Global Aerosol Forecasting System Applications to Houston/Costa Rica Aura Validation Experiments

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 CO2 • Implemented modules for CO and CO2 forecasting capability based on Code 613.3 PCTM • CO • sources from fossil fuel, biofuel, and biomass burning • chemical production from NMHC and CH4 oxidation, chemical loss to OH oxidation • oxidants for chemistry based on GEOS-CHEM/GMI and CMDL GLOBALVIEW-CH4 • CO2 • sources from biosphere, ocean, and fossil fuel following Transcom 3 protocol, and biomass burning Collaborators: Huisheng Bian, Randy Kawa, Code 613.3

5. GFED • Biomass Burning Emissions • QFED: Daily biomass burning emissions of aerosols, CO, CO2, and SO2 • Real-time MODIS firecounts from Aqua and Terra • Emission factors calibrated against Global Fire Emission Database (GFED) QFED Collaborators: Jim Collatz, Code 614.4, Mian Chin, Tom Kucsera, Code 613.3

6. Chemical Forecasts • Aerosols, CO, and CO2 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 0.5o 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 Aircraft Model Evaluation • Analysis of CRAVE mission data is preliminary

10. September 2000 (SAFARI-2000) Organic Carbon Mass Loadings Dust Sea salt GEOS-4 GOCART GEOS-4 GOCART Emis 4310 3150 Emis 6640 9740 Sed 2970 2470 Sed 3070 6000 Dep 370 120 Dep 1940 470 GOCART Wet 960 580 Wet 1620 3260 OC BC GEOS-4 GOCART GEOS-4 GOCART Emis 77 79 Emis 13 14 Dep 35 16 Dep 6 3 Wet 42 62 Wet 7 10 GEOS-4 SO4 GEOS-4 GOCART Emis 10 7 Dep 38 17 Wet 147 128 pLiq 153 80 pGas 22 58 Budgets for Year 2000 Reflect differences in meteorology, resolution, parameterizations, and ordering of processes 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

11. Model Evaluation September 2000 (SAFARI-2000) Monthly Mean AOT • 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 MODIS GEOS-4 unsampled GEOS-4 sampled like MODIS

12. Data Assimilation Weaver et al., 2006, JAS, in review • 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 GOCART Analysis AOT AERONET AOT Collaborators: Clark Weaver, Omar Torres, Amelia Colarco, Code 613.3

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 GSFC Capo Verde Mongu Model +/- 1 AERONET +/- 1