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The IOCAS intermediate coupled model(IOCAS ICM) and its real-time predictions of the 2015–2016 El Nio event

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Science Bulletin 2016年第13期61卷 1061-1070页

作者： rong-Hua zhang Key Laboratory of Ocean Circulation and Waves Institute of Oceanology Chinese Academy of SciencesQingdao 266071 China Laboratory for Ocean and Climate Dynamics Qingdao National Laboratory for Marine Science and TechnologyQingdao 266237 China University of Chinese Academy of Sciences Beijing 100049 China

The tropical Pacific is currently experiencing an El Nifio event. Various coupled models with different degrees of complexity have been used to make real-time E1 Nifio predictions, but large uncertainties exist in the inten- sity forecast and are strongly model dependent. An intermediate coupled model （ICM） is used at the Institute of Oceanology, Chinese Academy of Sciences （IOCAS）, named the IOCAS ICM, to predict the sea surface temper- ature （SST） evolution in the tropical Pacific during the 2015-2016 E! Nifio event. One unique feature of the IOCAS ICM is the way in which the temperature of subsurface water entrained in the mixed layer （Te） is parameterized. Observed SST anomalies are only field that is utilized to initialize the coupled prediction using the IOCAS ICM. Examples are given of the model＇s ability to predict the SST conditions in a real-time manner. As is commonly evident in E1 Nifio- Southern Oscillation predictions using coupled models, large discrepancies occur between the observed and pre- dicted SST anomalies in spring 2015. Starting from early summer 2015, the model can realistically predict warming conditions. Thereafter, good predictions can be made through the summer and fall seasons of 2015. A transition to normal and cold conditions is predictecl to occur in rote spring 2016. Comparisons with other model predictions are made and factors influencing the prediction performance of the IOCAS ICM are also discussed.

关键词： The 2015 E1 Nifio event IOCAS ICM Real-time prediction Model performance and improvement Air-sea interactions

A DIFFERENTIAL GAME MODEL FOR A DEVELOPING AND A DEVELOPED COUNTRY

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Journal of Systems Science & Complexity 2009年第2期22卷 171-185页

作者： rong zhang Xuexiang HUANG College of Economics and Business Administration Chongqing University Chongqing 400030 China. Xuexiang HUANG School of Management Fudan University Shanghai 200433 China.

A differential game (DG) model for a developing and a developed country is *** player makes decisions about how much resource to be used to restrict the opponent's developmentso as to maximize his weighted sum of current consumption and final *** consumption isassumed to be preferred to final output for both *** developing country is assumed to havea higher economic growth rate and a higher preference to final output,whereas the developed countryis assumed to have a higher initial income and a higher efficiency in restricting his *** is investigated under three kinds of information structures,i.e.,a zerosum,a nonzero-sum,anda Stackelberg ***-loop equilibrium solutions are obtained for all the three *** of the result are provided.

关键词： Developed country developing country differential game Nash equilibrium.

Complex SAR Image Compression Using Entropy-Constrained Dictionary Learning and Universal Trellis Coded Quantization

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Chinese Journal of Electronics 2016年第4期25卷 686-691页

作者： ZHAN Xin zhang rong Department of Electronic Engineering and Information Science University of Science and Technology of China Key Laboratory of Electromagnetic Space Information Chinese Academy of Sciences

In this paper,an Entropy-constrained dictionary learning algorithm(ECDLA) is introduced for efficient compression of Synthetic aperture radar(SAR) complex *** RI encodes the Real and imaginary parts of the images using ECDLA and sparse representation,and ECDLA AP encodes the Amplitude and phase parts *** compared with the compression method based on the traditional Dictionary learning algorithm(DLA),ECDLA RI improves the Signal-to-noise ratio(SNR) up to 0.66 dB and reduces the Mean phase error(MPE) up to 0.0735 than DLA *** the same MPE,ECDLA AP outperforms DLA AP by up to 0.87 dB in ***,the proposed method is also suitable for real-time applications.

关键词： Synthetic aperture radar image compression Dictionary learning Sparse representation

A Hybrid Coupled Model for the Pacific Ocean–Atmosphere *** I: Description and Basic Performance

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Advances in Atmospheric Sciences 2015年第3期32卷 301-318页

作者： zhang rong-Hua Key Laboratory of Ocean Circulation and Waves Institute of Oceanology Chinese Academy of Sciences

