Surface Water Temperature Heterogeneity at Subpixel Satellite Scales and Its Effect on the Surface Cooling Estimates of a Large Lake: Airborne Remote Sensing Results From Lake Geneva

Abstract

The dynamics of spatial heterogeneity of lake surface water temperature (LSWT) at subpixel satellite scale O(1 m) and its effect on the surface cooling estimation at typical satellite pixel areas O(1 km 2 ) were investigated using an airborne platform. The measurements provide maps that revealed spatial LSWT variability with unprecedented detail. The cold season data did not show significant LSWT heterogeneity and hence no surface cooling spatial variability. However, based on three selected daytime subpixel-scale maps, LSWT patterns showed a variability of >2°C in the spring and >3.5°C in the summer, corresponding to a spatial surface cooling range of >20 and >40 W/m 2 , respectively. Due to the nonlinear relationship between turbulent surface heat fluxes and LSWT, negatively skewed LSWT 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 area-averaged LSWT on the surface cooling estimation up to a typical satellite pixel was assessed. The effect of the averaging filter size on the mean spatial surface cooling values was negligible, except for predominantly stable ABL conditions. In that situation, a reduction of~3.5 W/m 2 was obtained when moving from high O(1 m) to low O(1 km) pixel resolution.Plain Language Summary Lake surface water temperature (LSWT) is one of the main parameters required for estimating surface cooling at the air-water interface and is also essential for understanding other processes (such as ecosystem dynamics, climate change, and numerical weather prediction) in lakes. Usually, surface cooling is determined from in situ point measurements or satellite images. Satellite thermal images resolve surface areas with a typical pixel resolution of O(1 km). Therefore, satellite data can depict large-scale thermal patterns. But can LSWT spatial variability be significant at subpixel satellite resolution over a large lake? What is the effect of such variability on area-averaged surface cooling estimates? To address these questions, a measurement system, including a balloon-launched airborne platform for thermography and a catamaran for in situ measurements along predefined tracks, was used for LSWT mapping and calibration. Surface cooling patterns were then estimated using a calibrated bulk model. Results showed insignificant LSWT heterogeneity and hence no surface cooling spatial variability during the cold seasons. However, a notable spatial variability of >2°C and > 3.5°C was found in spring and summer, respectively. The effect of LSWT heterogeneity on surface cooling variability was significant, in particular, when air-water temperature differences were close to 0.

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

“…COSMO‐2 distinguishes lakes from land by using a lake model for the momentum transfer calculation (Mironov, ), but COSMO‐2 cannot spatially resolve LSWT. Although this might affect the meteorological patterns over the lake, short‐term in situ measurements over Lake Geneva using a moving platform (Rahaghi et al, ), as well as long‐term point measurements on this lake (Vercauteren et al, ) and other water bodies (e.g., Assouline et al, ; Solcerova et al, ), showed that no correlation between the patterns of air temperature and LSWT could be established. These studies indicated that the meteorological patterns over small to moderately large lakes are mainly driven by large‐scale atmospheric patterns rather than by lake thermal structure.…”

“…In addition to the over-lake meteorological patterns, LSWT spatial variability can also have an effect on the SurHF estimates of large lakes (e.g., Mahrt & Hristov, 2017;Mahrt & Khelif, 2010;Rahaghi et al, 2019). Therefore, LSWT maps (section 2.3) are essential for a better quantification of lake SurHF.…”

“…Spatiotemporal maps of wind speed (U 10 ), air temperature (T a ), relative humidity (ϕ rel ), cloudiness (C), global radiation (Q sc ), air pressure, and LSWT (T w ) were used in this study. Previous studies demonstrated that SurHF is more sensitive to wind speed and LSWT than to air temperature variability and relative humidity (Austin & Allen, 2011;Rahaghi et al, 2019).…”

LéXPLORE: A floating laboratory on Lake Geneva offering unique lake research opportunities

“…An illustrative example of the influence of small‐scale features is the up to 0.5°C temperature differential that can develop between the thermal sublayer skin and underlying bulk water, which becomes particularly pronounced under weak wind (Wilson et al, 2013; Irani Rahaghi et al, 2019). This difference exceeds the detection limits of high‐resolution satellite radiometers currently used to monitor lakes.…”

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“…For example, systematic measurements over larger areas over wider range of conditions, and possibly at different sites, can be used for satellite ground-truthing [47], and can provide better insight into spatial heterogeneity of LSWT warming rates, within [52] and among lakes [53]. The measurements can also improve understanding/quantification of mass, heat and momentum exchanges at the air-water interface (e.g., [54, 55]) and so improve numerical weather prediction results (e.g., [56, 57]). Visualizing LSWT details using this platform can also be achieved for river inflows, wastewater discharges and near-shore processes, e.g., thermal biomes, all of which will affect the lake ecosystem dynamics.…”