Integrating satellite and surface network observations into a 3-D Community Multi-scale Air Quality (CMAQ) Modeling System—a first step towards generating atmospheric chemistry reanalysis field for the contiguous Unites States

The National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR) reanalysis products have been widely used since their introduction. There is a similar need to have a gridded data set that best represents the atmospheric chemistry for air quality, climate, epidemiology, and many other fields in their research and policy related studies. Ozone and PM2.5 forecasts for the U.S. have been operationally and experimentally generated using a 3-D Community Multi-scale Air Quality (CMAQ) Modeling System under the auspices of the National Air Quality Forecast Capability (NAQFC) program by the National Oceanic and Atmospheric Administration (NOAA) for the contiguous Unites States (CONUS) since 2006. While NAQFC is capable of providing useful air quality forecasts, the accuracy of the products is limited substantially by the lack of a real-time emission modeling or constraint provided through chemical data assimilation implementation. In a first attempt to generate an atmospheric chemistry reanalysis field, the NAQFC experimental products will be improved by integrating the AIRNow surface network observations and MODIS (MOderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) with the 3-D CMAQ model results. July 2011 is chosen as a test period to coincide with the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field experiment. Different assimilation strategies for the atmospheric chemistry reanalysis are investigated utilizing the DISCOVER-AQ measurements. In the end, a month of 3-D gridded atmospheric chemistry reanalysis covering the contiguous Unites States is generated.