Inter-annual variation in lake ice composition in the European Arctic: observations based on high-resolution thermistor strings

• Published in: Earth System Science Data
• Main Authors: Cheng, Bin, Cheng, Yubing, Vihma, Timo, Kontu, Anna, Zheng, Fei, Lemmetyinen, Juha, Qiu, Yubao, Pulliainen, Jouni
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2021
• Subjects: article; Verlagsveröffentlichung; Climate change; Global warming; Sodankylä; Lapland
• Online Access: https://doi.org/10.5194/essd-13-3967-2021; https://noa.gwlb.de/receive/cop_mods_00057753; https://noa.gwlb.de/servlets/MCRFileNodeServlet/cop_derivate_00057403/essd-13-3967-2021.pdf; https://essd.copernicus.org/articles/13/3967/2021/essd-13-3967-2021.pdf

Climate change and global warming strongly impact the cryosphere. The rise of air temperature and change of precipitation patterns lead to dramatic responses of snow and ice heat and mass balance. Sustainable field observations on lake air–snow–ice–water temperature regime have been carried out in Lake Orajärvi in the vicinity of the Finnish Space Centre, a Flagship Supersite in Sodankylä in Finnish Lapland since 2009. A thermistor-string-based snow and ice mass balance buoy called “Snow and ice mass balance apparatus (SIMBA)” was deployed in the lake at the beginning of each ice season. In this paper, we describe snow and ice temperature regimes, snow depth, ice thickness, and ice compositions retrieved from SIMBA observations as well as meteorological variables based on high-quality observations at the Finnish Space Centre. Ice thickness in Lake Orajärvi showed an increasing trend. During the decade of data collection (1) the November–May mean air temperature had an increasing trend of 0.16 ∘C per year, and the interannual variations were highly correlated (r = 0.93) with the total seasonal accumulated precipitation; (2) the maximum granular ice thickness ranged from 15 % to 80 % of the maximum total ice thickness; and (3) the snow depth on lake ice was not correlated (r = 0.21) with the total precipitation. The data set can be applied to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and to improve the parameterization of snow to ice transformation in snow and ice models. The data are archived at https://doi.org/10.5281/zenodo.4559368 (Cheng et al., 2021).