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Nonlinear balance constraints in 3DVAR data assimilation

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Science China Earth Sciences 2006年第3期49卷 331-336页

作者： zhu jiang YAN Changxiang International Center for Climate and Environment Sciences Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China International Center for Climate and Environment Sciences Institute of Atmospheric Physics Chinese Academy of Sciences Beijing 100029 China

In many applications of 3DVAR, the balance constraints can be considered via two main approaches: weak constraint method which adds penalty terms to the cost function; and proper defi- nition of the background error covariance matrix with non-zero cross-correlation sub-matrices. The weak constraint approach requires determining the weighting matrices of the penalty terms. The background error covariance approach does not require determining those additional weighting ma- trices. However, it is only applicable to those linear or linearized balance constraints. A novel ap- proach is proposed based on the background error covariance approach by generalizing the so-called Derber-Bouttier formulation. An assimilation experiment of estimating temperature and salinity from the sea surface dynamic height observation is given to illustrate the proposed treatments of nonlinear balance constraints.

关键词： 3DVAR, linear balance constraint, nonlinear balance constraint, background error covariance matrix, sea surface dynamic height.

L^p-decay rates to nonlinear diffusion waves for p-system with nonlinear damping

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Science China Mathematics 2006年第6期49卷 721-739页

作者： zhu Changjiang jiang Mina Laboratory of Nonlinear Analysis Department of Mathematics Central China Normal University Wuhan 430079 China Laboratory of Nonlinear Analysis Department of Mathematics Central China Normal University Wuhan 430079 China

In this paper, we study the Lp (2≤p≤ +∞) convergence rates of the solutions to the Cauchy problem of the so-called p-system with nonlinear damping. Precisely, we show that the corresponding Cauchy problem admits a unique global solution (v (x,t), u(x, t)) and such a solution tends time-asymptotically to the corresponding nonlinear diffusion wave ((v|-)(x,t),(u|-)(x,t)) governed by the classical Darcy's law provided that the corresponding prescribed initial error function lies in and is sufficiently small. Furthermore, the Lp (2≤p≤ +∞) convergence rates of the solutions are also obtained.

关键词： nonlinear damping, nonlinear diffusion waves, convergence rates, energy estimates.

Assessments of Data-Driven Deep Learning Models on One-Month Predictions of Pan-Arctic Sea Ice Thickness

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Advances in Atmospheric Sciences 2024年第7期41卷 1379-1390页

作者： Chentao SONG jiang zhu Xichen LI Institute of Atmospheric Physics Chinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China

In recent years,deep learning methods have gradually been applied to prediction tasks related to Arctic sea ice concentration,but relatively little research has been conducted for larger spatial and temporal scales,mainly due to the limited time coverage of observations and reanalysis ***,deep learning predictions of sea ice thickness(SIT)have yet to receive ample *** this study,two data-driven deep learning(DL)models are built based on the ConvLSTM and fully convolutional U-net(FC-Unet)algorithms and trained using CMIP6 historical simulations for transfer learning and fine-tuned using reanalysis/*** models enable monthly predictions of Arctic SIT without considering the complex physical processes *** comprehensive assessments of prediction skills by season and region,the results suggest that using a broader set of CMIP6 data for transfer learning,as well as incorporating multiple climate variables as predictors,contribute to better prediction results,although both DL models can effectively predict the spatiotemporal features of SIT *** the predicted SIT anomalies of the FC-Unet model,the spatial correlations with reanalysis reach an average level of 89%over all months,while the temporal anomaly correlation coefficients are close to unity in most *** models also demonstrate robust performances in predicting SIT and SIE during extreme *** effectiveness and reliability of the proposed deep transfer learning models in predicting Arctic SIT can facilitate more accurate pan-Arctic predictions,aiding climate change research and real-time business applications.

关键词： Arctic sea ice thickness deep learning spatiotemporal sequence prediction transfer learning

Gridless Variational Bayesian Inference of Line Spectral from Quantized Samples

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China Communications 2021年第10期18卷 77-95页

作者： jiang zhu Qi Zhang Xiangming Meng The Engineering Research Center of Oceanic Sensing Technology and Equipment Ministry of EducationZhoushan 316021China Ocean College Zhejiang UniversityZhoushan 316021China Institute for Physics of Intelligence Graduate School of ScienceThe University of Tokyo7-3-1HongoTokyo 113-0033Japan

Efficient estimation of line spectral from quantized samples is of significant importance in information theory and signal processing,e.g.,channel estimation in energy efficient massive MIMO systems and direction of arrival *** goal of this paper is to recover the line spectral as well as its corresponding parameters including the model order,frequencies and amplitudes from heavily quantized *** this end,we propose an efficient gridless Bayesian algorithm named VALSE-EP,which is a combination of the high resolution and low complexity gridless variational line spectral estimation(VALSE)and expectation propagation(EP).The basic idea of VALSE-EP is to iteratively approximate the challenging quantized model of line spectral estimation as a sequence of simple pseudo unquantized models,where VALSE is ***,to obtain a benchmark of the performance of the proposed algorithm,the Cram′er Rao bound(CRB)is ***,numerical experiments on both synthetic and real data are performed,demonstrating the near CRB performance of the proposed VALSE-EP for line spectral estimation from quantized samples.

