no model version — the alert engine records that as `publication_blocked` rather than issuing the alert.
The 50 km/h floor means a calm week scores zero on the wind term regardless of rainfall.
Drivers: maximum sustained wind in the horizon (W, km/h) · precipitation accumulated over the horizon (P_total).
clip(x) clamps a term to [0, 1] — max(0, min(1, x)) — which is how every formula in the pipeline bounds its terms. Each term is clipped before it is weighted, so no single driver can run away with a score.
In the run this deployment ships (prediction date 2026-09-16), 3 district-horizon units are classified as Tropical Cyclone: 3 at 7 days.
Highest model severity: Barguna (0.95, 7 days), Satkhira (0.93, 7 days), Bagerhat (0.85, 7 days).
These are classifications from the current run, not a forecast of impact. The model version behind them is not stamped yet, and PRODUCT_SPEC §1.6 keeps publication closed above the WATCH level until one exists.
Typical season: April–May and October–November; the post-monsoon window is the more destructive. This describes when the hazard is climatologically plausible, not when this run flags it.
Ground-truth reports (district, hazard, horizon, date, what was observed) are the only route by which this project can publish skill metrics. The contact page reaches the maintainers.
No. The severity index is the model's continuous score for how strongly the drivers resemble this class, on a 0.00–1.00 scale. It is not a probability, not a percentage, and it does not model exposure. The physics cross-check is a second, independent estimate; where the two diverge, both numbers are shown rather than averaged.
The published confidence is the model's own softmax over its eight classes, labelled uncalibrated_model_softmax in the data. It says how certain the classifier is about the class it picked, not how often that class actually materialises. No calibration map has been fitted yet, which is also why nothing above the WATCH level can be published automatically.
The district pages cover all 64 districts. This page summarises the districts the current run covers — a run can be partial, and the coverage stamp on the snapshot says exactly how partial, which the status page reports.
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