Abstract

This study evaluates the potential of using aerosol optical depth (τa) measurements to characterise the microphysical and optical properties of atmospheric aerosols. With this aim, we used the recently developed GRASP (Generalized Retrieval of Aerosol and Surface Properties) code for numerical testing of six different aerosol models with different aerosol loads. The direct numerical simulations (self-consistency tests) indicate that the GRASP-AOD retrieval provides modal aerosol optical depths (fine and coarse) to within 0.01 of the input values. The retrieval of the fine-mode radius, width and volume concentration are stable and precise if the real part of the refractive index is known. The coarse-mode properties are less accurate, but they are significantly improved when additional a priori information is available. The tests with random simulated errors show that the uncertainty in the bimodal log-normal size distribution parameters increases as the aerosol load decreases. Similarly, the reduction in the spectral range diminishes the stability of the retrieved parameters. In addition to these numerical studies, we used optical depth observations at eight AERONET locations to validate our results with the standard AERONET inversion products. We found that bimodal log-normal size distributions serve as useful input assumptions, especially when the measurements have inadequate spectral coverage and/or limited accuracy, such as moon photometry. Comparisons of the mode median radii between GRASP-AOD and AERONET indicate average differences of 0.013 μm for the fine mode and typical values of 0.2–0.3 μm for the coarse mode. The dominant mode (i.e. fine or coarse) indicates a 10 % difference in mode radii between the GRASP-AOD and AERONET inversions, and the average of the difference in volume concentration is around 17 % for both modes. The retrieved values of the fine-mode τa(500) using GRASP-AOD are generally between those values obtained by the standard AERONET inversion and the values obtained by the AERONET spectral deconvolution algorithm (SDA), with differences typically lower than 0.02 between GRASP-AOD and both algorithms. Finally, we present some examples of application of GRASP-AOD inversion using moon photometry and the airborne PLASMA sun photometer during the ChArMEx summer 2013 campaign in the western Mediterranean.

Highlights

  • Aerosol optical depth measurements that are complemented with angular radiance measurements are routinely used by the scientific community to infer the microphysical and optical properties of atmospheric aerosols

  • The main goal of the present work was to show the potential of retrieving the total column aerosol size distributions from spectral optical depth measurements without the aid of coincident radiance measurements, and estimating a set of secondary aerosol properties derived from it

  • The current analysis indicates that bimodal log-normal size distributions and a priori estimates of refractive indices and sphericity parameter provide a practically efficient retrieval

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Summary

Introduction

Aerosol optical depth (τa) measurements that are complemented with angular radiance measurements are routinely used by the scientific community to infer the microphysical and optical properties of atmospheric aerosols (e.g. the AErosol RObotic NETwork or AERONET). It is desirable to derive meaningful aerosol information from spectral optical depth measurements when complementary radiance measurements are not available. In the last few decades, the focus of remote sensing retrieval development shifted towards an analysis of more complex observations: angular and polarimetric properties of transmitted and reflected diffuse radiation. In principle, such observations have high sensitivity, which allows complete and accurate characterisation of the aerosol features. The complexity and efficiency of the retrieval algorithms have significantly improved compared to the those originally developed for the interpretation of aerosol optical depth. In current study, we have decided to revisit this problem and provide a complete analysis and illustration of τa inversion using state-of-the-art retrieval approaches and software

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