| Summary: | Snow and lake ice have very high albedos compared to other surfaces found in nature. Surface albedo is an important component of the surface energy budget especially when albedos are high since albedo governs how much shortwave radiation is absorbed or reflected at a surface. In particular, snow and lake ice albedos have been shown to affect the timing of lake ice break-up. Lakes are found throughout the Northern Hemisphere and lake ice has been shown to be sensitive to climatic variability. Therefore, the modelling of lake ice phenology, using lake ice models such as the Canadian Lake Ice Model (CLIMo), is important to the study of climatic variability in the Arctic and sub-Arctic regions and accurate snow and lake ice albedo measurements are required to ensure the accuracy of the simulations. However, snow and lake ice albedo can vary from day-to-day depending on factors such as air temperature, presence of impurities, age, and composition. Some factors are more difficult than others to model (e.g. presence of impurities). It would be more straight forward to just gather field measurements, but such measurements would be costly and lakes can be in remote locations and difficult to access. Instead, CLIMo contains an albedo parameterization scheme that models the evolution of snow and lake ice albedo in its simulations. However, parts of the albedo parameterization are based on sea-ice observations (which inherently have higher albedos due to brine inclusions) and the albedo parameterization does not take ice type (e.g. clear ice or snow ice) into account. Satellite remote sensing via the Moderate Resolution Imaging Spectroradiometer (MODIS) provides methods for retrieving albedo that may help enhance CLIMo’s albedo parameterization. CLIMo’s albedo parameterization as well the MODIS daily albedo products (MOD10A1 and MYD10A1) and 16-day product (MCD43A3) were evaluated against in situ albedo observations made over Malcolm Ramsay Lake near Churchill, Manitoba, during the winter of 2012. It was found that the snow ...
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