关键词： variational Bayesian inference expectation propagation quantization line spectral estimation mmse gridless

Social network users clustering based on multivariate time series of emotional behavior

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The Journal of China Universities of Posts and Telecommunications 2014年第2期21卷 21-31页

作者： zhu jiang WANG Bai WU Bin School of Computer Science Beijing University of Posts and Telecommunications

It is known that the social network is an excellent source for gathering the emotions of people. There are thousands of micro-blogs posted in every second and every micro-blog that may contain a variety of user＇s emotions. The users＇ collective emotional behaviors are with great impacts on today＇s societies, so it is good to find groups for society management based on users＇ emotional behavior. This article focuses on analyzing multivariate emotional behavior of users in social network and the goal is to cluster the users from a fully new perspective-emotions. The following tasks are completed： firstly, the multivariate emotion of Chinese micro-blog with vector is analyzed, and multivariate time series to describe the user＇s emotional behavior are constructed. Seconedly, considering principal component analysis （PCA） in similarity and distance similarity, the similarity of the multivariate emotion time series is measured. The contribution could be summarized as follows： groups of users though different emotions in social network are discovered. The emotional fluctuation and intensity of users are considered as well. Experiment in clustering effectively illustrates the emotional behavior characteristics of the Users in different groups.

关键词： social network multivariate emotional behavior PCA similarity distance similarity

An Incursion of Off-Equatorial Subsurface Cold Water and Its Role in Triggering the “Double Dip” La Nia Event of 2011

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Advances in Atmospheric Sciences 2015年第6期32卷 731-742页

作者： ZHENG Fei FENG Lisha zhu jiang International Center for Climate and Environment Science Institute of Atmospheric PhysicsChinese Academy of Sciences College of Atmospheric Sciences Chengdu University of Information Technology

Based on Global Ocean Data Assimilation System （GODAS） and NCEP reanalysis data, atmospheric and oceanic pro- cesses possibly responsible for the onset of the 2011/12 La Nifia event, which followed the 2010/11 La Nifia even--referred to as a ＂double dip＂ La Nifia--are investigated. The key mechanisms involved in activating the 2011/12 La Nifia are illus- trated by these datasets. Results show that neutral conditions were already evident in the equatorial eastern Pacific during the decaying phase of the 2010/11 La Nifia. However, isothermal analyses show obviously cold water still persisting at the surface and at subsurface depths in off-equatorial regions throughout early 2011, being most pronounced in the tropical South Pacific. The negative SST anomalies in the tropical South Pacific acted to strengthen a southern wind across the equator. The subsurface cold water in the tropical South Pacific then spread northward and broke into the equatorial region at the thermo- cline depth. This incursion process of off-equatorial subsurface cold water successfully interrupted the eastern propagation of warm water along the equator, which had previously accumulated at subsurface depths in the warm pool during the 2010/11 La Nifia event. Furthermore, the incursion process strengthened as a result of the off-equatorial effects, mostly in the tropical South Pacific. The negative SST anomalies then reappeared in the central basin in summer 2011, and acted to trigger local coupled air-sea interactions to produce atmospheric-oceanic anomalies that developed and evolved with the second cooling in the fall of 2011.

关键词： "double dip" La Nifia subsurface cold water incursion off-equatorial process

Assimilation of Sea Surface Temperature in a Global Hybrid Coordinate Ocean Model

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Advances in Atmospheric Sciences 2018年第10期35卷 1291-1304页

作者： Yueliang CHEN Changxiang YAN jiang zhu International Center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China University of Chinese Academy of Sciences Beijing 100049China State Key Laboratory of Acoustics Institute of AcousticsChinese Academy of SciencesBeijing 100190China

