Influence of cloud properties on satellite total ozone observations - Antón, Manuel; Loyola, Diego (Journal of Geophysical Research, 2011)
Clouds represent one of the most important atmospheric factors that can significantly reduce the accuracy of satellite total ozone column (TOC) data. The influence of clouds on the TOC retrieval from satellites is usually assessed by means of theoretical studies using radiative transfer models. In contrast, few experimental results were found in the literature about the effects of the cloud properties on the differences between satellite TOC data and accurate ground‐based measurements. This paper is focused on the study of the joined influence of the cloud properties under different satellite viewing conditions on the TOC data derived from four satellite instruments (GOME/ERS‐2, GOME‐2/MetOp‐A, SCIAMACHY/Envisat, and OMI/Aura) using as reference five Brewer spectrophotometers in the Iberian Peninsula. Satellite TOC data under cloud‐free and cloudy conditions are compared with ground‐based measurements for the time period 2006 to 2009. The TOC products derived using the Differential Optical Absorption Spectroscopy (DOAS) technique, GOME, GOME‐2, SCIAMACHY and OMI‐DOAS, show a notable underestimation for cloudy conditions that clearly decreases with increasing Sun zenith angles (SZA). For those DOAS TOC products, the viewing zenith angle (VZA) also shows a significant influence on the satellite‐Brewer differences, mainly for the west pixels and cloud‐free conditions. The OMI‐TOMS TOC product under cloud‐free and cloudy conditions presents a more stable pattern for both SZA and VZA values, but this result must be interpreted carefully because OMI‐TOMS classifies an unrealistic high number of scenes as cloud‐free (∼57% of all). The analysis of the relative TOC differences as a function of the satellite cloud fraction indicates that SCIAMACHY and OMI‐DOAS products have a large difference between the curves corresponding to low and high SZA cases. The two GOME algorithms and, mainly, the OMI‐TOMS algorithm present a remarkable stability for all cloud conditions.