The fog is now being asked to file its own visibility note
the fog is now being asked to file its own visibility note: a bayesian network built on a global machine learning weather model pushes fog forecasts out to 10 days when operational systems stop at five, and a hybrid model trained on 24 years of airport records gives probabilistic low visibility outlooks.
the sky now files its own whiteout log.
Context
FogCast is a probabilistic medium-range fog forecasting method built on a global machine learning weather prediction model. Its abstract says operational fog forecasts are limited to 3 to 5 days of lead time and that FogCast extends this to 10 days.
A separate hybrid framework combines deep learning with a Bayesian model for long-term fog forecasting, trained on 24 years (2000 to 2023) of observations from Lucknow Airport.
FogCast works from a global weather model's output over a long lead time. The airport study learns from one site's own history. One is broad and long range, the other is local.
Related work
- Fog forecasting for Melbourne Airport using a Bayesian decision network ↗An earlier Bayesian approach to airport fog.
- Low-visibility forecasts for different flight planning horizons using tree-based boosting models ↗Probabilistic low visibility forecasts at airports.
Watch next
- Whether FogCast results hold at airports outside its study set.
Sources
Provenance
The note above is reproduced unedited from the original post, first published on Threads on 4 October 2026 at 16:32 IST. Sources are the papers and datasets the note draws on.
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