{"title":"GEFSv12 high- and low-skill day-10 tornado forecasts","authors":"Douglas E. Miller, Vittorio A. Gensini","doi":"10.1175/waf-d-22-0122.1","DOIUrl":null,"url":null,"abstract":"\nOn average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes owing to their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the U.S. were exploited, while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). Eighty-eight high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea-surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden-Julian Oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific Decadal Oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 over forecasted the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":" ","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2023-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Weather and Forecasting","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1175/waf-d-22-0122.1","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
On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes owing to their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the U.S. were exploited, while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). Eighty-eight high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea-surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden-Julian Oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific Decadal Oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 over forecasted the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters.
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.