Researchers make small but important step in seasonal tornado forecasting

Year-to-year variations of US tornado activity are mostly driven by weather and thus largely unpredictable beyond several days. This can prove difficult for communities as they prepare for these hard-hitting weather disasters. By focusing on very active seasons that are more likely linked to climate signals, researchers at NOAA’s Atlantic Oceanographic and Meteorological Laboratory have made a small but important step in seasonal tornado forecasting—a model named SPOTer (Seasonal Probabilistic Outlook for Tornadoes) that shows promise in predicting active seasons 1-2 months in advance.

A new paper published in Monthly Weather Review shows some promise for predicting subseasonal to seasonal tornado activity based on how key atmospheric parameters over the US respond to various climate signals, including El Niño and La Niña activity in the Pacific. In this study, a team of researchers from NOAA’s Atlantic Oceanographic and Meteorological Laboratory, Geophysical Fluid Dynamics Laboratory, and Climate Prediction Center presented an experimental seasonal tornado outlook model, named SPOTer (Seasonal Probabilistic Outlook for Tornadoes), and evaluated its prediction skill. SPOTter provides an initial forecast in late February for March-April tornado activity, and is then updated in late March for April-May activity. This partly statistical and partly dynamic (i.e., hybrid) model was built based on NOAA’s severe weather database from NOAA’s Storm Prediction Center and NOAA’s Climate Forecast System version 2. SPOTter is the first of its kind that shows a fairly useful skill for predicting seasonal US tornado activity.

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