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

Area of Science:

• Atmospheric Science
• Climate Science
• Meteorology

Background:

• Tropical cyclone (TC) rainfall is a major hazard, but its risk is hard to estimate due to infrequent events.
• Parametric TC rain models and stochastic risk models are essential for quantifying TC rain risk.

Purpose of the Study:

• Introduce a novel parametric rain model for landfalling TCs within the Imperial College Storm Model (IRIS).
• Quantify global TC rain risk and assess climate change impacts on hurricane rainfall in the United States.

Main Methods:

• Developed a new parametric rain model for landfalling TCs, integrated into the IRIS statistical-thermodynamic global TC hazard model.
• Conducted a 10,000-year simulation to reproduce observed global TC rain risk metrics.
• Applied a storyline approach to a +2°C global warming scenario for US hurricane rainfall projections.

Main Results:

• The IRIS model accurately reproduces global TC landfall rain rate, volume, and lifetime production return periods.
• For US hurricanes under +2°C warming, rain rates increase by 20.1%, storm-total volume by 3.9%, and lifetime rainfall by 14.6%.
• Warming enhances rainfall across the eastern and southern US, with greater inland and poleward penetration.

Conclusions:

• The new IRIS model effectively quantifies TC rain risk and provides valuable climate projection capabilities.
• Global warming intensifies hurricane rainfall, particularly in specific regions, leading to increased inland and poleward rainfall extent.