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.

Cerium-tungsten oxides supported on activated red mud for the selective catalytic reduction of NO_(x)

Activated red mud(RM)has been proved to be a promising base material for the selective catalysis reduction(SCR)of NOx.The inherent low reducibility and acidity limited its low-temperature activity.In this work,molybdenum oxide,tungsten oxide,and cerium oxide were used to reconfigure the redox sites and acid sites of red mud based catalyst.When activated red mud was reconfigured by cerium-tungsten oxide(Ce-W@RM),the NOx conversion kept above 90%at 219-480℃.The existence of Ce^(3+)/Ce^(4+) redox electron pairs provided more surface adsorbed oxygen(O_(α)) and served as a redox cycle.Positive interactions between Ce,W species and Fe oxide in red mud occurred,which led to the formation of unsaturated chemical bond and promoted the activation of adsorbed NH_(3) species.WO_(3) and Ce_(2)(WO_(4))_(3)(formed by solid-state reaction between Ce and W species)could provide more Brønsted acid sites(W-O modes of WO_(3),W=O or W-O-W modes of Ce_(2)(WO_(4))_(3)).CeO_(2) species could provide more Lewis acid sites.The Langmuir-Hinshelwood(L-H)routes and Eley-Rideal(E-R)routes occurred in the low-temperature SCR reaction on the Ce-W@RM surface.NH_(4)^(+) species on Brønsted acid sites,NH_(3) species on Lewis acid sites,bidentate nitrate and bridging nitrate species were key active intermediates species.

A spatiotemporal 3D convolutional neural network model for ENSO predictions: A test case for the 2020/21 La Niña conditions

2020–22年间热带太平洋经历了持续性多年的拉尼娜事件,多数耦合模式都难以准确预测其演变过程,这为厄尔尼诺-南方涛动(ENSO)的实时预测带来了很大的挑战.同时,目前学术界对此次持续性双拉尼娜事件的发展仍缺乏合理的物理解释,其所涉及的物理过程和机制有待于进一步分析.本研究利用再分析数据产品分析了热带东南太平洋东南风异常及其引起的次表层海温异常在此次热带太平洋海表温度(SST)异常演变中的作用,并构建了一个时空分离(Time-Space)的三维(3D)卷积神经网络模型(TS-3DCNN)对此次双拉尼娜事件进行实时预测和过程分析.通过将TS-3DCNN与中国科学院海洋研究所(IOCAS)中等复杂程度海气耦合模式(IOCAS ICM)的预测结果对比,表明TS-3DCNN模型对2020–22年双重拉尼娜现象的预测能力与IOCAS ICM相当,二者均能够从2021年初的初始场开始较好地预测2021年末El Niño3.4区SST的演变.此外,基于TS-3DCNN和IOCAS ICM的敏感性试验也验证了赤道外风场异常和次表层海温异常在2021年末赤道中东太平洋海表二次变冷过程中的关键作用.未来将神经网络与动力模式模式间的有效结合,进一步发展神经网络与物理过程相结合的混合建模是进一步提高ENSO事件预测能力的有效途径.

Testing a Four-Dimensional Variational Data Assimilation Method Using an Improved Intermediate Coupled Model for ENSO Analysis and Prediction

A four-dimensional variational （4D-Var） data assimilation method is implemented in an improved intermediate coupled model （ICM） of the tropical Pacific. A twin experiment is designed to evaluate the impact of the 4D-Var data assimilation algorithm on ENSO analysis and prediction based on the ICM. The model error is assumed to arise only from the parameter uncertainty. The ＂observation＂ of the SST anomaly, which is sampled from a ＂truth＂ model simulation that takes default parameter values and has Gaussian noise added, is directly assimilated into the assimilation model with its parameters set erroneously. Results show that 4D-Var effectively reduces the error of ENSO analysis and therefore improves the prediction skill of ENSO events compared with the non-assimilation case. These results provide a promising way for the ICM to achieve better real-time ENSO prediction.