A hybrid coupled model （HCM） is constructed for El Nifio-Southern Oscillation （ENSO）-related modeling studies over almost the entire Pacific *** ocean general circulation model is coupled to a statistical atmospheric model for interannual wind stress anomalies to represent their dominant coupling with sea surface *** addition,various relevant forcing and feedback processes exist in the region and can affect ENSO in a significant way; their effects are simply represented using historical data and are incorporated into the HCM,including stochastic forcing of atmospheric winds,and feedbacks associated with freshwater flux,ocean biology-induced heating （OBH）,and tropical instability waves （TIWs）.In addition to its computational efficiency,the advantages of making use of such an HCM enable these related forcing and feedback processes to be represented individually or collectively,allowing their modulating effects on ENSO to be examined in a clean and clear *** this paper,examples are given to illustrate the ability of the HCM to depict the mean ocean state,the circulation pathways connecting the subtropics and tropics in the western Pacific,and interannual variability associated with *** satellite data are taken to parameterize processes that are not explicitly represented in the HCM,this work also demonstrates an innovative method of using remotely sensed data for climate *** model applications related with ENSO modulations by extratropical influences and by various forcings and feedbacks will be presented in Part Ⅱ of this study.

关键词： hybrid coupled model ocean-atmosphere coupling ENSO forcing feedback satellite data

A DISCRETIZING LEVENBERG-MARQUARDT SCHEME FOR SOLVING NONLIEAR ILL-POSED INTEGRAL EQUATIONS

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Journal of Computational Mathematics 2022年第5期40卷 686-710页

作者： rong zhang Hongqi Yang School of Mathematics and Computer Science Gannan Normal UniversityGanzhou 341004China Guangdong Province Key Laboratory of Computational Science School of Computer Science and EngineeringSun Yat-sen UniversityGuangzhou 510275China

To reduce the computational cost,we propose a regularizing modified LevenbergMarquardt scheme via multiscale Galerkin method for solving nonlinear ill-posed *** results for the regularizing modified Levenberg-Marquardt scheme for the solution of nonlinear ill-posed problems have been *** on these results,we propose a modified heuristic parameter choice rule to terminate the regularizing modified Levenberg-Marquardt *** imposing certain conditions on the noise,we derive optimal convergence rates on the approximate solution under special source *** results are presented to illustrate the performance of the regularizing modified Levenberg-Marquardt scheme under the modified heuristic parameter choice.

关键词： The regularizing Levenberg-Marquardt scheme Multiscale Galerkin methods Nonlinear ill-posed problems Heuristic parameter choice rule Optimal convergence rate.

Structure and Evolution of Decadal Spiciness Variability in the North Pacific during 2004-20,Revealed from Argo Observations

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Advances in Atmospheric Sciences 2022年第6期39卷 953-966页

作者： Guanghui ZHOU rong-Hua zhang CAS Key Laboratory of Ocean Circulation and Waves Institute of Oceanologyand Center for Ocean Mega-ScienceChinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100029China Laboratory for Ocean and Climate Dynamics Pilot National Laboratory for Marine Science and TechnologyQingdao 266237China Center for Excellence in Quaternary Science and Global Change Chinese Academy of SciencesXi’an 710061China

Ocean spiciness is referred to as density-compensated temperature and salinity variations with warm(cool)and salty(fresh)waters having high(low)spiciness,*** structure and evolution of density-compensated(warm/salty or cool/fresh)spiciness anomalies are investigated in the North Pacific thermocline using Argo observations during the period *** well-organized decadal spiciness events are identified through isopycnal surface *** warm/salty spiciness anomaly of about 0.15°C and 0.05 g kg^(−1)temperature and salinity perturbations on the 25 kg m^(−1)isopycnal surface appeared in the eastern subtropical North Pacific at(18°-30°N,120°-150°W)in 2007,which then migrated southwestward along the mean circulation and arrived in the western tropics at(~15°N,145°E-175°W)in 2012-13,with the reduced salinity perturbation of about 0.043 g kg^(−1).Another cool/fresh spiciness anomaly of about−0.2°C and−0.07 g kg^(−1)temperature and salinity perturbations originated from the eastern subtropics at(120°-150°W,~30°N)in 2014 and followed a similar advective pathway during the period from 2014-15 to *** subduction pathway can be adequately determined by the mean Montgomery stream function on the isopycnal surface;the propagation direction and speed are in good agreement with the expectation for the role played by advection due to the mean geostrophic ***,the subducted decadal spiciness anomalies can have negative feedback on sea surface temperature(SST)variability in the western tropical Pacific through the diapycnal *** identifications of these density-compensated spiciness anomalies and their propagation pathways provide a clear illustration of the oceanic extratropics-tropics interactions in the North Pacific Ocean.

