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. Satellite-based aerosol products are routinely validated againstground-based reference data, usually obtained from sun photometer networkssuch as AERONET (AEROsol RObotic NETwork). In a typical validation exercise aspatial sample of the instantaneous satellite data is compared against atemporal sample of the point-like ground-based data. The observations do notcorrespond to exactly the same column of the atmosphere at the same time, andthe representativeness of the reference data depends on the spatiotemporalvariability of the aerosol properties in the samples. The associateduncertainty is known as the collocation mismatch uncertainty (CMU). Thevalidation results depend on the sampling parameters. While small samplesinvolve less variability, they are more sensitive to the inevitable noise inthe measurement data. In this paper we study systematically the effect of thesampling parameters in the validation of AATSR (Advanced Along-Track ScanningRadiometer) aerosol optical depth (AOD) product against AERONET data and theassociated collocation mismatch uncertainty. To this end, we study thespatial AOD variability in the satellite data, compare it against thecorresponding values obtained from densely located AERONET sites, and assessthe possible reasons for observed differences. We find that the spatial AOD variability in the satellite data isapproximately 2 times larger than in the ground-based data, and the spatialvariability correlates only weakly with that of AERONET for short distances.We interpreted that only half of the variability in the satellite data is dueto the natural variability in the AOD, and the rest is noise due to retrievalerrors. However, for larger distances ( ∼  0.5 ∘ ) the correlation isimproved as the noise is averaged out, and the day-to-day changes in regionalAOD variability are well captured. Furthermore, we assess the usefulness ofthe spatial variability of the satellite AOD data as an estimate of CMU bycomparing the retrieval errors to the total uncertainty estimates includingthe CMU in the validation. We find that accounting for CMU increases thefraction of consistent observations.

Collocation mismatch uncertainties in satellite aerosol retrieval validation