Wavelet Multiview-Based Hybrid Deep Learning Model for Forecasting El Niño-Southern Oscillation Cycles

The El Niño-Southern Oscillation (ENSO) is a significant climate phenomenon with far-reaching impacts on global weather patterns, ecosystems, and economies. This study aims to enhance ENSO forecasting with the Extended Reconstruction Sea Surface Temperature v5 (ERSSTv5) climate model. The M-band discrete wavelet transforms (DWT) are utilized to capture multi-scale temporal and spatial features effectively. Long-short term memory (LSTM) autoencoders are also used to capture significant spatial and temporal patterns in sea surface temperature (SST) anomaly data. Deep learning techniques such as the convolutional neural networks (CNN) are used with non-image and image time series data. We also employ parallel computing in a various support vector regression (SVR) approximators to enhance accuracy. Preliminary results indicate that this hybrid model effectively identifies key precursors and patterns associated with El Niño events, surpassing traditional forecasting methods. Results of the hybrid model produce a correlation of 0.93 in 4-month lagged forecasting of the Oceanic Niño Index (ONI)—indicative of high success rate of the model. Future work will focus on evaluating the model’s performance using additional reanalysis datasets and other methods of deep learning to further refine its robustness and applicability. We propose wavelet-based deep learning models which have potential to shine a light on achieving United Nations’ 2030 Agenda for Sustainable Development’s goal 13: “Climate Action”, as an innovation with potential in improving time series image forecasting in all fields.

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.

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.

Simulated Indonesian Throughflow in Makassar Strait across the SODA3 products

The Indonesian Throughflow(ITF), which connects the tropical Pacific and Indian oceans, plays important roles in the inter-ocean water exchange and regional or even global climate variability. The Makassar Strait is the main inflow passage of the ITF, carrying about 77% of the total ITF volume transport. In this study, we analyze the simulated ITF in the Makassar Strait in the Simple Ocean Data Assimilation version 3(SODA3) datasets. A total of nine ensemble members of the SODA3 datasets, of which are driven by different surface forcings and bulk formulas, and with or without data assimilation, are used in this study. The annual mean water transports(i.e.,volume, heat and freshwater) are related to the combination of surface forcing and bulk formula, as well as whether data assimilation is employed. The phases of the seasonal and interannual variability in water transports cross the Makassar Strait, are basically consistent with each other among the SODA3 ensemble members. The interannual variability in Makassar Strait volume and heat transports are significantly correlated with El Ni?oSouthern Oscillation(ENSO) at time lags of-6 to 7 months. There is no statistically significant correlation between the freshwater transport and the ENSO. The Makassar Strait water transports are not significantly correlated with the Indian Ocean Dipole(IOD), which may attribute to model deficiency in simulating the propagation of semiannual Kelvin waves from the Indian Ocean to the Makassar Strait.

Salinity effect-induced ENSO amplitude modulation in association with the interdecadal Pacific Oscillation

A 110-year ensemble simulation of an ocean general circulation model(OGCM)was analyzed to identify the modulation of salinity interdecadal variability on El Niño-Southern Oscillation(ENSO)amplitude in the tropical Pacific during 1901-2010.The simulating results show that sea surface salinity(SSS)variation in the region exhibits notable and coherent interdecadal variability signal,which is closely associated with the Interdecadal Pacific Oscillation(IPO).As salinity increases or reduces,the SSS modulations on ENSO amplitude during its warm/cold events vary asymmetrically with positive/negative IPO phases.Physically,salinity interdecadal variability can enhance or reduce ENSO-related conditions in upper-ocean stratification,contributing noticeably to ENSO variability.Salinity anomalies associated with the mixed layer depth and barrier layer thickness can modulate ENSO amplitude during positive and negative IPO phases,resulting in the asymmetry of sea surface temperature(SST)anomaly in the tropical Pacific.During positive IPO phases,SSS interdecadal variability contributes positively to El Niño amplitude but negatively to La Niña amplitude by enhancing or reducing SSS interannual variability,and vice versa during negative IPO phases.Quantitatively,the results indicate that the modulation of the ENSO amplitude by the SSS interdecadal variability is 15%-28%during negative IPO phases and 30%-20%during positive IPO phases,respectively.Evidently,the SSS interdecadal variability associated with IPO and its modulation on ENSO amplitude in the tropical Pacific are among factors essentially contributing ENSO diversity.

