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

Abstract

Simulation of surface energy fluxes and stratification of a small boreal lake by a set of one-dimensional models A B S T R A C T Five one-dimensional (1D) lake models were run for the open water season in 2006 for Lake Valkea-Kotinen (Finland) using on-lake measured meteorological forcing. The model results were validated using measurements of water temperature and of eddy covariance (EC) fluxes. The surface temperature is satisfactorily simulated by all models showing slight overestimation (by 0.1Á1.18C). Both sensible and latent heat fluxes are positively biased in respect to EC data, consistent with earlier studies. However, correlation coefficients between EC-fluxes and those simulated are relatively high ranging from 0.55 to 0.74. The skill to simulate vertical temperature profiles by different models is assessed as well. It is found that the lake models underestimate the EC-derived surface drag coefficient, however providing realistic temperature profiles. It is argued that the real momentum flux from the atmosphere is larger than simulated, however it is split up between the wave development and the acceleration of lake currents. Adopting the simple parameterisation for momentum flux partitioning in one of the models showed that this mechanism can be significant. Finally, the effect of including the lake bathymetry data in k-o models was the drastic overheating of water below the thermocline. This is likely to be caused by omitting the heat flux at the lake margins. Thus, the parameterisation of heat flux at the lake's margins should be included in the models; otherwise it is recommended to neglect bathymetry effects for such small water bodies as the Lake Valkea-Kotinen.

Exploring, exploiting and evolving diversity of aquatic ecosystem models: a community perspective

“…There is an increasing number of applications in hydrology and hydrodynamics as well (e.g. Stepanenko et al 2014;Thiery et al 2014). In aquatic ecosystem modelling, the use of ensemble techniques is still rare (but see examples in, for instance, Lenhart et al 2010;Ramin et al 2012;Gal et al 2014;Nielsen et al 2014;Trolle et al 2014).…”

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

“…see reasoning based on results of largeeddy simulation (LES) (Glazunov and Stepanenko, 2015) or laboratory experiments (Markfort et al, 2013)). However, it turns out that in the practice of 1-D lake model applications to such lakes not only Monin-Obukhov is the most physically based option in these models for obtaining surface heat fluxes so far, but also it still delivers acceptable accuracy for calculated surface temperature at seasonal timescales (Stepanenko et al, 2014;. As to momentum flux, it has been shown to be a crucial parameter regulating the rate of mixed-layer deepening during summer (see e.g.…”

“…As to momentum flux, it has been shown to be a crucial parameter regulating the rate of mixed-layer deepening during summer (see e.g. Stepanenko et al, 2014). This resulted in a widespread modelling practice where the drag coefficient, defining momentum flux at a given wind speed, has become a tunable parameter in k − -based lake models.…”

“…Boundary conditions for momentum equations are momentum flux from the atmosphere, calculated according to air surface layer bulk formulae (Paulson, 1970;Businger et al, 1971;Beljaars and Holtslag, 1991), and friction at the deepest part of bottom following quadratic dependence on velocity using the Chézy coefficient. Momentum flux accelerating currents is parameterized as a fraction of total momentum flux from the atmosphere (Stepanenko et al, 2014), because in conditions of limited fetch (small lakes) a part of total momentum flux is consumed by wave development. Partitioning momentum flux between waves and in-water currents significantly reduces shear-driven vertical mixing during summertime.…”

“…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.…”