El Nio/La Nia影响下北部湾海域浮游桡足类种类组成与多样性

以1998年1月至1999年5月对北部湾海域进行的4个航次生态环境综合调查的资料为基础,分析El Nio/La Nia期间北部湾四季浮游桡足类种类组成与多样性,并对其与气候及海洋水文的关系进行初步探讨。结果显示,调查期间共出现浮游桡足类122种,其中32种周年出现,以春(82种)、夏(84种)较多,秋(52种)、冬(67种)较少;四季共出现优势桡足类13种,以广温广盐类型占主导,除微刺哲水蚤(Canthocalanus pauper)外,其余12种为季节性优势种;冬、夏两季受El Nio影响较大,优势种以中型桡足类为主;秋、春季大型桡足类优势地位较高,受La Nia影响明显;北部湾浮游桡足类多样性较高。分析表明,夏季北部湾水温和盐度对浮游桡足类群落多样性有一定影响,但在其他季节,这种影响不明显。

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

Responses of the Southern Ocean mixed layer depth to the eastern and central Pacific El Niño events during austral winter

Based on the Ocean Reanalysis System version 5(ORAS5)and the fifth-generation reanalysis datasets derived from European Centre for Medium-Range Weather Forecasts(ERA5),we investigate the different impacts of the central Pacific(CP)El Niño and the eastern Pacific(EP)El Niño on the Southern Ocean(SO)mixed layer depth(MLD)during austral winter.The MLD response to the EP El Niño shows a dipole pattern in the South Pacific,namely the MLD dipole,which is the leading El Niño-induced MLD variability in the SO.The tropical Pacific warm sea surface temperature anomaly(SSTA)signal associated with the EP El Niño excites a Rossby wave train propagating southeastward and then enhances the Amundsen Sea low(ASL).This results in an anomalous cyclone over the Amundsen Sea.As a result,the anomalous southerly wind to the west of this anomalous cyclone advects colder and drier air into the southeast of New Zealand,leading to surface cooling through less total surface heat flux,especially surface sensible heat(SH)flux and latent heat(LH)flux,and thus contributing to the mix layer(ML)deepening.The east of the anomalous cyclone brings warmer and wetter air to the southwest of Chile,but the total heat flux anomaly shows no significant change.The warm air promotes the sea ice melting and maintains fresh water,which strengthens stratification.This results in a shallower MLD.During the CP El Niño,the response of MLD shows a separate negative MLD anomaly center in the central South Pacific.The Rossby wave train triggered by the warm SSTA in the central Pacific Ocean spreads to the Amundsen Sea,which weakens the ASL.Therefore,the anomalous anticyclone dominates the Amundsen Sea.Consequently,the anomalous northerly wind to the west of anomalous anticyclone advects warmer and wetter air into the central and southern Pacific,causing surface warming through increased SH,LH,and longwave radiation flux,and thus contributing to the ML shoaling.However,to the east of the anomalous anticyclone,there is no statistically significant impact on the MLD.

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.

Estimating the Yield Loss of Winter Wheat from Drought in the United States Southern Plains Region as Influenced by El Niño-Southern Oscillation (ENSO)

Wheat (Triticum aestivum L.) production is a major economic activity in most regional and rural areas in the Southern Plains, a semi-arid region of the United States. This region is vulnerable to drought and is projected to experience a drier climate in the future. Since the interannual variability in climate in this region is linked to an ocean-atmospheric phenomenon, called El Niño-Southern Oscillation (ENSO), droughts in this region may be associated with ENSO. Droughts that occur during the critical growth phases of wheat can be extremely costly. However, the losses due to an impending drought can be minimized through mitigation measures if it is predicted in advance. Predicting the yield loss from an imminent drought is crucial for stakeholders. One of the reliable ways for such prediction is using a plant physiology-based agricultural drought index, such as Agricultural Reference Index for Drought (ARID). This study developed ENSO phase-specific, ARID-based models for predicting the drought-induced yield loss for winter wheat in this region by accounting for its phenological phase-specific sensitivity to drought. The reasonable values of the drought sensitivity coefficients of the yield model for each ENSO phase (El Niño, La Niña, or Neutral) indicated that the yield models reflected reasonably well the phenomena of water stress decreasing the winter wheat yields in this region during different ENSO phases. The values of various goodness-of-fit measures used, including the Nash-Sutcliffe Index (0.54 to 0.67), the Willmott Index (0.82 to 0.89), and the percentage error (20 to 26), indicated that the yield models performed fairly well at predicting the ENSO phase-specific loss of wheat yields from drought. This yield model may be useful for predicting yield loss from drought and scheduling irrigation allocation based on the phenological phase-specific sensitivity to drought as impacted by ENSO.

