Gezahegn Teklesadik; Marc van den Homberg; et al. (2024) Academic journal article

Towards a global impact-based forecasting model for tropical cyclones

Natural Hazards and Earth System Sciences (Copernicus)

Ref: SRC-004-PHL-001

https://nhess.copernicus.org/articles/24/309/2024/

Accessed: 10/31/2025

Summary

Peer-reviewed academic paper by the 510 model development team describing the XGBoost-based typhoon impact model and its extension towards global applicability. Provides technical details on the machine learning approach using ECMWF ensemble tracks, winds, and rainfall with exposure/vulnerability inputs to predict housing damage at the municipality level.

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Teklesadik, G., van den Homberg, M. et al. (2024) 'Towards a global impact-based forecasting model for tropical cyclones', Natural Hazards and Earth System Sciences, 24, pp. 309-ff. Available at: https://nhess.copernicus.org/articles/24/309/2024/ (Accessed: 31 October 2025).

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PHL-001 PHL Pilot / Controlled Trial Phase

AI-Enabled Typhoon Impact Forecasting for Anticipatory Action (Philippines, OCHA/CERF)

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