A global parametric rain model for landfalling tropical cyclones: a case study for the U.S

Rainfall associated with tropical cyclones (TCs) is a crucial driver of TC hazards, yet estimating TC rain risk from observations is hindered by their relative infrequency. Parametric TC rain models coupled with stochastic TC risk models provide an efficient mean for quantifying such risk. This study introduces a new parametric rain model for landfalling TCs, integrated into the Imperial College Storm Model (IRIS), a statistical-thermodynamic global TC hazard model. Using a 10,000-year simulation, IRIS reproduces observed global return periods of landfall rain rate, storm-total rain volume, and lifetime rain production over land. Over the United States, the model captures observed rainfall climatology and event accumulations with skill comparable to or slightly exceeding existing parametric models. The capability of the model for climate projection is demonstrated through a United States case study using a storyline approach that isolates thermodynamic effects, specifically increases in potential intensity and total column water, under a +2 °C global warming scenario. The pre-landfall maximum azimuthal mean rain rate of United States hurricanes increases by 20.1%, while contraction of the rain field limits the storm-total rain volume increase to 3.9%. Across their lifetimes over land, hurricanes produce 14.6% more rainfall. Spatially, warming enhances rain rates and accumulations across the eastern and southern United States, with the largest absolute increases in the southeast but the strongest relative increases inland and in the northeast, indicating greater inland and poleward penetration of hurricane rainfall under warming.

The online version contains supplementary material available at 10.1007/s11069-026-08150-5.