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.

ENSO事件下赤道中东太平洋海温场非对称性特征

利用1950—2020年冬季HadISST逐月海面温度(sea surface temperature, SST)资料、SODAv2.2.4逐月SST和三维海洋流速同化资料以及NCEP/NCAR 2 m高度上的逐月气温(surface air temperature, SAT)资料,使用非对称合成差分析方法、海洋混合层热量收支诊断方法等,探究El Ni1o事件和La Ni1a事件下造成赤道东太平洋(E区:110°W~80°W,10°S~10°N)、赤道中太平洋(C区:160°E~170°W,10°S~10°N)SST异常场显著不同非对称性特征的可能海洋动力过程,分析ENSO事件非对称强迫下2 m高度上SAT异常场的非对称空间响应。结果表明:E区El Ni1o事件的强度显著强于La Ni1a事件,C区则相反。非线性动力学加热作用对E区和C区El Ni1o年和La Ni1a年SST异常场的非对称分量都起到了正反馈作用,是造成这两个区域SST异常场产生正、负非对称分量的主导动力因子。埃克曼输送作用不利于E区SST异常场正非对称分量的形成,但有利于C区SST异常场负非对称分量的形成。平均流、纬向平流和温跃层的非对称正反馈作用阻碍了C区SST异常场负非对称分量的形成。2 m高度上SAT异常场的非对称分布与SST异常场的非对称分布较为一致,但SAT异常场正、负非对称分量的显著范围明显减小,部分区域的非对称结果不显著。

Mathematical Analysis of the Jin-Neelin Model of El Niño-Southern-Oscillation

The Jin-Neelin model for the El Nio–Southern Oscillation(ENSO for short) is considered for which the authors establish existence and uniqueness of global solutions in time over an unbounded channel domain. The result is proved for initial data and forcing that are sufficiently small. The smallness conditions involve in particular key physical parameters of the model such as those that control the travel time of the equatorial waves and the strength of feedback due to vertical-shear currents and upwelling; central mechanisms in ENSO dynamics.From the mathematical view point, the system appears as the coupling of a linear shallow water system and a nonlinear heat equation. Because of the very different nature of the two components of the system, the authors find it convenient to prove the existence of solution by semi-discretization in time and utilization of a fractional step scheme. The main idea consists of handling the coupling between the oceanic and temperature components by dividing the time interval into small sub-intervals of length k and on each sub-interval to solve successively the oceanic component, using the temperature T calculated on the previous sub-interval, to then solve the sea-surface temperature(SST for short) equation on the current sub-interval. The passage to the limit as k tends to zero is ensured via a priori estimates derived under the aforementioned smallness conditions.

Enhanced Seasonal Predictability of Spring Soil Moisture over the Indo-China Peninsula for Eastern China Summer Precipitation under Non-ENSO Conditions

Seasonal prediction of summer precipitation over eastern China is closely linked to the East Asian monsoon circulation,which is largely affected by the El Niño-Southern Oscillation(ENSO).In this study,results show that spring soil moisture(SM)over the Indo-China peninsula(ICP)could be a reliable seasonal predictor for eastern China summer precipitation under non-ENSO conditions.When springtime SM anomalies are present over the ICP,they trigger a structured response in summertime precipitation over most of eastern China.The resultant south-to-north,tri-polar configuration of precipitation anomalies has a tendency to yield increased(decreased)precipitation in the Yangtze River basin and decreased(increased)in South and North China with a drier(wetter)spring soil condition in the ICP.The analyses show that ENSO exerts a powerful control on the East Asian circulation system in the ENSO-decaying summer.In the case of ENSO forcing,the seasonal predictability of the ICP spring SM for eastern China summer precipitation is suppressed.However,in the absence of the influence of ENSO sea surface temperature anomalies from the preceding winter,the SM anomalies over the ICP induce abnormal local heating and a consequent geopotential height response owing to its sustained control on local temperature,which could,in turn,lead to abnormal eastern China summer precipitation by affecting the East Asian summer monsoon circulation.The present findings provide a better understanding of the complexity of summer climate predictability over eastern China,which is of potential significance for improving the livelihood of the people.

