Aerosol optical depth retrieval over snow using AATSR data

Abstract

Aerosol observations over the Arctic are important because of the effects of aerosols on Arctic climate, such as their direct and indirect effects on the Earth's radiation balance and on snow albedo. Although information on aerosol properties is available from ground-based measurements, passive remote sensing using satellite measurements would offer the advantage of large spatial coverage with good temporal resolution, even though, due to light limitations, this is only available during the Arctic summer. However, aerosol optical depth (AOD) retrieval over the Arctic region is a great challenge due to the high reflectance of snow and ice and due to the high solar zenith angle. In this article, we describe a retrieval algorithm using Advanced Along-Track Scanning Radiometer (AATSR) data, a radiometer flying on the European Space Agency (ESA) Environmental Satellite (ENVISAT), which offers two views (near nadir and at 55° forward) at seven wavelengths in the visible thermal-infrared (VIS-TIR). The main idea of the Dual-View Multi-Spectral (DVMS) approach is to use the dual view to separate contributions to reflectance measured at the top of the atmosphere (TOA) due to atmospheric aerosol and the underlying surface. The algorithm uses an analytical snow bidirectional reflectance distribution function (BRDF) model for the estimation of the ratio of snow reflectances in the nadir and forward views, as well as an estimate of the atmospheric contribution to TOA reflectance obtained using the dark pixel method over the adjacent ocean surface, assuming that this value applies over nearby land surfaces in the absence of significant sources across the coastline. An iteration involving all four AATSR wavebands in the visible near-infrared (VIS-NIR) is used to retrieve the relevant information. The method is illustrated for AATSR overpasses over Greenland with clear sky in April 2009. Comparison of the retrieved AOD with AErosol Robotic Network (AERONET) data shows a correlation coefficient of 0.75. The AODs retrieved from AATSR using the DVMS approach and those obtained from AERONET data show similar temporal trends, but the AERONET results are more variable and the highest AOD values are mostly missed by the DVMS approach. Limitations of the DVMS method are discussed. The pure-snow BRDF model needs further correction in order to obtain a better estimation for mixtures of snow and ice.

Acknowledgements

This work was partly supported by the Ministry of Science and Technology (MOST) of China under Grant No. 2009CB723906, the Major International Cooperation and Exchange Project of National Natural Science Foundation of China (Grant No. 41120114001), and the National Natural Science Foundation of China (NSFC) under Grants 41101323. The contribution of Gerrit de Leeuw is supported by CRAICC (Cryosphere-atmosphere interactions in a changing Arctic climate), which is part of the Top-level Research Initiative (TRI) of the joint Nordic research and innovation initiative. The author would also like to thank Dr Andrew M. Sayer from NASA's Goddard Space Flight Center for providing codes to read AATSR data. L.L. Mei would like to thank the Director Prize from the Institute of Remote Sensing Applications of the Chinese Academy of Sciences. AATSR data were available through ESA (http://ats-merci-uk.eo.esa.int:8080/merci/welcome.do). Many thanks are due to the PI investigators from the AERONET sites used in this article. Thanks also for the NECP data from http://www.ncep.noaa.gov/.