On the Role of Next Generation Geostationary Satellite Data in Improving Severe Storm and Tornado Prediction

Since 1980, the United States has experienced more than 130 weather-related disasters resulting in at least $1 billion in standardized losses, and tornadoes and severe thunderstorms are associated with a large number of these high impact events. For example, in 2011 and 2012 there were 26 separate billion dollar weather disasters and half were caused by tornadoes and severe thunderstorms. Accurate prediction of major tornado and severe storm outbreaks is an essential part of the NOAA/National Weather Service's Weather Ready Nation (WRN) initiative, which is designed to increase the ability of communities to prepare for and respond to weather disasters. Key components of this vision include the application of innovative scientific and technological solutions that will enable improved accuracy of weather and water forecasts and effective communication of risk to decision-makers.

Substantially improved capabilities of the next generation of meteorological satellites are expected to play a large role in meeting the science and technology demands to support a WRN, in part by providing observational data at much higher spatial and temporal resolution. These new data sets will be critical to improve initialization of advanced numerical weather prediction models, including convection-allowing models. In addition, these data sets will provide operational forecasters with new, advanced products to increase situational awareness about ongoing and upcoming hazardous weather threats, including severe thunderstorm and tornadoes.

A brief historical overview of major tornado outbreaks is provided to illustrate the nature of tornado impacts on society. While noteworthy improvements in tornado forecasts and warnings have occurred in recent decades, a number of major events during 2011-2013 underscore the need for additional progress if storm-related fatalities are to be reduced. Given the short time scales and rapid evolution of thunderstorms and associated hazards, geostationary satellite data, combined with other observational data from radar and lightning detection systems, play a foundational role in the near-term monitoring of environments favorable for convective storm development as well as the life cycle of subsequent storms. Through multi-organizational collaborative efforts in the GOES-R Proving Grounds co-located with NOAA/NWS Testbeds, such as the Hazardous Weather Testbed at the Storm Prediction Center/National Severe Storms Laboratory, we are learning how to test and evaluate proxy satellite datasets for products that will be available from the GOES-R series of satellites to improve the prediction of severe thunderstorms and tornadoes. Examples are provided that highlight the expected benefits of GOES-R in unique and complementary ways as the NWS moves toward achieving WRN status.