Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks:Climatology,Interannual Variability,and Extremes

Climate models are vital for understanding and projecting global climate change and its associated impacts.However,these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections.Addressing these challenges requires addressing internal variability,hindering the direct alignment between model simulations and observations,and thwarting conventional supervised learning methods.Here,we employ an unsupervised Cycle-consistent Generative Adversarial Network(CycleGAN),to correct daily Sea Surface Temperature(SST)simulations from the Community Earth System Model 2(CESM2).Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation(ENSO)and the Indian Ocean Dipole mode,as well as SST extremes.Notably,it substantially corrects climatological SST biases,decreasing the globally averaged Root-Mean-Square Error(RMSE)by 58%.Intriguingly,the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies,a common issue in climate models that traditional methods,like quantile mapping,struggle to rectify.Additionally,it substantially improves the simulation of SST extremes,raising the pattern correlation coefficient(PCC)from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32.This enhancement is attributed to better representations of interannual,intraseasonal,and synoptic scales variabilities.Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.

Different El Niño Flavors and Associated Atmospheric Teleconnections as Simulated in a Hybrid Coupled Model

A previously developed hybrid coupled model(HCM)is composed of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model(AGCM),denoted as HCMAGCM.In this study,different El Niño flavors,namely the Eastern-Pacific(EP)and Central-Pacific(CP)types,and the associated global atmospheric teleconnections are examined in a 1000-yr control simulation of the HCMAGCM.The HCMAGCM indicates profoundly different characteristics among EP and CP El Niño events in terms of related oceanic and atmospheric variables in the tropical Pacific,including the amplitude and spatial patterns of sea surface temperature(SST),zonal wind stress,and precipitation anomalies.An SST budget analysis indicates that the thermocline feedback and zonal advective feedback dominantly contribute to the growth of EP and CP El Niño events,respectively.Corresponding to the shifts in the tropical rainfall and deep convection during EP and CP El Niño events,the model also reproduces the differences in the extratropical atmospheric responses during the boreal winter.In particular,the EP El Niño tends to be dominant in exciting a poleward wave train pattern to the Northern Hemisphere,while the CP El Niño tends to preferably produce a wave train similar to the Pacific North American(PNA)pattern.As a result,different climatic impacts exist in North American regions,with a warm-north and cold-south pattern during an EP El Niño and a warm-northeast and cold-southwest pattern during a CP El Niño,respectively.This modeling result highlights the importance of internal natural processes within the tropical Pacific as they relate to the genesis of ENSO diversity because the active ocean–atmosphere coupling is allowed only in the tropical Pacific within the framework of the HCMAGCM.

CMIP 6 models simulation of the connection between North/South Pacific Meridional Mode and ENSO

The subtropical North and South Pacific Meridional Modes(NPMM and SPMM)are well known precursors of El Niño-Southern Oscillation(ENSO).However,relationship between them is not constant.In the early 1980,the relationship experienced an interdecadal transition.Changes in this connection can be attributed mainly to the phase change of the Pacific decadal oscillation(PDO).During the positive phase of PDO,a shallower thermocline in the central Pacific is responsible for the stronger trade wind charging(TWC)mechanism,which leads to a stronger equatorial subsurface temperature evolution.This dynamic process strengthens the connection between NPMM and ENSO.Associated with the negative phase of PDO,a shallower thermocline over southeastern Pacific allows an enhanced wind-evaporation-SST(WES)feedback,strengthening the connection between SPMM and ENSO.Using 35 Coupled Model Intercomparison Project Phase 6(CMIP6)models,we examined the NPMM/SPMM performance and its connection with ENSO in the historical runs.The great majority of CMIP6 models can reproduce the pattern of NPMM and SPMM well,but they reveal discrepant ENSO and NPMM/SPMM relationship.The intermodal uncertainty for the connection of NPMM-ENSO is due to different TWC mechanism.A stronger TWC mechanism will enhance NPMM forcing.For SPMM,few models can simulate a good relationship with ENSO.The intermodel spread in the relationship of SPMM and ENSO owing to SST bias in the southeastern Pacific,as WES feedback is stronger when the southeastern Pacific is warmer.

