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CLC number: TP391

On-line Access: 2018-10-05

Received: 2017-11-29

Revision Accepted: 2018-03-16

Crosschecked: 2018-08-09

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Hussein Yahia

http://orcid.org/0000-0002-4284-096X

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Frontiers of Information Technology & Electronic Engineering  2018 Vol.19 No.8 P.1056-1062

http://doi.org/10.1631/FITEE.1700797


Effect of wind stress forcing on ocean dynamics at air-sea interface


Author(s):  Hussein Yahia, Veronique Garçon, Joel Sudre, Christophe Maes

Affiliation(s):  Research Center INRIA Bordeaux - South West, Talence 33405, France; more

Corresponding email(s):   hussein.yahia@inria.fr, veronique.garcon@legos.obs-mip.fr, joel.sudre@legos.obs-mip.fr, christophe.maes@ird.fr

Key Words:  Ocean dynamics, Remote sensing, Turbulence, Signal processing, Multi-fractal formalism


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Hussein Yahia, Veronique Garçon, Joel Sudre, Christophe Maes. Effect of wind stress forcing on ocean dynamics at air-sea interface[J]. Frontiers of Information Technology & Electronic Engineering, 2018, 19(8): 1056-1062.

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Abstract: 
We evidence and study the differences in turbulence statistics in ocean dynamics carried by wind forcing at the air-sea interface. Surface currents at the air-sea interaction are of crucial importance because they transport heat from low to high latitudes. At first order, oceanic currents are generated by the balance of the Coriolis and pressure gradient forces (geostrophic current) and the balance of the Coriolis and the frictional forces dominated by wind stress (Ekman current) in the surface ocean layers. The study was conducted by computing statistical moments on the shapes of spectra computed within the framework of microcanonical multi-fractal formalism. Remotely sensed daily datasets derived from one year of altimetry and wind data were used in this study, allowing for the computation of two kinds of vector fields: geostrophy with and geostrophy without wind stress forcing. We explore the statistical properties of singularity spectra computed from velocity norms and vorticity data, notably in relation with kurtosis information to underline the differences in the turbulent regimes associated with both kinds of velocity fields.

风力对海空界面海洋动力学的影响

概要:证实并研究了海气界面风力强迫作用下的海洋动力学湍流统计差异。海气相互作用下的海洋表层流至关重要,因为它能够将热量从低纬度输送到高纬度。在一阶方程中,海洋表层的洋流包括由科里奥利力和压力梯度力的平衡产生的地转流,以及科里奥利力和以风应力为主的摩擦力平衡产生的埃克曼流。本研究是在微正则多重分形形态学框架下,计算光谱形状的统计矩。应用一年的每日遥感高度计和遥感风数据资料,可以计算两种矢量场:有风场和无风场强迫的地转流。利用速度规范和涡度数据研究了奇异谱的统计特性,特别是与峰度信息的关系,以强调两种地转流速度场在湍流状态下的差异。

关键词:海洋动力学;遥感;湍流;信号处理;多重分形形式

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Arbic BK, Polzin KL, Scott JG, et al., 2013. On eddy viscosity, energy cascades, and the horizontal resolution of gridded satellite altimeter products. textitJ Phys Oceanogr, 43(2):283-300.

[2]Arneodo A, Bacry E, Muzy JF, 1995. The thermodynamics of fractals revisited with wavelets. textitPhys A, 213(1-2):232-275.

[3]Benzi R, Paladin G, Parisi G, et al., 1984. On the multi-fractal nature of fully developed turbulence and chaotic systems. textitJ Phys A, 17:3521-3531.

[4]Boffetta G, Cencini M, Falcioni M, et al., 2002. Predictability: a way to characterize complexity. textitPhys Rep, 356(6):367-474.

[5]Chelton DB, Ries JC, Haines BJ, et al., 2001. Satellite altimetry. In: Fu LL, Cazenave A (Eds.), Satellite Altimetry and Earth Sciences: a Handbook of Techniques and Applications. Academic Press, London, UK, p.1-122.

[6]Frisch U, 1995. Turbulence: the Legacy of A. N. Kolmogorov. Cambridge University Press, Cambridge, UK.

[7]Garccon VC, Bell TG, Wallace D, et al., 2013. Perspectives and integration in SOLAS Science. In: Liss PS, Johnson MT (Eds.), Ocean-Atmosphere Interactions of Gases and Particles. Springer Berlin Heidelberg, p.247-306.

[8]Hernández-Carrasco I, Sudre J, Garccon V, et al., 2015. Reconstruction of super-resolution ocean pCO2 and air-sea fluxes of CO2 from satellite imagery in the southeastern Atlantic. textitBiogeosciences, 12(17):5229-5245.

[9]Hernández-Carrasco I, Garccon V, Sudre J, et al., 2018. Increasing the resolution of ocean pCO2 maps in the South Eastern Atlantic Ocean merging multi-fractal satellite-derived ocean variables. textitIEEE Trans Geosci Remote Sens, in press.

[10]Lee T, Stammer D, Awaji T, et al., 2010. Ocean state estimation for climate research. Proc OceanObs'09: Sustained Ocean Observations and Information for Society, p.1-9.

[11]Mashayek A, Ferrari R, Merrifield S, et al., 2017. Topographic enhancement of vertical turbulent mixing in the Southern Ocean. textitNat Commun, 8:14197.

[12]Parisi G, Frisch U, 1985. On the singularity structure of fully developed turbulence. In: Ghil M, Benzi R, Parisi G (Eds.), Turbulence and Predictability in Geophysical Fluid Dynamics. North Holland, Amsterdam, p.84-87.

[13]She ZS, Leveque E, 1994. Universal scaling laws in fully developed turbulence. textitPhys Rev Lett, 72(3):336-339.

[14]Sudre J, Maes C, Garccon V, 2013. On the global estimates of geostrophic and Ekman surface currents. textitLimnol Oceanogr: Fluids Environ, 3(1):1-20.

[15]Turiel A, Pérez-Vicente CJ, Grazzini J, 2006. Numerical methods for the estimation of multi-fractal singularity spectra on sampled data: a comparative study. textitJ Comput Phys, 216(1):362-390.

[16]Turiel A, Yahia H, Pérez-Vicente CJ, 2008. Microcanonical multi-fractal formalism—a geometrical approach to multi-fractal systems: Part I. Singularity analysis. textitJ Phys A, 41(1):015501.

[17]Turiel A, Isern-Fontanet J, Umbert M, 2014. Sensibility to noise of new multi-fractal fusion methods for ocean variables. textitNonl Processes Geophys, 21(1):291-301.

[18]Venugopal V, Roux SG, Foufoula-Georgiou E, et al., 2006. Revisiting multi-fractality of high-resolution temporal rainfall using a wavelet-based formalism. textitWater Resour Res, 42(6):W06D14.

[19]Yahia H, Sudre J, Pottier C, et al., 2010. Motion analysis in oceanographic satellite images using multiscale methods and the energy cascade. textitPatt Recogn, 43(10):3591-3604.

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