Preprints
https://doi.org/10.5194/essd-2021-54
https://doi.org/10.5194/essd-2021-54

  01 Apr 2021

01 Apr 2021

Review status: this preprint is currently under review for the journal ESSD.

Meteorological, snow and soil data (2013–2019) from a herb tundra permafrost site at Bylot Island, Canadian high Arctic, for driving and testing snow and land surface models

Florent Domine1,2,3, Georg Lackner1,2,4, Denis Sarrazin2, Mathilde Poirier2,5, and Maria Belke-Brea1,2,6 Florent Domine et al.
  • 1Takuvik Joint International Laboratory, Université Laval (Canada) and CNRS-INSU (France), Québec, Canada
  • 2Centre d’Études Nordiques, Université Laval, Québec, Canada
  • 3Département de chimie, Université Laval, Québec, Canada
  • 4Département de génie civil et de génie des eaux, Université Laval, Québec, Canada
  • 5Département de biologie, Université Laval, Québec, Canada
  • 6Département de géographie, Université Laval, Québec, Canada

Abstract. Seasonal snow covers Arctic lands 6 to 10 months of the year and is therefore an essential element of the Arctic geosphere and biosphere. Yet, even the most sophisticated snow physics models are not able to simulate fundamental physical properties of Arctic snowpacks such as density, thermal conductivity and specific surface area. The development of improved snow models is in progress but testing requires detailed driving and validation data for high Arctic herb tundra sites, which are presently not available. We present 6 years of such data for an ice-wedge polygonal site in the Canadian high Arctic, in Qarlikturvik valley on Bylot Island at 73.15 °N. The site is on herb tundra with no erect vegetation and thick permafrost. Detailed soil properties are provided. Driving data are comprised of air temperature, air relative and specific humidity, wind speed, short wave and long wave downwelling radiation, atmospheric pressure and precipitation. Validation data include time series of snow depth, shortwave upwelling radiation, surface temperature, snow temperature profiles, soil temperature and water content profiles at five depths, snow thermal conductivity at three heights and soil thermal conductivity at 10 cm depth. Field campaigns in mid-May for 5 of the 6 years of interest provided spatially-averaged snow depths and vertical profiles of snow density and specific surface area in the polygon of interest and at other spots in the valley. Data are available at https://doi.org/10.5885/45693CE-02685A5200DD4C38 (Domine et al., 2021). Data files will be updated as more years of data become available.

Florent Domine et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2021-54', Joshua King, 04 May 2021
  • RC2: 'Comment on essd-2021-54', Anonymous Referee #2, 11 May 2021

Florent Domine et al.

Data sets

Meteorological, snow and soil data from Bylot Island, Canadian high-Arctic, for driving and testing snow and land surface models Domine, F., Lackner, G., Sarrazin, D., Poirier, M., and Belke-Brea, M. https://doi.org/10.5885/45693CE-02685A5200DD4C38

Florent Domine et al.

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Short summary
Current sophisticated snow physics models were mostly designed for Alpine conditions and cannot adequately simulate the physical properties of Arctic snowpacks. New snow models will require Arctic data sets for forcing and validation. We provide an extensive driving and testing data set from a high Arctic herb tundra site in Canada. Unique validating data include continuous time series of snow and soil thermal conductivity and temperature profiles. Field observations in spring are provided.