Dynamical Predictability of Leading Interannual Variability Modes of the Asian-Australian Monsoon in Climate Models

The dynamical prediction of the Asian-Australian monsoon(AAM)has been an important and long-standing issue in climate science.In this study,the predictability of the first two leading modes of the AAM is studied using retrospective prediction datasets from the seasonal forecasting models in four operational centers worldwide.Results show that the model predictability of the leading AAM modes is sensitive to how they are defined in different seasonal sequences,especially for the second mode.The first AAM mode,from various seasonal sequences,coincides with the El Niño phase transition in the eastern-central Pacific.The second mode,initialized from boreal summer and autumn,leads El Niño by about one year but can exist during the decay phase of El Niño when initialized from boreal winter and spring.Our findings hint that ENSO,as an early signal,is conducive to better performance of model predictions in capturing the spatiotemporal variations of the leading AAM modes.Still,the persistence barrier of ENSO in spring leads to poor forecasting skills of spatial features.The multimodel ensemble(MME)mean shows some advantage in capturing the spatiotemporal variations of the AAM modes but does not provide a significant improvement in predicting its temporal features compared to the best individual models in predicting its temporal features.The BCC_CSM1.1M shows promising skill in predicting the two AAM indices associated with two leading AAM modes.The predictability demonstrated in this study is potentially useful for AAM prediction in operational and climate services.

Distributed consensus algorithm for networked Euler-Lagrange systems with self-delays and uncertainties

A distributed coordinated consensus problem for multiple networked Euler-Lagrange systems is studied. The communication between agents is subject to time delays, unknown parameters and nonlinear inputs, but only with their states available for measurement. When the communication topology of the system is connected, an adaptive control algorithm with selfdelays and uncertainties is suggested to guarantee global full-state synchro-nization that the difference between the agent＇s positions and ve-locities asymptotically converges to zero. Moreover, the distributed sliding-mode law is given for chaotic systems with nonlinear inputs to compensate for the effects of nonlinearity. Finally, simulation results show the effectiveness of the proposed control algorithm.

海气相互作用在模式FGOALS-g3模拟东亚夏季风及其对前冬El Niño响应中的贡献

本文基于观测、再分析资料和中国科学院大气物理研究所大气科学和地球流体力学数值模拟国家重点实验室(LASG)最新版本气候系统模式FGOALS-g3,探究了海气相互作用在模拟东亚夏季风及其对前冬El Niño响应中的贡献。大气环流模式(AGCM)模拟的气候态夏季风雨带偏东,东亚季风区表现为干偏差,耦合模式(CGCM)虽模拟出了夏季风雨带的位置,但降水仍偏弱。AGCM由于缺乏海气耦合过程,夏季西北太平洋地区对流模拟过强,使得副热带高压(简称副高)偏东、南中国海季风槽偏东,造成东亚夏季风雨带偏东;东亚陆地区域水汽偏少,也是降水干偏差的一个重要原因,此两项可以解释70%以上的干偏差。在考虑海气相互作用后,西北太平洋的降水正异常减弱了局地海表温度,因此CGCM显著改进了副高以及南中国海季风槽偏东等偏差,使得夏季风雨带位置得到改进,季风区降水干偏差减小了36%,但由于水汽偏少,水汽纬向输送偏少,东亚季风区仍维持着显著的干偏差。另一方面,对前冬El Niño的响应,CGCM能够再现El Niño衰减年夏季印度—西太平洋电容器效应(IPOC机制)对西北太平洋异常反气旋(WNPAC)的维持作用及偶极型分布的降水异常。而AGCM中夏季西北太平洋以及孟加拉湾、印度半岛周围海域对流对于海温的响应过于敏感,一方面西北太平洋局地暖异常造成的对流质量输送一定程度上抑制了WNPAC的建立,另一方面孟加拉湾、印度半岛周围海域过强的上升异常,通过局地环流,抑制了其南侧印度洋的对流异常,导致无法模拟出IPOC机制对衰减年夏季WNPAC的维持作用。因此,缺乏海气耦合过程是AGCM不能模拟出东亚夏季风对前冬El Niño滞后响应的关键原因。

SHEL:a semantically enhanced hardware-friendly entity linking method

With the help of pre-trained language models,the accuracy of the entity linking task has made great strides in recent years.However,most models with excellent performance require fine-tuning on a large amount of training data using large pre-trained language models,which is a hardware threshold to accomplish this task.Some researchers have achieved competitive results with less training data through ingenious methods,such as utilizing information provided by the named entity recognition model.This paper presents a novel semantic-enhancement-based entity linking approach,named semantically enhanced hardware-friendly entity linking(SHEL),which is designed to be hardware friendly and efficient while maintaining good performance.Specifically,SHEL's semantic enhancement approach consists of three aspects:(1)semantic compression of entity descriptions using a text summarization model;(2)maximizing the capture of mention contexts using asymmetric heuristics;(3)calculating a fixed size mention representation through pooling operations.These series of semantic enhancement methods effectively improve the model's ability to capture semantic information while taking into account the hardware constraints,and significantly improve the model's convergence speed by more than 50%compared with the strong baseline model proposed in this paper.In terms of performance,SHEL is comparable to the previous method,with superior performance on six well-established datasets,even though SHEL is trained using a smaller pre-trained language model as the encoder.

