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TitleValidation of an UV Inversion Algorithm Using Satellite and Surface Measurements
 
AuthorWang, P; Li, Z; Cihlar, J; Wardle, D I; Kerr, J
SourceJournal of Geophysical Research 1999.
Year1999
Alt SeriesEarth Sciences Sector, Contribution Series 20042758
Documentserial
Lang.English
Mediapaper
AbstractSatellite-based estimation of surface UV-B radiation is an important supplement to ground-based observations from the sparsely distributed UV-B monitoring networks. In a previous study, we proposed a simple inversion algorithm to derive surface UV fluxes from satellite observations. This physical algorithm consists of a few analytical expressions with a small number of input parameters such as solar zenith angle, ozone amount, and albedo at the Top Of the Atmosphere (TOA) at an ozone insensitive wavelength. Achieving a high level of accuracy also requires information on aerosol optical thickness and single scattering albedo. In this study, the performance of the algorithm is validated with observational data. In the validation, the algorithm is applied to satellite measurements of total ozone amount and 360 nm reflectance from Meteor-3/TOMS and visible reflectance from NOAA/AVHRR. The retrieved UV-B and erythemal UV (EUV) fluxes are compared with ground measurements of downwelling UV spectral irradiance made in the Canadian UV monitoring network with Brewer instruments from 1992 to 1994. Under all-sky conditions, the comparisons showed very small mean differences and relatively large standard (SD) deviations: 0.033 W/m2 (mean) and 0.287 W/m2 (SD) for total UV-B, and 3.18 mW/m2 (mean) and 12.4 mW/m2 (SD) for erythemal weighted UV radiation. The large SD deviations are attributed to the inhomogeneity and mobility of cloudy scenes, which renders an inaccurate match between satellite and surface measurements. The comparisons under clear-sky conditions showed very small mean and standard differences. By means of running average over a period of time, satellite inversion can track the variation of surface observed UV-B and EUV very well.
GEOSCAN ID219560

 
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