Christoph Keller (610.1/MSU) and team were awarded funding for their proposal "Development of a next-generation ensemble prediction system for atmospheric composition", submitted to NASA's Advanced Information Systems Technology (AIST) call. In addition to Dr. Keller as PI, the team consists of Co-I Patricia Castellano (610.1/GSFC), machine learning expert Jennifer Sleeman (610.1/Johns Hopkins University), and collaborators Steven Pawson (610.1/GSFC) along with NOAA scientists Raffaele Montuoro and Ivanka Stajner.
According to Dr. Keller, "The goal of this AIST project is to develop a new modeling framework to support the real-time simulation of reactive gases and aerosols at very high resolution. The project comprises two science tasks: the implementation of simplified parameterizations for atmospheric chemistry and tracer transport into the GEOS Earth System Model, and the development of an efficient methodology for generating probabilistic estimates of atmospheric composition using state-of-the science machine learning algorithms. The utility of this framework will first be demonstrated in the GEOS Composition Forecast system (GEOS-CF), with a technology transfer to NOAA's next-generation air quality forecasting system planned in a second step."
Posted: June 1, 2022, 9:07 AM