Evaluating impact-based forecasting models for tropical cyclone anticipatory action
The article compares two contrasting Impact-based Forecasting models used for tropical-cyclone Anticipatory Action (Philippines/Bangladesh): a machine-learning model and an elementary damage-curve model, using a model-card framework and Typhoon Kammuri (2019) as a case study. An interactive portal shows how lead time, trigger thresholds, and uncertainty buffers shape decisions. It supports transparent, interpretable triggers tailored to local data and operations.
Type de ressource
PDF, 11.40 Mo
Année
2025
Pays
Bangladesh, Philippines
Type de contenu
Documents académiques
Risques
Cyclone / ouragan / tempête tropicale / typhon
Conflit armé
Inondation