Surface thermal patterns of Lake Geneva, Switzerland, from 2008 to 2012

In this study we characterize the spatial and temporal variability of the lake surface water temperature (LSWT), lake surface heat fluxes as well as the heat content of Lake Geneva from March 2008 to December 2012. This was accomplished using Advanced Very High Resolution Radiometer (AVHRR) data for the LSWT and an operational numerical weather prediction model, namely COSMO-2, for the meteorological data. Available bulk models for different components of the surface heat flux were cataloged and then combined (using all possible combinations). Each of the assembled models was calibrated to produce the best overall model for the surface heat flux. Calibration was based on the temporal evolution of the heat budget, which was estimated using two long-term time series of vertical temperature profiles (one in the Lake Geneva’s large basin and one in its small basin). Empirical Orthogonal Function (EOF) analysis was used to assess the relationship between the variability of the LSWT and meteorological forcing. The dominant EOF mode, which explains 74% of the observed variance for wind speed, 78% for evaporative heat flux and more than 90% for other parameters, shows uniform patterns associated with the annual cycle. Their temporal amplitude reveal a time lag between total surface heat flux and LSWT variation. On the other hand, some zones are detectable in the spatial patterns of the second and third modes. This analysis indicates a good correlation between the variation of wind forcing and evaporative heat flux in the first three modes.

Surface heat flux variability of a large lake: Lake Geneva, Switzerland

David Andrew Barry, Damien Bouffard, Abolfazl Irani Rahaghi, Ulrich Lemmin

The heat budget of a lake is a fundamental component of physical limnology, and is strongly dependent on the surface heat flux. However, the surface energy exchange depends on several factors, making it difficult to estimate. In this study we employed several bulk formulas to estimate Lake Geneva’s surface heat flux. Combination of different surface heat flux terms leads to a surface heat exchange model which requires various data. Different data sources were used in the heat flux estimates. Meteorological data were taken from an operational numerical weather prediction model, namely COSMO-2 (run by the Swiss meteorological service), while satellite imagery was used for the lake surface water temperature (LSWT). In order to find the best combination of the bulk formulas and to calibrate the model, the temporal evolution of the heat budget was estimated using long-term time series of vertical temperature profiles. Vertical temperature profiles at two points (one in the Lake Geneva’s large basin and one in its small basin) were used. A sensitivity analysis was performed to find the key parameters, and more significantly the optimal combination of different heat flux terms. Finally, the spatio-temporal surface heat flux variation was calculated according to the proposed model. In addition, the relationship between variability of the surface heat flux and meteorological forcing was assessed. The different models, which are of differing complexity, gave reasonably consistent results, with differences attributed to simplifications inherent in them. The modeling results revealed that the LSWT and wind forcing are dominant factors underlying Lake Geneva surface heat flux spatial variation, while its temporal variability is mainly due to the global radiation and air temperature changes. In conclusion, the bulk heat balance approach is a useful tool to estimate various heat flux terms as well as their monthly or seasonally contributions. But, in large lakes where the LSWT is highly variable, the variable surface heat flux would be unavoidable.

2014

The Importance of Systematic Spatial Variability in the Surface Heat Flux of a Large Lake: A Multiannual Analysis for Lake Geneva

David Andrew Barry, Andrea Cimatoribus, Abolfazl Irani Rahaghi, Ulrich Lemmin

The spatiotemporal surface heat flux (SurHF) distribution over Lake Geneva, the largest lake in Western Europe, was estimated for a 7‐year period (2008–2014). Data sources included hourly maps of over‐the‐lake assimilated meteorological data from a validated numerical weather model and lake surface water temperature (LSWT) from satellite imagery. A set of bulk algorithms, previously optimized and calibrated at two locations in Lake Geneva, was used. Results indicate a systematic long‐term average spatial range of >40 Wm‐2 between different parts of the lake and little year‐to‐year variability. This variability is mainly due to topographically induced wind sheltering over parts of the lake, which in turn produces spatial variability in the sensible and latent heat fluxes. These results are supported by a systematic spatial heat content variability obtained from long‐term temperature profile measurements in the lake. During spring, a lower SurHF spatial range was evident. Unlike other seasons, the spring spatial variability of air‐water temperature differences and, to a lesser extent, the global radiation variability resulting from sheltering by the mountainous topography were the main drivers of the SurHF spatial variability. Analysis of the atmospheric thermal boundary layer showed stable conditions from March to early June and unstable conditions for the rest of the year. This regime change can explain the low SurHF spatial variability observed during spring. The results emphasize that spatial variability in meteorological and LSWT patterns, and consequently in the spatiotemporal SurHF data, should be considered when assessing the time evolution of the heat budget of large lakes.

2019

Large-Eddy Simulation of the Convective Atmospheric Boundary Layer over Heterogeneous Land Surfaces

Chad Higgins, Daniel Nadeau, Eric Richard Pardyjak, Marc Parlange

The parameterization of the atmospheric boundary layer is essential for accurate numerical weather predictions. The near-surface values of air temperature or wind speed for instance are highly dependent on the complex land – atmosphere interactions over heterogeneous terrain. Over such surfaces, several open challenges remain regarding the growth of internal boundary layers, the determination of mixing layer heights and the spatial distribution of heat and momentum fluxes. The large-eddy simulation (LES) code we apply is based on the robust Lagrangian scale-dependent dynamic subgrid-scale model (Bou-Zeid et al., 2005, Physics of Fluids). The flow is driven by a mean pressure gradient expressed in terms of horizontal geostrophic winds. The code is pseudo-spectral with spectral decomposition in the horizontal dimensions. Land surface heterogeneities take the form of spatially distributed patches of surface temperature and roughness derived from satellite imagery and land use analysis. The simulation of the complete diurnal cycle is possible but we restrict our discussion to fully convective conditions. Data from LITFASS – 2003 (Lindenberg Inhomogeneous Terrain Fluxes between Atmosphere and Surface: a long-term Study) are used to validate the simulation results. The LES domain covers a 99-m meteorological tower with turbulent measurements and five surface micrometeorological stations. We investigate the presence of large-scale turbulent structures that are typical for daytime conditions with a particular interest in the blending height. Overall, this study illustrates how important is the accurate parameterization of heterogeneous terrain in studies of the atmospheric boundary layer.

2009

Surface heat flux variability of a large lake: Lake Geneva, Switzerland

David Andrew Barry, Damien Bouffard, Abolfazl Irani Rahaghi, Ulrich Lemmin

2014