Effect of meso-scale surface water temperature heterogeneity on surface cooling estimates of a large lake: Airborne remote sensing results from Lake Geneva

Satellite thermal images are frequently used in the study of surface heat exchange dynamics over lakes. Such investigations can depict large-scale thermal patterns with a resolution of O(1 km2), but not meso- or small-scale processes, requiring O(1 m) and O(1 cm) resolution. Using an airborne platform, the effect of meso-scale spatial heterogeneity of Lake Surface Water Temperature (LSWT) on the surface cooling estimation at the sub-pixel satellite scale O(1 km2) was investigated in Lake Geneva. The measurement system consists of a tethered balloon launched imaging and monitoring platform, equipped with an uncooled infrared camera that records the LSWT, and an autonomous catamaran that simultaneously measures in situ surface/near surface temperatures. Cold season data did not show significant LSWT heterogeneity, and hence surface cooling spatial variability. However, based on three selected daytime meso-scale maps, a LSWT contrast of > 2°C in spring and > 3.5°C in summer is observed, corresponding to the spatial surface cooling range of > 20 Wm-2 and > 40 Wm-2, respectively. Due to the nonlinear relationship between turbulent surface heat fluxes and LSWT, negatively skewed LSWT spatial distributions resulted in negatively skewed surface cooling patterns under very stable or predominantly unstable Atmospheric Boundary Layer (ABL) conditions and positively skewed surface cooling patterns under predominantly stable ABL conditions. Implementing a mean spatial filter, the effect of the area-averaged LSWT on the surface cooling estimation of a typical satellite pixel was assessed. The effect of the averaging filter size on the mean spatial surface cooling values was negligible, except for the predominantly stable ABL conditions when a reduction of ~3.5 Wm-2 from high O(1 m) to low O(1 km) pixel resolution was obtained. The results revealed that the bias in the sampling of meteorological parameters, particularly wind speed, could affect both the mean and the range of spatial surface cooling. Errors in air temperature may also alter the surface cooling distribution from negatively to positively skewed, and hence affect the area-averaged estimates.

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

Small-scale and mesoscale lake surface water temperature structure: Thermography and in situ measurements from Lake Geneva, Switzerland

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

Lake surface water temperature (LSWT), which varies spatially and temporarily, 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. Depending on cloud cover, satellite data can depict large-scale thermal patterns, but not the meso- or small scale processes. Thermography at the meso-scale provides the ability to resolve (and hence ground-truth) satellite imagery at the sub-pixel scale. A Balloon Launched Imaging and Monitoring Platform (BLIMP) was used to measure the LSWT at the meso-scale. The BLIMP consists of a small balloon tethered to a boat and which is equipped with thermal and RGB cameras, as well as other instrumentation for location and communication. Simultaneous ground-truthing of the BLIMP data was achieved using an autonomous craft measuring a variety of data, including in situ surface/near surface temperatures, radiation and meteorological data. The latent and sensible surface heat fluxes were calculated using the bulk parameterization algorithm based on similarity theory. A feature matching-based algorithm was implemented to create composite thermal images. Results are presented for the daily stratified low wind speed (up to 3 m/s) conditions over Lake Geneva. Two field campaigns, each of ~6 h from 18 March and 19 July 2016 are presented. The mesoscale temperature field (~1-m pixel resolution) had a range and standard deviation of 2.4°C and 0.3°C, respectively, over a 1-km2 area (typical satellite pixel size). Interestingly, at the sub-pixel scale, various temporal and spatial thermal eddy structures are evident – an obvious example being streaks in the along-wind direction during March, which we hypothesize are caused by the steady ~3 h wind condition. The results also show that the spatial variability of the estimated total heat flux is due to the corresponding variability of the longwave cooling from the water surface and the latent heat flux.

2017

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

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

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.

2018

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

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

2014

Small-scale and mesoscale lake surface water temperature structure: Thermography and in situ measurements from Lake Geneva, Switzerland

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

2017