A new application of conditional nonlinear optimal perturbation approach to boundary condition uncertainty

Wang, Qiang; Mu, Mu

doi:10.1002/2015jc011095

Cited by 22 publications

(17 citation statements)

References 54 publications

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“…To distinguish with CNOP-I, we call such an optimal parameter perturbation in the constraint as CNOP-P. The CNOP method has been also extended to investigate the effects of boundary condition uncertainty (CNOP-B, Wang and Mu 2015).…”

Section: Conditional Nonlinear Optimal Perturbationmentioning

confidence: 99%

Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model

Wei

Ren

et al. 2019

Clim Dyn

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Although the moisture feedback has been well known to be essential in the Madden-Julian Oscillation (MJO) dynamics, whether its pre-moistening effect plays a key role in exciting the onset of primary MJO events, as has been confirmed in the successive initiation, remains elusive. In this study, using a hybrid coupled climate model that has a good fidelity in simulating the intraseasonal variability, we develop a new framework of methodology to investigate the nonlinear excitation of primary MJO event, of which the key achievement is the successful implementation of the conditional nonlinear optimal perturbation (CNOP). In an application of this new framework, the CNOP-type moisture perturbations are calculated for the pre-chosen non-MJO reference states and generally favor a moistening in the equatorial region while drying in the poleward. Comparisons of the model simulation with observation give credibility to the existence of moisture signals several weeks before some primary MJO events. A suite of numerical experiments confirms that the CNOPs of moisture can contribute to the excitation and propagation of strong primary MJO events while random perturbations cannot. The moisture budget analysis further reveals the central importance of the horizontal moisture advection, especially the nonlinearly upscaled moisture transports associated with the high-frequency disturbances on the quasi-3-4-day and 6-8-day synoptic time scales, in supporting the nonlinear excitation of the primary MJO events. The subgrid-scale processes of evaporation, condensation and eddy transport of moisture are found to be critical for the pre-moistening effect in the boundary layer as well. This study directly supports the vital importance of the moisture perturbations, which are characterized by a particular pattern concentrated at low levels, to the nonlinear growth and propagation of the primary MJO events.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Section: Conditional Nonlinear Optimal Perturbationmentioning

confidence: 99%

Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model

Wei

Ren

et al. 2019

Clim Dyn

Self Cite

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“…Many methods have been proposed to solve this problem, and conditional nonlinear optimal perturbation (CNOP) is one that fully considers nonlinear processes. The CNOP approach was originally proposed to solve the uncertainty in the initial condition (Mu et al, 2003), and further extended to the uncertainties in the model parameters (Mu et al, 2010), model tendency (Duan and Zhou, 2013) and boundary condition (Wang and Mu, 2015). The CNOP approach is well summarized by Wang et al (2019), and so we just briefly introduce the application of CNOP in estimating the initial and boundary condition uncertainties.…”

Section: Methodsmentioning

confidence: 99%

“…In addition to initial perturbations, optimal boundary per-turbations have been investigated in an ocean ecosystem model (Wang and Mu, 2015). The results revealed that nonlinear processes play important roles in the phytoplankton evolution caused by nutrient perturbations at the bottom boundary.…”

Section: Applications Of the Cnop Approach In Related Investigationsmentioning

confidence: 99%

Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events

Dai

2020

Adv. Atmos. Sci.

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The linkage between the Arctic and midlatitudes has received much attention recently due to the rapidly changing climate. Many investigations have been conducted to reveal the relationship between the Arctic and Eurasian extreme events from the perspective of climatological statistics. As a prediction source for extreme events in Eurasia, Arctic conditions are crucial for extreme event predictions. Therefore, it is urgent to explore the Arctic influence on the predictability of Eurasian extreme events due to the large uncertainties in Arctic conditions. Considering the sensitivity and nonlinearity of the atmospheric circulations in midlatitude to Arctic conditions, it is necessary to investigate the Arctic influences on Eurasian extreme weather events in case studies at weather time scales. Previous studies indicate that only perturbations in specific patterns have fast growth. Thus, the conditional nonlinear optimal perturbation approach is recommended for exploring the uncertainties in Arctic initial and boundary conditions and their synergistic effect on Eurasian extreme events. Moreover, the mechanism for extreme event formation may differ in different cases. Therefore, more extreme cases should be investigated to reach robust conclusions.

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“…2003 年, CNOP 方法首次被提出时主要是探讨初始条件误差对大气 -海洋预报的影响 (参见文献 [12]), 此后, 该方法被逐步发展完善. 2010 年, 此方法被扩展到评估模式参数误差的影响 (参见文献 [21]), 最近其又被进一步扩展到研究模式倾向误差 [22] 和边界条件误差 [23] 的影响. 本节将这些工作统一到一个框架下来阐述 CNOP 方法.…”

Section: 拓展的条件非线性最优扰动方法unclassified

Applications of nonlinear optimization approach to atmospheric and oceanic sciences

Mu¹,

Wang²

2017

Sci. Sin.-Math.

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This paper mainly introduces recent applications of nonlinear optimization approach to atmospheric and oceanic sciences. Emphasis is placed on the theoretical framework of the conditional nonlinear optimal perturbation (CNOP) method that is based on nonlinear optimization, and the works aiming to make it comprehensive. The application progresses of the CNOP method in atmospheric and oceanic sciences are briefly presented, including the applications for ensemble forecast, predictability of some high-impact ocean-atmospheric environmental events, recognition of model parameter sensitivities, assessments of model tendency error and boundary condition error. In addition, we also discuss the difficulties and challenges for the application of the CNOP approach and suggest directions for future development.

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A new application of conditional nonlinear optimal perturbation approach to boundary condition uncertainty

Cited by 22 publications

References 54 publications

Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model

Nonlinear optimal moisture perturbations as excitation of primary MJO events in a hybrid coupled climate model

Influence of the Arctic on the Predictability of Eurasian Winter Extreme Weather Events

Applications of nonlinear optimization approach to atmospheric and oceanic sciences

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