Abstract

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 °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.

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