Abstract
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.
Highlights
Clouds play an important role in the Earth’s climate system
In order to obtain reasonable surface UV irradiance from the remotely sensed cloud optical thickness (COT) fields, we developed a simple parameterization based on simulations performed with the Tropospheric Ultraviolet and Visible (TUV) radiative transfer model (Madronich, 1997), version 5.0
Optical thickness is obtained by combining radar measurements with reflectances measured by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Aqua platform, which flies in tandem with the CloudSat platform
Summary
Clouds play an important role in the Earth’s climate system. In addition to Earth’s hydrological cycle (Lin et al, 2000), cloud properties are crucial to global climate studies (Nakajima and King, 1990). Pandey et al.: Implementing a semi-analytical cloud retrieval algorithm duce the UV radiation reaching the Earth’s surface, but under certain conditions clouds can enhance the surface UV radiation compared to clear sky condition (Crawford et al, 2003; Sabburg and Parisi, 2006) These studies reveal the diverse influence of cloud. Several methods (see e.g. Nakajima et al, 1990; King et al, 1992) are available to estimate the physical properties of clouds, such as cloud optical thickness and droplet effective radius, from remote sensing imagery. They are based on clouds’ spectral absorption and reflection properties in the shortwave radiation spectrum.
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