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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 22, issue 10 | Copyright
Hydrol. Earth Syst. Sci., 22, 5559-5578, 2018
https://doi.org/10.5194/hess-22-5559-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 26 Oct 2018

Research article | 26 Oct 2018

Evaluating and improving modeled turbulent heat fluxes across the North American Great Lakes

Umarporn Charusombat1, Ayumi Fujisaki-Manome2,3, Andrew D. Gronewold1, Brent M. Lofgren1, Eric J. Anderson1, Peter D. Blanken4, Christopher Spence5, John D. Lenters6, Chuliang Xiao2, Lindsay E. Fitzpatrick2, and Gregory Cutrell7 Umarporn Charusombat et al.
  • 1NOAA Great Lakes Environmental Research Laboratory, Ann Arbor, Michigan 48108, USA
  • 2University of Michigan, Cooperative Institute for Great Lakes Research, Ann Arbor, Michigan 48108, USA
  • 3University of Michigan, Climate & Space Sciences and Engineering Department, Ann Arbor, Michigan 48109, USA
  • 4University of Colorado, Department of Geography, Boulder, Colorado 80309, USA
  • 5Environment and Climate Change Canada, Saskatoon, Saskatchewan, S7N 5C5, Canada
  • 6University of Wisconsin-Madison, Center for Limnology, Boulder Junction, Wisconsin 54512, USA
  • 7LimnoTech, Ann Arbor, Michigan 48108, USA

Abstract. Turbulent fluxes of latent and sensible heat are important physical processes that influence the energy and water budgets of the North American Great Lakes. These fluxes can be measured in situ using eddy covariance techniques and are regularly included as a component of lake–atmosphere models. To help ensure accurate projections of lake temperature, circulation, and regional meteorology, we validated the output of five algorithms used in three popular models to calculate surface heat fluxes: the Finite Volume Community Ocean Model (FVCOM, with three different options for heat flux algorithm), the Weather Research and Forecasting (WRF) model, and the Large Lake Thermodynamic Model. These models are used in research and operational environments and concentrate on different aspects of the Great Lakes' physical system. We isolated only the code for the heat flux algorithms from each model and drove them using meteorological data from four over-lake stations within the Great Lakes Evaporation Network (GLEN), where eddy covariance measurements were also made, enabling co-located comparison. All algorithms reasonably reproduced the seasonal cycle of the turbulent heat fluxes, but all of the algorithms except for the Coupled Ocean–Atmosphere Response Experiment (COARE) algorithm showed notable overestimation of the fluxes in fall and winter. Overall, COARE had the best agreement with eddy covariance measurements. The four algorithms other than COARE were altered by updating the parameterization of roughness length scales for air temperature and humidity to match those used in COARE, yielding improved agreement between modeled and observed sensible and latent heat fluxes.

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The authors evaluated several algorithms of heat loss and evaporation simulation by comparing with direct measurements at four offshore flux towers in the North American Great Lakes. The algorithms reproduced the seasonal cycle of heat loss and evaporation reasonably, but some algorithms significantly overestimated them during fall to early winter. This was due to false assumption of roughness length scales for temperature and humidity and was improved by employing a correct parameterization.
The authors evaluated several algorithms of heat loss and evaporation simulation by comparing...
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