Initial Error-induced Optimal Perturbations in ENSO Predictions, as Derived from an Intermediate Coupled Model

The initial errors constitute one of the main limiting factors in the ability to predict the E1 Nino-Southem Oscillation （ENSO） in ocean-atmosphere coupled models. The conditional nonlinear optimal perturbation （CNOP） approach was em- ployed to study the largest initial error growth in the E1 Nino predictions of an intermediate coupled model （ICM）. The optimal initial errors （as represented by CNOPs） in sea surface temperature anomalies （SSTAs） and sea level anomalies （SLAs） were obtained with seasonal variation. The CNOP-induced perturbations, which tend to evolve into the La Nifia mode, were found to have the same dynamics as ENSO itself. This indicates that, if CNOP-type errors are present in the initial conditions used to make a prediction of E1 Nino, the E1 Nino event tends to be under-predicted. In particular, compared with other seasonal CNOPs, the CNOPs in winter can induce the largest error growth, which gives rise to an ENSO amplitude that is hardly ever predicted accurately. Additionally, it was found that the CNOP-induced perturbations exhibit a strong spring predictability barrier （SPB） phenomenon for ENSO prediction. These results offer a way to enhance ICM prediction skill and, particularly, weaken the SPB phenomenon by filtering the CNOP-type errors in the initial state. The characteristic distributions of the CNOPs derived from the ICM also provide useful information for targeted observations through data assimilation. Given the fact that the derived CNOPs are season-dependent, it is suggested that seasonally varying targeted observations should be implemented to accurately predict ENSO events.

Idealized Experiments for Optimizing Model Parameters Using a 4D-Variational Method in an Intermediate Coupled Model of ENSO

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational （4D-Vat） data assimilation system was developed for an intermediate coupled model （ICM） and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer （Te）, which is empirically and explicitly related to sea level （SL） variation. The strength of the thermocline effect on SST （referred to simply as ＂the thermocline effect＂） is represented by an introduced parameter, （l＇Te. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Vat data assimilation system implemented in the ICM are also discussed.

On the Second-Year Warming in Late 2019 over the Tropical Pacific and Its Attribution to an Indian Ocean Dipole Event

After its maturity,El Niño usually decays rapidly in the following summer and evolves into a La Niña pattern.However,this was not the case for the 2018/19 El Niño event.Based on multiple reanalysis data sets,the space-time evolution and triggering mechanism for the unusual second-year warming in late 2019,after the 2018/19 El Niño event,are investigated in the tropical Pacific.After a short decaying period associated with the 2018/19 El Niño condition,positive sea surface temperature anomalies(SSTAs)re-intensified in the eastern equatorial Pacific in late 2019.Compared with the composite pattern of El Niño in the following year,two key differences are evident in the evolution of SSTAs in 2019.First,is the persistence of the surface warming over the central equatorial Pacific in May,and second,is the re-intensification of the positive SSTAs over the eastern equatorial Pacific in September.Observational results suggest that the re-intensification of anomalous westerly winds over the western and central Pacific,induced remotely by an extreme Indian Ocean Dipole(IOD)event,acted as a triggering mechanism for the second-year warming in late 2019.That is,the IOD-related cold SSTAs in the eastern Indian Ocean established and sustained anomalous surface westerly winds over the western equatorial Pacific,which induced downwelling Kelvin waves propagating eastward along the equator.At the same time,the subsurface ocean provided plenty of warm water in the western and central equatorial Pacific.Mixed-layer heat budget analyses further confirm that positive zonal advection,induced by the anomalous westerly winds,and thermocline feedback played important roles in leading to the second-year warming in late 2019.This study provides new insights into the processes responsible for the diversity of El Niño evolution,which is important for improving the physical understanding and seasonal prediction of El Niño events.

