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Discussion papers | Copyright
https://doi.org/10.5194/gmd-2018-168
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 31 Aug 2018

Development and technical paper | 31 Aug 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Evaluation of the WRF lake module (v1.0) and its improvements at a deep reservoir

Fushan Wang1,2, Guangheng Ni1, William J. Riley2, Jinyun Tang2, Dejun Zhu1, and Ting Sun3 Fushan Wang et al.
  • 1Department of Hydraulic Engineering, Tsinghua University, Beijing, China
  • 2Earth and Environmental Sciences Area, Lawrence Berkeley National Lab, Berkeley, CA, USA
  • 3Department of Meteorology, University of Reading, Reading, UK

Abstract. Large lakes and reservoirs play important roles in modulating regional hydrological cycles and climate; however, their representations in coupled models remain uncertain. The existing lake module in the Weather Research and Forecasting (WRF) system (hereafter WRF-Lake), although widely used, did not accurately predict temperature profiles in deep lakes mainly due to poor lake surface property parameterizations and underestimation of heat transfer between lake layers. We therefore revised WRF-Lake by improving its (1) numerical discretization scheme; (2) surface property parameterization; (3) diffusivity parameterization for deep lakes; and (4) convection scheme, the outcome of which became WRF-rLake (i.e., revised lake model). We evaluated WRF-rLake by comparing simulated and measured water temperature at the Nuozhadu Reservoir, a deep reservoir in southwestern China. WRF-rLake performs better than its predecessor by reducing the root-mean-square-error (RMSE) against observed lake surface temperatures (LSTs) from 1.4°C to 1.1°C and consistently improving simulated vertical temperature profiles. We also evaluated the sensitivity of simulated water temperature and surface energy fluxes to various modelled lake processes and parameters. We found (1) large changes in surface heat fluxes (up to 60Wm−2) associated with the improved surface property parameterization and (2) that the simulated lake thermal structure depends strongly on the light extinction coefficient and vertical diffusivity. Although currently only evaluated at the Nuozhadu Reservoir, we expect that these model parameter and structural improvements could be universal and therefore recommend further testing at other deep lakes and reservoirs.

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Short summary
The current lake model in the Weather Research and Forecasting system was reported to be insufficient in simulating deep lakes and reservoirs. We thus revised the lake model by improving its spatial discretization scheme, surface property parameterization, diffusivity parameterization and convection scheme. The revised model was evaluated at a deep reservoir in southwestern China and the results were in good agreement with measurements.
The current lake model in the Weather Research and Forecasting system was reported to be...
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