A21A-0009
Verification of CMAQ modeling with Discover-AQ campaigns against measurements and efficacy of emission inversion modeling

Tuesday, 15 December 2015
Poster Hall (Moscone South)
Pius Lee1, Youhua Tang2, Li Pan3, James Szykman4, Todd Plessel5, Daniel Tong3 and Quanhua Liu1, (1)NOAA College Park, NOAA Center for Weather and Climate Prediction, College Park, MD, United States, (2)NOAA Camp Springs, Camp Springs, MD, United States, (3)Cooperative Institute for Climate and Satellites University of Maryland, College Park, MD, United States, (4)US EPA, ORD, National Exposure Research Laboratory, Hampton, VA, United States, (5)US EPA / Lockheed, Research Triangle Park, NC, United States
Abstract:
NASA has led a few DISCOVER-AQ campaigns in recent years: (1) Baltimore/Washington in July 2011, (2) Central valley, CA in January – February 2013, (3) Houston, TX in September 2013, and co-led with NCAR (4) Front Range, CO in July – August 2014. NOAA Air Resources Laboratory has participated in all these campaigns in the role of air quality forecasting support. For some of these campaigns post analyses were performed with the possible help of after-the-fact observed data from satellite retrieved radiances to constrain emissions through the Community Radiative Transfer Model (CRTM) developed at the Joint Center for Satellite Data Assimilation. It is our experience that despite the vastly different chemical regime, season, terrain, and meteorological conditions of the domain for the campaigns, we found that the emissions input and the U.S. EPA Community Air Quality model (CMAQ), the forecasting chemical transport model used to generate the forecast had severely under-estimated formaldehyde (HCHO), and carbon monoxide (CO) aloft between surface and the middle of the free troposphere – 500 hPa. Post analyses point to two strong suspects of these deficiencies: (a) emission projection fed into CMAQ, and/or (b) erroneously fast removal of the species. We investigate both of these potential deficiencies and for the former possible reason we looked into data assimilation and possible inverse modeling to adjust emission projection for CMAQ. We will elaborate more on the CRTM which plays a critical role in this aspect of remedying erroneous inputs to CMAQ.

In addition, we will utilize some satellite products to improve initial fields of aerosols and CO for air quality forecasting. Suomi NPP VIIRS aerosol optical depth (AOD) environmental data record (EDR) delivers global aerosol information daily. The Unique CrIS/ATMS Processing System (NUCAPS) operationally generates vertical profiles of atmospheric carbonate EDRs (CO, CO2, and CH4) and ozone during day and night. The AOD can be assimilated by using the CRTM. The carbonate EDRs and ozone EDR can be directly assimilated.