河北省城乡居民消费结构变动研究——基于ELES模型的实证分析

基于ELES模型,对2013-2021年河北省城乡居民消费结构变动情况进行了研究.从边际消费倾向可以看出,随着生活水平的提高,河北省城乡居民的消费逐渐从“温饱型”向“小康型”转变.消费结构变动度分析显示,除个别年份外,居民消费结构整体变动不大,相对较稳定.通过分析消费结构熵数发现,河北省城乡居民整体消费质量较高,但是消费结构升级速度相对较慢.根据分析结果,提出了增加居民收入、优化消费环境、拓展新型消费、坚持推进城乡融合发展、提高农村居民的社会保障水平等建议.

CMIP5/6气候模式对ElNiño多样性模拟能力的评估

利用第五次和第六次国际间耦合模式比较计划(coupled model intercomparison project,CMIP)中全球气候模式的历史时期和未来增暖情景模拟结果,结合观测资料,文章对比评估了23个CMIP6模式和32个CMIP5模式对El Niño多样性的模拟能力,并预估了东部(eastern Pacific,EP)型和中部(central Pacific,CP)型El Niño对未来全球变暖的响应特征。结果表明,绝大多数CMIP5/6气候模式能够合理地模拟El Niño的多样性特征,且CMIP6多模式的模拟性能较CMIP5有明显提升。CMIP6模式不仅减弱了EP型El Niño空间模态模拟的离散性,而且还显著提高了CP型El Niño空间模态的模拟能力;CMIP5/6多模式基本能够模拟出两类El Niño的季节锁相性特征,但CP型El Niño衰亡时间较观测明显滞后3个月;同时CMIP5/6多模式模拟的EP型El Niño强度与观测值较为接近,但CP型El Niño的振幅却强于观测。在未来全球变暖背景下,CP型El Niño事件的发生频率相对于EP型事件将趋于降低;EP型和CP型El Niño振幅强度随着全球变暖加剧将被增强,且EP型增强幅度显著强于CP型。

Asymptotic solution for a class of sea-air oscillator model for El Nio-southern oscillation

The El Nifio-Southern Oscillation （ENSO） is an interannual phenomenon involved in the tropical Pacific Oceanatmosphere interactions. In this paper, an asymptotic method of solving the nonlinear equation for the ENSO model is used. And based on a class of oscillator of ENSO model, the approximate solution of a corresponding problem is studied by employing the perturbation method. Firstly, an ENSO model of nonlinear time delay equation of equatorial Pacific is introduced, Secondly, by using the perturbed method, the zeroth and first order asymptotic perturbed solutions are constructed. Finally, from the comparison of the values for a figure, it is seen that the first asymptotic perturbed solution using the perturbation method has a good accuracy. And it is proved from the results that the perturbation method can be used as an analytic operation for the sea surface temperature anomaly in the equatorial Pacific of the atmosphere-ocean oscillation for the ENSO model.

城镇居民不同收入群体消费习惯的差异研究——基于具有习惯效应的面板ELES模型

有效融合ELES模型、效用函数和外部习惯理论,可以构建具有外部习惯效应的面板ELES模型,实证分析现阶段高、中收入群体对低收入群体在各类消费支出的外部习惯效应及在不同收入地区的主动需求和被动需求大小。研究结果表明:第一,高、中收入群体在食品、居住、交通和文教的外部习惯效应较强,在衣着、医疗和家庭设备的外部习惯效应较弱,且中等收入群体的外部习惯效应要都强于高收入群体的外部习惯效应。第二,当收入差距处于较低水平时,外部习惯效应对城镇居民消费影响较大,可支配收入影响较小;当收入差距持续拉大时,可支配收入对城镇居民消费影响也会随之增强,此时外部习惯效应的影响强度会相应减弱。第三,就主动需求和被动需求而言,总体上存在主动需求大于被动需求;就不同收入群体而言,高收入群体对各类消费支出的需求影响(包含主动需求和被动需求)大于中等收入群体;就地区整体需求而言,高收入地区需求最大,中等收入地区次之,低收入地区需求最小。

Asymptotic solution for the El Nio time delay sea-air oscillator model

A sea-air oscillator model is studied using the time delay theory. The aim is to find an asymptotic solving method for the El Nino-southern oscillation （ENSO） model. Employing the perturbed method, an asymptotic solution of the corresponding problem is obtained. Thus we can obtain the prognoses of the sea surface temperature （SST） anomaly and the related physical quantities.