关键词： isopycnal analysis spiciness anomalies subduction pathway advection role decadal variability North Pacific

U-Net Models for Representing Wind Stress Anomalies over the Tropical Pacific and Their Integrations with an Intermediate Coupled Model for ENSO Studies

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Advances in Atmospheric Sciences 2024年第7期41卷 1403-1416页

作者： Shuangying Du rong-Hua zhang Key Laboratory of Ocean Circulation and Waves Institute of OceanologyChinese Academy of SciencesQingdao266071China School of Marine Sciences Nanjing University of Information Science and TechnologyNanjing210044China Laosan Laboratory Qingdao266237China University of Chinese Academy of Sciences Beijing100049China

El Niño-Southern Oscillation(ENSO)is the strongest interannual climate mode influencing the coupled ocean-atmosphere system in the tropical Pacific,and numerous dynamical and statistical models have been developed to simulate and predict *** some simplified coupled ocean-atmosphere models,the relationship between sea surface temperature(SST)anomalies and wind stress(τ)anomalies can be constructed by statistical methods,such as singular value decomposition(SVD).In recent years,the applications of artificial intelligence(AI)to climate modeling have shown promising prospects,and the integrations of AI-based models with dynamical models are active areas of *** study constructs U-Net models for representing the relationship between SSTAs andτanomalies in the tropical Pacific;the UNet-derivedτmodel,denoted asτUNet,is then used to replace the original SVD-basedτmodel of an intermediate coupled model(ICM),forming a newly AI-integrated ICM,referred to as *** simulation results obtained from ICM-UNet demonstrate their ability to represent the spatiotemporal variability of oceanic and atmospheric anomaly fields in the equatorial *** the ocean-only case study,theτUNet-derived wind stress anomaly fields are used to force the ocean component of the ICM,the results of which also indicate reasonable simulations of typical ENSO *** results demonstrate the feasibility of integrating an AI-derived model with a physics-based dynamical model for ENSO modeling ***,the successful integration of the dynamical ocean models with the AI-based atmospheric wind model provides a novel approach to ocean-atmosphere interaction modeling studies.

关键词： U-Net models wind stress anomalies ICM integration of AI and physical components

A Hybrid Neural Network Model for ENSO Prediction in Combination with Principal Oscillation Pattern Analyses

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Advances in Atmospheric Sciences 2022年第6期39卷 889-902页

作者： Lu ZHOU rong-Hua zhang CAS Key Laboratory of Ocean Circulation and Waves Institute of Oceanologyand Center for Ocean Mega-ScienceChinese Academy of SciencesQingdao 266071China University of Chinese Academy of Sciences Beijing 100029China Laboratory for Ocean and Climate Dynamics Pilot National Laboratory for Marine Science and TechnologyQingdao 266237China Center for Excellence in Quaternary Science and Global Change Chinese Academy of SciencesXi’an 710061China

El Niño-Southern Oscillation(ENSO)can be currently predicted reasonably well six months and longer,but large biases and uncertainties remain in its real-time *** approaches have been taken to improve understanding of ENSO processes,and different models for ENSO predictions have been developed,including linear statistical models based on principal oscillation pattern(POP)analyses,convolutional neural networks(CNNs),and so ***,we develop a novel hybrid model,named as POP-Net,by combining the POP analysis procedure with CNN-long short-term memory(LSTM)algorithm to predict the Niño-3.4 sea surface temperature(SST)*** predictions are compared with each other from the corresponding three models:POP model,CNN-LSTM model,and POP-Net,*** POP-based pre-processing acts to enhance ENSO-related signals of interest while filtering unrelated ***,an improved prediction is achieved in the POP-Net relative to *** POP-Net shows a high-correlation skill for 17-month lead time prediction(correlation coefficients exceeding 0.5)during the 1994-2020 validation *** POP-Net also alleviates the spring predictability barrier(SPB).It is concluded that value-added artificial neural networks for improved ENSO predictions are possible by including the process-oriented analyses to enhance signal representations.

关键词： ENSO prediction the principal oscillation pattern(POP)analyses neural network a hybrid approach

Phase-field simulation of dendritic growth in a forced liquid metal flow coupling with boundary heat flux

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Science China(Technological Sciences) 2013年第10期56卷 2586-2593页

作者： DU LiFei zhang rong zhang LiMin School of Science Key Laboratory of Space Applied Physics and Chemistry Ministry of EducationNorthwestern Polytechnical University

A phase-field model with forced liquid metal flow was employed to study the effect of boundary heat flux on the dendritic structure forming of a Ni-40.8%Cu alloy with liquid flow during *** effect of the flow field coupling with boundary heat extractions on the morphology change and distributions of concentration and temperature fields was analyzed and *** forced liquid flow could significantly affect the dendrite morphology,concentration and temperature distributions in the solidifying *** coupling with boundary heat extraction,the solute segregation and concentration diffusion were changed with different heat *** morphology,concentration and temperature distributions were significantly influenced by increasing the heat extraction,which could relatively make the effect of liquid flow *** increasing the initial velocity of liquid flow,the lopsided rate of the primary dendrite arm was enlarged and the transition of developing manner of the secondary arms moved to the large heat extraction *** was the competition between heat flux and forced liquid flow that finally determined microstructure forming during solidification.

关键词： phase-field simulation liquid flow heat flux solidification