1. Global Aerosol Forecasting System Applications to Houston/Costa Rica Aura Validation Experiments Arlindo da Silva Global Modeling and Assimilation Office, Code 610.1 Peter Colarco Atmospheric Chemistry and Dynamics Branch, Code 613.3

2. Goals Incorporate state of the art aerosol and chemistry packages into the GEOS-5 global climate model and data assimilation system Provide to the NASA and wider science community “chemical weather” forecasts Forecasts produced in same modeling framework used to support funded investigations of aerosol effects on climate and assimilation of A-Train aerosol products -Aerosol/Chemistry packages are ESMF components integrated into MAP modeling environment

3. Aerosols Developed an implementation of the GOCART aerosol module for major tropospheric aerosol species Collaborator: Mian Chin, Code 613.3

4. CO and CO 2 Implemented modules for CO and CO 2 forecasting capability based on Code 613.3 PCTM CO -sources from fossil fuel, biofuel, and biomass burning -chemical production from NMHC and CH 4 oxidation, chemical loss to OH oxidation -oxidants for chemistry based on GEOS-CHEM/GMI and CMDL GLOBALVIEW-CH4 CO 2 -sources from biosphere, ocean, and fossil fuel following Transcom 3 protocol, and biomass burning Collaborators: Huisheng Bian, Randy Kawa, Code 613.3

5. Biomass Burning Emissions QFED: Daily biomass burning emissions of aerosols, CO, CO 2, and SO 2 Real-time MODIS firecounts from Aqua and Terra Collaborators: Jim Collatz, Code 614.4, Mian Chin, Tom Kucsera, Code 613.3 Emission factors calibrated against Global Fire Emission Database (GFED) GFED QFED

6. Chemical Forecasts Aerosols, CO, and CO 2 currently transported “on-line” in current GEOS-4 global climate model -Same modules can also be run in GMAO’s next generation GEOS-5 system -Depending on mission requirements other packages are available, e.g, full stratospheric chemistry as used for PAVE -GMI combined tropospheric/stratospheric chemistry modules under integration (with SIVO) Model is run in global domain, 1° x 1.25 ° horizontal resolution, 55 vertical levels extending to 85 km -GEOS-5 version will be run at 0.5 o resolution 5-day forecasts run twice daily at 0Z and 12Z with atmospheric state from GMAO’s First Look Data Assimilation System Collaborators: GMAO Operations Group

7. Aura Validation Experiment Support http://code613-3.gsfc.nasa.gov/People/Colarco/CRAVE Please also see the HyperWall display in the Back, soon in the Bldg. 33 Lobby!

8. Aura Validation Experiment Products Forecast animations of aerosol optical thickness and tracer mixing ratios Forecast and analysis static plots of aerosol optical thickness and tracer mixing ratio Vertical cross-section “curtain plots” of tracer mixing ratio along north-south and east-west flight trajectories

9. Model Evaluation Analysis of CRAVE mission data is preliminary Model Aircraft

10. Model Evaluation Analysis of CRAVE mission data is preliminary Aerosols are being compared to previous off-line GOCART runs -GOCART is run at 2º x 2.5º resolution with GEOS-3 meteorology 5822pGas 80153pLiq 128147Wet 1738Dep 710Emis GOCARTGEOS-4 SO4 580960Wet 120370Dep 24702970Sed 31504310Emis GOCARTGEOS-4 Dust 32601620Wet 4701940Dep 60003070Sed 97406640Emis GOCARTGEOS-4 Sea salt 6242Wet 1635Dep 7977Emis GOCARTGEOS-4 OC 107Wet 36Dep 1413Emis GOCARTGEOS-4 BC Budgets for Year 2000 Reflect differences in meteorology, resolution, parameterizations, and ordering of processes September 2000 (SAFARI-2000) Organic Carbon Mass Loadings GOCART GEOS-4

11. Model Evaluation Analysis of CRAVE mission data is preliminary Aerosols are being compared to previous off-line GOCART runs Aerosols are being compared to AERONET and MODIS datasets -Sampling of model and satellite data in a consistent manner is important for comparison September 2000 (SAFARI-2000) Monthly Mean AOT MODIS GEOS-4 unsampled GEOS-4 sampled like MODIS

12. Data Assimilation MODIS Assimilation: -1D-Var assimilation of radiances (MODIS/OMI) -Observation bias corrections and source defect estimated by means of forecast bias estimates Combined MODIS/OMI Assimilation: -Improve estimation of absorption by using OMI UV/Visible channels -1D-Var assimilation of MODIS and OMI radiances -Monitoring of OMI radiances and assimilated aerosol fields Collaborators: Clark Weaver, Omar Torres, Amelia Colarco, Code 613.3 AERONET AOT GOCART Analysis AOT Weaver et al., 2006, JAS, in review

13. Future Directions Continue support for other NASA missions: INTEX, AMMA Funded and proposed work for data assimilation of MODIS, OMI, SAGE,CALIPSO, GLAS, etc., radiance and aerosol products Pending ROSES/DECISIONS proposal for GFS-GOCART -This project will give NCEP aerosol forecasting capabilities Funded work under MAP for incorporation of aerosol and cloud microphysics for improved aerosol composition, direct effect, and indirect effect estimations

14. GEOS-4 Model Description 1.25° x 1° horizontal, 32 vertical levels GSFC dynamical core and assimilated meteorology NCAR physics GOCART aerosols:dust (5 bins), seasalt (5 bins), sulfate, organic and black carbon GSFCCapo VerdeMongu Model +/- 1  AERONET +/- 1 