Impact-based forecasting of tropical cyclone-related human displacement to support anticipatory action

Tropical cyclones (TCs) cause millions of displacements annually. This paper introduces an open-source, globally consistent, and regionally calibrated TC displacement forecast model. The model combines meteorological forecasts with population exposure and vulnerability data, providing richer information for anticipatory actions. A case study on TC Yasa in Fiji demonstrates the model's ability to forecast displacement, highlighting the importance of considering uncertainties in hazard, exposure, and vulnerability. Sensitivity analysis reveals that meteorological uncertainty is crucial for longer lead times, while vulnerability becomes more important closer to landfall. The open-source nature facilitates transferability to other hazards and impact types.

Pui Man Kam, Fabio Ciccone, Chahan M. Kropf, Lukas Riedel, Christopher Fairless, David N. Bresch