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Arola et al. 2002
Arola, A., Kalliskota, S., den Outer, P.N., Edvardsen, K., Hansen, G., Koskela, T., Martin, T.J., Matthijsen, J., Meerkoetter, R., Peeters, P., Seckmeyer, G., Simon, P.C., Slaper, H., Taalas, P. and Verdebout, J. (2002). Assessment of four methods to estimate surface UV radiation using satellite data, by comparison with ground measurements from four stations in Europe. Journal of Geophysical Research 107: doi: 10.1029/2001JD000462. issn: 0148-0227.

Four different satellite-UV mapping methods are assessed by comparing them against ground-based measurements. The study includes most of the variability found in geographical, meteorological and atmospheric conditions. Three of the methods did not show any significant systematic bias, except during snow cover. The mean difference (bias) in daily doses for the Rijksinstituut voor Volksgezondheid en Milieu (RIVM) and Joint Research Centre (JRC) methods was found to be less than 10% with a RMS difference of the order of 30%. The Deutsches Zentrum f¿r Luft- und Raumfahrt (DLR) method was assessed for a few selected months, and the accuracy was similar to the RIVM and JRC methods. It was additionally used to demonstrate how spatial averaging of high-resolution cloud data improves the estimation of UV daily doses. For the Institut d'A¿ronomie Spatiale de Belgique (IASB) method the differences were somewhat higher, because of their original cloud algorithm. The mean difference in daily doses for IASB was about 30% or more, depending on the station, while the RMS difference was about 60%. The cloud algorithm of IASB has been replaced recently, and as a result the accuracy of the IASB method has improved. Evidence is found that further research and development should focus on the improvement of the cloud parameterization. Estimation of daily exposures is likely to be improved if additional time-resolved cloudiness information is available for the satellite-based methods. It is also demonstrated that further development work should be carried out on the treatment of albedo of snow-covered surfaces.

BACKGROUND DATA FILES

Abstract

Keywords
Meteorology and Atmospheric Dynamics, Remote sensing, Meteorology and Atmospheric Dynamics, Radiative processes, Meteorology and Atmospheric Dynamics, Theoretical modeling
Journal
Journal of Geophysical Research
http://www.agu.org/journals/jb/
Publisher
American Geophysical Union
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