Scientists hope images from the research drones will improve our understanding of tornadoes and lead to better forecasts.
All tornadoes -- whether large or small -- originate from thunderstorms, but not all thunderstorms are the same. Nighttime twisters, summer tornadoes and smaller events can be tougher to forecast. New research in the Bulletin of the American Meteorological Society presents a method for rating the skill of tornado warnings based on environmental challenges.
When a tornado threatens a community, NOAA National Weather Service forecasters issue a tornado warning. Local emergency management agencies sound emergency tornado sirens or send out phone alerts. Broadcast meteorologists tell everyone to take shelter. But how does all of this help the public and how does the public respond?
Tornados are one of nature’s most destructive forces. Currently, our capacity to predict tornados and other severe weather risks does not extend beyond seven days. In a recent paper published in Environmental Research Letters, scientists with NOAA and the University of Miami identified how patterns in the spring phases of the El Niño-Southern Oscillation (ENSO), coupled with variability in North Atlantic sea surface temperatures, could help predict U.S. regional tornado outbreaks.
Weather forecasters rely on an incredibly large amount of information when they make forecasts and issue warnings. A new system, activated by NOAA’s National Weather Service last week, quickly harnesses the tremendous amount of weather data from multiple sources, intelligently integrates the information, and provides a detailed picture of the current weather.
NOAA researchers have developed a method to help forecasters better predict the severity of tornado outbreaks.
NOAA and university researchers believe they have found a climate signal related to a specific phase of the El Niño-Southern Oscillation that could be linked to, and possibly serve as a predictor of, massive tornado outbreaks.