Abstract
AbstractNet 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.
Highlights
The single-location approach might be suitable for small water bodies, spatial variability of Surface Heat Flux (SurHF) due to variable meteorological conditions can be important for large lakes (e.g., Lofgren and Zhu 2000; Xue et al 2015; Moukomla and Blanken 2017)
Model calibration and assessment Uncalibrated versus calibrated net surface heat flux models Various combinations of SurHF models were studied applying the water column energy balance First, we examined the performance of the different models using coefficient values given in the literature, with an emphasis on those used in other lake studies in Switzerland
Using Models 2 and 5, the SHL2 and GE3 results are roughly distributed below and above the optimal dashed line, respectively, and have the largest scatter. This demonstrates that the worst combination of sensible-latent heat flux terms (Qev + Qco)2 (Supporting Information Eq S6, Table S3), underestimates the SurHF at SHL2, while it is overestimated at GE3
Summary
Study site Located between Switzerland and France, Lake Geneva (Local name: Lac Léman) is a large, deep perialpine lake with a mean surface altitude of 372 m. 130 conductivity-temperature-depth (CTD) profiles at SHL2 and 78 profiles at GE3 are available for the study period (2008–2014) Based on these temperature profiles, the water column heat content variation (Eq 1) at these two locations was calculated (Supporting Information Fig. S5). The satellite-based temperatures agreed well with the near-surface in situ measurements for our study with a bias and root mean square error (RMSE) within the range of −0.5 to 0.6 C and 1.0 to 1.6 C, respectively This range of values favorably corresponds with another long-term LSWT calibration for Lake Geneva (Oesch et al 2005). The cross-correlation between different stations is similar for COSMO-2 results and measurements, which confirms the capability of the COSMO-2 model to represent realistic large-scale wind patterns over Lake Geneva (Supporting Information Fig. S7c). We will further investigate this point below by examining the dynamics of the individual components and compare their values with those reported in the literature
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