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FY10 GOES-R3 Project Review Title Page

FY10 GOES-R3 Project Review Title Page. Title : ABI Proxy data studies: Regional Assimilation of SEVIRI Total Column Ozone Project Type : Product Utilization Proposal Status : Third Year Duration : 3 years Leads: R. Bradley Pierce, NOAA/NESDIS Other Participants : Chris Schmidt (CIMSS)

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FY10 GOES-R3 Project Review Title Page

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  1. FY10 GOES-R3 Project Review Title Page • Title: ABI Proxy data studies: Regional Assimilation of SEVIRI Total Column Ozone • Project Type: Product Utilization Proposal • Status: Third Year • Duration: 3 years • Leads: • R. Bradley Pierce, NOAA/NESDIS • Other Participants: • Chris Schmidt (CIMSS) • Todd Schaack (SSEC) • Allen Lenzen (SSEC)

  2. Project Summary • This project will use the WRF-CHEM1 regional chemical model coupled to the RAQMS global chemical analysis2 to evaluate the impacts of ABI like Tropospheric Column Ozone (TCO) retrievals on Air Quality forecasts. SEVIRI measurements will be used as ABI proxy data. • Results from these studies will provide guidance and develop capabilities for operational use of GOES-R TCO within the NOAA Operational AQ forecasting system (NAM-CMAQ). • This study will also demonstrate Committee on Earth Observation Satellites (CEOS) atmospheric composition constellation concepts contributing to the space component of the Global Earth Observing System of Systems (GEOSS) Air Quality Assessment and Forecasting Near Term Opportunity (NTO) 1Grell, G. A., et al., Fully coupled online chemistry within the WRF model, Atmos. Environ., 39, 6957-6975, 2005. 2Pierce, R. B., et al. (2007), Chemical data assimilation estimates of continental U.S. ozone and nitrogen budgets during the Intercontinental Chemical Transport Experiment–North America, J. Geophys. Res., 112, D12S21doi:10.1029/2006JD007722.

  3. Interactions with AWG • This project evaluates the impacts of assimilation of the GOES-R Total Column Ozone (TCO) retrieval, applied to SEVIRI radiances, developed by the GOES-R AWG (Chris Schmidt, CIMSS) • This project uses GOES-R Biomass Burning Emissions alogrithms, applied to SEVIRI radiances, developed by the GOES-R AWG (Shobha Kondragunta, STAR) • This project provided 36km WRF-CHEM ozone and aerosol analyses (constrained with SEVIRI TCO and MODIS Aerosol Optical Depth) that were used for initial and boundary conditions for subsequent 12km and 4km high resolution WRF-CHEM SEVIRI domain simulations. The 4km WRF-CHEM SEVIRI simulations were subsequently used with the CRTM to generate synthetic radiances for delivery to AIT for proxy data (Fuzhong Weng, STAR)

  4. First Year Accomplishments • WRF-CHEM/CRTM ported to CIMSS computing platforms • RAQMS/WRF-CHEM Linkage developed and tested • RAQMS/WRF-CHEM/CRTM Linkage developed and tested • Developed Radiance based observation operator for SEVIRI statistical TCO retrieval Second Year Accomplishments WRF-CHEM 36km SEVIRI domain • NESDIS SEVIRI fire emissions incorporated into WRF-CHEM emissions preprocessor • Baseline (no assimilation) simulation completed • SEVIRI Cloud clearing and diurnal bias correction algorithms developed • Initial (OI) SEVIRI assimilation studies testing appropriate means of assimilating SEVIRI TCO completed

  5. Unexpected Results • NO assimilation and bias corrected SEVIRI TCO assimilation results vs SHADOWS ozonesonde data. No Assimilation RAQMS MLS Analysis Large Bias

  6. Unexpected Results (cont) • SEVIRI assimilation increases Ozone mixing ratio in lower stratosphere to compensate for underestimate in ozone at 200mb Bias Corrected Assimilation RAQMS MLS Analysis Compensating increase Large Bias