The Hybrid Coordinate Ocean Model(HYCOM) uses different vertical coordinate choices in different regions. In HYCOM, the prognostic variables include not only the seawater temperature, salinity and current fields, but also the layer thickness. All prognostic variables are usually adjusted in the assimilation when multivariate data assimilation methods are used to assimilate sea surface temperature(SST). This paper investigates the effects of SST assimilation in a global HYCOM model using the Ensemble Optimal Interpolation multivariate assimilation method. Three assimilation experiments are conducted from 2006–08. In the first experiment, all model variables are adjusted during the assimilation process. In the other two experiments, the temperature alone is adjusted in the entire water column and in the mixed layer. For comparison, a control experiment without assimilation is also conducted. The three assimilation experiments yield notable SST improvements over the results of the control experiment. Additionally, the experiments in which all variables are adjusted and the temperature alone in all model layers is adjusted, produce significant negative effects on the subsurface temperature. Also, they yield negative effects on the subsurface salinity because it is associated with temperature and layer thickness. The experiment adjusting the temperature alone in the mixed layer yields positive effects and outperforms the other experiments. The heat content in the upper 300 m and 300–700 m layers further suggests that it yields the best performance among the experiments.

关键词： ensemble optimal interpolation multivariate data assimilation sea surface temperature ocean heat content

The Roles of Different Mechanisms Related to the Tide-induced Fronts in the Yellow Sea in Summer

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Advances in Atmospheric Sciences 2014年第5期31卷 1079-1089页

作者： REN Shihe XIE Jiping zhu jiang International Center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of Sciences University of Chinese Academy of Sciences Institute of Atmospheric Physics Chinese Academy of Sciences

In summer, the Yellow Sea Cold Water Mass （YSCWM） is a stable water mass of low temperature lying at the bottom of the central Yellow Sea （YS）. It is fringed by some typical tidal fronts, which separate deep, stratified water on the offshore side from the well-mixed, shallow water on the inshore side. Three striking fronts--Subei Bank Front （SBF）, Shandong Peninsula Front （SPF）, and Mokpo Front （MKF; a front off the southwestern tip of the Korean Peninsula）--have been iden- tified by various studies from both satellite observations and model results. Tide plays an important role in the formation and maintenance of these fronts. However, it is still a matter of debate as to the roles these two kinds of mechanisms of upwelling and tidal mixing play, and how importance they are in the maintenance processes of the above three fronts. Basing a nested high-resolution model HYCOM （the Hybrid Coordinate Ocean Model）, this study focuses on the different mechanisms of tidal effects on the thermal fronts in the YS in summertime. Through comparative experiments with and without tidal forcing, the results indicate that the MKF is mainly driven by tide-induced upwelling. For the SPF, tidal mixing is the dominant factor, when lower cold water is stirred upwards along the sloping topography of the western YS. Meanwhile, the combined effect of upwelling and tidal mixing is the main cause of the formation of the SBF. Diagnostic analysis of thermal balance shows that horizontal nonlinear advection induced by strong tidal currents also contributes to the thermal balance of frontal areas.

关键词： tidal front tide-induced upwelling tidal mixing thermal balance

An Ocean Data Assimilation System in the Indian Ocean and West Pacific Ocean

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Advances in Atmospheric Sciences 2015年第11期32卷 1460-1472页

作者： YAN Changxiang zhu jiang XIE Jiping International Center for Climate and Environment Sciences Institute of Atmospheric PhysicsChinese Academy of Sciences

The development and application of a regional ocean data assimilation system are among the aims of the Global Ocean Data Assimilation Experiment. The ocean data assimilation system in the regions including the Indian and West Pacific oceans is an endeavor motivated by this goal. In this study, we describe the system in detail. Moreover, the reanalysis in the joint area of Asia, the Indian Ocean, and the western Pacific Ocean （hereafter AIPOcean） constructed using multi-year model integration with data assimilation is used to test the performance of this system. The ocean model is an eddy-resolving, hybrid coordinate ocean model. Various types of observations including in-situ temperature and salinity profiles （mechanical bathythermograph, expendable bathythermograph, Array for Real-time Geostrophic Oceanography, Tropical Atmosphere Ocean Array, conductivity-temperature-depth, station data）, remotely-sensed sea surface temperature, and altimetry sea level anomalies, are assimilated into the reanalysis via the ensemble optimal interpolation method. An ensemble of model states sampled from a long-term integration is allowed to change with season, rather than remaining stationary. The estimated background error covariance matrix may reasonably reflect the seasonality and anisotropy. We evaluate the performance of AIPOcean during the period 1993-2006 by comparisons with independent observations, and some reanalysis products. We show that AIPOcean reduces the errors of subsurface temperature and salinity, and reproduces mesoscale eddies. In contrast to ECCO and SODA products, AIPOcean captures the interannual variability and linear trend of sea level anomalies very well. AIPOcean also shows a good consistency with tide gauges.

关键词： ocean data assimilation reanalysis ensemble optimal interpolation background error covariance