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

Simulation of surface energy fluxes and stratification of a small boreal lake by a set of one-dimensional models

“…The experimental setup in this study follows the LakeMIP protocol as described in Stepanenko et al (2010Stepanenko et al ( , 2013, and hence, it will be only briefly overviewed here. Physical parameters present in all models were unified as far as possible.…”

“…A short description of each model, relevant to ice-free conditions that are mostly simulated in this study, is given below, and a short summary of model features is presented in Table 2. More elaborate descriptions may be found in either original publications for each model cited below, or in Stepanenko et al (2013). Parameterisation of temperature profile in bottom sediments (soil) using self-similarity hypothesis CLM4-LISSS, Hostetler and Bartlein, 1990;Subin et al, 2012;Oleson et al, 2010 Multilayer/25 layers 600 An extended scheme from CLM4 model (Oleson et al, 2010;Subin et al, 2012) Henderson-Sellers parameterisation of eddy diffusivity, buoyant convection (Hostetler and Bartlein, 1990) Heat conductance in bottom sediments (soil) SimStrat, Goudsmit et al, 2002;Perroud et al, 2009 Multilayer/40/0.05 m 600 Empirical equations (Livingstone and Imboden, 1989;Kuhn, 1978;Dingman et al, 1968) FLake (Fresh-water Lake model; Mironov et al, 2010;Kirillin et al, 2011) uses a conceptual scheme of dividing the water column into two layers: the mixed layer, described by its temperature and depth, and the thermocline, in which the non-dimensional temperature profile is defined by a function of non-dimensional depth (selfsimilarity concept; Kitaigorodskii and Miropolsky, 1970).…”

“…This lake was chosen because: (i) it is quite different from previously studied lake Kossenblatter , being surrounded by forest and having much smaller size but similar depth; (ii) the available measurements at the Lake Valkea-Kotinen include the same set of variables that were used in Stepanenko et al (2013). This allows identifying the model skills to simulate the lake thermal regime and energy fluxes in two contrasting conditions.…”

Understanding the performance of the FLake model over two African Great Lakes

“…To better understand the present lake hydrodynamics and their relation to aquatic chemistry and biology, several comprehensive one-, two-or three-dimensional hydrodynamic models have been developed and applied in standalone mode to lakes in this region (Schmid et al, 2005;Naithani et al, 2007;Gourgue et al, 2011;Verburg et al, 2011). However, to investigate the two-way interactions between climate and lake processes over East Africa, a correct representation of lakes within regional climate models (RCMs) and general circulation models (GCMs) is essential (Stepanenko et al, 2013; see Appendix for a list of all acronyms, variables and simulation names). For now, the high computational expense of complex hydrodynamic lake models limits the applicability of coupled lake-atmosphere model systems to process studies (Anyah et al, 2006;Thiery et al, 2014).…”

LAKE 2.0: a model for temperature, methane, carbon dioxide and oxygen dynamics in lakes

“…Vertical turbulent flux of dissolved gases through hypolimnion and metalimnion are of special concern in this work, since CO 2 and CH 4 mostly originate in the hypolimnion, while the major interest for the community is how much of these species evade to the atmosphere. The lake model developed here is based on the LAKE model, which has been continuously advanced during the last decade at Moscow State University (Stepanenko and Lykossov, 2005;Stepanenko et al, 2011) and was extensively validated in LakeMIP (Lake Model Intercomparison Project) experiments (Stepanenko et al, , 2013(Stepanenko et al, , 2014 in terms of lake temperature and energy fluxes. The main development of LAKE 2.0 compared to LAKE includes a biogeochemical module, describing processes related to O 2 , CO 2 and CH 4 dynamics, multiple columns of sediments (facilitating heat and gas exchange between the water column and sediments at different depths) and surface seiche parameterization.…”