A one-dimensional model intercomparison study of thermal regime of a shallow, turbid midlatitude lake

Abstract

Results of a lake model intercomparison study conducted within the framework of Lake Model Intercomparison Project are presented. The investigated lake was Großer Kossenblatter See (Germany) as a representative of shallow, (2 m mean depth) turbid midlatitude lakes. Meteorological measurements, including turbulent fluxes and water temperature, were carried out by the Lindenberg Meteorological Observatory of the German Meteorological Service (Deutscher Wetterdienst, DWD). Eight lake models of different complexity were run, forced by identical meteorological variables and model parameters unified as far as possible given different formulations of processes. All models generally captured diurnal and seasonal variability of lake surface temperature reasonably well. However, some models were incapable of realistically reproducing temperature stratification in summer. Total heat turbulent fluxes, computed by the surface flux schemes of the compared lake models, deviated on average from those measured by eddy covariance by 17–28 W m−2. There are a number of possible reasons for these deviations, and the conclusion is drawn that underestimation of real fluxes by the eddy covariance technique is the most probable reason. It is supported by the fact that the eddy covariance fluxes do not allow to close the heat balance of the water column, the residual for the whole period considered being ≈–28 W m−2. The effect of heat flux to bottom sediments can become significant for bottom temperatures. It also has profound influence on the surface temperatures in autumn due to convective mixing but not in summer when the lake stratification is stable. Thus, neglecting sediments shifts the summer–autumn temperature difference in models lacking explicit treatment of sediments considerably. As a practical recommendation based on results of the present study, we also infer that in order to realistically represent lakes in numerical weather prediction and climate models, it is advisable to use depth-resolving turbulence models (or equivalent) in favor of models with a completely mixed temperature profile.