Abstract
Abstract. A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, “best estimate” AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.
Highlights
Uncertainty estimation in satellite remote sensing is a highly challenging endeavor that requires diligent assessment of many potential sources of error
The two terms, are often not properly differentiated in the literature. This is in part due to a lack of awareness about the issue as most studies focus on external validation of satellite data products, which often do not contain information about the uncertainties associated with individual retrievals
This study describes a new approach to determining aerosol optical depth (AOD) and AOD uncertainties in Multi-angle Imaging SpectroRadiometer (MISR) retrievals
Summary
Uncertainty estimation in satellite remote sensing is a highly challenging endeavor that requires diligent assessment of many potential sources of error. More appropriate attempts to address the true AOD retrieval uncertainty involved sensitivity tests of the retrieval algorithm with respect to varying external factors such as lower boundary conditions or aerosol microphysical properties (Kahn et al, 2001; Kalashnikova and Kahn, 2006; Sayer et al, 2016) These studies were limited in scope as they were unable to address all possible sources of error. The resulting spread of AOD solutions for this ensemble of aerosol mixtures offers quantitative insight into the uncertainty of the individual retrieval Such an approach, if extended to all poorly quantifiable nonlinear sources of error and physically plausible realizations of parameter space, has the potential for providing a robust and comprehensive measure of retrieval uncertainty in the manner suggested by Povey and Grainger (2015).
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