A Hybrid Coupled Ocean–Atmosphere Model and Its Simulation of ENSO and Atmospheric Responses

A new hybrid coupled model(HCM) is presented in this study, which consists of an intermediate tropical Pacific Ocean model and a global atmospheric general circulation model. The ocean component is the intermediate ocean model(IOM)of the intermediate coupled model(ICM) used at the Institute of Oceanology, Chinese Academy of Sciences(IOCAS). The atmospheric component is ECHAM5, the fifth version of the Max Planck Institute for Meteorology atmospheric general circulation model. The HCM integrates its atmospheric and oceanic components by using an anomaly coupling strategy. A100-year simulation has been made with the HCM and its simulation skills are evaluated, including the interannual variability of SST over the tropical Pacific and the ENSO-related responses of the global atmosphere. The model shows irregular occurrence of ENSO events with a spectral range between two and five years. The amplitude and lifetime of ENSO events and the annual phase-locking of SST anomalies are also reproduced realistically. Despite the slightly stronger variance of SST anomalies over the central Pacific than observed in the HCM, the patterns of atmospheric anomalies related to ENSO,such as sea level pressure, temperature and precipitation, are in broad agreement with observations. Therefore, this model can not only simulate the ENSO variability, but also reproduce the global atmospheric variability associated with ENSO, thereby providing a useful modeling tool for ENSO studies. Further model applications of ENSO modulations by ocean–atmosphere processes, and of ENSO-related climate prediction, are also discussed.

ENSO Predictions in an Intermediate Coupled Model Influenced by Removing Initial Condition Errors in Sensitive Areas： A Target Observation Perspective

Previous studies indicate that ENSO predictions are particularly sensitive to the initial conditions in some key areas（socalled ＂sensitive areas＂）. And yet, few studies have quantified improvements in prediction skill in the context of an optimal observing system. In this study, the impact on prediction skill is explored using an intermediate coupled model in which errors in initial conditions formed to make ENSO predictions are removed in certain areas. Based on ideal observing system simulation experiments, the importance of various observational networks on improvement of El Ni n？o prediction skill is examined. The results indicate that the initial states in the central and eastern equatorial Pacific are important to improve El Ni n？o prediction skill effectively. When removing the initial condition errors in the central equatorial Pacific, ENSO prediction errors can be reduced by 25%. Furthermore, combinations of various subregions are considered to demonstrate the efficiency on ENSO prediction skill. Particularly, seasonally varying observational networks are suggested to improve the prediction skill more effectively. For example, in addition to observing in the central equatorial Pacific and its north throughout the year,increasing observations in the eastern equatorial Pacific during April to October is crucially important, which can improve the prediction accuracy by 62%. These results also demonstrate the effectiveness of the conditional nonlinear optimal perturbation approach on detecting sensitive areas for target observations.

The Optimal Precursors for ENSO Events Depicted Using the Gradientdefinition-based Method in an Intermediate Coupled Model

The predictability of El Ni-o-Southern Oscillation (ENSO) has been an important area of study for years. Searching for the optimal precursor (OPR) of ENSO occurrence is an effective way to understand its predictability. The CNOP (conditional nonlinear optimal perturbation), one of the most effective ways to depict the predictability of ENSO, is adopted to study the optimal sea surface temperature (SST) precursors (SST-OPRs) of ENSO in the IOCAS ICM (intermediate coupled model developed at the Institute of Oceanology, Chinese Academy of Sciences). To seek the SST-OPRs of ENSO in the ICM, non-ENSO events simulated by the ICM are chosen as the basic state. Then, the gradient-definition-based method (GD method) is employed to solve the CNOP for different initial months of the basic years to obtain the SSTOPRs. The experimental results show that the obtained SST-OPRs present a positive anomaly signal in the western-central equatorial Pacific, and obvious differences exist in the patterns between the different seasonal SST-OPRs along the equatorial western-central Pacific, showing seasonal dependence to some extent. Furthermore, the non-El Ni-o events can eventually evolve into El Ni-o events when the SST-OPRs are superimposed on the corresponding seasons;the peaks of the Ni-o3.4 index occur at the ends of the years, which is consistent with the evolution of the real El Ni-o. These results show that the GD method is an effective way to obtain SST-OPRs for ENSO events in the ICM. Moreover, the OPRs for ENSO depicted using the GD method provide useful information for finding the early signal of ENSO in the ICM.

