Parmar et al. (2026) Evaluation of representation of seasonally frozen ground characteristics in Land Surface Models: JSBACH and CLM

Identification

• Journal: ˜The œcryosphere
• Year: 2026
• Date: 2026-07-28
• Authors: Mittal Parmar, Kristina Fröhlich, Antonella Sanna, Tobias Stacke, Marianna Benassi, Zhicheng Luo, Daniele Peano, Bodo Ahrens
• DOI: 10.5194/tc-20-4157-2026

Research Groups

• Institute for Atmospheric and Environmental Sciences, Goethe University Frankfurt, Germany
• Deutscher Wetterdienst, Offenbach, Germany
• Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici, CMCC, Bologna, Italy
• Max Planck Institute for Meteorology, Hamburg, Germany

Short Summary

This study evaluates the representation of seasonally frozen ground characteristics in two land surface models (LSMs), JSBACH and CLM, using ERA5 reanalysis data. The results show that JSBACH reproduces frozen ground extent most realistically but simulates reduced snow depth, leading to weaker insulation and deeper seasonal freezing.

Objective

• Evaluate the representation of seasonally frozen ground characteristics in two land surface models (LSMs), JSBACH and CLM.
• Investigate the causes of biases in simulated SFG characteristics.
• Assess how errors in simulated snow cover characteristics affect biases in SFG characteristics.

Study Configuration

• Spatial Scale: Global, with a focus on Russia.
• Temporal Scale: 1986-2022.

Methodology and Data

• Models used: JSBACH (Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg) and CLM (Community Land Model).
• Data sources: ERA5 reanalysis data, RIHMI-WDC observational dataset.

Main Results

• JSBACH reproduces frozen ground extent most realistically but simulates reduced snow depth, leading to weaker insulation and deeper seasonal freezing.
• CLM simulates soil temperatures comparatively close to observations under colder air temperatures but excessive snow cover leads to overestimated snow insulation.
• Systematic biases across models include premature autumn freezing and delayed spring thaw.

Contributions

• This study highlights the importance of improving model performance by better representing snow processes and detailed assessment of soil thermal and hydraulic properties.
• The results demonstrate that LSMs differ in how control of soil freeze-thaw is partitioned between air temperature and snow processes.

Funding

• Not specified.

Citation

@article{Parmar2026Evaluation,
  author = {Parmar, Mittal and Fröhlich, Kristina and Sanna, Antonella and Stacke, Tobias and Benassi, Marianna and Luo, Zhicheng and Peano, Daniele and Ahrens, Bodo},
  title = {Evaluation of representation of seasonally frozen ground characteristics in Land Surface Models: JSBACH and CLM},
  journal = {˜The œcryosphere},
  year = {2026},
  doi = {10.5194/tc-20-4157-2026},
  url = {https://doi.org/10.5194/tc-20-4157-2026}
}