Synthesis of satellite (MODIS), aircraft (ICARTT), and surface (IMPROVE, EPA-AQS, AERONET) aerosol observations over eastern North America to improve MODIS aerosol retrievals and constrain surface aerosol concentrations and sources

• Published in: Journal of Geophysical Research Vol. 115; no. D14
• Main Authors: Drury, Easan, Jacob, Daniel J., Spurr, Robert J. D., Wang, Jun, Shinozuka, Yohei, Anderson, Bruce E., Clarke, Antony D., Dibb, Jack, McNaughton, Cameron, Weber, Rodney
• Format: Journal Article
• Language: English
• Published: Washington, DC Blackwell Publishing Ltd 27.07.2010; American Geophysical Union
• Subjects: aerosol observations; Aerosols; Air pollution; Aircraft; Atmospheric aerosols; Atmospheric sciences; Chemical transport; Climate change; Earth; Earth sciences; Earth, ocean, space; ENVIRONMENTAL SCIENCES; Exact sciences and technology; Geophysics; MODIS; Optical properties; Organic carbon; Particulate matter; PM2.5; Radiation; Remote sensing; Sulfates; United States; satellites; synthesis; models; aerosols; Bias; Consistency; Summer; Satellite observation; concentration; global; transport; slopes; North America; platforms; Particle size distribution; optical properties; instruments; Clear sky; correlation; Fine particle; regression; Aircraft observation; Optical thickness; Reflectance
• ISSN: 0148-0227; 2169-897X; 2156-2202; 2169-8996
• DOI: 10.1029/2009JD012629

We use an ensemble of satellite (MODIS), aircraft, and ground‐based aerosol observations during the ICARTT field campaign over eastern North America in summer 2004 to (1) examine the consistency between different aerosol measurements, (2) evaluate a new retrieval of aerosol optical depths (AODs) and inferred surface aerosol concentrations (PM2.5) from the MODIS satellite instrument, and (3) apply this collective information to improve our understanding of aerosol sources. The GEOS‐Chem global chemical transport model (CTM) provides a transfer platform between the different data sets, allowing us to evaluate the consistency between different aerosol parameters observed at different times and locations. We use an improved MODIS AOD retrieval based on locally derived visible surface reflectances and aerosol properties calculated from GEOS‐Chem. Use of GEOS‐Chem aerosol optical properties in the MODIS retrieval not only results in an improved AOD product but also allows quantitative evaluation of model aerosol mass from the comparison of simulated and observed AODs. The aircraft measurements show narrower aerosol size distributions than those usually assumed in models, and this has important implications for AOD retrievals. Our MODIS AOD retrieval compares well to the ground‐based AERONET data (R = 0.84, slope = 1.02), significantly improving on the MODIS c005 operational product. Inference of surface PM2.5 from our MODIS AOD retrieval shows good correlation to the EPA‐AQS data (R = 0.78) but a high regression slope (slope = 1.48). The high slope is seen in all AOD‐inferred PM2.5 concentrations (AERONET: slope = 2.04; MODIS c005: slope = 1.51) and could reflect a clear‐sky bias in the AOD observations. The ensemble of MODIS, aircraft, and surface data are consistent in pointing to a model overestimate of sulfate in the mid‐Atlantic and an underestimate of organic and dust aerosol in the southeastern United States. The sulfate overestimate could reflect an excessive contribution from aqueous‐phase production in clouds, while the organic carbon underestimate could possibly be resolved by a new secondary pathway involving dicarbonyls.