HR: 14:40h
AN: A53H-05    [Abstracts]
TI: Impact of MODIS AOD Assimilation on Regional Aerosol Predictions
AU: * Kittaka, C
EM: Chieko.Kittaka-1@nasa.gov
AF: Science Systems and Applications INC., NASA Langley Research Center, Hampton, VA 23681, United States
AU: Pierce, R B
EM: Brad.Pierce@noaa.gov
AF: National Oceanic and Atmospheric Administration, 1225 West Dayton Street, Madison, WI 53706, United States
AU: Schaack, T
EM: todd.schaack@ssec.wisc.edu
AF: University of Wisconsin - Madison, Space Science and Engineering Center 1225 West Dayton Street, Madison, WI 53706, United States
AU: Al-Saadi, J
EM: j.a.al-saadi@nasa.gov
AF: NASA Langley Research Center, NASA Langley Research Center, Hampton, VA 23681, United States
AU: Soja, A
EM: Amber.J.Soja@nasa.gov
AF: National Institute of Aerospace, NASA Langley Research Center, Hampton, VA 23681, United States
AU: Winker, D
EM: david.m.winker@nasa.gov
AF: NASA Langley Research Center, NASA Langley Research Center, Hampton, VA 23681, United States
AU: Szykman, J
EM: james.j.szykman@nasa.gov
AF: US Environmental Protection Agency, NASA Langley Research Center, Hampton, VA 23681, United States
AU: Tripoli, G
EM: tripoli@aos.wisc.edu
AF: University of Wisconsin - Madison, Department of Atmospheric and Oceanic Sciences 1225 West Dayton Street, Madison, WI 53706, United States
AB: Direct Broadcast real-time retrievals of Aerosol Optical Depth (AOD) from the MODIS instrument onboard the Terra satellite have been used for monitoring regional particle pollution in the US on a daily basis. AOD provides column integrated aerosol loading which is supplemental to the ground-based in-situ measurements. Monitoring atmospheric loadings of dust and smoke and their subsequent transport using MODIS AOD has been found to be particularly effective, because these aerosol species are frequently transported aloft and not observed by ground-based in-situ networks. Air quality models have become a powerful tool to diagnose and predict three- dimensional distributions of aerosol species. The model performance with dust and smoke is, however, not as good as that with sulfate aerosol. This is because dust and smoke events are episodic and it is difficult to characterize their emissions. Consequently, these aerosol constituents introduce large uncertainties in modeled aerosol distributions. Assimilation of MODIS AOD within an aerosol forecast model makes it possible not only to understand the current aerosol distribution but also to predict it with constraints from the satellite observations. This study presents an assessment of the improvement in aerosol predictions due to the incorporation of MODIS AOD in a regional aerosol forecast model. The Real-time Air Quality Modeling System (RAQMS) with a MODIS AOD assimilation is used to simulate the aerosol distributions for Aug - Oct, 2006, when dust is being transported from Sahara to the Gulf of Mexico and smoke is emitted from biomass burning over the Pacific Northwest. The model performance is evaluated using the CALIPSO observations for assessing vertical profiles and the EPA AIRNow data for assessing the surface distribution. An impact of the MODIS AOD assimilation on each aerosol species is analyzed. Further improvement of the MODIS AOD assimilation is also discussed.
DE: 0300 ATMOSPHERIC COMPOSITION AND STRUCTURE
DE: 0345 Pollution: urban and regional (0305, 0478, 4251)
DE: 0365 Troposphere: composition and chemistry
DE: 0368 Troposphere: constituent transport and chemistry
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting