A novel approach for unraveling the energy balance of water surfaces with a single depth temperature measurement. (10th October 2016)

• Record Type: Journal Article
• Authors: Yang, Jiachuan; Wang, Zhi‐Hua; Li, Qi; Vercauteren, Nikki; Bou‐Zeid, Elie; Parlange, Marc B.
• Is Part Of: Limnology and oceanography. Volume 62:Number 1(2017)
• Page Start: 89
• Page End: 103
• Publication Date: 2016-10-10
• Subjects: Green's function approach -- Surface energy partitioning -- Water temperature -- Water–atmosphere interactions; Limnology -- Periodicals; Oceanography -- Periodicals; Océanographie; Limnologie; Limnology; Oceanography; Computer network resources; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); Periodicals; 551.4805
• DOI: 10.1002/lno.10378
• Languages: English
• ISSNs: 0024-3590

Abstract

Abstract: The partitioning of solar energy over the Earth's surface drives weather and climate of the coupled land–ocean–atmosphere system. Over water surfaces, the evolution of water temperatures at a given depth in the mixed layer implicitly contains the signature of surface energy partitioning, and as such it can be used to diagnose the surface energy balance. In this study, we develop a novel numerical scheme by combining the Green's function approach and linear stability analysis to estimate the water surface energy balance using water temperature measurement at a single depth. The proposed method is capable of predicting water temperature in the mixed layer, and solving for the components of the surface energy budgets with physically based schemes. Evaluation against in situ measurement and the maximum entropy production method demonstrates that this approach is robust and of good accuracy. It is found that performance of the proposed method depends strongly on the accurate estimation of turbulent thermal diffusivity from in situ measurements, which carries information of meteorological and limnological conditions. Without explicitly using wind speed or temperature/moisture gradient, the proposed approach reduces uncertainty and potential error associated with meteorological measurements in estimation of water surface energy balance.