Tropical Cyclone Wind Hazard Assessment and Modeling

Tropical cyclones rank among the most destructive natural hazards, generating extreme wind speeds that threaten lives, infrastructure and ecosystems across coastal regions worldwide. Assessment and modelling of wind hazards associated with these storms combine historical observations, statistical analyses and physical simulations to quantify the probability and severity of high‐wind events. Core approaches include the development of synthetic tropical cyclone catalogues to extend the record of storm occurrences well beyond available measurements, parametric wind field models to represent the spatial structure of cyclone winds, and boundary layer downscaling to translate gradient‐level winds to surface intensities. Statistical–parametric frameworks integrate stochastic sampling of genesis, track and intensity parameters with parametric wind profiles, enabling return period estimation of design wind speeds for engineering and insurance applications. Recent advances focus on refining parametric profiles to account for terrain and surface roughness, improving physical realism through limited dynamical modelling, and incorporating uncertainties via ensemble and probabilistic methods. Such tools support risk mapping, infrastructure resilience planning and real‐time hazard forecasting, with global and regional implementations now informing building codes and emergency management across multiple ocean basins.

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Tropical Cyclone Wind Hazard Assessment and Modeling publication trend

The graph below shows the total number of articles in tropical cyclone wind hazard assessment and modeling across all publications each year (not limited to Nature Index journals).

Technical terms

Synthetic tropical cyclone dataset: A catalogue of virtual storm tracks and intensities generated by statistical or physical models to extend the historical record for risk estimation.

Parametric wind field model: A mathematical description of the spatial distribution of cyclone winds based on radial profiles and empirical or semi‐empirical parameters.

Return period: The average interval between exceedances of a specified wind speed at a given location, used to inform design standards.

Boundary layer model: A representation of the vertical wind‐speed reduction from the gradient level to the surface, accounting for friction and turbulence.

Ensemble forecast: A set of simulations representing uncertainty in meteorological forcing or model parameters, used to produce probabilistic hazard estimates.

References

1. The Imperial College Storm Model (IRIS) Dataset. Scientific Data (2024).
2. Accounting for uncertainties in forecasting tropical-cyclone-induced compound flooding. Geoscientific Model Development (2024).
3. Knowledge-enhanced deep learning for simulation of tropical cyclone boundary-layer winds. Journal of Wind Engineering and Industrial Aerodynamics (2019).
4. Mapping the Wind Hazard of Global Tropical Cyclones with Parametric Wind Field Models by Considering the Effects of Local Factors. International Journal of Disaster Risk Science (2018).
5. A statistical–parametric model of tropical cyclones for hazard assessment. Natural Hazards and Earth System Science (2021).
6. Simulating synthetic tropical cyclone tracks for statistically reliable wind and pressure estimations. Natural Hazards and Earth System Science (2021).