A new climatology for remote sensing over land based on the inherent optical properties

Abstract

The AErosol RObotic NETwork (AERONET) of CIMEL ground-based radiometers, which covers the entire globe, has already been used in many previous studies for validating the inherent optical properties (IOPs) of aerosols. The IOPs are generally computed from microphysical properties using Mie's theory. Many recent studies link the uncertainties in these IOPs with the use of aerosol climatology based on microphysical properties. The objective of this study was to propose an alternative aerosol climatology based on the aerosol IOPs derived directly from CIMEL sky radiance measurements using our in-house iterative method. To achieve this task, an AERONET database of CIMEL sky radiance sequences was first processed using a specific set of criteria. Then, a representative subset of CIMEL data collected over the Venice site was used to refine the selected criteria and to evaluate new criteria for the data quality check, such as the preliminary tests applied to CIMEL sky radiances, the speed-up of convergence of our aerosol phase function retrieval algorithm, and the consistency of its outputs. Because the extraction of the phase function requires a good knowledge of the surface reflectance, we used MODerate Imaging Spectroradiometer (MODIS) albedo maps, which are available on a monthly basis. Statistical methods were then applied to the CIMEL database to discard the incorrect sequences and to suggest a classification of the aerosol models on the basis of their IOPs. The need to include specific aerosol models in this climatology to account for Saharan dust storms, as well as to describe the Asian dust events, was also investigated in this study. Moreover, the medium-resolution imaging spectrometer (MERIS) look-up tables (LUTs) generated over land with these new aerosol IOPs are fully compatible with the current level-2 algorithms. The improvement expected with this climatology will be evaluated using the MERIS imagery.