Sofia Menemenlis, Gabriel A. Vecchi, Kun Gao, James A Smith, Kai-Yuan Cheng
{"title":"Extreme Rainfall Risk in Hurricane Ida’s Extratropical Stage: An Analysis with Convection-Permitting Ensemble Hindcasts","authors":"Sofia Menemenlis, Gabriel A. Vecchi, Kun Gao, James A Smith, Kai-Yuan Cheng","doi":"10.1175/jas-d-23-0160.1","DOIUrl":null,"url":null,"abstract":"\nThe extratropical stage of Hurricane Ida (2021) brought extreme sub-daily rainfall and devastating flooding to parts of eastern Pennsylvania, New Jersey, and New York. We investigate the predictability and character of this event using 31-member ensembles of perturbed-initial condition hindcasts with T-SHiELD, a ∼13 km global weather forecast model with a ∼3 km nested grid. At lead times of up to four days, the ensembles are able to capture the most extreme observed hourly and daily rainfall accumulations, but are negatively biased in the spatial extent of heavy precipitation. Large intra-ensemble differences in the magnitudes and locations of simulated extremes suggest that although impacts were highly localized, risks were widespread. In Ida’s tropical stage, inter-ensemble spread in extreme hourly rainfall is well predicted by large-scale moisture convergence; by contrast, in Ida’s extratropical stage, the most extreme rainfall is governed by mesoscale processes that exhibit chaotic and diverse forms across the ensembles. Our results are relevant to forecasting and communication in advance of extratropical transition, and imply that flood preparedness efforts should account for the widespread possibility of severe localized impacts.","PeriodicalId":508177,"journal":{"name":"Journal of the Atmospheric Sciences","volume":"40 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the Atmospheric Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/jas-d-23-0160.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The extratropical stage of Hurricane Ida (2021) brought extreme sub-daily rainfall and devastating flooding to parts of eastern Pennsylvania, New Jersey, and New York. We investigate the predictability and character of this event using 31-member ensembles of perturbed-initial condition hindcasts with T-SHiELD, a ∼13 km global weather forecast model with a ∼3 km nested grid. At lead times of up to four days, the ensembles are able to capture the most extreme observed hourly and daily rainfall accumulations, but are negatively biased in the spatial extent of heavy precipitation. Large intra-ensemble differences in the magnitudes and locations of simulated extremes suggest that although impacts were highly localized, risks were widespread. In Ida’s tropical stage, inter-ensemble spread in extreme hourly rainfall is well predicted by large-scale moisture convergence; by contrast, in Ida’s extratropical stage, the most extreme rainfall is governed by mesoscale processes that exhibit chaotic and diverse forms across the ensembles. Our results are relevant to forecasting and communication in advance of extratropical transition, and imply that flood preparedness efforts should account for the widespread possibility of severe localized impacts.