Snow consists of snow grains with variable, often irregular shapes. A new study shows that the climate simulated by a numerical climate model can depend surprisingly much of what is assumed about the snow grain shapes when computing the reflection of solar radiation by the snowpack.
Clean snow appears white because it reflects back most of the solar radiation, especially at visible wavelengths. This is, however, a complex process: the reflection by snow results from scattering of sunlight by numerous snow grains with largely varying shapes and sizes. In most studies, the scattering by snow has been computed assuming, for simplicity, that snow grains are spherical. It is however known well that scattering by nonspherical particles (including snow grains) can differ systematically from the scattering by spheres.
In a study coordinated by the Finnish Meteorological Institute, the computation of snow reflectivity for solar radiation (aka. snow albedo) was modified in the NorESM climate model, by replacing an approach based on spherical snow grains with an approach assuming nonspherical snow grains. When the snow grains were assumed nonspherical, snow albedo was increased slightly, typically by 2-3 percentage units. Consequently, less solar radiation was absorbed by the snowpack. As a result, the climate simulated by NorESM became significantly colder. For example, the global-mean near-surface air temperature was more than 1 K lower than in the experiment assuming spherical snow grains. The relatively large temperature response is related to positive feedbacks which enhance the initial impact of changed snow grain size. Specifically, increasing the snow albedo delayed the melting of snow and sea ice in spring, which increased the albedo difference to the experiment in which snow grains were assumed spherical.
Overall, this study demonstrates that the climate simulated by a numerical climate model can be sensitive to how the snow albedo is treated. The snow albedo depends not only on snow grain shapes but also their sizes and other factors like impurities in snow. To better constrain the computation of snow albedo in climate models, more comprehensive observations on both snow albedo and on other snow physical properties are needed.
This study received funding from the Academy of Finland. In addition to Finnish Meteorological Institute, scientists from the University of Helsinki and the Norwegian Meteorological Institute participated in the work.
Senior research scientist Petri Räisänen, tel. 029 539 2224, email@example.com
Räisänen, P., Makkonen, R., Kirkevåg, A., and Debernard, J. B.: Effects of snow grain shape on climate simulations: sensitivity tests with the Norwegian Earth System Model, The Cryosphere, 11, 2919-2942, https://doi.org/10.5194/tc-11-2919-2017, 2017.
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