Evaluation of representation of seasonally frozen ground characteristics in Land Surface Models: JSBACH and CLM

Abstract. Land surface models (LSMs) differ in simulating winter soil conditions due to complex freeze-thaw processes and snow-soil interactions, leading to uncertainties in spring and summer soil moisture and runoff. This study evaluates standalone simulations from two LSMs, JSBACH and CLM, driven by ERA5 data (1986–2022), compares them with ERA5-Land to study model differences across cold regions, and then examines all three models against the reference RIHMI-WDC observational dataset at 26 sites to better understand how SFG characteristics (timing, duration, and freeze depth) are represented in these models. The research aims to identify biases in simulated seasonally frozen ground (SFG) characteristics, investigate their causes, and assess how snow cover errors propagate into frozen ground biases using site-level evaluation over Russia. The importance of snow parameterization is highlighted in this study through an improvement to the snow density scheme in JSBACH, which reduced its cold bias in soil temperature by up to 10–20 °C, and this improved version was used for the comparative analysis. Among the models assessed in this study, JSBACH reproduces frozen ground extent most realistically, closely matching reference estimates of SFG and permafrost (PEFT) extent, but it simulates reduced snow depth (mean bias = −14.2 cm), leading to weaker insulation, enhanced soil cooling (mean bias = −3.7 °C), and deeper seasonal freezing, whereas CLM simulates soil temperatures comparatively close to observations (+0.1 °C) under colder air temperatures (−3.4 °C) and excessive snow (12.2 cm), indicating overestimated snow insulation. Site-level freeze-thaw evaluation reveals systematic biases across models, including premature autumn freezing and delayed spring thaw, leading to longer frozen ground duration (16 to 19 days) associated with contrasting snow insulation effects in CLM and JSBACH. Soil freezing in JSBACH responded too strongly to surface thermal forcing, whereas ERA5-Land and CLM showed an overestimated relationship between SFG and snow characteristics. This discrepancy indicates that LSMs differ in how control of soil freeze-thaw is partitioned between air temperature and snow processes. The study highlights that improving model performance requires better snow representation and a detailed assessment aimed at enhancing the parameterization of soil thermal and hydraulic properties.