The impact of meteorological conditions on snow and ice thickness in an Arctic lake

• Published in: Tellus A: Dynamic Meteorology and Oceanography
• Main Authors: Lixin Wei, Xiaohua Deng, Bin Cheng, Timo Vihma, Henna-Reetta Hannula, Ting Qin, Jouni Pulliainen
• Format: Article in Journal/Newspaper
• Language: English
• Published: Stockholm University Press 2016
• Subjects: Snow; ice; temperature; precipitation; modelling Arctic lake; Oceanography; GC1-1581; Meteorology. Climatology; QC851-999; Arctic; Arctic Lake; Pacific; Unari
• Online Access: https://doi.org/10.3402/tellusa.v68.31590; https://doaj.org/article/e59e76a0051a44f6a92f4cc02471eacd

Inter-annual variation of meteorological conditions and their effects on snow and ice thickness in an Arctic lake Unari (67.14° N, 25.73° E) were investigated for winters 1980/1981–2012/2013. The lake snow and ice thicknesses were modelled applying a thermodynamic model, and the results were compared with observations. Regression equations were derived for the relationships between meteorological parameters and modelled snow and ice properties. The composite differences of large-scale atmospheric circulation patterns between seasons of thin and thick ice were analysed. The air temperature had an increasing trend (statistical significance p<0.05) during the freezing season (1.0° C/decade), associated with an increasing trend of liquid precipitation (p<0.05) in winter. Both observed and modelled average and maximum ice thicknesses showed a decreasing trend (p<0.05). The model results were statistically more reliable (1) for lake ice than snow and (2) for seasonal means than maxima. Low temperature with less precipitation prompted the formation of columnar ice, whereas strong winds and heavy snowfall were in favour of granular ice formation. The granular (columnar) ice thickness was positively (negatively) correlated with precipitation. The seasonal mean and maximum modelled lake ice and snow thicknesses were controlled by precipitation and temperature history, with 58–86 % of the inter-annual variance explained. Using regression equations derived from data from 1980 to 2013, snow and ice thickness for the following winter seasons was statistically forecasted, yielding errors of 9–12 %. Among large-scale climate indices, the Pacific Decadal Oscillation was the only one that correlated with inter-annual variations in the seasonal average ice thickness in Lake Unari.