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

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.

Large-scale and meso-scale surface heat flux patterns of Lake Geneva

Abolfazl Irani Rahaghi

Diverse studies have confirmed the adverse impact of global climate change in lakes. In order to establish effective water quality management policies, it is essential to understand how the heat exchange between the atmosphere and the lake evolves under these conditions. Lake Surface Water Temperature (LSWT), which is the key coupling parameter at the interface of the Atmospheric Boundary Layer (ABL) and the lake surface layer is often considered the reference climate variable in this context. The temporal development of the lake heat content is mainly controlled by the net Surface Heat Flux (SurHF) at this interface. LSWT, ABL conditions and SurHF are linked and may vary in space and time. However, past studies often relied on single point measurements for SurHF estimation and this can result in significant errors in the heat budget analysis, particularly over large lakes. In this thesis, the dynamics of SurHF over Lake Geneva, the largest water body in Western Europe, were investigated with an emphasis on the effect of spatial heterogeneity of the LSWT and meteorological parameters on two different scales. A large-scale study for the whole surface of the lake was carried out using meteorological data and satellite images with a pixel size of 1 km2 that can depict large-scale thermal patterns, but not the meso- or small-scale processes. To address the SurHF aspects at the meso-scale level, an airborne system for resolving LSWT with a ~1 m pixel resolution was developed that allowed investigating the structure of the processes on scales within a satellite pixel. In a multi-annual large-scale analysis, the SurHF of Lake Geneva was estimated for a 7-y period (2008 to 2014). Data sources included hourly maps of over-the-lake reanalysis meteorological data from a numerical weather model, LSWT from satellite imagery, and long-term temperature depth profiles at two locations. The most common formulas for different heat flux components were combined and calibrated at two locations based on the heat content balance in the water column. When optimized for one lake temperature profile location, SurHF models failed to predict the temperature profile at the other location due to the spatial variability of meteorological parameters. Consequently, a procedure for calibrating the optimal SurHF models was developed using two profile locations. The combination of the modified parameterization of the Brutsaert equation for incoming atmospheric radiation and of similarity theory bulk parameterization algorithms for turbulent SurHF provided the most accurate SurHF estimates. It was found that if a calibration was not carried out optimally, the calculated change in heat content could be much higher than the observed annual climate change-induced trend. The developed calibration procedure improved parameterization of bulk transfer coefficients, mainly under low wind regimes. The optimized and calibrated set of bulk models was then used to compute the spatiotemporal SurHF. Model results indicated an average spatial range of > ± 20 Wm-2. This was mainly caused by wind-sheltering over parts of the lake, which produced spatial anomalies in sensible and latent heat fluxes. During spring, much less spatial variability was evident compared to other seasons. The spring variability was ca

EPFL2018

Spatial variability of multi-annual seasonal surface heat flux patterns of Lake Geneva

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

The dynamics of the spatiotemporal surface heat flux (SurHF) of Lake Geneva (Switzerland/France) was estimated for a 7-y period. Data sources included hourly maps of over-the-lake assimilated meteorological data from a numerical weather model and Lake Surface Water Temperatures (LSWT) from satellite imagery. Analysis results indicate an average spatial SurHF range of > 40 W/m^2, mainly due to wind sheltering over parts of the lake. The difference between the time variation of the heat content in western and eastern parts of the lake derived from the SurHF estimates was consistent with the spatial heat content variation obtained from long-term temperature profile measurements in those parts. Our analyses also indicate a noticeable temporal change of the main controlling forcing when comparing heat fluxes in spring to the rest of the year. Such a regime change can be explained by the atmospheric thermal boundary layer dynamics that were unstable except in spring (March to early June). This resulted in much less spatial variability during springtime. The results emphasize that spatial variability in the meteorological and LSWT patterns will cause spatiotemporal SurHF variability that should be taken into consideration when assessing the time evolution of the heat budget of large water bodies.

2018

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.