Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/gmd-2017-50
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model evaluation paper
21 Mar 2017
Review status
This discussion paper is under review for the journal Geoscientific Model Development (GMD).
Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site
Mathieu Barrere1,2,3,4,5, Florent Domine1,2,3,6, Bertrand Decharme7, Samuel Morin4, Vincent Vionnet4, and Matthieu Lafaysse4 1Centre d’Études Nordiques, Université Laval, Québec City, QC, Canada
2Department of Geography, Université Laval, Québec City, QC, Canada
3Takuvik Joint International Laboratory, Université Laval (Canada) and CNRS-INSU (France), Québec City, QC, Canada
4Météo-France – CNRS, CNRM UMR 3589, CEN, Grenoble, France
5University Grenoble Alpes - CNRS - IRD, IGE, Grenoble, France
6Department of Chemistry, Université Laval, Québec City, QC, Canada
7Météo-France – CNRS, CNRM UMR 3589, Toulouse, France
Abstract. Global warming projections still suffer from a limited representation of the permafrost-carbon feedback. Predicting the response of the permafrost temperature to climate changes requires accurate simulations of the Arctic snow and soil properties. This study assesses the capacity of the coupled models ISBA-Crocus and ISBA-ES to simulate snow and soil properties at Bylot Island, a high Arctic site. Field measurements complemented with ERA-interim reanalysis were used to drive the models and to evaluate simulation outputs. Snow height, density, temperature, thermal conductivity and thermal resistance are examined to determine the critical variables involved in the soil thermal regime. Simulated soil properties are compared with measurements of thermal conductivity, temperature and water content. The simulated snow density profiles are erroneous, because Crocus and ES do not represent the upward water vapour fluxes generated by the strong temperature gradients within the snowpack. The resulting vertical profiles of thermal conductivity are inverted compared to observations, with high simulated values at the bottom of the snowpack. Still, ISBA-Crocus manages to successfully simulate the soil temperature in winter. Results are satisfactory in summer, but the temperature of the top soil could be better reproduced by representing adequately surface organic layers, i.e. mosses and litter, and in particular their water retention capacity. Transition periods (soil freezing and thawing) are the least well reproduced because the high basal snow thermal conductivity induces too rapid heat transfers between the soil and the snow in simulations. Hence, global climate models should carefully consider Arctic snow thermal properties, and especially the thermal conductivity of the basal snow layer, to perform accurate predictions of the permafrost evolution under climate changes.

Citation: Barrere, M., Domine, F., Decharme, B., Morin, S., Vionnet, V., and Lafaysse, M.: Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-50, in review, 2017.
Mathieu Barrere et al.
Mathieu Barrere et al.

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Evaluating the performance of coupled snow-soil models in SURFEXv8 to simulate the permafrost thermal regime at a high Arctic site - Data
M. Barrere and F. Domine
https://doi.org/10.5885/45460CE-9B80A99D55F94D95
Mathieu Barrere et al.

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Short summary
Global warming projections still suffer from a limited representation of the permafrost-carbon feedback. This study assesses the capacity of snow-soil coupled models to simulate the permafrost thermal regime at Bylot Island, a high Arctic site. Significant flaws are found in the description of Arctic snow properties, resulting in erroneous heat transfers between the soil and the snow in simulations. Improved snow schemes are needed to accurately predict the future of permafrost.
Global warming projections still suffer from a limited representation of the permafrost-carbon...
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