El Niño-Southern Oscillation (ENSO) Variations and Climate Changes Worldwide

This investigation aims to study the El-Niño-Southern Oscillation (ENSO) events in these three phases: El Niño, La Niña, and neutral. Warm and cold events relate to the Spring/Summer seasons. This paper will search for connections between the ENSO events and climate anomalies worldwide. There is some speculation that those events would be necessary for the climate anomalies observed worldwide. After analyzing the data from the reports to the ENSO, it shows almost periodicity from 1950-2023. We emphasized the occurrence of El Niño two years, when it was most prominent, and the climate anomalies (following NOAA maps), 2015 and 2023. The results indicated that the observed climate anomalies couldn’t be linked to the abnormal events observed. The worldwide temperatures in those years enhanced mostly in 2023. It shows an abnormal behavior compared with all the years scrutinized and analyzed since the records began. Therefore, there must be unknown factors beyond ENSO that rule the worldwide temperatures and the climate anomalies observed.

基于时空综合分型的El Niňo事件对中国东部降水的影响差异

基于1961—2022年中国高分辨率降水格点资料、合成分析和经验正交函数分解方法,揭示了时空综合分型得到的生命史较长-异常中心位置偏东的低频-东部(LF-EP)型和生命史较短-异常中心位置偏西的准两年-中部(QB-CP)型El Niňo事件对中国东部降水的不同影响。结果表明,LF-EP型事件对降水的影响显著且稳定:自发展年秋季到衰减年夏季长达近4个季节,长江以南区域降水持续地显著偏多,且异常雨带中心自衰减年春季起逐步北抬。QB-CP型事件发生时降水异常特征变化更加复杂多变:发展年夏秋季其空间分布与LF-EP型事件中的特征大致相反,长江以南区域降水整体偏少,冬季开始长江以南逐渐有正异常降水出现,且春季以后异常雨带表现出逐渐南退特征,至衰减年夏季发展为华北-长江中下游-华南地区降水异常“正-负-正”分布。进一步通过比较不同类型事件中大尺度水汽输送的差异探讨了其影响不同的可能机制,发现由海温异常纬向位置差异导致的西太平洋区域大气环流直接响应以及衍生模态响应差异是造成中国东部降水异常空间分布特征差异的重要原因。同时,两类时空事件持续性和转相时间的差异也会使得对降水影响的时间尺度出现差别。

Understanding the Low Predictability of the 2015/16 El Niño Event Based on a Deep Learning Model

The 2015/16 El Niño event ranks among the top three of the last 100 years in terms of intensity,but most dynamical models had a relatively low prediction skill for this event before the summer months.Therefore,the attribution of this particular event can help us to understand the cause of super El Niño–Southern Oscillation events and how to forecast them skillfully.The present study applies attribute methods based on a deep learning model to study the key factors related to the formation of this event.A deep learning model is trained using historical simulations from 21 CMIP6 models to predict the Niño-3.4 index.The integrated gradient method is then used to identify the key signals in the North Pacific that determine the evolution of the Niño-3.4 index.These crucial signals are then masked in the initial conditions to verify their roles in the prediction.In addition to confirming the key signals inducing the super El Niño event revealed in previous attribution studies,we identify the combined contribution of the tropical North Atlantic and the South Pacific oceans to the evolution and intensity of this event,emphasizing the crucial role of the interactions among them and the North Pacific.This approach is also applied to other El Niño events,revealing several new precursor signals.This study suggests that the deep learning method is useful in attributing the key factors inducing extreme tropical climate events.