Will the Historic Southeasterly Wind over the Equatorial Pacific in March 2022 Trigger a Third-year La Niña Event?

Based on the updates of the Climate Prediction Center and International Research Institute for Climate and Society(CPC/IRI)and the China Multi-Model Ensemble(CMME)El Niño-Southern Oscillation(ENSO)Outlook issued in April 2022,La Niña is favored to continue through the boreal summer and fall,indicating a high possibility of a three-year La Niña(2020-23).It would be the first three-year La Niña since the 1998-2001 event,which is the only observed three-year La Niña event since 1980.By examining the status of air-sea fields over the tropical Pacific in March 2022,it can be seen that while the thermocline depths were near average,the southeasterly wind stress was at its strongest since 1980.Here,based on a quaternary linear regression model that includes various relevant air-sea variables over the equatorial Pacific in March,we argue that the historic southeasterly winds over the equatorial Pacific are favorable for the emergence of the third-year La Niña,and both the anomalous easterly and southerly wind stress components are important and contribute~50%of the third-year La Niña growth,respectively.Additionally,the possible global climate impacts of this event are discussed.

The Subsurface and Surface Indian Ocean Dipoles and Their Association with ENSO in CMIP6 models

This study assesses the reproducibility of 31 historical simulations from 1850 to 2014 in the Coupled Model Intercomparison Project phase 6(CMIP6) for the subsurface(Sub-IOD) and surface Indian Ocean Dipole(IOD) and their association with El Ni?o-Southern Oscillation(ENSO). Most CMIP6 models can reproduce the leading east-west dipole oscillation mode of heat content anomalies in the tropical Indian Ocean(TIO) but largely overestimate the amplitude and the dominant period of the Sub-IOD. Associated with the much steeper west-to-east thermocline tilt of the TIO, the vertical coupling between the Sub-IOD and IOD is overly strong in most CMIP6 models compared to that in the Ocean Reanalysis System 4(ORAS4). Related to this, most models also show a much tighter association of Sub-IOD and IOD events with the canonical ENSO than observations. This explains the more(less) regular Sub-IOD and IOD events in autumn in those models with stronger(weaker) surface-subsurface coupling in TIO. Though all model simulations feature a consistently low bias regarding the percentage of the winter–spring Sub-IOD events co-occurring with a Central Pacific(CP) ENSO, the linkage between a westward-centered CP-ENSO and the Sub-IOD that occurs in winter–spring, independent of the IOD, is well reproduced.

