Accurate understanding and modeling of soil hydrothermal dynamics in permafrost regions is essential for reliably assessing future permafrost changes and their impacts. However, the inadequate representation of soil water-heat transport processes in current land surface models (LSMs) introduces large uncertainty in simulating permafrost dynamics, particularly on the Qinghai-Tibet Plateau (QTP). In this study, we modified the parameterizations of soil thermal conductivity, unfrozen water and soil evaporation resistance in version 5.0 of the Community Land Model (CLM5.0) and assessed their effects on soil hydrothermal dynamics in permafrost regions on the QTP using in-situ measurements the depths of 10-40 cm. The results showed that soil temperature was more sensitive to the modified soil thermal conductivity and unfrozen water schemes, with average RMSE reduced by approximately 0.60 degrees C compared to the default CLM5.0. Soil moisture was mainly affected the unfrozen water scheme during freezing and by the optimized soil evaporation resistance scheme during thawing, with maximum accuracy improvements of 8% and 25%, respectively. All three schemes significantly improved soil thermal conductivity simulations, reducing RMSE over 80%. Overall, our modifications remarkably reduced simulation errors compared to the default schemes, improving the average accuracy soil temperature, soil moisture and soil thermal conductivity by approximately 16%, 21% and 81% respectively. Additionally, this study emphasized the importance of accurately representing permafrost-related processes in LSMs, as they significantly affected simulation results. Specifically, soil thermodynamics is strongly sensitive to subtle changes in soil moisture transport processes, such as the hysteresis effect unfrozen water content, and parameterizations of snowpack and vegetation. Therefore, future work should focus on enhancing the accurate representations of these processes and optimized parameters in LSMs to improve the simulation accuracy in permafrost regions on the QTP. This study enhanced the understanding of soil hydrothermal processes in LSMs and provided valuable insights for the future model development for permafrost regions under the context of climate change.

气候变暖对北极多年冻土和植被产生了重要的影响。CLM(Community Land Model)是应用最广泛的陆面过程模式之一，但其中复杂的边界条件和参数化过程导致模式模拟结果存在一定的不确定性。本研究评估了CLM5.0对阿拉斯加多年冻土区表层土壤温度和碳循环的模拟能力，结果表明，CLM5.0可以捕捉到表层土壤温度的季节变化。在苔原和针叶林站点，CLM5.0在日尺度和月尺度都可以很好地模拟出总初级生产力（GPP）随时间的变化，但对净生态系统碳交换（NEE）的模拟结果存在一定的不确定性。CLM5.0可以较为合理地模拟高纬度多年冻土区的土壤温度季节变化，在未来的研究中可能还需要从结构、参数化方案等过程进行改进，从而进一步提升高纬度多年冻土区碳循环的模拟精度。

气候变暖对北极多年冻土和植被产生了重要的影响。CLM(Community Land Model)是应用最广泛的陆面过程模式之一，但其中复杂的边界条件和参数化过程导致模式模拟结果存在一定的不确定性。本研究评估了CLM5.0对阿拉斯加多年冻土区表层土壤温度和碳循环的模拟能力，结果表明，CLM5.0可以捕捉到表层土壤温度的季节变化。在苔原和针叶林站点，CLM5.0在日尺度和月尺度都可以很好地模拟出总初级生产力（GPP）随时间的变化，但对净生态系统碳交换（NEE）的模拟结果存在一定的不确定性。CLM5.0可以较为合理地模拟高纬度多年冻土区的土壤温度季节变化，在未来的研究中可能还需要从结构、参数化方案等过程进行改进，从而进一步提升高纬度多年冻土区碳循环的模拟精度。

气候变暖对北极多年冻土和植被产生了重要的影响。CLM(Community Land Model)是应用最广泛的陆面过程模式之一，但其中复杂的边界条件和参数化过程导致模式模拟结果存在一定的不确定性。本研究评估了CLM5.0对阿拉斯加多年冻土区表层土壤温度和碳循环的模拟能力，结果表明，CLM5.0可以捕捉到表层土壤温度的季节变化。在苔原和针叶林站点，CLM5.0在日尺度和月尺度都可以很好地模拟出总初级生产力（GPP）随时间的变化，但对净生态系统碳交换（NEE）的模拟结果存在一定的不确定性。CLM5.0可以较为合理地模拟高纬度多年冻土区的土壤温度季节变化，在未来的研究中可能还需要从结构、参数化方案等过程进行改进，从而进一步提升高纬度多年冻土区碳循环的模拟精度。

