Influence of topography on Tibetan Plateau snow cover simulations in land surface modeling
crossref(2022)
Abstract
The Tibetan Plateau (TP) is the highest plateau in the world and has complex topography. On the TP, seasonal snow cover is widespread in different topographic areas, but the influence of topography on snow cover simulations is often ignored in most land surface models. In this study, the relationships among the snow cover fraction (SCF) and complex topography are investigated over the TP based on satellite observations. The standard deviation of topography is used as an index to describe the topographic complexity. We conduct 12 numerical experiments using the Simplified Simple Biosphere Model version 3 (SSiB3) to investigate the influence of topography on the snow cover simulations. Our results show that ignoring topography leads to significant SCF simulation biases. By adding a topographic factor to the original scheme, the SCF simulations are greatly improved. Compared with the simulation results of the default SCF scheme, the annual mean SCF bias at location at CMA stations is reduced from 3.833% to -0.097% by adding a topographic factor. The improved SCF simulations further lead to reduced biases in winter surface albedo and land surface temperature simulations. Compared with in situ observations, the winter surface albedo bias over the TP is reduced from 0.02 to 0.007 compared with GLASS albedo data, and the winter land surface temperature bias is reduced from -3.43 K to -3.04 K. This study highlights the importance of the topographic effect in simulating snow and energy exchanges between the land and atmosphere over the TP, and it can contribute to reducing the “cold bias” in winter climate simulations over the TP.
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