Journal
HYDROLOGY RESEARCH
Volume 40, Issue 2-3, Pages 234-248Publisher
IWA PUBLISHING
DOI: 10.2166/nh.2009.030
Keywords
climate change; lake thermodynamics; Markov chain Monte Carlo; modelling
Categories
Funding
- Commission of European Communities
- Research Council of Norway
- Norwegian Institute for Water Research [GOCE-CT-2003-505540]
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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 degrees C increase in epilimnion and 2.7-4.4 degrees 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.
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