Jason Otkin
Dr. Otkin has been a research scientist at the Cooperative Institute for Meteorological Satellite Studies (CIMSS) within the Space Science and Engineering Center (SSEC) since 2003. His early work focused on performing high-resolution numerical weather prediction model simulations and then using output from those simulations to generate proxy radiance datasets to support efforts to develop the GOES-R series of geostationary satellites. These physically realistic datasets played a vital role in demonstrating the capabilities of new satellite sensors and supported GOES-R research and algorithm development for more than a decade.
In the late 2000s, Dr. Otkin expanded his research into improving numerical weather prediction model forecasts. His group developed innovative object-based verification methods that used all-sky satellite observations to assess the accuracy of high-resolution model forecasts. This work produced new insights into atmospheric processes and advanced the accuracy of short-range model forecasts.
Dr. Otkin has also made important contributions to satellite data assimilation. His studies in the early 2010s were among the first to demonstrate that assimilating cloud and water vapor sensitive satellite observations in ensemble data assimilation systems leads to more accurate forecasts of high-impact weather events such as thunderstorms and winter storms. From 2015 to 2020, he completed a Ph.D. at the University of Reading in the United Kingdom, where he developed a novel nonlinear bias correction method capable of removing both linear and nonlinear conditional biases from satellite observations prior to their assimilation. His work showed that applying this technique leads to more accurate weather forecasts.
Dr. Otkin is also internationally recognized as an expert on flash droughts, which are droughts that develop very quickly over a few weeks. His research on flash droughts during the early 2010s led to the first set of publications to examine the evolution and characteristics of flash drought across the U.S. using satellite observations, crop reports, and near-surface atmospheric variables. He has also led many projects where physical and social scientists worked with agricultural and ecological stakeholders to better understand their vulnerability to drought and to develop machine learning prediction tools. He has also been involved with numerous projects led by external collaborators that examined the characteristics of flash drought around the world.
More recently, Dr. Otkin has been leading a large multidisciplinary team at SSEC in partnership with NOAA and university partners to develop the Next Generation Fire System (NGFS), which is an artificial intelligence system that uses satellite observations to detect wildfires and to provide automated notifications whenever new fires are detected. The NGFS uses an innovative feature-based algorithm designed to emulate human expert analysis of multi-spectral satellite imagery. Its near-continuous monitoring capabilities supports initial and extended attack efforts by firefighters and enhances National Weather Service decision-support services such as hot spot notifications, integrated warning team fire warnings, and incident meteorologist deployments. The NGFS has quickly become an important operational resource that has improved situational awareness and enabled faster, more informed decisions to protect lives and property.
On a personal note, Dr. Otkin’s growth as a scientist during the past 20+ years has been shaped by exceptional mentors who encouraged his curiosity, helped refine his communication skills, and introduced him to collaborators and friends who have enriched his career. He remains grateful to everyone who has supported, guided, and worked with him over the years.