A unified approach to fuzzy modelling and robust synchronization of different hyperchaotic systems

In this paper, a Takagi Sugeno （T-S） fuzzy model-based method is proposed to deal with the problem of synchronization of two identical or different hyperchaotic systems. The T S fuzzy models with a small number of fuzzy IF-THEN rules are employed to represent many typical hyperchaotic systems exactly. The benefit of employing the T-S fuzzy models lies in mathematical simplicity of analysis. Based on the T-S fuzzy hyperchaotic models, two fuzzy controllers arc designed via parallel distributed compensation （PDC） and exact linearization （EL） techniques to synchronize two identical hyperchaotic systems with uncertain parameters and two different hyperchaotic systems, respectively. The sufficient conditions for the robust synchronization of two identical hyperchaotic systems with uncertain parameters and the asymptotic synchronization of two different hyperchaotic systems are derived by applying the Lyapunov stability theory. This method is a universal one of synchronizing two identical or different hyperchaotic systems. Numerical examples are given to demonstrate the validity of the proposed fuzzy model and hyperchaotic synchronization scheme.

Simulating Eastern-and Central-Pacific Type ENSO Using a Simple Coupled Model

Severe biases exist in state-of-the-art general circulation models（GCMs） in capturing realistic central-Pacific（CP） El Nino structures. At the same time, many observational analyses have emphasized that thermocline（TH） feedback and zonal advective（ZA） feedback play dominant roles in the development of eastern-Pacific（EP） and CP El Nino-Southern Oscillation（ENSO）, respectively. In this work, a simple linear air-sea coupled model, which can accurately depict the strength distribution of the TH and ZA feedbacks in the equatorial Pacific, is used to investigate these two types of El Nino. The results indicate that the model can reproduce the main characteristics of CP ENSO if the TH feedback is switched off and the ZA feedback is retained as the only positive feedback, confirming the dominant role played by ZA feedback in the development of CP ENSO. Further experiments indicate that, through a simple nonlinear control approach, many ENSO characteristics,including the existence of both CP and EP El Nino and the asymmetries between El Nino and La Nina, can be successfully captured using the simple linear air-sea coupled model. These analyses indicate that an accurate depiction of the climatological sea surface temperature distribution and the related ZA feedback, which are the subject of severe biases in GCMs, is very important in simulating a realistic CP El Nino.

Backstepping-based distributed coordinated tracking formultiple uncertain Euler-Lagrange systems

Based on the idea of backstepping design, distributedcoordinated tracking problems under directed topology are discussedfor multiple Euler-Lagrange （EL） systems. The dynamicleader case is considered. First, with the parameter-linearity property,a distributed coordinated adaptive control scheme is proposedfor EL systems in the presence of parametric uncertainties.Then, subject to nonlinear uncertainties and external disturbances,an improved adaptive control algorithm is developed by usingneural-network （NN） approximation of nonlinear functions. Bothproposed algorithms can make tracking errors for each followerultimately bounded. The closed-loop systems are investigated byusing the combination of graph theory, Lyapunov theory, and BarbalatLemma. Numerical examples and comparisons with othermethods are provided to show the effectiveness of the proposedcontrol strategies.

Research on Consumption Structure of Rural Residents in Gansu Province Based on ELES Model

By using cross-section data on consumption structure of rural residents in Gansu Province in 2007 and 2008,this paper adopts ELES model to conduct empirical analysis on consumption structure of rural residents in Gansu Province.It indicates that in the current consumption structure of rural residents in Gansu Province,food expenditure is still at the most important and basic level;the overall consumption level of rural residents in Gansu Province is not high;at present,the consumption of rural residents in Gansu Province still hinges in a large measure on income,vulnerable to the price fluctuation.Consequently,increasing farmers' income and stabilizing the level of commodity price,turns out to be a foundation as well as an important approach to improve consumption structure of rural residents in Gansu Province.