Current Status for Oral Platinum (IV) Anticancer Drug Development

Platinum-based chemotherapeutic drugs such as cisplatin, carboplatin and oxaliplatin are widely applied for the treatment of various types of tumors. However, poor solubility, serious side effects, and more importantly, the intrinsic and acquired resistance limit their clinical applications. These factors motivate scientists to design and synthesize novel and more potent analogues lacking disadvantages of clinical platinum drugs. Platinum (IV) complexes are one of representatives. In this review, we summarized the investigations undertaken into Platinum (IV) antitumor compounds since Rosenberg first noted their antitumor activity. The synthesis method and mechanism of action of Platinum (IV) complexes are outlined, as well as their chemical and pharmacological properties. Recent advances in Platinum (IV) anticancer agents that have been in clinical trials and photoactivatable Platinum (IV) complexes are also summarized, and the purpose here is to provide insight into the requirements for the antitumor activity of Platinum (IV) complexes and a basis for progressing in a new platinum compound.

恶性胸膜间皮瘤免疫检查点抑制剂疗效及安全性meta分析

本研究旨在评价免疫检查点抑制剂(immune checkpoint inhibitors,ICIs)治疗在恶性胸膜间皮瘤(malignant pleural mesothelioma,MPM)中的疗效和安全性。计算机检索PubMed、Embase、The Cochrane Library、Web of science等数据库,建库起至2022年10月,检索ICIs治疗MPM的前瞻性临床研究。按照纳入与排除标准独立筛选文献、提取资料并评价偏倚风险后,采用Stata17.0软件进行统计分析。结果发现,共纳入8个单臂研究,3个随机对照试验,包括839例患者。Meta分析结果显示,接受了ICIs治疗的研究合并ORR为37%(95%CI,23–51),中位OS为14.02个月(95%CI,11.40–17.64),中位PFS为4.72个月(95%CI,3.62–6.16)。根据治疗方法的类型:ICI单药治疗或ICI联合治疗(联合双药ICI/ICI联合化疗)进行亚组分析。结果为ORR 51%(95%CI,39–62)vs 19%(95%CI,8–29);OS 18.30个月(95%CI,16.42–20.40)vs 11.03个月(95%CI,9.46–12.86);PFS 6.78个月(95%CI,6.18–7.44)vs 3.40个月(95%CI,2.41–4.79);提示ICI联合治疗在ORR、OS、PFS上明显优于ICI单药治疗。所有研究中3–4级AEs发生率为30%,ICIs治疗最常见不良事件为乏力、腹泻、及皮疹。其中联合用药的3–4级AEs高于单药组(35%vs 22%)。因此,ICI联合治疗在MPM患者中有临床应用价值,支持在MPM患者中大规模临床应用。ICI联合治疗在安全性方面较一线化疗方案3–4级不良反应事件发生率更高。

A multi-model prediction system for ENSO

The El Niño and Southern Oscillation(ENSO)is the primary source of predictability for seasonal climate prediction.To improve the ENSO prediction skill,we established a multi-model ensemble(MME)prediction system,which consists of 5 dynamical coupled models with various complexities,parameterizations,resolutions,initializations and ensemble strategies,to account for the uncertainties as sufficiently as possible.Our results demonstrated the superiority of the MME over individual models,with dramatically reduced the root mean square error and improved the anomaly correlation skill,which can compete with,or even exceed the skill of the North American Multi-Model Ensemble.In addition,the MME suffered less from the spring predictability barrier and offered more reliable probabilistic prediction.The real-time MME prediction adequately captured the latest successive La Niña events and the secondary cooling trend six months ahead.Our MME prediction has,since April 2022,forecasted the possible occurrence of a third-year La Niña event.Overall,our MME prediction system offers better skill for both deterministic and probabilistic ENSO prediction than all participating models.These improvements are probably due to the complementary contributions of multiple models to provide additive predictive information,as well as the large ensemble size that covers a more reasonable uncertainty distribution.

