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Warn-on-Forecast System: From Vision to Reality

雷雨 气象学 数据同化 计算机科学 临近预报 恶劣天气 全球预报系统 龙卷风 数值天气预报 风暴 天气预报 运筹学 地理 工程类
作者
Pamela L. Heinselman,Patrick C. Burke,Louis J. Wicker,Adam J. Clark,John S. Kain,Jidong Gao,Nusrat Yussouf,Thomas A. Jones,Patrick S. Skinner,Corey K. Potvin,Katie A. Wilson,Burkely T. Gallo,Montgomery L. Flora,Joshua Martin,Gerald J. Creager,Kent H. Knopfmeier,Yunheng Wang,Brian C. Matilla,David C. Dowell,Edward R. Mansell,Brett Roberts,Kimberly A. Hoogewind,Derek R. Stratman,J.E. Castillo Guerra,Anthony E. Reinhart,Christopher A. Kerr,William J. Miller
出处
期刊:Weather and Forecasting [American Meteorological Society]
卷期号:39 (1): 75-95 被引量:2
标识
DOI:10.1175/waf-d-23-0147.1
摘要

Abstract In 2009, advancements in NWP and computing power inspired a vision to advance hazardous weather warnings from a warn-on-detection to a warn-on-forecast paradigm. This vision would require not only the prediction of individual thunderstorms and their attributes but the likelihood of their occurrence in time and space. During the last decade, the warn-on-forecast research team at the NOAA National Severe Storms Laboratory met this challenge through the research and development of 1) an ensemble of high-resolution convection-allowing models; 2) ensemble- and variational-based assimilation of weather radar, satellite, and conventional observations; and 3) unique postprocessing and verification techniques, culminating in the experimental Warn-on-Forecast System (WoFS). Since 2017, we have directly engaged users in the testing, evaluation, and visualization of this system to ensure that WoFS guidance is usable and useful to operational forecasters at NOAA national centers and local offices responsible for forecasting severe weather, tornadoes, and flash floods across the watch-to-warning continuum. Although an experimental WoFS is now a reality, we close by discussing many of the exciting opportunities remaining, including folding this system into the Unified Forecast System, transitioning WoFS into NWS operations, and pursuing next-decade science goals for further advancing storm-scale prediction. Significance Statement The purpose of this research is to develop an experimental prediction system that forecasts the probability for severe weather hazards associated with individual thunderstorms up to 6 h in advance. This capability is important because some people and organizations, like those living in mobile homes, caring for patients in hospitals, or managing large outdoor events, require extended lead time to protect themselves and others from potential severe weather hazards. Our results demonstrate a prediction system that enables forecasters, for the first time, to message probabilistic hazard information associated with individual severe storms between the watch-to-warning time frame within the United States.
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