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Modeling high-impact weather and climate: lessons from a tropical cyclone perspective

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  • James Done
  • Greg Holland
  • Cindy Bruyère
  • L. Leung
  • Asuka Suzuki-Parker

Abstract

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding and capacity to model the underlying physical processes. This challenge is driving fresh approaches to assess high-impact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be adequate to: include relevant regional climate physical processes; resolve key impact parameters; and accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters. Copyright The Author(s) 2015

Suggested Citation

  • James Done & Greg Holland & Cindy Bruyère & L. Leung & Asuka Suzuki-Parker, 2015. "Modeling high-impact weather and climate: lessons from a tropical cyclone perspective," Climatic Change, Springer, vol. 129(3), pages 381-395, April.
    • Handle: RePEc:spr:climat:v:129:y:2015:i:3:p:381-395
    DOI: 10.1007/s10584-013-0954-6
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    References listed on IDEAS

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    1. Gabriel A. Vecchi & Brian J. Soden, 2007. "Effect of remote sea surface temperature change on tropical cyclone potential intensity," Nature, Nature, vol. 450(7172), pages 1066-1070, December.
    2. Kunreuther, Howard C. & Michel-Kerjan, Erwann O., 2011. "At War with the Weather: Managing Large-Scale Risks in a New Era of Catastrophes," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262516543, April.
    3. Lee Parker, 2011. "The conference paper," Accounting, Auditing & Accountability Journal, Emerald Group Publishing, vol. 25(1), pages 204-204, December.
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    2. Mathieu Mure-Ravaud & M. Levent Kavvas & Alain Dib, 2019. "Investigation of Intense Precipitation from Tropical Cyclones during the 21st Century by Dynamical Downscaling of CCSM4 RCP 4.5," IJERPH, MDPI, vol. 16(5), pages 1-27, February.
    3. Piyush Jain & Mari R. Tye & Debasish Paimazumder & Mike Flannigan, 2020. "Downscaling fire weather extremes from historical and projected climate models," Climatic Change, Springer, vol. 163(1), pages 189-216, November.
    4. Kevin M. Simmons & Jeffrey Czajkowski & James M. Done, 2019. "Building code economic performance under variable wind risk," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(2), pages 235-258, February.
    5. Jeffrey Czajkowski & Kevin M. Simmons & James M. Done, 2017. "Demonstrating the Intensive Benefit to the Local Implementation of a Statewide Building Code," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 20(3), pages 363-390, December.
    6. Altay, Nezih & Narayanan, Arunachalam, 2022. "Forecasting in humanitarian operations: Literature review and research needs," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1234-1244.

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