A review of progress in coupled ocean-atmosphere model developments for ENSO studies in China

El Nino-Southern Oscillation(ENSO) is the strongest interannual signal that is producedby basinscale processes in the tropical Pacific,with significant effects on weather and climate worldwide.In the past,extensive and intensive international efforts have been devoted to coupled model developments for ENSO studies.A hierarchy of coupled ocean-atmo sphere models has been formulated;in terms of their complexity,they can be categorized into intermediate coupled models(ICMs),hybrid coupled models(HCMs),and fully coupled general circulation models(CGCMs).ENSO modeling has made significant progress over the past decades,reaching a stage where coupled models can now be used to successfully predict ENSO events 6 months to one year in advance.Meanwhile,ENSO exhibits great diversity and complexity as observed in nature,which still cannot be adequately captured by current state-of-the-art coupled models,presenting a challenge to ENSO modeling.We primarily reviewed the long-term efforts in ENSO modeling continually and steadily made at different institutions in China;some selected representative examples are presented here to review the current status of ENSO model developments and applications,which have been actively pursued with noticeable progress being made recently.As ENSO simulations are very sensitive to model formulations and process representations etc.,dedicated efforts have been devoted to ENSO model developments and improvements.Now,different ocean-atmosphere coupled models have been available in China,which exhibit good model performances and have already had a variety of applications to climate modeling,including the Coupled Model Intercomparison Project Phase 6(CMIP6).Nevertheless,large biases and uncertainties still exist in ENSO simulations and predictions,and there are clear rooms for their improvements,which are still an active area of researches and applications.Here,model performances of ENSO simulations are assessed in terms of advantages and disadvantages with these differently formulated coupled models,pinpointing to the areas where they need to be further improved for ENSO studies.These analyses provide valuable guidance for future improvements in ENSO simulations and predictions.

Response of Growing Season Gross Primary Production to El Nino in Different Phases of the Pacific Decadal Oscillation over Eastern China Based on Bayesian Model Averaging

Gross primary production(GPP) plays a crucial part in the carbon cycle of terrestrial ecosystems.A set of validated monthly GPP data from 1957 to 2010 in 0.5°× 0.5° grids of China was weighted from the Multi-scale Terrestrial Model Intercomparison Project using Bayesian model averaging(BMA).The spatial anomalies of detrended BMA GPP during the growing seasons of typical El Nino years indicated that GPP response to El Nino varies with Pacific Decadal Oscillation(PDO) phases: when the PDO was in the cool phase,it was likely that GPP was greater in northern China(32°–38°N,111°–122°E) and less in the Yangtze River valley(28°–32°N,111°–122°E);in contrast,when PDO was in the warm phase,the GPP anomalies were usually reversed in these two regions.The consistent spatiotemporal pattern and high partial correlation revealed that rainfall dominated this phenomenon.The previously published findings on how El Nino during different phases of PDO affecting rainfall in eastern China make the statistical relationship between GPP and El Nino in this study theoretically credible.This paper not only introduces an effective way to use BMA in grids that have mixed plant function types,but also makes it possible to evaluate the carbon cycle in eastern China based on the prediction of El Nino and PDO.

Comparison among the Consumption Structures of Different Income Groups of Urban Residents in Guangxi Based on ELES Model

According to the household consumption data of urban residents in Guangxi Statistical Yearbook in the year 2009, the ELES (Extended Linear Expenditure System) is used to analyze the consumption structure, the propensity to consume, and the consumer flexibility of urban residents in Guangxi Zhuang Autonomous Region of China in the year 2008. Result shows that urban residents in Guangxi has relatively low propensity to consume. And their consumption, especially the middle and low-income families, is mostly concentrated in food, cloth, lodging and other basic necessities of life, which account for more than a half of their income. Based on this, corresponding suggestions are put forward to enlarge the consumption demand of urban residents in Guangxi, such as increasing the regulation of income redistribution, minimizing the gap between the rich and the poor, enhancing the overall consumption level, cultivating the consumption hot spots for the urban residents, and actively guiding the enjoyable consumption.

Asymptotic solving method for a sea air oscillator model of atmospheric physics

In this paper, a class of coupled system for the E1 Nifio/La Nifia southern oscillation （ENSO） atmospheric physics oscillation model is considered. We propose an ENSO atmospheric physics model using a method from the asymptotic theory. It is indicated from the results that the asymptotic method can be used for analyzing the sea surface temperature anomaly and the thermocline depth anomaly of the atmosphere-ocean oscillation for the ENSO model in the equatorial Pacific.