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Hydrology Research Vol 40 No 2-3 pp 234–248 © IWA Publishing 2009 doi:10.2166/nh.2009.030

Impacts of projected climate change on the thermodynamics of a shallow and a deep lake in Finland: model simulations and Bayesian uncertainty analysis

Tuomo M. Saloranta, Martin Forsius, Marko Järvinen and Lauri Arvola

Norwegian Institute for Water Research (NIVA), Gaustadalléen 21, Oslo N-0349, Norway Tel.: +47 9916 4559 Fax: +47 2218 5200 E-mail: tuomo.saloranta@niva.no
Finnish Environment Institute (SYKE), PO Box 140, Helsinki FI-00251, Finland
Lammi Biological Station, University of Helsinki, Pääjärventie 320, Lammi FI-16900, Finland


A lake model (MyLake) has been used to simulate the impacts of the projected future (2071–2100) climate on the thermodynamic properties of a shallow and a deep lake in Finland. The model has been calibrated using a Bayesian Markov chain Monte Carlo (MCMC) simulation method. The model results show, among others, that the largest change in water temperature in a projected future climate occurs in April–May when a 4.6–7.6°C increase in epilimnion and 2.7–4.4°C increase in whole-lake monthly mean temperature occurs compared to the climate of 1961–1990. This corresponds to a large decrease in the probability of ice cover in March–April. In winter and early spring a negative correlation was obtained between lake water and air temperatures in a projected future climate due to the thermal buffering feature of the lake ice and snow cover. The uncertainties connected to the choice of the general circulation model and the boundary condition forcing for the regional atmospheric climate model were often significantly larger than the uncertainties connected to MyLake model parameter values.

Keywords: climate change; lake thermodynamics; Markov chain Monte Carlo; modelling

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