The theory described above was applied to analyze a comprehensive set of measurements taken in Kongsfjorden, Svalbard (Gerland et al., 1999; Hamre et al., 2004). Physical and structural properties (snow and ice thickness, density, in situ temperature, and salinity profiles) were measured in addition to irradiances above the surface and under the ice. On the basis of measured snow grain sizes, snow depth, ice temperature, and ice salinity, Hamre et al. (2004) computed the transmittance of first-year sea ice with and without snow cover. These computations were done with a CASIO-DISORT code, and the bubble sizes and the snow grain sizes were estimated by assuming that the absorption by impurities can be neglected at near-infrared wavelengths. Also, it was assumed that the volume fractions of air bubbles and brine pockets (fyu and fV) could be determined from the salinity, bulk ice density, and temperature (Cox and Weeks, 1983; Jin et al., 1994). The results of this study may be summarized as follows:
• a best fit between measured and computed transmittances was obtained with snow grains that were only 5% larger than the smallest observed values;
• the shape of the impurity absorption spectrum resulting from forcing agreement between modeled and measured transmittances resembled that of ice algae;
• a 2.5 cm-thick layer of snow had the same transmittance for visible light and UV radiation as a 61 cm-thick ice layer;
• UV radiation is removed more efficiently than visible light for snow depths greater than 3 cm - 4 cm implying that algae growing under snow cover may be protected from harmful UV radiation, yet receives sufficient visible light for photosynthesis;
• the CASIO-DISORT model is a useful tool for computing energy deposition in the snow, ice, and ocean, and can be used to investigate the influence of changes in environmental conditions, such as ozone amount, snow thickness, and cloud cover on UV radiation and visible light, and hence, on the aquatic biology in polar regions.
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