Innovations in Winter Storm Forecasting and Decision Support Services
Author:
Novak David R.1, Perfater Sarah E.2, Demuth Julie L.3, Bieda Stephen W.2, Carbin Gregory1, Craven Jeffrey4, Erickson Michael J.5, Jeglum Matthew E.6, Kastman Joshua1, Nelson James A.1, Rudack David E.4, Staudenmaier Michael J.6, Waldstreicher Jeff S.7
Affiliation:
1. NOAA/NWS/Weather Prediction Center, College Park, Maryland; 2. NOAA/NWS Headquarters, Silver Spring, Maryland; 3. National Center for Atmospheric Research, Boulder, Colorado; 4. NOAA/NWS Meteorological Development Laboratory, Silver Spring, Maryland; 5. Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Colorado, and NOAA/NWS/Weather Prediction Center, College Park, Maryland; 6. NOAA/NWS Western Region Headquarters, Salt Lake City, Utah; 7. NOAA/NWS Eastern Region Headquarters, Bohemia, New York
Abstract
Abstract
Winter storms are disruptive to society and the economy, and they often cause significant injuries and deaths. Innovations in winter storm forecasting have occurred across the value chain over the past two decades, from physical understanding, to observations, to model forecasts, to postprocessing, to forecaster knowledge and interpretation, to products and services, and ultimately to decision support. These innovations enable more accurate and consistent forecasts, which are increasingly being translated into actionable information for decision-makers. This paper reviews the current state of winter storm forecasting in the context of the U.S. National Weather Service operations and describes a potential future state. Given predictability limitations, a key challenge of winter storm forecasting has been characterizing uncertainty and communicating the forecast in ways that are understandable and useful to decision-makers. To address this challenge, particular focus is placed on establishing a probabilistic framework, with probabilistic hazard information serving as a foundation for winter storm decision support services. The framework is guided by social science research to ensure effective communication of risk to meet users’ needs. Solutions to gaps impeding progress in winter storm forecasting are highlighted, including better understanding of mesoscale phenomenon, the need for better ensemble calibration, a rigorous and consistent database of observed impacts, and linking multiparameter probabilities (e.g., probability of intense snowfall rates at rush hour) with users’ information needs and decisions.
Publisher
American Meteorological Society
Subject
Atmospheric Science
Reference106 articles.
1. Drivers’ awareness of and response to two significant winter storms impacting a metropolitan area in the intermountain west: Implications for improving traffic flow in inclement weather;Barjenbruch, K.,2016 2. The quiet revolution of numerical weather prediction;Bauer, P.,2015 3. Benjamin, S. G., J. M. Brown, G. Brunet, P. Lynch, K. Saito, and T. W. Schlatter, 2019: 100 years of progress in forecasting and NWP applications. A Century of Progress in Atmospheric and Related Sciences: Celebrating the American Meteorological Society Centennial, Meteor. Monogr., No. 59, Amer. Meteor. Soc., https://doi.org/10.1175/AMSMONOGRAPHS-D-18-0020.1. 4. Characteristics of winter-precipitation-related transportation fatalities in the United States;Black, A. W.,2015 5. The THORPEX Interactive Grand Global Ensemble;Bougeault, P.,2010
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|