DELETE_A fast intensity simulator for tropical cyclone risk analysis
Abstract Robust estimates of tropical cyclone risk can be made using large sets of storm events synthesized from historical data or from physics-based algorithms. While storm tracks can be synthesized very rapidly from statistical algorithms or simple dynamical models (such as the bet...
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| Format: | Article |
| Language: | English |
| Published: |
Springer Netherlands
2017
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| Online Access: | http://hdl.handle.net/1721.1/111035 |
| _version_ | 1811082645664169984 |
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| author | Emanuel, Kerry |
| author2 | Lorenz Center (Massachusetts Institute of Technology) |
| author_facet | Lorenz Center (Massachusetts Institute of Technology) Emanuel, Kerry |
| author_sort | Emanuel, Kerry |
| collection | MIT |
| description | Abstract
Robust estimates of tropical cyclone risk can be made using large sets of storm events synthesized from historical data or from physics-based algorithms. While storm tracks can be synthesized very rapidly from statistical algorithms or simple dynamical models (such as the beta-and-advection model), estimation of storm intensity by using full-physics models is generally too expensive to be practical. Although purely statistical intensity algorithms are fast, they may not be general enough to encompass the effects of natural or anthropogenic climate change. Here we present a fast, physically motivated intensity algorithm consisting of two coupled ordinary differential equations predicting the evolution of a wind speed and an inner core moisture variable. The algorithm includes the effects of ocean coupling and environmental wind shear but does not explicitly simulate spatial structure, which must be handled parametrically. We evaluate this algorithm by using it to simulate several historical events and by comparing a risk analysis based on it to an existing method for assessing long-term tropical cyclone risk. For simulations based on the recent climate, the two techniques perform comparably well, though the new technique does better with interannual variability in the Atlantic. Compared to the existing method, the new method produces a smaller increase in global tropical cyclone frequency in response to global warming, but a comparable increase in power dissipation. |
| first_indexed | 2024-09-23T12:06:42Z |
| format | Article |
| id | mit-1721.1/111035 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T12:06:42Z |
| publishDate | 2017 |
| publisher | Springer Netherlands |
| record_format | dspace |
| spelling | mit-1721.1/1110352024-06-26T15:05:34Z DELETE_A fast intensity simulator for tropical cyclone risk analysis Emanuel, Kerry Lorenz Center (Massachusetts Institute of Technology) Abstract Robust estimates of tropical cyclone risk can be made using large sets of storm events synthesized from historical data or from physics-based algorithms. While storm tracks can be synthesized very rapidly from statistical algorithms or simple dynamical models (such as the beta-and-advection model), estimation of storm intensity by using full-physics models is generally too expensive to be practical. Although purely statistical intensity algorithms are fast, they may not be general enough to encompass the effects of natural or anthropogenic climate change. Here we present a fast, physically motivated intensity algorithm consisting of two coupled ordinary differential equations predicting the evolution of a wind speed and an inner core moisture variable. The algorithm includes the effects of ocean coupling and environmental wind shear but does not explicitly simulate spatial structure, which must be handled parametrically. We evaluate this algorithm by using it to simulate several historical events and by comparing a risk analysis based on it to an existing method for assessing long-term tropical cyclone risk. For simulations based on the recent climate, the two techniques perform comparably well, though the new technique does better with interannual variability in the Atlantic. Compared to the existing method, the new method produces a smaller increase in global tropical cyclone frequency in response to global warming, but a comparable increase in power dissipation. 2017-08-28T18:54:38Z 2017-08-28T18:54:38Z 2017-05 2017-08-01T05:05:26Z Article http://purl.org/eprint/type/JournalArticle 0921-030X 1573-0840 http://hdl.handle.net/1721.1/111035 Emanuel, Kerry. “A Fast Intensity Simulator for Tropical Cyclone Risk Analysis.” Natural Hazards 88, no. 2 (May 6, 2017): 779–796. doi:10.1007/s11069-017-2890-7. en http://dx.doi.org/10.1007/s11069-017-2890-7 Natural Hazards Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Netherlands Springer Netherlands |
| spellingShingle | Emanuel, Kerry DELETE_A fast intensity simulator for tropical cyclone risk analysis |
| title | DELETE_A fast intensity simulator for tropical cyclone risk analysis |
| title_full | DELETE_A fast intensity simulator for tropical cyclone risk analysis |
| title_fullStr | DELETE_A fast intensity simulator for tropical cyclone risk analysis |
| title_full_unstemmed | DELETE_A fast intensity simulator for tropical cyclone risk analysis |
| title_short | DELETE_A fast intensity simulator for tropical cyclone risk analysis |
| title_sort | delete a fast intensity simulator for tropical cyclone risk analysis |
| url | http://hdl.handle.net/1721.1/111035 |
| work_keys_str_mv | AT emanuelkerry deleteafastintensitysimulatorfortropicalcycloneriskanalysis |