We investigated radiatively driven under-ice convection in Lake Onego (Russia) during 3 consecutive late winters. In ice-covered lakes, where the temperature of water is below the temperature of maximum density, radiatively driven heating in the upper water column induces unstable density distributions leading to gravitational convection. In this work, we quantified the key parameters to characterise the radiatively driven under-ice convection: (1) the effective buoyancy flux, B * (driver), and its vertical distribution; (2) the convective mixed-layer thickness, h CML (depth scale); and (3) the convective velocity, w * (kinematic scale). We compared analytical w * scaling estimates to in situ observations from high-resolution acoustic Doppler current profilers. The results show a robust correlation between w * and the direct observations, except during the onset and decay of the solar radiation. Our results highlight the importance of accurately defining the upper limit of h CML in highly turbid water and the need for spectrally resolving solar radiation measurements and their attenuation for accurate B * estimates. Uncertainties in the different parameters were also investigated. We finally examined the implications of under-ice convection for the growth rate of nonmotile phytoplankton and provide a simple heuristic model as a function of easily measurable parameters.

Abstract. One-dimensional hydrodynamic models are nowadays widely recognized as key tools for lake studies. They offer the possibility to analyze processes at high frequency, here referring to hourly timescales, to investigate scenarios and test hypotheses. Yet, simulation outputs are mainly used by the modellers themselves and often not easily reachable for the outside community. We have developed an open-access web-based platform for visualization and promotion of easy access to lake model output data updated in near-real time (http://simstrat.eawag.ch, last access: 29 August 2019). This platform was developed for 54 lakes in Switzerland with potential for adaptation to other regions or at global scale using appropriate forcing input data. The benefit of this data platform is practically illustrated with two examples. First, we show that the output data allows for assessing the long-term effects of past climate change on the thermal structure of a lake. The study confirms the need to not only evaluate changes in all atmospheric forcing but also changes in the watershed or throughflow heat energy and changes in light penetration to assess the lake thermal structure. Then, we show how the data platform can be used to study and compare the role of episodic strong wind events for different lakes on a regional scale and especially how their thermal structure is temporarily destabilized. With this open-access data platform, we demonstrate a new path forward for scientists and practitioners promoting a cross exchange of expertise through openly sharing in situ and model data.

Anthropogenic heat emissions into inland waters influence water temperature and affect stratification, heat and nutrient fluxes, deep water renewal, and biota. Given the increased thermal stress on these systems by growing cooling demands of riparian/coastal infrastructures in combination with climate warming, the question arises on how to best monitor and manage these systems. In this study, we investigate local and system‐wide physical effects on the medium‐sized perialpine Lake Biel (Switzerland), influenced by point‐source cooling water emission from an upstream nuclear power plant (heat emission ∼700 MW, ∼18 W m−2 lake wide). We use one‐dimensional (SIMSTRAT) and three‐dimensional (Delft3D‐Flow) hydrodynamic numerical simulations and provide model resolution guidelines for future studies of thermal pollution. The effects on Lake Biel by the emitted excess heat are summarized as: (i) clear seasonal trend in temperature increase, locally up to 3.4°C and system‐wide volume mean ∼0.3°C, which corresponds to one decade of regional surface water climate warming; (ii) the majority of supplied thermal pollution (∼60%) leaves this short residence time (∼58 days) system via the main outlet, whereas the remaining heat exits to the atmosphere; (iii) increased length of stratified period due to the stabilizing effects of additional heat; (iv) system‐wide effects such as warmer temperature, prolonged stratified period, and river‐caused epilimnion flushing are resolved by both models whereas local raised temperature and river short circuiting was only identifiable with the three‐dimensional model approach. This model‐based method provides an ideal tool to assess man‐made impacts on lakes and their downstream outflows.

Abstract. This paper presents an improvement of a onedimensional lake hydrodynamic model (Simstrat) to characterize the vertical thermal structure of deep lakes. Using physically based arguments, we refine the transfer of wind energy to basin-scale internal waves (BSIWs). We consider the properties of the basin, the characteristics of the wind time series and the stability of the water column to filter and thereby optimize the magnitude of wind energy transferred to BSIWs. We show that this filtering procedure can significantly improve the accuracy of modelled temperatures, especially in the deep water of lakes such as Lake Geneva, for which the root mean square error between observed and simulated temperatures was reduced by up to 40 %. The modification, tested on four different lakes, increases model accuracy and contributes to a significantly better reproduction of seasonal deep convective mixing, a fundamental parameter for biogeochemical processes such as oxygen depletion. It also improves modelling over long time series for the purpose of climate change studies.

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