Albedo Reduction by Light Absorbing Impurities and the Associated Radiative Forcing over High Mountain Asia: GFDL Global Climate Model and MODIS Observations

The reduction of snow albedo by light absorbing impurities (LAI) can increase the amount of solar energy absorbed by the snowpack, accelerate snowmelt, and consequently, impact the regional climate and hydrological cycle. The impacts of snow darkening is highly relevant in High Mountain Asia (HMA), a region that relies on meltwater as a major water supply for over a billion people downstream. Ground based observations are limited due to accessibility and it is difficult to infer regional patterns. Both modeling and observations from remote sensing can provide an understanding of LAIs not attainable from the limited observations. Here, we use MODIS observations to evaluate the snow albedo reduction simulated by the new Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric-land coupled model (AM4/LM4) in conjunction with an offline snow parameterization that estimates snow properties based on aging and darkening by LAPs. Comparison between model output and satellite retrievals show relatively no bias in snow cover days with a mean difference of -7 to 12 days in the years 2011 to 2015. In some regions there is reasonable agreement in the temporal patterns of snow cover and albedo, while in others we see a shift of maximum snow cover delayed 1-2 months likely due to high snowfall/snow depth in regions like the Karakoram leading to an overestimate the overall albedo of the grid cell, a much colder temperature, more snowfall & later onset of melt. In these regions comparisons of albedo reduction are more challenging because of the temporal mismatch. Building on these results, we can improve model parameterizations, identify the dominant processes that are responsible for the snow albedo reduction, quantify the corresponding radiative impacts in different seasons across HMA, and gain trust in our model for projections into the future.