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dc.contributor.authorLu, Ping
dc.contributor.authorLin, Ning
dc.contributor.authorSmith, James
dc.contributor.authorEmanuel, Kerry Andrew
dc.contributor.authorChavas, Daniel Robert
dc.date.accessioned2018-10-01T15:40:22Z
dc.date.available2018-10-01T15:40:22Z
dc.date.issued2018-06
dc.date.submitted2017-09
dc.identifier.issn0022-4928
dc.identifier.issn1520-0469
dc.identifier.urihttp://hdl.handle.net/1721.1/118306
dc.description.abstractWe examine a recently developed physics-based tropical cyclone rainfall (TCR) model and apply it to assess the mechanisms that dominate the magnitude and spatial distribution of TC rainfall, with Hurricanes Isabel (2003) and Irene (2011) as study cases. We evaluate the TCR model using Weather and Research Forecasting (WRF) Model simulations. TCR-generated rainfall fields for the two storms compare well with WRF estimates in terms of both azimuthal mean and spatial distributions. When coupled with a hydrologic model, TCR generates flood peaks over the Delaware River basin for Irene as accurately as WRF. TCR accounts for four major rainfall mechanisms: surface frictional convergence, vortex stretching, interaction of the storm with topography, and interaction of the storm with large-scale baroclinity. We show that these rainfall mechanisms affected the rainfall pattern differently for Isabel and Irene. Frictional convergence is the dominant factor, while other mechanisms are also significant. The frictional convergence depends on the boundary layer formulation, which is relatively simple in TCR and may require calibration of boundary layer parameters. Furthermore, we find that the TC rainfall distribution is strongly dependent on the temporal and spatial variation of the TC wind field, mediated by the physical mechanisms represented by TCR. When coupled with various analytical wind models, TCR generally captures the rainfall distribution, with the Holland wind model performing the best. Given its high computational efficiency, TCR can be coupled with an analytical wind model, a hydrological model, and a TC climatology model to generate large numbers of synthetic events to assess the risk associated with TC rainfall and inland flooding. Keywords: Rainfall; Tropical cyclonesen_US
dc.publisherAmerican Meteorological Societyen_US
dc.relation.isversionofhttp://dx.doi.org/10.1175/JAS-D-17-0264.1en_US
dc.rightsCreative Commons Attribution 4.0 International Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en_US
dc.sourceAmerican Meteorological Societyen_US
dc.titleAssessing Hurricane Rainfall Mechanisms Using a Physics-Based Model: Hurricanes Isabel (2003) and Irene (2011)en_US
dc.typeArticleen_US
dc.identifier.citationLu, Ping et al. “Assessing Hurricane Rainfall Mechanisms Using a Physics-Based Model: Hurricanes Isabel (2003) and Irene (2011).” Journal of the Atmospheric Sciences 75, 7 (July 2018): 2337–2358 © 2018 American Meteorological Societyen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Earth, Atmospheric, and Planetary Sciencesen_US
dc.contributor.mitauthorEmanuel, Kerry Andrew
dc.contributor.mitauthorChavas, Daniel Robert
dc.relation.journalJournal of the Atmospheric Sciencesen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-09-21T15:55:09Z
dspace.orderedauthorsLu, Ping; Lin, Ning; Emanuel, Kerry; Chavas, Daniel; Smith, Jamesen_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-2066-2082
mit.licensePUBLISHER_CCen_US


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