Abstract:
Knowledge of cloud properties such as cloud effective radius (aef) and optical thickness (?) is essential to understand their role in the dynamic radiation budget and climate change. The Spinning Enhanced Visible and Infrared Instrument (SEVIRI) on board Meteosat Second Generation (MSG) with its high temporal resolution (15 min), permits a quasi-continuous monitoring of the evolution of cloud properties. This has motivated the adaptation of the SLALOM (SimpLe Approximations for cLOudy Media) algorithm, a semi-analytical cloud property retrieval technique to MSG SEVIRI. The optical properties retrieved by SLALOM are compared against the well known and validated NASA MODIS cloud property product (MODIS 06) as well as the cloud optical depth product (2B-TAU) of CloudSat. The results are shown over the North Atlantic and over the European continent with the intention of determine the relative accuracy between SLALOM and the other retrievals. Over the North Atlantic, SLALOM-based cloud properties retrieved from SEVIRI datasets show a good agreement with the MODIS 06 product with correlation coefficients of 0.93 (?) and 0.82 (aef). The largest deviations were found in less homogeneous cloud areas that are characterized by broken clouds and toward the cloud borders. Moreover, SLALOM optical thickness values are well within the range of corresponding CloudSat 2B-TAU optical thickness values which can be found within a SEVIRI pixel, except for ? < 5 where SLALOM tends to overestimate ?. Despite the different sensor characteristics and viewing geometries, the retrieved cloud properties compare very well. Over Europe, the evaluation between SLALOM and MODIS 06 showed larger differences. We attribute this to (a) uncertainties related to the surface albedo which is treated differently in the algorithms and is based on different albedo maps and (b) inhomogeneities of clouds which exhibit quite complex structures particularly over land. The latter are detected on different scales by MODIS and SEVIRI because of their different spatial resolutions. Given the demonstrated accuracy of SLALOM using MSG SEVIRI data there is a wide spread of potential applications.
