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

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 c

Non-photochemical quenching estimates from in situ spectroradiometer measurements: implications on remote sensing of sun-induced chlorophyll fluorescence in lakes

Quantum yield of fluorescence (ϕF) is key to interpret remote measurements of sun-induced fluorescence (SIF), and whether the SIF signal is governed by photochemical quenching (PQ) or non-photochemical quenching (NPQ). Disentangling PQ from NPQ allows using SIF estimates in various applications in aquatic optics. However, obtaining ϕF is challenging due to its high temporal and physiological variability, and the combined measurements needed to enclose all relevant optical paths. In inland waters, this type of data is scarce and information on diurnal and seasonal ϕF dynamics are almost unknown. Using an autonomous hyperspectral Thetis profiler in Lake Geneva, we demonstrate how to estimate ϕF using an ensemble of in-situ measurements acquired between 2018 to 2021. We use vertical and temporal changes in retrieved ϕF to determine NPQ and PQ conditions. We observed NPQ in 36% of the total daytime profiles used in the ϕF analysis. While downwelling irradiance is a significant contributor to ϕF, its role cannot be easily interpreted. Other factors such as phytoplankton photoregulation and assemblages also likely play significant roles in quenching mechanisms. We conclude that an adapted approach exploiting in-situ data is suitable to determine diurnal and seasonal NPQ occurrence, and helps develop future remote sensing algorithms

The imprint of primary production on high-frequency profiles of lake optical properties

Water inherent optical properties (IOPs) contain integrative information on the optical constituents of surface waters. In lakes, IOP measurements have not been traditionally collected. This study describes how high-frequency IOP profiles can be used to document short-term physical and biogeochemical processes that ultimately influence the long-term trajectory of lake ecosystems. Between October 2018 and May 2020, we collected 1373 high-resolution hyperspectral IOP profiles in the uppermost 50 m of the large mesotrophic Lake Geneva (Switzerland-France), using an autonomous profiler. A data set of this size and content does not exist for any other lake. Results showed seasonal variations in the IOPs, following the expected dynamic of phytoplankton. We found systematic diel patterns in the IOPs. Phases of these diel cycles were consistent year-round, and amplitudes correlated to the diurnal variations of dissolved oxygen, clarifying the link between IOPs and phytoplankton metabolism. Diel amplitudes were largest in spring and summer under low wind condition. Wind-driven changes in thermal stratification impacted the dynamic of the IOPs, illustrating the potential of high-frequency profiles of water optical properties to increase our understanding of carbon cycling in lake ecosystems

Achieving high-resolution thermal imagery in low-contrast lake surface waters by aerial remote sensing and image registration

A two-platform measurement system for realizing airborne thermography of the Lake Surface Water Temperature (LSWT) with ~0.8 m pixel resolution (sub-pixel satellite scale) is presented. It consists of a tethered Balloon Launched Imaging and Monitoring Platform (BLIMP) that records LSWT images and an autonomously operating catamaran (called ZiviCat) that measures in situ surface/near surface temperatures within the image area, thus permitting simultaneous ground-truthing of the BLIMP data. The BLIMP was equipped with an uncooled InfraRed (IR) camera. The ZiviCat was designed to measure along predefined trajectories on a lake. Since LSWT spatial variability in each image is expected to be low, a poor estimation of the common spatial and temporal noise of the IR camera (nonuniformity and shutter-based drift, respectively) leads to errors in the thermal maps obtained. Nonuniformity was corrected by applying a pixelwise two-point linear correction method based on laboratory experiments. A Probability Density Function (PDF) matching in regions of overlap between sequential images was used for the drift correction. A feature matching-based algorithm, combining blob and region detectors, was implemented to create composite thermal images, and a mean value of the overlapped images at each location was considered as a representative value of that pixel in the final map. The results indicate that a high overlapping field of view (~95%) is essential for image fusion and noise reduction over such low-contrast scenes. The in situ temperatures measured by the ZiviCat were then used for the radiometric calibration. This resulted in the generation of LSWT maps at sub-pixel satellite scale resolution that revealed spatial LSWT variability, organized in narrow streaks hundreds of meters long and coherent patches of different size, with unprecedented detail

Improving surface heat flux estimation for a large lake through model optimization and two-point calibration: The case of Lake Geneva

Net Surface Heat Flux (SurHF) was estimated from 2008 to 2014 for Lake Geneva (Switzerland/France), using long‐term temperature depth profiles at two locations, hourly maps of reanalysis meteorological data from a numerical weather model and lake surface water temperatures from calibrated satellite imagery. Existing formulas for different heat flux components were combined into 54 different total SurHF models. The coefficients in these models were calibrated based on SurHF optimization. Four calibration factors characterizing the incoming long‐wave radiation, sensible, and latent heat fluxes were further investigated for the six best performing models. The combination of the modified parameterization of the Brutsaert equation for incoming atmospheric radiation and of similarity theory‐based bulk parameterization algorithms for latent and sensible surface heat fluxes provided the most accurate SurHF estimates. 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 between the two locations. Consequently, the optimal SurHF models were calibrated using two profile locations. The results emphasize that even relatively small changes in calibration factors, particularly in the atmospheric emissivity, significantly modify the estimated long‐term heat content. The lack of calibration can produce changes in the calculated heat content that are much higher than the observed annual climate change‐induced trend. The calibration improved parameterization of bulk transfer coefficients, mainly under low wind regimes

