The Extended-Range Tornado Activity Forecast (ERTAF) Project

Author:

Gensini Vittorio A.1,Barrett Bradford S.2,Allen John T.3,Gold David4,Sirvatka Paul5

Affiliation:

1. Department of Geographic and Atmospheric Sciences, Northern Illinois University, DeKalb, Illinois

2. Oceanography Department, United States Naval Academy, Annapolis, Maryland

3. Department of Earth and Atmospheric Science, Central Michigan University, Mount Pleasant, Michigan

4. Weather Analytics Center of Competency, Global Business Services, IBM, Armonk, New York

5. Meteorology Program, College of DuPage, Glen Ellyn, Illinois

Abstract

AbstractLarge-scale weather patterns favorable for tornado occurrence have been understood for many decades. Yet prediction of tornadoes, especially at extended lead periods of more than a few days, remains an arduous task, partly due to the space and time scales involved. Recent research has shown that tropical convection, sea surface temperatures, and the Earth-relative atmospheric angular momentum can induce jet stream configurations that may increase or decrease the probability of tornado frequency across the United States. Applying this recent theoretical work in practice, on 1 March 2015, the authors began the Extended-Range Tornado Activity Forecast (ERTAF) project, with the following goals: 1) to have a map room–style discussion of the anticipated atmospheric state in the 2–3-week lead window; 2) to predict categorical level of tornado activity in that lead window; and 3) to learn from the forecasts through experience by identifying strengths and weaknesses in the methods, as well as identifying any potential scientific knowledge gaps. Over the last five years, the authors have shown skill in predicting U.S. tornado activity two to three weeks in advance during boreal spring. Unsurprisingly, skill is shown to be greater for forecasts spanning week 2 versus week 3. This manuscript documents these forecasting efforts, provides verification statistics, and shares the challenges and lessons learned from predicting tornado activity on the subseasonal time scale.

Publisher

American Meteorological Society

Subject

Atmospheric Science

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