Impacts of central-Pacific El Niño and physical drivers on eastern Pacific bigeye tuna

Bigeye tuna Thunnus obesus is an important migratory species that forages deeply,and El Niño events highly influence its distribution in the eastern Pacific Ocean.While sea surface temperature is widely recognized as the main factor affecting bigeye tuna(BET)distribution during El Niño events,the roles of different types of El Niño and subsurface oceanic signals,such as ocean heat content and mixed layer depth,remain unclear.We conducted A spatial-temporal analysis to investigate the relationship among BET distribution,El Niño events,and the underlying oceanic signals to address this knowledge gap.We used monthly purse seine fisheries data of BET in the eastern tropical Pacific Ocean(ETPO)from 1994 to 2012 and extracted the central-Pacific El Niño(CPEN)indices based on Niño 3 and Niño 4indexes.Furthermore,we employed Explainable Artificial Intelligence(XAI)models to identify the main patterns and feature importance of the six environmental variables and used information flow analysis to determine the causality between the selected factors and BET distribution.Finally,we analyzed Argo datasets to calculate the vertical,horizontal,and zonal mean temperature differences during CPEN and normal years to clarify the oceanic thermodynamic structure differences between the two types of years.Our findings reveal that BET distribution during the CPEN years is mainly driven by advection feedback of subsurface warmer thermal signals and vertically warmer habitats in the CPEN domain area,especially in high-yield fishing areas.The high frequency of CPEN events will likely lead to the westward shift of fisheries centers.

El Niño事件发展期对中国东部夏季极端降水的影响

利用1961−2020年的再分析资料和中国台站观测降水数据集,研究了东部型El Niño事件发展期夏季对中国夏季极端降水的影响.结果表明,东部型El Niño在发展期夏季对中国极端降水的影响主要表现在中国东部地区,造成华北和江南地区极端降水减少,江淮地区极端降水显著增多.进一步分析其中的物理过程发现,当东部型El Niño事件处于发展期夏季时,赤道东太平洋出现显著的海表面温度(sea surface temperature,SST)暖异常,西太平洋区域表现为冷异常,导致反气旋性环流异常.同时,西北太平洋区域存在SST暖异常,对应气旋性环流异常.异常的SST分布激发了“正-负-正(+−+)”的东亚-太平洋型(East Asia-Pacific,EAP)波列异常,对应着“负-正-负(−+−)”的降水配置.在2个异常环流的交汇处有显著的辐合上升运动,为江淮地区带去了充足的水汽.而华北地区主要受到反气旋性环流和蒙古高压的共同控制,并受到来自高纬度地区的异常西北风影响,存在显著的辐散下沉运动,降水的动力条件不足.并且,在东部型El Niño事件发展期夏季,西太平洋副热带高压位置异常偏东,不利于江南地区降水的发生及水汽的输送,进一步造成江南地区极端降水减少.以上结果显示东部型El Niño事件在其发展期夏季对中国极端降水存在重要的影响,为区域极端气候预测提供了理论依据.

The El Niño-Southern Oscillation (ENSO) Effects on Cowpea and Winter Wheat Yields in the Semi-Arid Region of the Southern US