  7. Unexpected Results (cont) • Underestimates in upper tropospheric Ozone lead to negative impacts when SEVIRI TCO is assimilated • Need to incorporate Lightning NOx source into WRF-CHEM before valid assimilation studies are conducted. • Use Price and Rind (Mon. Weather Rev., 122, 1930-1939, 1994) scheme currently implemented into RAQMS. RAQMS 200mb NO2 (2006-08-23, 18Z) WRF-CHEM 200mb NO2 (2006-08-23, 18Z)

  8. Unexpected Results (cont) • Lack of upper tropospheric ozone production down wind from Lightning NOx emissions leads to underestimates in WRF-CHEM upper tropospheric ozone over Equatorial and Southern Africa. RAQMS 200mb O3 (2006-08-23, 18Z) WRF-CHEM 200mb O3 (2006-08-23, 18Z)

  9. Third Year Accomplishments • Price and Rind Lightning source introduced into WRF-CHEM. • Baseline (no assimilation) simulation and OI SEVIRI assimilation studies redone with Lightning NOx source. • Regional GSI SEVIRI ozone assimilation capability developed based on existing global OMI ozone assimilation (Craig Long, NCEP) • RAQMS based error covariance statistics generated for regional GSI SEVIRI ozone assimilation (necessary since existing GFS based error covariance statistics don’t reflect tropospheric ozone production). Unexpected Results • Full cycling of GSI/WRF-CHEM on CIMSS cluster failed due to memory constraints. GSI/WRF-CHEM SEVIRI ozone assimilation experiments require NCSA computing environment.

  10. Third Year Accomplishments (cont) • NO Lightning NOx vs Lightning NOx results vs SHADOWS ozonesonde data. No Lightning NOx RAQMS MLS Analysis

  11. Third Year Accomplishments (cont) • Incorporation of Lightning NOx into WRF-CHEM reduces upper tropospheric biases but also increases lower stratospheric biases relative to SHADOWS ozonesonde data. Lightning NOx RAQMS MLS Analysis Impact of LNOx

  12. Third Year Accomplishments (cont) • GSI SEVIRI assimilation improves lower stratospheric biases relative to SHADOWS ozonesonde data. Lightning NOx/GSI SEVIRI ASSIM RAQMS MLS Analysis Impact of SEVIRI

  13. Experiment RMS (%) Bias (%) WRF-CHEM NO ASSIM NO LNOX 30.19 -18.44 WRF-CHEM NO ASSIM LNOX 30.28 10.06 WRF-CHEM SDF SEVIRI TCO 28.39 11.00 WRF-CHEM GSI SEVIRI TCO 30.81 4.31 RAQMS 21.24 -12.25 Third Year Accomplishments (cont) • Summary Statistics (Averaged from Surface to 50mb) Note: WRF-CHEM averaged statistics arise due to balance between compensating errors in the lower stratosphere/upper troposphere. RAQMS averaged statistics arise due to underestimates in troposphere. Underestimates in the depth of convective exchange of low O3 marine boundary layer air may account for compensating errors in WRF-CHEM.

  14. Recommendations for follow on research • We have a newly funded JCSDA Science Development & Implementation (JSDI) proposal to implement and evaluate GOES and OMI Total Column Ozone assimilation using GSI within the Operational NAM-CMAQ Air Quality Forecast model (with Daewon Byun, NOAA/OAR/ARL and Jeffery McQueen,NWS/EMC/MMB). • We intend to submit an FY11 GOES-R Risk Reduction proposal to develop and test GSI and Ensemble Kalman Filter (ENKF) assimilation of MODIS Aerosol Optical Depth (AOD) and SEVIRI volcanic ash retrievals within WRF-CHEM (with Georg Grell, NOAA/OAR/ESRL, Mike Pavolonis, NOAA/NESDIS/STAR, Jason Otkin, UW/CIMSS, and Avelino Arellando, NCAR/ACD) • Need to investigate impact of upper troposphere/lower stratospshere vertical resolution and 50mb upper boundary condition on WRF-CHEM ozone profiles.

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