Snow plays an important role in catastrophic weather, climate change, and water recycling. In order to analyze the ability of different land surface models to simulate snow depth in China, we used atmospheric forcing data from the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) to drive the CLM3.5 (the Community Land Model version 3.5), Noah (NCEP, OSU, Air Force and Office of Hydrology Land Surface Model), and Noah-MP (the community Noah land surface model with multi-parameterization options) land surface models. We also used 2380 daily snow-depth site observations of CMA to analyze the simulation effects of different models on the snow depth in China and different regions during the periods of snow accumulation and snowmelt from 2015 to 2019. The results show that CLM3.5, Noah, and Noah-MP can simulate the spatial distribution of the snow depth in China, but there are some differences between the models. In particular, the snow depth and snow cover simulated by CLM3.5 are lower than those simulated by Noah and Noah-MP in Northwest China and the Tibetan Plateau. From the overall quantitative assessment results for China, the snow depth simulated by CLM3.5 is underestimated, while that simulated by Noah is overestimated. Noah-MP has the best overall performance; for example, the biases of the three models during the snow-accumulation periods are -0.22 cm, 0.27 cm, and 0.15 cm, respectively. Furthermore, the three models perform differently in the three snowpack regions of Northeast China, Northwest China, and the Tibetan Plateau; Noah-MP has the best snow-depth performance in Northeast China, while CLM3.5 has the best snow-depth performance in the Tibetan Plateau region. Noah-MP performs best in the snow-accumulation period, and Noah performs best in the snowmelt period for Northwest China. In conclusion, no single model can perform optimally for snow simulations in different regions of China and at different times of the year, and the multi-model integration of snow may be an effective way to obtain high-quality snow simulation results. So this study provides some scientific references for the spatiotemporal evolution of snow in the context of climate change, monitoring and analysis of snow, the study of land surface models for snow, and the sustainable development and utilization of snow resources in China and other regions.

The hydrothermal dynamics of the active layer is a key issue in the study of surface processes in permafrost regions. Even though the soil energy budget is controlled by thermal conduction and latent heat transfer, few studies have focused on their effects upon the active layer thickness (ALT). In the present study, the community land model (CLM) version 5.0 is used to simulate the soil temperature and moisture of the active layers at the Tanggula (TGL) and Beiluhe (BLH) stations in permafrost regions of the Qinghai-Tibet Plateau based on the theory of soil enthalpy in order to estimate the soil energy state and analyze the energy changes in the active layer during freezing and thawing. The results indicate that the soil enthalpy has significant seasonal variation characteristics, which accurately reflected the freezing and thawing processes of the active layer. The change in soil enthalpy is significantly related to the thawing depth of the active layer in TGL and BLH, and its changing process can be expressed as an exponential relationship. Near the surface, the variation of the energy due to temperature gradient and actual evaporation can also be expressed as an exponential relationship. The promoting effect of heat conduction on the ALT is greater than the inhibiting effect of latent heat transfer, with the energy contribution from the phase change accounting for about 20-40% of the energy due to the temperature gradient. The thawing depth increases by 14.16-18.62 cm as the energy due to the temperature gradient increases by 1 MJ/m(2) and decreases by 2.75-7.16 cm as the energy due to the phase change increases by 1 MJ/m(2). Thus, the present study quantifies the effects of soil energy upon the ALT and facilitates an understanding of the hydrothermal processes in soils in permafrost regions.

不同初始值对多年冻土水热过程的模拟有着深刻的影响。本文利用青藏高原三江源多年冻土区西大滩站观测数据，驱动通用陆面模式CLM4.5（Community Land Model version 4.5）对该站多年冻土进行为期14个月的模拟研究。设计三组试验，检验CLM4.5模式对多年冻土模拟性能，探究不同初始土壤温度、液态水含量以及含冰量对模拟结果的影响，并对土壤初始含冰量的计算进行改进，提高了模式对多年冻土水热过程的模拟。通过对比土壤含冰量模拟值，液态水含量和土壤温度观测值与模拟值，结果表明：（1）初始土壤温度、液态水含量会通过影响初始土壤含冰量进而影响CLM4.5模式对多年冻土水热过程的模拟。（2）CLM4.5默认初始土壤温度、液态水含量时，计算出的初始含冰量为0 m3·m-3，这使得模式不能准确模拟出多年冻土的特征。在2015年11月上旬至2016年8月上旬土壤含冰量大于0.01m3·m-3，其余时段土壤含冰量几乎为0 m3·m-3；整层土壤液态水含量从冬...