A low-cost, autonomous mobile platform for limnological investigations, supported by high-resolution mesoscale airborne imagery

Two complementary measurement systems – built upon an autonomous floating craft and a tethered balloon – for lake research and monitoring are presented. The autonomous vehicle was assembled on a catamaran for stability, and is capable of handling a variety of instrumentation for in situ and near-surface measurements. The catamaran hulls, each equipped with a small electric motor, support rigid decks for arranging equipment. An electric generator provides full autonomy for about 8 h. The modular power supply and instrumentation data management systems are housed in two boxes, which enable rapid setup. Due to legal restrictions in Switzerland (where the craft is routinely used), the platform must be observed from an accompanying boat while in operation. Nevertheless, the control system permits fully autonomous operation, with motion controlled by speed settings and waypoints, as well as obstacle detection. On-board instrumentation is connected to a central hub for data storage, with real-time monitoring of measurements from the accompanying boat. Measurements from the floating platform are complemented by mesoscale imaging from an instrument package attached to a He-filled balloon. The aerial package records thermal and RGB imagery, and transmits it in real-time to a ground station. The balloon can be tethered to the autonomous catamaran or to the accompanying boat. Missions can be modified according to imagery and/or catamaran measurements. Illustrative results showing the surface thermal variations of Lake Geneva demonstrate the versatility of the combined floating platform/balloon imagery system setup for limnological investigations

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring

A Multiscale Surface Water Temperature Data Acquisition Platform: Tests on Lake Geneva, Switzerland

An improved understanding of surface transport processes is necessary to predict sediment, pollutant and phytoplankton patterns in large lakes. Lake surface water temperature (LSWT) which may spatially and temporarily vary over the lake surface reflects meteorological and climatological forcing more than any other physical lake parameter. There are different data sources for LSWT mapping, including remote sensing and in situ measurements. The available satellite data might be suitable for detecting the large-scale thermal patterns, but not the meso- or small scale processes. Lake surface thermography, investigated in this study, has finer resolution compared to satellite images. Thermography at the meso-scale provides the ability to ground-truth satellite imagery over scales of one to several satellite image pixels. On the other hand, thermography data can be used as a control in schemes to upscale local measurements that account for the surface energy fluxes and vertical energy budget. Independently, since such data can be collected at high frequency, they can be also useful in capturing the surface signatures of meso-scale eddies and thus to quantify mixing processes. In the present study, we report results from a Balloon Launched Imaging and Monitoring Platform (BLIMP), which was developed in order to measure the LSWT at meso-scale. The BLIMP consists of a small balloon which is tethered to a boat and equipped with the thermal and RGB cameras, as well as other instrumentation for location and communication. Several deployments were carried out on Lake Geneva. In a typical deployment, the BLIMP is towed by a boat, and collects high frequency data from different heights (i.e., spatial resolutions) and locations. Simultaneous ground-truthing of the BLIMP data is achieved using an autonomous craft that collects a variety of data, including in situ surface/near surface temperatures, radiation and meteorological data in the area covered by the BLIMP images. With suitable scaling, our results show good consistency between in situ, BLIMP and concurrent satellite data. In addition, the BLIMP thermography reveals (hydrodynamically-driven) structures in the LSWT – an obvious example being mixing of river discharges

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

Seasonal Spatial Patterns of Surface Water Temperature, Surface Heat Fluxes and Meteorological Forcing Over Lake Geneva

In many lakes, surface heat flux (SHF) is the most important component controlling the lake’s energy content. Accurate methods for the determination of SHF are valuable for water management, and for use in hydrological and meteorological models. Large lakes, not surprisingly, are subject to spatially and temporally varying meteorological conditions, and hence SHF. Here, we report on an investigation for estimating the SHF of a large European lake, Lake Geneva. We evaluated several bulk formulas to estimate Lake Geneva’s SHF based on different data sources. A total of 64 different surface heat flux models were realized using existing representations for different heat flux components. Data sources to run the models included meteorological data (from an operational numerical weather prediction model, COSMO-2) and lake surface water temperature (LSWT, from satellite imagery). Models were calibrated at two points in the lake for which regular depth profiles of temperature are available, and which enabled computation of the total heat content variation. The latter, computed for 03.2008-12.2013, was the metric used to rank the different models. The best calibrated model was then selected to calculate the spatial distribution of SHF. Analysis of the model results shows that evaporative and convective heat fluxes are the dominant terms controlling the spatial pattern of SHF. The former is significant in all seasons while the latter plays a role only in fall and winter. Meteorological observations illustrate that wind-sheltering, and to some extent relative humidity variability, are the main reasons for the observed large-scale spatial variability. In addition, both modeling and satellite observations indicate that, on average, the eastern part of the lake is warmer than the western part, with a greater temperature contrast in spring and summer than in fall and winter whereas the SHF spatial splitting is stronger in fall and winter. This is mainly due to negative heat flux values (net cooling) and stronger wind forcing, and consequently stronger mixing, in cold seasons