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Snow cover on the Tibetan Plateau (TP) is an important component of the Eurasian snow cover, which is also one of the primary forms of freshwater storage in Asia. The snow-related hydrological processes in this region have an important influence on the land-atmosphere interactions, ecosystems, weather, climate and hydrological cycle processes at both the local and regional scales.
As a special form of mass and energy transport, the blowing snow process significantly affects the temporal and spatial distribution of snow cover through the transport of snow particles and the concurrent in-transit snow mass removal by sublimation. This process not only intensifies the spatial-temporal heterogeneity of snow distribution in mountainous terrain, but also reshapes the material and energy balance of snowpack in snow covered areas, greatly influencing subsequent land surface processes, such as radiation absorption, energy partitioning, snowpack evolution, and springtime runoff patterns. For a long time, however, the effects of blowing snow have been neglected in mesoscale hydrological models, land surface models, and large‐scale climate models despite the important role the process plays in the land surface and atmospheric water and energy budgets, resulting in significant deviations in the simulation of snow processes and land-atmosphere interactions over the TP.
To provide a better estimate of the snow dynamics for the consideration of snow redistribution induced by wind, researchers from the project of “The temporal and spatial dynamics of water and ecology in the Third Pole” (XDA19070300) have developed a land surface model with the impacts of blowing snow process considered by coupling the blowing snow model PIEKTUK with the land process model Community Land Model Version 4.5 (CLM 4.5). Two simulations with a 0.065°spatial resolution were performed in 2010 over the TP, namely, a sensitivity experiment with the inclusion of blowing snow effects (CLM_BS) and a control run with the original model (CLM). A key objective of this study was to evaluate the improvements in the simulations of snow dynamics and other key variables in surface energy partitioning provided by the coupled model, such as the surface albedo and land surface temperature (LST). By comparing with a variety of remote‐sensing observations, such as the MODIS snow cover and snow area products, the IMS daily snow cover product, the GLASS surface albedo product, the MODIS land surface temperature product, and the China daily snow depth product, the results show that the surface snow cover, snow depth, and surface albedo can be reproduced for most of the TP region much better by using the coupled CLM_BS model as compared tothe original CLM, particularly in the Kunlun Mountains, Hoh Xil area, and the southwestern TP. In areas with reduced bias, variations in the monthly mean snow cover fraction were re?ected particularly well by CLM_BS. For LST, however, a significant decrease in the nighttime LST bias was detected in CLM_BS, while the bias in the daytime LST increased. The results show considerable potential for the inclusion of the blowing snow process to promote the modeling of snow dynamics and land‐atmosphere interactions on the TP.
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Variations in the simulated (CLM_BS and CLM) and observed (MODIS) monthly mean snow cover fractions in grid cells with a decrease of bias in snow cover fraction simulation. MODIS = Moderate Resolution Imaging Spectroradiometer; CLM = Community Land Model; CLM_BS = Community Land Model with blowing snow effects (Xie et al., 2019)
Reference:Xie Z, Hu Z, Ma Y, et al. Modeling blowing snow over the Tibetan Plateau with the Community Land Model: Method and preliminary evaluation[J]. Journal of Geophysical Research: Atmospheres, 2019, 124(16): 9332-9355.https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2019JD030684.
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