Abstract

Understanding air-water interactions is critical to establishing the role of inland water bodies in regulating local and regional weather so that more accurate parameterizations of flux exchange in numerical weather models can be achieved. Wind-induced mixing actively alters environmental variables, leading to changes in turbulent exchanges of latent heat (LE) and sensible heat (H) fluxes above water surfaces. It remains extensively unexplored as to how winds in different wind speed ranges modulate coupling of different variables, which in turn regulates LE and H. Here, we analyze 28-month eddy covariance data collected over a large reservoir. We categorize the dataset into four wind classes with different wind speed ranges: I ( 5.13 m s−1). The enhanced mechanical mixing promotes LE and H with the increased wind classes due to the increased sensitivity to Δe and ΔT despite the reduced role of atmospheric stability. Hence, the highest LE and H occur in IV, under moderately unstable and stable conditions. Overall, the bulk transfer coefficients behave similarly under a certain stability condition across all wind classes while the similarity theory systematically underestimates their magnitudes. These results have important applications in improving parameterization schemes to estimate fluxes over water surfaces in numerical models.

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