Building Better Full Manganese‑Based Cathode Materialsfor Next‑Generation Lithium‑Ion Batteries

Lithium-manganese-oxides have been exploited as promising cathode materials for many years due to their environmental friendliness,resource abundance and low biotoxicity.Nevertheless,inevitable problems,such as Jahn-Teller distortion,manganese dissolution and phase transition,still frustrate researchers;thus,progress in full manganese-based cathode materials(FMCMs)has been relatively slow and limited in recent decades.Recently,with the fast growth of vehicle electrification and large-scale energy-storage grids,there has been an urgent demand to develop novel FMCMs again;actually,new waves of research based on FMCMs are being created.Herein,we systematically review the history of FMCMs,correctly describe their structures,evaluate the advantages and challenges,and discuss the resolution strategies and latest developments.Additionally,beyond FMCMs,a profound discussion of current controversial issues,such as oxygen redox reaction,voltage decay and voltage hysteresis in Li_(2)MnO_(3)-based cathode materials,is also presented.This review summarizes the effectively optimized approaches and offers a few new possible enhancement methods from the perspective of the electronic-coordination-crystal structure for building better FMCMs for next-generation lithium-ion batteries.

Estrogen receptorα-mediated signaling inhibits type Ⅰ interferon response to promote breast carcinogenesis

Estrogen receptorα(ERα)is an important driver and therapeutic target in∼70%of breast cancers.How ERαdrives breast carcinogenesis is not fully understood.In this study,we show that ERαis a negative regulator of type I interferon(IFN)response.Activation of ERαby its natural ligand estradiol inhibits IFN-β-induced transcription of downstream IFN-stimulated genes(ISGs),whereas ERαdeficiency or the stimulation with its antagonist fulvestrant has opposite effects.Mechanistically,ERαinduces the expression of the histone 2A variant H2A.Z to restrict the engagement of the IFN-stimulated gene factor 3(ISGF3)complex to the promoters of ISGs and also interacts with STAT2 to disrupt the assembly of the ISGF3 complex.These two events mutually lead to the inhibition of ISG transcription induced by type I IFNs.In a xenograft mouse model,fulvestrant enhances the ability of IFN-βto suppress ERα^(+)breast tumor growth.Consistently,clinical data analysis reveals that ERα^(+)breast cancer patients with higher levels of ISGs exhibit higher long-term survival rates.Taken together,our findings suggest that ERαinhibits type I IFN response via two distinct mechanisms to promote breast carcinogenesis.

The 2020–2021 prolonged La Niña evolution in the tropical Pacific

The evolution of sea surface temperature(SST)in the tropical Pacific during 2020–2021 indicates a second-year cooling in late 2021 again,following the 2020 La Niña event.Its physical explanations are still lacking,and there is a clear need to understand the underlying processes involved.Observational data and reanalysis products are used to describe the characteristics and spatiotemporal evolution of upper-ocean thermal anomalies;an intermediate coupled model(ICM)is also used to perform numerical experiments to confirm these observation-based inferences.The evolution of subsurface thermal anomalies is critically important to that of SST in the central-eastern equatorial Pacific;the effects of the former on the latter can be well represented by the temperature of subsurface waters entrained into the mixed layer(Te),a field that reflects a subsurface forcing on SST.The SST evolution is sensitively dependent on the intensities of the local effect associated with Te anomalies in the eastern equatorial Pacific and the remote effect associated with subsurface anomalies from the western Pacific.During early-and mid-2021,a competition was present between these local and remote effects associated with Te anomalies.When the remote warming effect dominates the local cooling effect,the cold SST condition in the east is likely to turn into neutral and warm conditions;otherwise,it tends to continue.In addition,the negative Te anomalies were sustained and enhanced by off-equatorial processes due to equatorial wave reflections at the eastern boundary associated with the 2020 La Niña event.The SST evolution in mid-2021 corresponded to a situation in which the warming effect associated with positive subsurface thermal anomalies from the west were not strong enough to counteract the local cooling effect associated with negative anomalies in the east.In due course,cold SST anomalies in the east developed again and the second-year cooling reoccurred in late 2021,with a turning point in June 2021.Modeling experiments support these arguments and indicate that the intensity of subsurface thermal effect on SST,as represented by Te anomalies,needs to be adequately depicted for coupled models to capture the 2021 second-year cooling conditions in the tropical Pacific.

