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Discussion papers | Copyright
https://doi.org/10.5194/hess-2017-725
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 10 Jan 2018

Research article | 10 Jan 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Hydrology and Earth System Sciences (HESS) and is expected to appear here in due course.

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

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. Validation and improvement of bulk flux algorithms to simulate these turbulent heat fluxes are critical for accurate prediction of lake hydrodynamics, water levels, weather, and climate over the region. Here we consider five heat flux algorithms from three parent model systems; 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 Thermodynamics Model, which are used in research and operational environments and concentrate on different aspects of the Great Lakes’ physical system. The heat flux algorithms were isolated from each model and driven by meteorological data from four over-lake stations within the Great Lakes Evaporation Network (GLEN). The simulation results were then compared with eddy covariance flux measurements from the same GLEN sites. All algorithms reasonably reproduced the seasonal cycle of the turbulent heat fluxes while the original 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. Simulations with the four algorithms other than COARE were improved by updating the parameterization of roughness length scales for air temperature and humidity to match those used in COARE. Agreement between modeled and observed fluxes notably varied according to the geographic locations of the GLEN sites.

Umarporn Charusombat et al.
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Umarporn Charusombat et al.
Umarporn Charusombat et al.
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Short summary
The authors evaluated several algorithms of heat loss and evaporation simulation in comparison 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-early winter. This was due to false assumption of roughness length scales for temperature and humidity and was improved by employing a correct assumption.
The authors evaluated several algorithms of heat loss and evaporation simulation in comparison...
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