Open AccessAccounting for Topographic Effects on Snow Cover Fraction and Surface Albedo Simulations Over the Tibetan Plateau in Winter
Author(s) -
Miao Xin,
Guo Weidong,
Qiu Bo,
Lu Sha,
Zhang Yu,
Xue Yongkang,
Sun Shufen
Publication year - 2022
Publication title -
journal of advances in modeling earth systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.03
H-Index - 58
ISSN - 1942-2466
DOI - 10.1029/2022ms003035
Subject(s) - albedo (alchemy) , snow , plateau (mathematics) , environmental science , biosphere model , climatology , forcing (mathematics) , biosphere , land cover , atmospheric sciences , snow cover , climate model , meteorology , climate change , geology , land use , geography , mathematics , art , mathematical analysis , ecology , oceanography , civil engineering , performance art , engineering , biology , art history
The Tibetan Plateau (TP) is the highest land in the world and has a very complex topography. However, the influence of topography on TP snow cover simulations has not been adequately addressed in most land surface models. The analysis of satellite observations indicates that snow cover fraction (SCF) simulation biases increase with the topography complexity, and this increasing trend slows down when the standard deviation of topography is greater than 200 m. The result also shows that using the SCF schemes without consideration of topography leads to a consistent overestimation in winter. To account for the topographic effects, we introduce a modified topographic factor to the SCF schemes. Then we conduct regional simulations using the Simplified Simple Biosphere Model version 3 (SSiB3) and evaluate the results at the location of observation sites to reduce the uncertainty induced by forcing data. Compared with the default SCF scheme, the mean winter SCF bias is reduced from 3.83% to −0.10%. The optimization of SCF simulations further improves the winter surface albedo and land surface temperature (LST) simulations. The winter surface albedo bias over the TP is reduced from 0.020 to 0.007, with a maximum reduction by −0.133. The winter LST bias is reduced from −3.33 to −3.04 K, with a maximum reduction by 3.60 K. This study highlights the importance of topographic effects in simulating snow cover distribution and land surface energy budget for reducing the “cold bias” in winter climate simulations over the TP.