dc.contributor.author | Chang, Derek | |
dc.contributor.author | Amin, Saurabh | |
dc.contributor.author | Emanuel, Kerry | |
dc.date.accessioned | 2022-01-18T19:20:40Z | |
dc.date.available | 2021-10-27T19:53:52Z | |
dc.date.available | 2022-01-18T19:20:40Z | |
dc.date.issued | 2020-04 | |
dc.identifier.issn | 1558-8424 | |
dc.identifier.issn | 1558-8432 | |
dc.identifier.uri | https://hdl.handle.net/1721.1/133621.2 | |
dc.description.abstract | © 2020 American Meteorological Society. This article presents an azimuthally asymmetric gradient hurricane wind field model that can be coupled with hurricane-track models for engineering wind risk assessments. The model incorporates low-wavenumber asymmetries into the maximum wind intensity parameter of the Holland et al. wind field model. The am-plitudes and phases of the asymmetries are parametric functions of the storm-translation speed and wind shear. Model parameters are estimated by solving a constrained, nonlinear least squares (CNLS) problem that minimizes the sum of squared residuals between wind field intensities of historical storms and model-estimated winds. There are statistically significant wavenumber-1 asymmetries in the wind field resulting from both storm translation and wind shear. Adding the translation vector to the wind field model with wavenumber-1 asymmetries further improves the model’s estimation performance. In addition, inclusion of the wavenumber-1 asymmetry resulting from translation results in a greater decrease in modeling error than does inclusion of the wavenumber-1 shear-induced asymmetry. Overall, the CNLS estimation method can handle the inherently nonlinear wind field model in a flexible manner; thus, it is well suited to capture the radial variability in the hurricane wind field’s asymmetry. The article concludes with brief remarks on how the CNLS-estimated model can be applied for simulating wind fields in a statistically generated ensemble. | en_US |
dc.language.iso | en | |
dc.publisher | American Meteorological Society | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1175/JAMC-D-19-0126.1 | en_US |
dc.rights | Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. | en_US |
dc.source | American Meteorological Society (AMS) | en_US |
dc.title | Modeling and Parameter Estimation of Hurricane Wind Fields with Asymmetry | en_US |
dc.type | Article | en_US |
dc.contributor.department | Massachusetts Institute of Technology. Center for Computational Engineering | |
dc.contributor.department | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering | |
dc.contributor.department | Massachusetts Institute of Technology. Institute for Data, Systems, and Society | |
dc.contributor.department | Massachusetts Institute of Technology. Program in Atmospheres, Oceans, and Climate | |
dc.relation.journal | Journal of Applied Meteorology and Climatology | en_US |
dc.eprint.version | Final published version | en_US |
dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
dc.date.updated | 2021-09-15T17:48:18Z | |
dspace.orderedauthors | Chang, D; Amin, S; Emanuel, K | en_US |
dspace.date.submission | 2021-09-15T17:48:19Z | |
mit.journal.volume | 59 | en_US |
mit.journal.issue | 4 | en_US |
mit.license | PUBLISHER_POLICY | |
mit.metadata.status | Authority Work Needed | en_US |