Abstract. The evaluation of aerosol radiative effect on broadband hemispherical solar flux is often performed using simplified spectral and directional scattering characteristics of atmospheric aerosol and underlying surface reflectance. In this study we present a rigorous yet fast computational tool that accurately accounts for detailed variability of both spectral and angular scattering properties of aerosol and surface reflectance in calculation of direct aerosol radiative effect. The tool is developed as part of the GRASP (Generalized Retrieval of Aerosol and Surface Properties) project. We use the tool to evaluate instantaneous and daily average radiative efficiencies (radiative effect per unit aerosol optical thickness) of several key atmospheric aerosol models over different surface types. We then examine the differences due to neglect of surface reflectance anisotropy, nonsphericity of aerosol particle shape and accounting only for aerosol angular scattering asymmetry instead of using full phase function. For example, it is shown that neglecting aerosol particle nonsphericity causes mainly overestimation of the aerosol cooling effect and that magnitude of this overestimate changes significantly as a function of solar zenith angle (SZA) if the asymmetry parameter is used instead of detailed phase function. It was also found that the nonspherical–spherical differences in the calculated aerosol radiative effect are not modified significantly if detailed BRDF (bidirectional reflectance distribution function) is used instead of Lambertian approximation of surface reflectance. Additionally, calculations show that usage of only angular scattering asymmetry, even for the case of spherical aerosols, modifies the dependence of instantaneous aerosol radiative effect on SZA. This effect can be canceled for daily average values, but only if sun reaches the zenith; otherwise a systematic bias remains. Since the daily average radiative effect is obtained by integration over a range of SZAs, the errors vary with latitude and season. In summary, the present analysis showed that use of simplified assumptions causes systematic biases, rather than random uncertainties, in calculation of both instantaneous and daily average aerosol radiative effect. Finally, we illustrate application of the rigorous aerosol radiative effect calculations performed as part of GRASP aerosol retrieval from real POLDER/PARASOL satellite observations.
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Theoretical Uncertainty Analysis of Satellite Retrieved Aerosol Optical Depth Associated with Surface Albedo and Aerosol Optical Properties
Deriving aerosol optical depth (AOD) from space-borne observations is still challenging due to uncertainties associated with sensor calibration drift, cloud screening, aerosol type classification, and surface reflectance characterization. As an initial step to understanding the physical processes impacting these uncertainties in satellite AOD retrievals, this study outlines a theoretical approach to estimate biases in the satellite aerosol retrieval algorithm affected by surface albedo and prescribed aerosol optical properties using a simplified radiative transfer model with a traditional error propagation approach. We expand the critical surface reflectance concept to obtain the critical surface albedo (CSA), critical single scattering albedo (CSSA), and critical asymmetry parameter (CAP). The top-of-atmosphere (TOA) reflectance is not sensitive to significant variability in aerosol loading (AOD) at the critical value; thus, the AOD cannot be determined. Results show that 5% bias in surface albedo (A), single scattering albedo (SSA), or asymmetry parameter (g) lead to large retrieved AOD errors, especially high under conditions when A, SSA, or g are close to their critical values. The results can be useful for future research related to improvements of satellite aerosol retrieval algorithms and provide a preliminary framework to analytically quantify AOD uncertainties from satellite retrievals.
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- Award ID(s):
- 1838024
- PAR ID:
- 10212252
- Date Published:
- Journal Name:
- Remote Sensing
- Volume:
- 13
- Issue:
- 3
- ISSN:
- 2072-4292
- Page Range / eLocation ID:
- 344
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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