15.3 Improving Short-Term Air Quality Predictions over the U.S. Using Chemical Data Assimilation

Thursday, 26 January 2017: 4:00 PM
607 (Washington State Convention Center )
Rajesh Kumar, NCAR, Boulder, CO; and L. Delle Monache, S. Alessandrini, P. E. Saide, J. Bresch, Z. Liu, G. Pfister, D. P. Edwards, I. V. Djalalova, B. Baker, P. Lee, Y. Tang, and J. Wilczak

State and local air quality forecasters across the U. S. use the National Oceanic and Atmospheric Administration (NOAA) operational National Air Quality Forecasting Capability (NAQFC) as one of the key tools to protect the public from adverse air pollution related health effects by dispensing timely information about air pollution episodes. In this project funded by the National Aeronautics and Space Administration (NASA), we aim to enhance the decision making process by improving the accuracy of NAQFC short-term predictions of ground-level ozone and particulate matter less than 2.5 µm in diameter (PM2.5) by exploiting NASA Earth Science Data with chemical data assimilation. The main objective of this effort is to improve initialization of the NAQFC that is based on the Community Multiscale Air Quality (CMAQ) model, via chemical data assimilation of multiple satellite retrieval products within the Community Gridpoint Statistical Interpolation (GSI) system. We have developed a framework in GSI to assimilate retrievals of aerosol optical depth from the NASA Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS) and surface observations of PM2.5 (and possibly of ground-level ozone) from selected stations of the AIRNow and the Interagency Monitoring of Protected Visual Environments (IMPROVE) air quality observing networks. Specifically, we have developed capabilities within GSI to read/write CMAQ data, a forward operator that calculates aerosol optical depth at 550 nm from CMAQ aerosol chemical composition and an adjoint of the forward operator that calculates the sensitivity of AOD to aerosol chemical composition. A generalized background error covariance program called “GEN_BE” has been extended to calculate background error covariance using CMAQ output. These developments are being tested currently. We also plan to assimilate carbon monoxide from the Measurement of Pollution in the Troposphere (MOPITT) and nitrogen dioxide from the Ozone Monitoring Instrument (OMI). This presentation will discuss these developments and results in detail.
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