1VITO – Flemish Institute for Technological Research, Mol, Belgium
2Department of Earth- and Environmental Sciences, K. U. Leuven, Leuven, Belgium
3Belgian Institute for Space Aeronomy, Brussels, Belgium
Received: 06 Nov 2011 – Published in Atmos. Chem. Phys. Discuss.: 09 Jan 2012
Abstract. In this paper, we describe the implementation of the Semi-Analytical Cloud Retrieval Algorithm (SACURA), to obtain scaled cloud optical thickness (SCOT) from satellite imagery acquired with the SEVIRI instrument and surface UV irradiance levels. In estimation of SCOT particular care is given to the proper specification of the background (i.e. cloud-free) spectral albedo and the retrieval of the cloud water phase from reflectance ratios in SEVIRI's 0.6 μm and 1.6 μm spectral bands. The SACURA scheme is then applied to daytime SEVIRI imagery over Europe, for the month of June 2006, at 15-min time increments. The resulting SCOT fields are compared with values obtained by the CloudSat experimental satellite mission, yielding a negligible bias, correlation coefficients ranging from 0.51 to 0.78, and a root mean square difference of 1 to 2 SCOT increments. These findings compare favourably to results from similar intercomparison exercises reported in the literature. Based on the retrieved SCOT from SEVIRI and radiative transfer modelling approach, simple parameterisations are proposed to estimate the surface UV-A and UV-B irradiance. The validation of the modelled UV-A and UV-B irradiance against the measurements over two Belgian stations, Redu and Ostend, indicate good agreement with the high correlation, index of agreement and low bias. The SCOT fields estimated by implementing SACURA on imagery from geostationary satellite are reliable and its impact on surface UV irradiance levels is well produced.
Revised: 14 Aug 2012 – Accepted: 21 Aug 2012 – Published: 06 Sep 2012
Pandey, P., De Ridder, K., Gillotay, D., and van Lipzig, N. P. M.: Estimating cloud optical thickness and associated surface UV irradiance from SEVIRI by implementing a semi-analytical cloud retrieval algorithm, Atmos. Chem. Phys., 12, 7961-7975, doi:10.5194/acp-12-7961-2012, 2012.