Abstract
In this study we analyzed turbulent heat fluxes over a seasonal ice cover on boreal lake located in southern Finland. Eddy covariance (EC) measurements from four ice-on seasons between 2014 and 2019 are compared to three different bulk transfer models: one with a constant transfer coefficient, and two with stability adjusted transfer coefficients: the Lake Heat Flux Analyzer and SEA-ICE. All three models correlate to the EC results well in general, although typically underestimating the magnitude and the variance of the flux in comparison to the EC observations. Differences between the models are small, with the constant transfer coefficient model performing slightly better than the stability adjusted models. Small difference in temperature and humidity between surface and air results in low correlation between models and EC. During melting periods (surface temperature T0 > 0 °C), the model performance for LE decreases when comparing to the freezing periods (T0 < 0 °C), while the opposite is true for H. At low wind speed EC shows relatively high fluxes (±20 W m−2) for H and LE due to non-local effects that the bulk models are not able to reproduce. Finally, the uncertainty in the estimation of the surface temperature and humidity affects the bulk heat fluxes, especially when the difference between surface and air values are small.
Highlights
In this study we analyzed turbulent heat fluxes over a seasonal ice cover on boreal lake located in southern Finland
4 Discussions & conclusions Turbulent heat fluxes were studied with an Eddy covariance (EC) setup for four winters over the ice cover of a boreal lake and these results were 340 compared to three bulk aerodynamic models, one that does not take into account the atmospheric boundary layer stability and
The greatest error producing effect can be attributed to the fact that estimating the skin tempera355 ture of a snowy surface is difficult, which has been previously reported as a major issue in modeling turbulent heat fluxes over snow and ice (Franz et al, 2018; Bourassa et al, 2013)
Summary
According to latest satellite based estimates, there are approximately 117 million lakes larger than 0.002 km globally (Verpoorter et al, 2014). 65 As the EC setup is not suited for all applications due to the technical complexity of its installation, simpler methods to compute the turbulent heat fluxes from more basic meteorological observations have been developed, with bulk aerodynamic method and profile method being the most popular They originated from the need to estimate turbulent heat fluxes in situations where only basic meteorological parameters were available, like with remote buoy based oceanographical measurement stations with very low power available. Ice-on lake energy balance has been studied, for example, on Lake Kilpisjärvi in NW Finnish Lapland (Leppäranta et al, 2017) and Lake Pääjärvi in Southern Finland (Wang et al, 2005; Jakkila et al, 2009), but these experiments were done without EC equipment and estimated turbulent heat fluxes by bulk aerodynamic formulae and the profile method. 9.12.2014 – 20.4.2015 (132 d) 23.1.2017 – 3.5.2017 (100 d) 3.12.2017 – 23.4.2018 (141 d) 16.11.2018 – 25.4.2019 (160 d)
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