大兴安岭南段小孤山锡锌矿床锡石U-Pb年龄、流体包裹体和H-O-S-Pb同位素特征

毛登-小孤山地区是大兴安岭南段锡多金属成矿带代表性矿区,由小孤山锡锌矿床和毛登锡钼铋多金属矿床组成。小孤山矿床锡石U-Pb Tera-Wasserburg谐和年龄为134.8±1.9Ma,表明其形成于早白垩世。该矿床成矿过程可划分为4个阶段:锡石-黄铁矿-石英-电气石阶段(Ⅰ阶段)、锡石-黄铜矿-闪锌矿-石英-萤石阶段(Ⅱ阶段)、闪锌矿-方铅矿-石英-萤石阶段(Ⅲ阶段)、黄铁矿-石英-方解石阶段(Ⅳ阶段)。小孤山矿床主要发育富液两相包裹体(WL型)、富气两相包裹体(WG型)及含子矿物包裹体(S型)。Ⅰ、Ⅱ和Ⅲ阶段均发育WL、WG和S型包裹体,Ⅳ阶段仅出现WL型包裹体。从Ⅰ至Ⅳ阶段流体包裹体均一温度/盐度分别为420-443℃/8.3%-52.0%NaCleqv、286-379℃/4.0%-40.2%NaCleqv、214-299℃/3.8%-36.1%NaCleqv、178-195℃/2.1%-3.3%NaCleqv,表明从早阶段到晚阶段成矿流体由高温高盐度向低温低盐度转化,且前三个阶段流体盐度波动大,暗示成矿流体发生了多次沸腾。矿床的δ18O水介于-2.6‰-11.0‰,δD介于-107‰--91‰,Ⅰ和Ⅱ阶段的成矿流体以岩浆水为主,Ⅲ阶段开始有大气降水的加入。硫化物的δ34SCDT值介于-3.3‰--0.6‰,206Pb/204Pb介于17.772-18.427,207Pb/204Pb介于15.482-15.679,208Pb/204Pb介于37.668-38.622,表明成矿物质来源于早白垩世花岗质岩浆。流体沸腾和降温是矿质沉淀的两种主要机制。

中西太平洋鲣鱼空间聚类特征及其与ENSO的关系

为了解在不同厄尔尼诺-南方涛动(ENSO)事件下中西太平洋鲣鱼(Katsuwonus pelamis)资源的变动规律,本研究根据中西太平洋渔业委员会(WCPFC)2008—2018年中西太平洋鲣鱼的生产数据,结合海洋尼诺指数(ONI),利用聚类分析和灰色关联分析,研究季时间尺度下鲣鱼的自由鱼群和随附鱼群的渔场空间特征及其与ENSO事件的关系。季尺度下渔场重心聚类分析表明,各簇所包含季度发生的异常气候事件具有一致性。拉尼娜时期,两种鱼群的主要渔场都有向西移动的趋势,厄尔尼诺时期则相反。在异常气候事件下,随附鱼群的迁移幅度小于自由鱼群,且随附鱼群渔场的经向分布更稳定。不同ENSO模态下,资源丰度的空间分布存在差异。对自由鱼群而言,在拉尼娜事件发生于第1、2季度时165°E以西海域的资源丰度最高,灰色关联度为0.650,在拉尼娜事件发生于第3、4季度时165°E—180°海域的资源丰度最高,灰色关联度为0.411,在厄尔尼诺时期,180°以东海域的资源丰度最高,灰色关联度为0.727。对随附鱼群而言,165°E以西海域及165°E—180°海域资源丰度最高时期为拉尼娜时期,灰色关联度分别为0.852和1.000,180°以东海域资源丰度最高时期为厄尔尼诺时期,灰色关联度为1.000。研究结果可用于气候变化背景下鲣鱼渔情的预报。

南昌市大气降水H-O稳定同位素特征及其水汽来源解析

南昌市位于长江流域中下游,濒临中国第一大淡水湖—鄱阳湖,水文网系发育。为了深入理解南昌市大气降水来源与路径,并为区域水循环研究提供基础数据,本研究于2015~2016年期间采集南昌市93个日降水事件样品,开展降水H-O稳定同位素特征及其影响因素研究,并试图阐明该区域大气降水水汽来源。结果表明:(1)降水δ^(18)O和δ^(2)H值变化范围较大,相对于其它季节春季偏正,不是单一气候因子的制约而是多种因子共同影响的结果;(2)建立的当地大气降水线方程为δ^(2)H=8.03δ^(18)O+12.1,H-O稳定同位素分馏处于相对平衡状态,为区域水循环研究提供可靠的参考线。氘盈余(d-excess)和HYSPLIT模型综合分析进一步表明:夏秋季降水多与东南和西南季风携带的太平洋和印度洋水汽有关,而冬春季降水来源广泛,涉及季风、西风带、极地气流及局地蒸发的水汽。本研究成果有助于完善中国南方大气湿度循环理论,对指导当地水资源管理、防洪减灾有重要的实际意义。

