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Heat Storage Effect on Evaporation Estimates of China's Largest Freshwater Lake
Author(s) -
Gan Guojing,
Liu Yuanbo
Publication year - 2020
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1029/2019jd032334
Subject(s) - latent heat , thermal energy storage , evaporation , environmental science , daytime , sensible heat , latitude , hydrology (agriculture) , atmospheric sciences , meteorology , geology , thermodynamics , geography , geotechnical engineering , physics , geodesy
Evaporation of water bodies is significantly controlled by the available energy (net radiation R n minus heat storage G). Compared to deep lakes or lakes in the high‐latitude or high‐altitude regions, the heat storage effects of shallow lakes in subtropical regions are less well studied. In this paper, we tested the heat storage effect on the latent heat fluxes estimation using the Priestley‐Taylor (PT) equation and numerical water temperature simulations in an ephemeral and shallow lake, Poyang Lake, in China. Results showed that the estimation bias was significantly correlated with heat storage changes ( r = 0.97). Overlooking the impacts of the heat storage changes will induce an increase in the RMSE (root‐mean‐square error) of the evaporation estimation from 10.1 to 54.4 W m −2 . Evaporation was overestimated in June and underestimated in August because the daytime R n tended to be stored in water in June, whereas the heat storage during daytime tended to be released as nighttime evaporation in August, when the vapor gradient between the saturated surface and the air was generally larger than in other months. Water temperature simulations showed that the diurnal changes in the heat storage in the layer that were less than 2 m deep govern G of the total water column. PT estimation of a shallow lake can be improved if the temperature of the top 2 m of water is known. Also, from the modeling perspective, because G was linearly correlated with R n ( r = 0.77), a simple equation (a*R n + b) that approximates the available energy can improve the evaporation estimate.