Operational Storm Surge Forecasting at the National Hurricane Center: The Case for Probabilistic Guidance and the Evaluation of Improved Storm Size Forecasts Used to Define the Wind Forcing

Author:

Penny Andrew B.12,Alaka Laura12,Taylor Arthur A.3,Booth William12,DeMaria Mark4,Fritz Cody2,Rhome Jamie2

Affiliation:

1. a University Corporation for Atmospheric Research/Cooperative Programs for the Advancement of Earth System Science, Boulder, Colorado

2. b National Hurricane Center, Miami, Florida

3. c Meteorological Development Laboratory, Silver Spring, Maryland

4. d Colorado State University/Cooperative Institute for Research in the Atmosphere, Fort Collins, Colorado

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 to 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.

Funder

NOAA’s Science Collaboration Program administered by UCAR’s Cooperative Programs for the Advancement of Earth System Science

Publisher

American Meteorological Society

Subject

Atmospheric Science

Reference44 articles.

1. Beven, J. L., II, R. Berg, and A. Hagen, 2019: Tropical cyclone report: Hurricane Michael (7–11 October 2018). NHC Tech. Rep. AL142018, 86 pp., https://www.nhc.noaa.gov/data/tcr/AL142018_Michael.pdf.

2. The influence of domain size on the response characteristics of a hurricane storm surge model;Blain, C. A.,1994

3. Cangialosi, J. P., 2021: Forecast verification report: 2020 Hurricane Season. NHC Tech. Rep., 77 pp., http://www.nhc.noaa.gov/verification/pdfs/Verification_2020.pdf.

4. An examination of model and official National Hurricane Center tropical cyclone size forecasts;Cangialosi, J. P.,2016

5. A simple model for predicting the tropical cyclone radius of maximum wind from outer size;Chavas, D. R.,2022

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3