Uncertainties in satellite remote sensing of aerosols and impact on monitoring its long-term trend: a review and perspective

Abstract

Abstract. As a result of increasing attention paid to aerosols in climate studies, numerous global satellite aerosol products have been generated. Aerosol parameters and underlining physical processes are now incorporated in many general circulation models (GCMs) in order to account for their direct and indirect effects on the earth's climate, through their interactions with the energy and water cycles. There exists, however, an outstanding problem that these satellite products have substantial discrepancies, that must be lowered substantially for narrowing the range of the estimates of aerosol's climate effects. In this paper, numerous key uncertain factors in the retrieval of aerosol optical depth (AOD) are articulated for some widely used and relatively long satellite aerosol products including the AVHRR, TOMS, MODIS, MISR, and SeaWiFS. We systematically review the algorithms developed for these sensors in terms of four key elements that influence the quality of passive satellite aerosol retrieval: calibration, cloud screening, classification of aerosol types, and surface effects. To gain further insights into these uncertain factors, the NOAA AVHRR data are employed to conduct various tests, which help estimate the ranges of uncertainties incurred by each of the factors. At the end, recommendations are made to cope with these issues and to produce a consistent and unified aerosol database of high quality for both environment monitoring and climate studies.

New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

“…(4) is a measure of the sensitivity of the algorithm to the assumed aerosol microphysical properties. This is an important factor affecting retrieval uncertainty (Li et al, 2009;Povey and Grainger, 2015), but, as mentioned in the introduction, there are many other sources of error not accounted for in this approach. Hence, the AOD uncertainty obtained from the algorithm should not be interpreted as a measure of how far the retrieved AOD deviates from the truth.…”

Vertical and horizontal variation of aerosol number size distribution in the boreal environment

“…The system provides aerosol optical depth, volume backscatter coefficient, cross section, and depolarization profiles with high temporal and vertical resolution (Eloranta 2005). These quantities can be used for example in identifying the dominant aerosol type for different layers using a combination of lidar ratio and depolarization (Li et al 2009, Petzold et al 2009). 15…”

A decadal regional and global trend analysis of the aerosol optical depth using a data-assimilation grade over-water MODIS and Level 2 MISR aerosol products

“…IPCC) the decadal variations of atmospheric aerosol loadings are gaining increased interest from both the scientific and policy community (e.g. Kishcha et al, 2007;Mishchenko et al, 2007aMishchenko et al, , 2009Remer et al, 2008;Zhao et al, 2008;Li et al, 2009a;Herman et al, 2009;Li et al, 2009b;Streets et al, 2009;Yu et al, 2009;Cermak et al, 2010). Such studies are plagued by calibration issues (both within and between multiple sensors), signal to noise issues, and the aforementioned retrieval biases (e.g., Zhang and Reid, 2006;Li et al, 2009b).…”

“…Kishcha et al, 2007;Mishchenko et al, 2007aMishchenko et al, , 2009Remer et al, 2008;Zhao et al, 2008;Li et al, 2009a;Herman et al, 2009;Li et al, 2009b;Streets et al, 2009;Yu et al, 2009;Cermak et al, 2010). Such studies are plagued by calibration issues (both within and between multiple sensors), signal to noise issues, and the aforementioned retrieval biases (e.g., Zhang and Reid, 2006;Li et al, 2009b). For example, using 23 years of Advanced Very High Resolution Radiometer (AVHRR) data, Mishchenko et al (2007b) studied the averaged aerosol optical depth (AOD) over global ocean and found a significant decreasing trend in AOD from 1991 to 2005 (GACP, Mishchenko et al, 2007b).…”