不同初始值对多年冻土水热过程的模拟有着深刻的影响。本文利用青藏高原三江源多年冻土区西大滩站观测数据，驱动通用陆面模式CLM4.5（Community Land Model version 4.5）对该站多年冻土进行为期14个月的模拟研究。设计三组试验，检验CLM4.5模式对多年冻土模拟性能，探究不同初始土壤温度、液态水含量以及含冰量对模拟结果的影响，并对土壤初始含冰量的计算进行改进，提高了模式对多年冻土水热过程的模拟。通过对比土壤含冰量模拟值，液态水含量和土壤温度观测值与模拟值，结果表明：（1）初始土壤温度、液态水含量会通过影响初始土壤含冰量进而影响CLM4.5模式对多年冻土水热过程的模拟。（2）CLM4.5默认初始土壤温度、液态水含量时，计算出的初始含冰量为0 m3·m-3，这使得模式不能准确模拟出多年冻土的特征。在2015年11月上旬至2016年8月上旬土壤含冰量大于0.01m3·m-3，其余时段土壤含冰量几乎为0 m3·m-3；整层土壤液态水含量从冬...

不同初始值对多年冻土水热过程的模拟有着深刻的影响。本文利用青藏高原三江源多年冻土区西大滩站观测数据，驱动通用陆面模式CLM4.5（Community Land Model version 4.5）对该站多年冻土进行为期14个月的模拟研究。设计三组试验，检验CLM4.5模式对多年冻土模拟性能，探究不同初始土壤温度、液态水含量以及含冰量对模拟结果的影响，并对土壤初始含冰量的计算进行改进，提高了模式对多年冻土水热过程的模拟。通过对比土壤含冰量模拟值，液态水含量和土壤温度观测值与模拟值，结果表明：（1）初始土壤温度、液态水含量会通过影响初始土壤含冰量进而影响CLM4.5模式对多年冻土水热过程的模拟。（2）CLM4.5默认初始土壤温度、液态水含量时，计算出的初始含冰量为0 m3·m-3，这使得模式不能准确模拟出多年冻土的特征。在2015年11月上旬至2016年8月上旬土壤含冰量大于0.01m3·m-3，其余时段土壤含冰量几乎为0 m3·m-3；整层土壤液态水含量从冬...

Soil thermal conductivity (STC) is essential parameter for revealing thermodynamic changes and projecting changes in soil thermal regimes. However, the incorporation of different STC schemes into land surface process models (LSMs) can afford large errors. Thus, to accurately simulate soil thermal regimes in permafrost regions, a suitable STC scheme in LSMs is important. Herein, we selected nine normalized STC schemes and evaluated their performance in simulating STC and soil temperatures with in situ measurements in permafrost regions on the Tibetan Plateau (TP). These schemes were divided into three categories and incorporated into the latest version of the Community Land Model (CLM5.0). The results showed that the category comprising minerals, soil organic matter, and gravel soil afforded better performance at most sites than the other categories. The Balland and Arp (BA2005), Chadburn (C2015), and Bao (B2016) schemes had better performances in their affiliated categories, respectively. The BA2005 scheme ranked the best among the selected schemes with an average root-mean-square error decreased of 56.2% and 15.0% in simulating STC and soil temperatures compared to the default scheme, respectively. Additionally, the different schemes yielded a maximum difference of 2.69 W.m(-1) K-1 and 2.55 degrees C in simulating STC and soil temperature, respectively. Possible causes affecting the results were also investigated. The results indicated that soil moisture is a determinant: slight changes in soil moisture may cause large changes in thermal processes. However, the CLM5.0 yields large uncertainties of soil moisture. In addition, soil properties, atmospheric forcing data, and model structures also yielded errors in the simulated results. Note that no single STC scheme can be applied to all regions with satisfactory results. Therefore, multiple schemes need to be employed depending on their suitability in different regions. And more studies should focus on the accuracy of the hydraulic processes, especially soil hydraulic conductivity, unfrozen water, and snow processes.