Aerosol retrieval experiments in the ESA Aerosol_cci project

[摘要] Within the ESA Climate Change Initiative (CCI) projectAerosol_cci (2010–2013), algorithms for the production oflong-term total column aerosol optical depth (AOD) datasets from EuropeanEarth Observation sensors are developed. Starting with eight existingpre-cursor algorithms three analysis steps are conducted to improve andqualify the algorithms: (1) a series of experiments applied to one month ofglobal data to understand several major sensitivities to assumptions neededdue to the ill-posed nature of the underlying inversion problem, (2) a roundrobin exercise of "best" versions of each of these algorithms (definedusing the step 1 outcome) applied to four months of global data to identifymature algorithms, and (3) a comprehensive validation exercise applied toone complete year of global data produced by the algorithms selected asmature based on the round robin exercise. The algorithms tested includedfour using AATSR, three using MERIS and one using PARASOL.

This paper summarizes the first step. Three experiments were conducted toassess the potential impact of major assumptions in the various aerosolretrieval algorithms. In the first experiment a common set of four aerosolcomponents was used to provide all algorithms with the same assumptions. Thesecond experiment introduced an aerosol property climatology, derived from acombination of model and sun photometer observations, as a prioriinformation in the retrievals on the occurrence of the common aerosolcomponents. The third experiment assessed the impact of using a common nadircloud mask for AATSR and MERIS algorithms in order to characterize thesensitivity to remaining cloud contamination in the retrievals against thebaseline dataset versions. The impact of the algorithm changes was assessedfor one month (September 2008) of data: qualitatively by inspection ofmonthly mean AOD maps and quantitatively by comparing daily griddedsatellite data against daily averaged AERONET sun photometer observationsfor the different versions of each algorithm globally (land and coastal) andfor three regions with different aerosol regimes.

The analysis allowed for an assessment of sensitivities of all algorithms,which helped define the best algorithm versions for the subsequent roundrobin exercise; all algorithms (except for MERIS) showed some, in partssignificant, improvement. In particular, using common aerosol components andpartly also a priori aerosol-type climatology is beneficial. On the otherhand the use of an AATSR-based common cloud mask meant a clear improvement(though with significant reduction of coverage) for the MERIS standardproduct, but not for the algorithms using AATSR. It is noted that all theseobservations are mostly consistent for all five analyses (global land, globalcoastal, three regional), which can be understood well, since the set ofaerosol components defined in Sect. 3.1 was explicitly designed to coverdifferent global aerosol regimes (with low and high absorption fine mode, seasalt and dust).

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