The atmospheric composition geostationary satellite constellation for air quality and climate science: Evaluating performance with Observation System Simulation Experiments

Friday, 19 December 2014: 2:10 PM
David P Edwards1, Jerome Barre1, Helen Marie Worden1, Avelino F Arellano2, Benjamin Gaubert1, Jeffrey L Anderson1, Arthur P Mizzi1 and William A Lahoz3, (1)National Center for Atmospheric Research, Boulder, CO, United States, (2)University of Arizona, Tucson, AZ, United States, (3)Norwegian Institute for Air Research, Kjeller, Norway
Current satellite observations of tropospheric composition made from low Earth orbit provide at best one or two measurements each day at any given location. Coverage is global but sparse, often with large uncertainties in individual measurements that limit examination of local and regional atmospheric composition over short time periods. This has hindered the operational uptake of these data for monitoring air quality and population exposure, and for initializing and evaluating chemical weather forecasts. By the end of the current decade there are planned geostationary Earth orbit (GEO) satellite missions for atmospheric composition over North America, East Asia and Europe with additional missions proposed. Together, these present the possibility of a constellation of GEO platforms to achieve continuous time-resolved high-density observations of continental domains for mapping pollutant sources and variability on diurnal and local scales. We describe Observing System Simulation Experiments (OSSEs) to evaluate the contributions of these GEO missions to improve knowledge of near-surface air pollution due to intercontinental long-range transport and quantify chemical precursor emissions. We discuss the requirements on measurement simulation, chemical transport modeling, and data assimilation for a successful OSSE infrastructure. Our approach uses an efficient computational method to sample a high-resolution global GEOS-5 chemistry Nature Run over each geographical region of the GEO constellation. The demonstration carbon monoxide (CO) observation simulator, which is being expanded to other chemical pollutants, currently produces multispectral retrievals and captures realistic scene-dependent variation in measurement vertical sensitivity and cloud cover. We use the DART Ensemble Adjustment Kalman Filter to assimilate the simulated observations in a CAM-Chem global chemistry-climate model Control Run. The impact of observing over each region is evaluated using data denial experiments. Finally, we report on international collaborations using the OSSE approach to determine expected performance of planned satellite systems and set requirements for future missions.