Snow cover over the Tibetan Plateau (TP) plays an important role in Asian climate. State‐of‐the‐art models, however, show significant simulation biases. In this study, we assess the main uncertainty associated with model physics in snow cover modeling over the TP using ground‐based observations and high‐resolution snow cover satellite products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and FengYun‐3B (FY3B). We first conducted 10‐km simulations using the Noah with multiparameterization (Noah‐MP) land surface model by optimizing physics‐scheme options, which reduces 8.2% absolute bias of annual snow cover fraction (SCF) compared with the default model settings. Then, five SCF parameterizations in Noah‐MP were optimized and assessed, with three of them further reducing the annual SCF biases from around 15% to less than 2%. Thus, optimizing SCF parameterizations appears to be more important than optimizing physics‐scheme options in reducing the uncertainty of snow modeling. As a result of improved SCF, the positive bias of simulated surface albedo decreases significantly compared to the GLASS albedo data, particularly in high‐elevation regions. This substantially enhances the absorbed solar radiation and further reduces the annual mean biases of ground temperature from −3.5 to −0.8°C and snow depth from 4.2 to 0.2 mm. However, the optimized model still overestimates SCF in the western TP and underestimates SCF in the eastern TP. Further analysis using a higher‐resolution (4 km) simulation driven by topographically adjusted air temperature shows slight improvement, suggesting a rather limited contribution of the finer‐scale land surface characteristics to SCF uncertainty.

中文翻译：

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青藏高原积雪模拟中不确定性源的评估

青藏高原（TP）的积雪在亚洲气候中起着重要作用。但是，最新模型显示出明显的模拟偏差。在这项研究中，我们使用中分辨率成像光谱仪（MODIS）和FengYun-3B（FY3B）的地面观测和高分辨率积雪卫星产品评估了TP积雪建模中与模型物理学相关的主要不确定性。我们首先使用诺亚多参数化（Noah-MP）地表模型，通过优化物理方案选择进行了10 km的模拟，与默认模型设置相比，该模型可减少年度积雪分数（SCF）的8.2％绝对偏差。然后，对Noah-MP中的五个SCF参数设置进行了优化和评估，其中三个进一步将年度SCF偏差从大约15％降低到了小于2％。从而，在减少积雪建模的不确定性方面，优化SCF参数化似乎比优化物理方案更为重要。由于改善了SCF，与GLASS反照率数据相比，模拟表面反照率的正偏差显着降低，尤其是在高海拔地区。这显着增强了吸收的太阳辐射，并将地面温度的年平均偏差从-3.5降低到-0.8°C，降雪深度从4.2降低到0.2 mm。但是，优化模型仍然高估了西部TP的SCF，而低估了东部TP的SCF。使用由地形调整过的气温驱动的更高分辨率（4 km）模拟进行的进一步分析显示，已有轻微改善，这表明较小尺度的地表特征对SCF不确定性的贡献相当有限。