%0 Journal Article
%T Retrieval of aerosol optical depth over land surfaces from AVHRR data
%A L. Mei
%A Y. Xue
%A A. A. Kokhanovsky
%A W. von Hoyningen-Huene
%J Atmospheric Measurement Techniques Discussions
%D 2013
%I Copernicus Publications
%R 10.5194/amtd-6-2227-2013
%X The Advanced Very High Resolution Radiometer (AVHRR) radiance data provide a global, long-term, consistent time series having high spectral and spatial resolution and thus being valuable for the retrieval of surface spectral reflectance, albedo and surface temperature. Long term time series of such data products are necessary for studies addressing climate change, sea ice distribution and movement, and ice sheet coastal configuration. These data have also been used to retrieve aerosol properties over ocean and land surfaces. However, the retrieval of aerosol over land and land surface albedo are challenging because of the information content of the measurement is limited and the inversion of these data products being ill defined. Solving the radiative transfer equations requires additional information and knowledge to reduce the number of unknowns. In this contribution we utilise an empirical linear relationship between the surface reflectances in the AVHRR channels at wavelengths of 3.75 ¦Ìm and 2.1 ¦Ìm, which has been identified in Moderate Resolution Imaging Spectroradiometer (MODIS) data. Next, following the MODIS dark target approach, the surface reflectance at 0.64 ¦Ìm was obtained. The comparison of the estimated surface reflectance at 0.64 ¦Ìm with MODIS reflectance products (MOD09) shows a strong correlation (R = 0.7835). Once this was established, the MODIS "dark-target" aerosol retrieval method was adapted to Advanced Very High Resolution Radiometer (AVHRR) data. A simplified Look-Up Table (LUT) method, adopted from Bremen AErosol Retrieval (BAER) algorithm, was used in the retrieval. The Aerosol Optical Depth (AOD) values retrieved from AVHRR with this method compare favourably with ground-based measurements, with a correlation coefficient R = 0.861 and Root Mean Square Error (RMSE) = 0.17. This method can be easily applied to other satellite instruments which do not have a 2.1 ¦Ìm channel, such as those currently planned to geostationary satellites.
%U http://www.atmos-meas-tech-discuss.net/6/2227/2013/amtd-6-2227-2013.pdf