Abstract

The Geostationary Environment Monitoring Spectrometer (GEMS) is the world's first air quality instrument in the geostationary (GEO) orbit to monitor trace gases and aerosols at an unprecedented spatial and temporal resolution over East Asia, shedding light on the gradually alarming ozone pollution contrary to declining precursor emissions in this region. Here we use synthetic GEMS ozone profiles through the Observing System Simulation Experiment (OSSE) for evaluating the benefit of GEMS hourly measurements on chemical data simulation based on a Kalman filter technique. Assimilating synthetic GEMS data improves surface ozone simulation as its root-mean-square error (RMSE) is reduced by 7.2–19.2% over major urban areas in East Asia, along with a more accurate (6.3–29.2%) capturing of high-ozone events. The assimilation also better represents ozone vertical distributions in the middle to upper troposphere and better captures stratospheric intrusion events, with an RMSE reduction of 18.2–49.2% between 200 and 300 hPa. Our OSSE study offers a valuable reference for future ozone simulations, especially when massive observations become available in the coming era of GEO satellites.

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