Soil water and heat transfer is one of the most important parts of water and energy partition between atmosphere and land surface, and it is more complicated over the cold regions. In this study, the observed soil moisture and temperature are selected from four sites over the Tibetan Plateau (TP) to evaluate the performances two versions of Community Land Model (CLM), that is, CLM4.5 and CLM5.0. In addition, soil temperature observations from 67 sites and soil moisture observations from Maqu and Naqu monitoring network over the TP were used to evaluate the performances of regional simulations. The results indicated that the simulated soil temperature generally coincided with that of the observed, while CLM5.0 outputs are closer to the observed soil temperature in the arid and semiarid regions compared to CLM4.5. Generally, CLM5.0 tended to overestimate soil moisture at most sites at four soil depths (5, 10, 20, and 40 cm) but got some improvements at Maqu site. The overestimation of soil moisture was mainly caused by the introduction of a dry surface layer-based (DSL) soil evaporation resistance parameterization in CLM5.0, which improves the soil evaporation simulation over the TP, especially in the semiarid region. Moreover, we tried to distinguish the factors that affect the soil water and heat transfer in the models. The results showed that soil property data play a main role in soil water and heat transfer modeling. Plain Language Summary The CLM5.0 is the latest version of the Community Land Model (CLM). Here, we selected observed soil moisture and temperature data over the Tibetan Plateau (TP) to evaluate the performances of CLM4.5 and CLM5.0. The results showed that the simulated soil temperature generally coincided with that of the observed, while CLM5.0 outputs are closer to the observed soil temperature in the arid and semiarid regions. Moreover, the simulated soil moisture by CLM5.0 tended to reduce the bias of soil moisture at subhumid area and overestimated soil moisture at semiarid area. The overestimation of soil moisture was mainly caused by the introduction of a dry surface layer-based (DSL) soil evaporation resistance parameterization in CLM5.0, which improves the soil evaporation and surface total water storage simulation over the TP, especially in the semiarid region. Finally, we replaced the forcing data (ITP) and soil property data by using the observed data to investigate the possibly causes in soil water and heat transfer. Single-point simulations show that model bias was possibly influenced by the uncertainties of soil category data and atmospheric forcing data. The impact of soil property data is more important than that caused by the forcing data.

In this study, soil moisture data from two reanalysis datasets (ERA‐Interim, ERA5), a satellite soil moisture product from the European Space Agency (ESA) and three assimilation datasets from the Global Land Data Assimilation System (GLDAS), that is, GLADS‐NOAH025, GLADS‐NOAH10, and GLDAS‐CLM were compared with the observed soil moisture data in Maqu and Maduo stations over the Three Rivers Source Region (TRSR) on the Tibetan Plateau in China. Comparative statistical parameters between the soil moisture observations and the products, including the root mean square error, correlation coefficient (R), and standard deviation ratio were calculated to evaluate the products in different seasons. It was found that most products overestimated the soil moisture values, among which GLADS‐NOAH025 had relatively good consistency with the observations in the surface soil layer (0–10 cm), whereas GLDAS‐CLM agreed well with the observations in the 10–40 cm layer. Both ERA5 and ERA‐interim soil moisture overestimated soil moisture at all levels. The responses of soil moisture to regional climate change over the TRSR were also investigated by using the GLDAS‐NOAH025 soil moisture product, the ESA soil moisture product, and the observations during the nonfreezing period. The results show that the trends of soil moisture are consistent with the precipitation changes in the main central part of the TRSR. A significant positive correlation was found between soil moisture and precipitation in most regions of the TRSR, which indicates that soil moisture increases with the increase of precipitation, except in the northwest TRSR, where the variation of soil moisture was possibly influenced by both the precipitation changes and the increase of evapotranspiration.

Soil water and heat transfer is especially complicated during the freezing and thawing processes over the high‐altitude cold regions. In this study, four sensitivity tests of soil water and heat transfer parameterizations including replacing soil property data (SP1), soil resistance scheme modification (SP2), soil thermal conductivity scheme (SP3) and virtual temperature scheme (SP4), and four combination experiments (SP1+SP2+SP3/SP5, SP1+SP2+SP4/SP6, SP1+SP3+SP4/SP7, and SP1+SP2+SP3+SP4/SP8) were done using Community Land Model (CLM5.0) to examine its performances for soil water and heat transfer modeling on the Tibetan Plateau (TP) both in single‐point and regional simulations. The observed data from five eddy covariance sites, four soil moisture and temperature networks and 60 sites of soil temperature observations on the TP were used to evaluate the results. Single‐point simulations show that SP2 experiment reduced the wet biases of soil moisture in semiarid area, but enhanced the error of soil temperature. SP6 shows the best performances in simulating soil moisture, and SP3 in soil temperature. Regional simulations show that the SP7 experiment had the best performances for soil water and heat transfer simulation on the TP, and improved the simulation of soil freezing‐thawing processes. Compared to CLM5.0 default simulation, SP7 shows the best performances. For soil moisture, it reduced average Bias by 23%, Root Mean Square Error (RMSE) by 18%, and increased the Correlation Coefficient (Corr) by2%. For soil temperature, it reduced the Bias by 9%, 10%, 23%, and 13% at four soil depths on the TP, respectively.