Predicting Rapid Intensification in North Atlantic and Eastern North Pacific Tropical Cyclones Using a Convolutional Neural Network

Sarah M. Griffin, Anthony Wimmers, Christopher S. Velden

Weather and Forecasting 2022 article cited by 33

importance 8/10 partially solved Tropical and Extratropical Cyclones Research meteorology stage: research

Problem

Predicting rapid intensification of tropical cyclones in the North Atlantic and eastern North Pacific, where storms suddenly strengthen faster than traditional guidance anticipates.

Why it matters

Rapid intensification forecasts are critical for timely coastal evacuations and saving lives.

What the AI did

A convolutional neural network ('I-RI') learns from satellite imagery spatial fields and scalar features to output rapid-intensification probabilities at 12-72 hour lead times.

Results

In North Atlantic, more skillful than both operational RI guidances at 12- and 24-h lead times; in eastern North Pacific, more skillful than empirical guidance at most thresholds but less skillful than deterministic guidance at all thresholds

Impact

Evidence supports a model that beats some operational baselines at short lead times, with mixed results across basins.

Record

Venue	Weather and Forecasting
Published	2022
Work type	article
Authors	Sarah M. Griffin, Anthony Wimmers, Christopher S. Velden
Citations	33 (OpenAlex, at import time)
References	43
Model or method	Convolutional neural network (I-RI / AI-RI)
Organization	not stated in source
Primary source	https://doi.org/10.1175/waf-d-21-0194.1
Open access	closed
Keywords	CNN, rapid intensification, tropical cyclones, satellite imagery, probabilistic forecasting

Importance rating

8 / 10

major — millions of lives, an industry or a field

Rapid intensification of tropical cyclones affects millions in coastal regions; model beats some operational baselines at short lead times, mixed across basins.

Basis: inferred. Judged from the source text, which gives no explicit scale. Stated scale: not stated in source. Method and limits.

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