Precise regulation of acid pretreatment for red mud SCR catalyst:Targeting on optimizing the acidity and reducibility

Red mud(RM),as an alkaline waste,was recently proved to be a promising substitute for the SCR catalyst.Dealkalization could improve the acidity and reducibility of red mud,which were critical for SCR reaction.However,the dealkalization effect depended on the reaction between acid solution and red mud.In this study,we realized the directional control of the chemical state of active sites through tuning the acid pretreatment(dealkalization)process.The pretreatment endpoint was controlled at pH values of 3–5 with diluted nitric acid.When the pH values of red mud were 3 and 5(CRM-3 and CRM-5),activated catalysts showed NOx conversion above 90%at 275℃–475℃.The high initial reaction rate,Ce^(3+)/(Ce^(3+)+Ce^(4+))ratio,and surface acidity accounted for the excellent SCR performance of CRM-5 catalyst.Meanwhile,more Fe^(3+) on the CRM-3 surface improved the NH_(3) adsorption.There was a strong interaction between Al and Fe in both CRM-5 and CRM-3 catalysts.DFT results showed that the adsorption capacity of the Al-O_(3)-Fe for NH_(3) and NO is stronger than that of Fe-O_(3)-Fe,which enhanced the NOx conversion of the catalyst.However,the almandine was formed in CRM-4,consumed part of Fe^(3+) and Al^(3+),and the interaction between Al and Fe was weakened.Also,deposited almandine on the catalyst surface covered the active sites,thus leading to lower NH_(3)-SCR activity.

Isatin hybrids and their anti-tuberculosis activity

Tuberculosis（TB） is one of the most common and even fatal infectious diseases known to mankind.Millions of new cases are reported every year over the world,and one-third of the world＇s population is potentially infected with mycobacteria tuberculosis（MTB）.Research to develop novel anti-TB drugs led to the identification of several isatin-based antimycobacterial agents,among which a number of potential candidates displayed excellent antimycobacterial activity and were found to be free of cytotoxicity.This review outlines the advances in the application of isatin hybrids as antimycobacterial agents and the critical aspects of design and structure-activity relationship of these derivatives.

Triggering a [2]rotaxane molecular shuttle through hydrogen sulfide

A novel chemically-controlled [2]rotaxane molecular shuttle was successfully designed and synthesized. A H_2 S-responsive bulk barrier was introduced between the two identical recognition stations of the [2]rotaxane to prevent dynamic shuttling of the macrocycle. Upon addition of H_2 S, the complete intramolecular cascade reaction occurs in a controllable manner, resulting in removal of the bulk barrier and the shuttling motion of the macrocycle between the two stations recovers.

A transformer-based coupled ocean-atmosphere model for ENSO studies

The El Nino-Southern Oscillation (ENSO) is the strongest interannual anomalies affecting weather and climate worldwide. As has been well recognized, ENSO originates from the coupling between the ocean and atmosphere in the tropical Pacific, characterized by a coherent evolution of subsurface temperature anomalies that profoundly impact sea surface temperature (SST) and surface wind fields.