Operational storm surge forecasting at the National Hur ricane Center: The case for probabilistic guidance and the evaluation of improved storm size forecasts used to define the wind forcing

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES Weather and Forecasting Pub Date : 2023-10-20 DOI:10.1175/waf-d-22-0209.1
Andrew B. Penny, Laura Alaka, Arthur A. Taylor, William Booth, Mark DeMaria, Cody Fritz, Jamie Rhome
{"title":"Operational storm surge forecasting at the National Hur ricane Center: The case for probabilistic guidance and the evaluation of improved storm size forecasts used to define the wind forcing","authors":"Andrew B. Penny, Laura Alaka, Arthur A. Taylor, William Booth, Mark DeMaria, Cody Fritz, Jamie Rhome","doi":"10.1175/waf-d-22-0209.1","DOIUrl":null,"url":null,"abstract":"Abstract The primary source of guidance used by the Storm Surge Unit (SSU) at the National Hurricane Center (NHC) for issuing storm surge watches and warnings is the Probabilistic Tropical Storm Surge model (P-Surge). P-Surge is an ensemble of Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model forecasts that is generated based on historical error distributions from NHC official forecasts. A probabilistic framework is used for operational storm surge forecasting to account for uncertainty related to the tropical cyclone track and wind forcing. Previous studies have shown that the size of a storm’s wind field is an important factor that can affect storm surge. A simple radius of maximum wind (RMW) prediction scheme was developed to forecast RMW based on NHC forecast parameters. Verification results indicate this scheme is an improvement over the RMW forecasts used by previous versions of P-Surge. To test the impact of the updated RMW forecasts in P-Surge, retrospective cases were selected from 25 storms from 2008-2020 that had an adequate number of observations. Evaluation of P-Surge forecasts using these improved RMW forecasts shows that the probability of detection is higher for most probability of exceedance thresholds. In addition, the forecast reliability is improved, and there is an increase in the number of high probability forecasts for extreme events at longer lead times. The improved RMW forecasts were recently incorporated into the operational version of P-Surge (v2.9), and serve as an important step toward extending the lead time of skillful and reliable storm surge forecasts.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"79 1","pages":"0"},"PeriodicalIF":3.0000,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather and Forecasting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1175/waf-d-22-0209.1","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"METEOROLOGY & ATMOSPHERIC SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

Abstract The primary source of guidance used by the Storm Surge Unit (SSU) at the National Hurricane Center (NHC) for issuing storm surge watches and warnings is the Probabilistic Tropical Storm Surge model (P-Surge). P-Surge is an ensemble of Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model forecasts that is generated based on historical error distributions from NHC official forecasts. A probabilistic framework is used for operational storm surge forecasting to account for uncertainty related to the tropical cyclone track and wind forcing. Previous studies have shown that the size of a storm’s wind field is an important factor that can affect storm surge. A simple radius of maximum wind (RMW) prediction scheme was developed to forecast RMW based on NHC forecast parameters. Verification results indicate this scheme is an improvement over the RMW forecasts used by previous versions of P-Surge. To test the impact of the updated RMW forecasts in P-Surge, retrospective cases were selected from 25 storms from 2008-2020 that had an adequate number of observations. Evaluation of P-Surge forecasts using these improved RMW forecasts shows that the probability of detection is higher for most probability of exceedance thresholds. In addition, the forecast reliability is improved, and there is an increase in the number of high probability forecasts for extreme events at longer lead times. The improved RMW forecasts were recently incorporated into the operational version of P-Surge (v2.9), and serve as an important step toward extending the lead time of skillful and reliable storm surge forecasts.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
国家飓风中心的风暴潮预报:用于定义风力的改进风暴大小预报的概率指导和评估案例
美国国家飓风中心(NHC)风暴潮小组(SSU)发布风暴潮观察和预警时使用的主要指导来源是概率热带风暴潮模型(P-Surge)。P-Surge是基于NHC官方预报的历史误差分布生成的海、湖和陆地飓风(SLOSH)模型预测的集合。风暴潮预报采用概率框架,以考虑与热带气旋路径和风力有关的不确定性。以往的研究表明,风暴风场的大小是影响风暴潮的一个重要因素。基于NHC预报参数,提出了一种简单的最大风半径预报方案。验证结果表明,该方案比以前版本的P-Surge所使用的RMW预测有了改进。为了测试更新的RMW预报对P-Surge的影响,从2008-2020年有足够观测数量的25个风暴中选择了回顾性案例。使用这些改进的RMW预测对p浪涌预测的评估表明,对于大多数超出阈值的概率,检测的概率更高。此外,预测的可靠性得到了提高,并且在较长的前置时间内对极端事件的高概率预测数量有所增加。改进的RMW预报最近被纳入P-Surge (v2.9)的操作版本,并作为延长熟练和可靠的风暴潮预报的提前时间的重要一步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Weather and Forecasting
Weather and Forecasting 地学-气象与大气科学
CiteScore
5.20
自引率
17.20%
发文量
131
审稿时长
6-12 weeks
期刊介绍: Weather and Forecasting (WAF) (ISSN: 0882-8156; eISSN: 1520-0434) publishes research that is relevant to operational forecasting. This includes papers on significant weather events, forecasting techniques, forecast verification, model parameterizations, data assimilation, model ensembles, statistical postprocessing techniques, the transfer of research results to the forecasting community, and the societal use and value of forecasts. The scope of WAF includes research relevant to forecast lead times ranging from short-term “nowcasts” through seasonal time scales out to approximately two years.
期刊最新文献
The Impact of Analysis Correction-based Additive Inflation on subseasonal tropical prediction in the Navy Earth System Prediction Capability Comparison of Clustering Approaches in a Multi-Model Ensemble for U.S. East Coast Cold Season Extratropical Cyclones Collaborative Exploration of Storm-Scale Probabilistic Guidance for NWS Forecast Operations Verification of the Global Forecast System, North American Mesoscale Forecast System, and High-Resolution Rapid Refresh Model Near-Surface Forecasts by use of the New York State Mesonet The influence of time varying sea-ice concentration on Antarctic and Southern Ocean numerical weather prediction
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1