Global and regional evaluation of over-land spectral aerosol optical depth retrievals from SeaWiFS
1Goddard Earth Sciences Technology And Research (GESTAR), Universities Space Research Association (USRA), Columbia, Maryland, USA
2NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
3Science Systems Applications Inc., Lanham, Maryland, USA
4Department of Atmospheric and Environmental Sciences, Gangneung-Wonju National University, Gangneung, Gangwon-do, Korea
5Department of Atmospheric Sciences, University of North Dakota, Grand Forks, North Dakota, USA
Abstract. This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over land. First, the data are validated against Aerosol Robotic Network (AERONET) direct-sun AOD measurements, and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-yr (1997–2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where SeaWiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record is suitable for quantitative scientific use.