全球变暖背景下气候内部变率导致热带辐合带移动的不确定性

基于两套模式的大集合试验结果,评估了气候内部自然变率对热带辐合带(ITCZ,Intertropical convergence zone)未来南北移动的影响。研究发现,模式间ITCZ的移动差异源自中高纬度的外强迫模拟差异,而气候内部变率主要通过热带过程调控ITCZ的位置变化。在通用地球系统模式大集合(Community Earth System Model Large Ensemble,CESM-LE)试验中,厄尔尼诺-南方涛动(El Nino-Southern Oscillation,ENSO)振幅变化的自然变率会通过中等和极端厄尔尼诺降水的非线性信号调制ITCZ的移动幅度,而在MPI-GE(the Max Planck Institute Great Ensemble)试验中,ITCZ的位置变化主要与大西洋海温梯度信号异常有关,相较而言ENSO振幅对ITCZ的影响很有限。总体而言,全球变暖背景下由于内部自然变率引起的ITCZ南北移动不确定性幅度能解释未来预估模式间的差异约为20%,但对ITCZ移动的模拟不确定性有贡献。

辽东半岛顶端海域上升流长期变化特征及影响因素

利用回归分析、相关性分析等分析方法,对全球气候变暖背景下辽东半岛顶端海域上升流的变化特征及影响因素进行了研究。结果表明:夏季,辽东半岛顶端邻近海域上升流以38°52′N、120°55′E为中心,呈纺锤状分布于复州湾-辽东半岛顶端-北砣矶水道沿线海域,其位置较为固定。1988-2018年,海表温度上升流指数呈显著增加的变化趋势,其变化速率为0.27℃/10a,研究海域上升流显著增强,其中1998-2018年上升流增强尤为显著。在全球气候变暖背景下,渤海及北黄海部分海域净辐射通量的增加和夏季风场的减弱是研究海域上升流增强的两个影响因素。净辐射通量的增加和夏季风场的减弱分别有利于非上升流与上升流区的温差增大和底层冷水的上涌,进而使上升流现象增强。在长时间尺度上,ENSO(El Niño-Southern Oscillation)不会影响研究海域上升流强度的变化趋势,但在强厄尔尼诺发展阶段(1997年和2014年),ENSO可使研究海域纬向风(西风)增强,从而减弱研究海域上升流。

厄尔尼诺-南方涛动(ENSO)研究的战略部署与研究热点

厄尔尼诺—南方涛动(ENSO)影响着全球气候,被认为与众多全球灾害性天气事件有关。为了更好地了解ENSO研究的发展趋势及其对全球海洋事务的影响,本文对WCRP、GOOS和TPOS 2020等与ENSO研究相关的国际研究计划和各国家地区的ENSO研究战略情况进行梳理,并结合VOSviewer文献计量学方法进行分析,探讨ENSO研究的国际发展趋势及研究热点,以便为我国ENSO相关研究与决策提供参考。

福建省马尾松毛虫发生与ENSO事件的关系

以1971～1991年(反)厄尔尼诺事件、南方涛动指数及福建省马尾松毛虫发生程度的资料为基础,探讨它们之间的关系,揭示这种关系产生的内在机制,并建立福建省马尾松毛虫发生预测预报模型.结果表明:福建省马尾松毛虫发生与(反)厄尔尼诺事件年、南方涛动指数总和变动异常年有显著关联;所建立模型精度达83.33%,可以对马尾松毛虫发生、气候异常起监测作用.

厄尔尼诺及南方涛动对杉木生长影响的研究

通过对 2 0多年来 ENSO事件的发生与杉木人工林胸径生长关系的研究 ,探讨全球气候异常对林木生长动态的影响。结果表明 :厄尔尼诺及南方涛动对杉木人工林胸径生长存在显著影响 ( α=0 .1 0 )。以南方涛动为自变量 ,建立杉木人工林胸径生长模型 ,模拟精度达93.61 % ,为林木生长预测提供了新途径。

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.