File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Evaluation of a physics-based tropical cyclone rainfall model for risk assessment

TitleEvaluation of a physics-based tropical cyclone rainfall model for risk assessment
Authors
KeywordsModel evaluation/performance
Rainfall
Tropical cyclones
Issue Date2020
Citation
Journal of Hydrometeorology, 2020, v. 21, n. 9, p. 2197-2218 How to Cite?
AbstractHeavy rainfall generated by landfalling tropical cyclones (TCs) can cause extreme flooding. A physics-based TC rainfall model (TCRM) has been developed and coupled with a TC climatology model to study TC rainfall climatology. In this study, we evaluate TCRM with rainfall observations made by satellite (of North Atlantic TCs from 1999 to 2018) and radar (of 36 U.S. landfalling TCs); we also examine the influence on the rainfall estimation of the key input to TCRM—the wind profile. We found that TCRM can simulate relatively well the rainfall from TCs that have a coherent and compact structure and limited interaction with other meteorological systems. The model can simulate the total rainfall from TCs well, although it often overes-timates rainfall in the inner core of TCs, slightly underestimates rainfall in the outer regions, and renders a less asymmetric rainfall structure than the observations. It can capture rainfall distribution in coastal areas relatively well but may underestimate rainfall maximums in mountainous regions and has less capability to accurately simulate TC rainfall in higher latitudes. Also, it can capture the interannual variability of TC rainfall and averaged features of the time series of TC rainfall but cannot accurately reproduce the probability distribution of short-term (1 h) rainfall. Among the tested theoretical wind profile inputs to TCRM, a complete wind profile that accurately describes the wind structure in both the inner ascending and outer de-scending regions of the storm is found to perform the best in accurately generating various rainfall metrics.
Persistent Identifierhttp://hdl.handle.net/10722/346892
ISSN
2023 Impact Factor: 3.1
2023 SCImago Journal Rankings: 1.432

 

DC FieldValueLanguage
dc.contributor.authorXi, Dazhi-
dc.contributor.authorLin, Ning-
dc.contributor.authorSmith, James-
dc.date.accessioned2024-09-17T04:14:00Z-
dc.date.available2024-09-17T04:14:00Z-
dc.date.issued2020-
dc.identifier.citationJournal of Hydrometeorology, 2020, v. 21, n. 9, p. 2197-2218-
dc.identifier.issn1525-755X-
dc.identifier.urihttp://hdl.handle.net/10722/346892-
dc.description.abstractHeavy rainfall generated by landfalling tropical cyclones (TCs) can cause extreme flooding. A physics-based TC rainfall model (TCRM) has been developed and coupled with a TC climatology model to study TC rainfall climatology. In this study, we evaluate TCRM with rainfall observations made by satellite (of North Atlantic TCs from 1999 to 2018) and radar (of 36 U.S. landfalling TCs); we also examine the influence on the rainfall estimation of the key input to TCRM—the wind profile. We found that TCRM can simulate relatively well the rainfall from TCs that have a coherent and compact structure and limited interaction with other meteorological systems. The model can simulate the total rainfall from TCs well, although it often overes-timates rainfall in the inner core of TCs, slightly underestimates rainfall in the outer regions, and renders a less asymmetric rainfall structure than the observations. It can capture rainfall distribution in coastal areas relatively well but may underestimate rainfall maximums in mountainous regions and has less capability to accurately simulate TC rainfall in higher latitudes. Also, it can capture the interannual variability of TC rainfall and averaged features of the time series of TC rainfall but cannot accurately reproduce the probability distribution of short-term (1 h) rainfall. Among the tested theoretical wind profile inputs to TCRM, a complete wind profile that accurately describes the wind structure in both the inner ascending and outer de-scending regions of the storm is found to perform the best in accurately generating various rainfall metrics.-
dc.languageeng-
dc.relation.ispartofJournal of Hydrometeorology-
dc.subjectModel evaluation/performance-
dc.subjectRainfall-
dc.subjectTropical cyclones-
dc.titleEvaluation of a physics-based tropical cyclone rainfall model for risk assessment-
dc.typeArticle-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1175/JHM-D-20-0035.1-
dc.identifier.scopuseid_2-s2.0-85092045553-
dc.identifier.volume21-
dc.identifier.issue9-
dc.identifier.spage2197-
dc.identifier.epage2218-
dc.identifier.eissn1525-7541-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats