The eddy kinetic energy budget in the Red Sea

Peng Zhan, Aneesh C. Subramanian, Fengchao Yao, Aditya R. Kartadikaria, Daquan Guo, Ibrahim Hoteit

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60 Scopus citations


The budget of eddy kinetic energy (EKE) in the Red Sea, including the sources, redistributions and sink, is examined using a high-resolution eddy-resolving ocean circulation model. A pronounced seasonally varying EKE is identified, with its maximum intensity occurring in winter, and the strongest EKE is captured mainly in the central and northern basins within the upper 200 m. Eddies acquire kinetic energy from conversion of eddy available potential energy (EPE), from transfer of mean kinetic energy (MKE), and from direct generation due to time-varying (turbulent) wind stress, the first of which contributes predominantly to the majority of the EKE. The EPE-to-EKE conversion occurs almost in the entire basin, while the MKE-to-EKE transfer appears mainly along the shelf boundary of the basin (200 miso-bath) where high horizontal shear interacts with topography. The EKE generated by the turbulent wind stress is relatively small and limited to the southern basin. All these processes are intensified during winter, when the rate of energy conversion is about four to five times larger than that in summer. The EKE is redistributed by the vertical and horizontal divergence of energy flux and the advection of the mean flow. As a main sink of EKE, dissipation processes is ubiquitously found in the basin. The seasonal variability of these energy conversion terms can explain the significant seasonality of eddy activities in the Red Sea. This article is protected by copyright. All rights reserved.
Original languageEnglish (US)
Pages (from-to)4732-4747
Number of pages16
JournalJournal of Geophysical Research: Oceans
Issue number7
StatePublished - Jul 10 2016

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: The research reported in this manuscript was supported by King Abdullah University
of Science and Technology (KAUST) and made use of the resources of the Supercomputing Laboratory and computer clusters at KAUST. The data used in this study may be
obtained from the authors upon request ([email protected]).


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