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Nonlinear optimization method in the atmosphere - in marine scientific research several applications dedicated to Professor

Dahu Li

Abstract


This article mainly introduces the application of nonlinear optimization method in the atmospheric in recent years by the authors ' research group. - Marine scientific research has close work , Emphasis is on nonlinear optimization based on conditional nonlinear optimal perturbation (cnop) Method's theoretical framework and recent years ' development and in Atmosphere - latest applications in marine scientific research , Mainly includes set forecast , Some high impact sea - Gas Environment Item Predictability , Identification of pattern parameter sensitivity and evaluation of pattern inclination error and boundary condition error . also , This article also describes the about the Difficulties and challenges of applying CNOP methods , and looking forward to future development .

Keywords


Nonlinear optimization conditions nonlinear optimal perturbation

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References


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Applications of nonlinear optimization approach to atmospheric and oceanic sciences

mu mu & WANG Qiang

Abstract This paper mainly introduces recent applications of nonlinear optimization approach to atmospheric and oceanic s Ciences. Emphasis is placed on the theoretical framework of the conditional nonlinear opti-mal-perturbation (Cnop) method is Ba sed on nonlinear optimization, and the works aiming to make it compre-hensive. The application progresses of the Cnop method in atmospheric and oceanic Sciences are briefly, pre-sented the app Lications for ensemble forecast, predictability of some high-impact ocean-atmospheric environ-mental events, recognition of Model parameter sensitivities, assessments of model tendency error and boundary error. In addition, we also discuss the difficulties and challenges for the application of the CNOP approach and suggest NS for future development.

Keywords nonlinear optimization, conditional nonlinear optimal perturbation (CNOP), Atmosphere, Ocean MSC (+) 35q93, 49N 65k10, 65m32, 90C30, 90C31

doi:10.1360/n012016-00200




DOI: http://dx.doi.org/10.18686/jaoe.v4i1.1161

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