Weather and Climate Extremes (Dec 2019)

Physically-based landfalling tropical cyclone scenarios in support of risk assessment

  • Cindy L. Bruyère,
  • James M. Done,
  • Abigail B. Jaye,
  • Greg J. Holland,
  • Bruce Buckley,
  • David J. Henderson,
  • Mark Leplastrier,
  • Peter Chan

Journal volume & issue
Vol. 26

Abstract

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Populations and property values are increasing in tropical cyclone prone regions, driving up repair and replacement costs following a tropical cyclone impact. Climate change influences on tropical cyclones and sea levels will only exacerbate these rises. For example, Australia's Severe Tropical Cyclone Debbie in 2017 was one of the most destructive cyclones to make landfall in Australia since Tropical Cyclone Tracy in 1974. The primary impacts of Cyclone Debbie were due to extreme short duration intense wind driven rainfall and widespread major flooding, both linked to uncharacteristically warm sea surface temperatures. Studying the impact of climate change on tropical cyclones is limited by the lack of well observed historical events. Traditional hazard risk assessment approaches are limited since they are primarily based on statistical models which only deal with single meteorological hazards, or use simplified parameterized relationships when more than one phenomenon is included. Here we explore the value of dynamical models for creating targeted, detailed, and physically plausible multi-hazard tropical cyclone scenarios, through the development of a modeling system that i) retains a high degree of simulation control, ii) is globally applicable, and iii) is responsive to climate variability and change. Application of the modeling system to a thermodynamic climate change scenario finds that the tropical cyclone penetrates much further inland with a marked expansion of the heavy rainfall area, resulting in significantly larger areas subjected to damaging and destructive wind speeds and rainfall totals capable of producing flash and riverine flooding. Keywords: Tropical cyclones, WRF, Hybrid approach, Risk modeling