Information is limited on the effects of climate variability on cowpea (Vigna unguiculata L.) and winter wheat (Triticum aestivum L.) yields in the semiarid region of the southern US. Using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model and weather data spanning 81 years, we assessed the impact of El Niño-Southern Oscillation (ENSO) on the grain yields of these crops in the Llano Estacado region of the southern US as affected by cowpea and wheat planting dates and N application rate. Simulated results showed that the El Niño phase of ENSO produced about 30% more yields of mono-cropped cowpea than those produced under the La Niña phase, especially with the cowpeas planted in July. The cowpea yields under El Niño were about 10% more than the 81-year average normal yield, whereas those under La Niña were about 20% less. At the N rates of 0, 50, and 100 kg·ha−1, regardless of wheat planting dates, the El Niño years produced, respectively, about 8%, 40%, and 60% higher wheat yields than those produced in the La Niña years, and about 5%, 20%, and 27% more than the 81-year average normal yield. In the La Niña years, the wheat yields at 0, 50, and 100 kg N ha−1 were, respectively, about 5%, 15%, and 20% less than the normal yield with similar N levels. The impact of ENSO on wheat yields under cowpea-wheat double-cropping systems was significant, especially for the wheat crops planted on October 15 (October 30) or later following the cowpea crops planted in June (July). At zero N, the mono-cropped wheat yields were not impacted by ENSO due to N limitation. However, the double-cropped wheat yields were impacted by ENSO even when no N fertilizer was applied due to high soil N status caused by N transfer from cowpea stover residues and roots. Results indicated that management strategies need to be attentive to ENSO forecasts and adjust potential planting dates and N application rates with the ENSO phase to avert risks of crop failure and economic loss.

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。

The Drought of Amazonia in 2023-2024

The Amazon basin has experienced an extreme drought that started in the austral summer of 2022-23 and extends into 2024. This drought started earlier than other previous droughts. Although some rain fell during the austral summer, totals remained below average. Higher temperatures during austral winter and spring 2023, which affected most of Central South America, then aggravated drought conditions. This coincided with an intense El Niño and abnormally warm tropical North Atlantic Ocean temperatures since mid-2023. Decreased rainfall across the Amazon basin, negative anomalies in evapotranspiration (derived from latent heat) and soil moisture indicators, as well as increased temperatures during the dry-to-wet transition season, September-October-November (SON) 2023, combined to delay the onset of the wet season in the hydrological year 2023-24 by nearly two months and caused it to be uncharacteristically weak. SON 2023 registered a precipitation deficit of the order of 50 to 100 mm/month, and temperatures +3˚C higher than usual in Amazonia, leading to reduced evapotranspiration and soil moisture indicators. These processes, in turn, determined an exceptionally late onset and a lengthening of the dry season, affecting the 2023-2024 hydrological year. These changes were aggravated by a heat wave from June to December 2023. Drought-heat compound events and their consequences are the most critical natural threats to society. River levels reached record lows, or dried up completely, affecting Amazonian ecosystems. Increased risk of wildfires is another concern exacerbated by these conditions.

东部型El Niño事件发展期秋季对中国极端降水的影响

利用1961-2020年中国地面降水逐日数据集和NCEP/NCAR逐月再分析资料,采用相关及合成分析等方法分析了东部型El Niño事件发展期秋季对同期我国极端降水的可能影响及物理过程。结果表明:东部型El Niño事件在发展期秋季对华中和华南地区的极端秋季降水有显著的影响,造成华南地区秋季极端降水增多而华中地区减少。进一步分析了造成这种影响的物理过程发现,当东部型El Niño事件处于发展期的秋季时,中东太平洋表现为显著的正海温异常,热带西太平洋及我国南海为负的海温异常。相应地,热带中东太平洋表现为异常的上升气流,西太平洋为异常的下沉气流,在华南地区表现为异常的辐合上升,为降水创造了有利的动力条件;同时,异常海温进一步对西北太平洋副热带高压(以下简称西太副高)位置产生影响,造成西太副高异常偏西,在南海到西太平洋地区表现为反气旋性环流异常,意味着西南气流的水汽输送增强,这促进了华南地区极端降水的发生。而在华中地区则表现为异常的偏北风和水汽辐散,不利于降水的生成。以上结果对认识我国东部地区的极端降水事件的物理机理提供了科学线索。

Cross-Correlation between Global Temperature and Atmospheric CO2 with a Temperature-Leading Time Lag

The temperature change and rate of CO2 change are correlated with a time lag, as reported in a previous paper. The correlation was investigated by calculating a correlation coefficient r of these changes for selected ENSO events in this study. Annual periodical increases and decreases in the CO2 concentration were considered, with a regular pattern of minimum values in August and maximum values in May each year. An increased deviation in CO2 and temperature was found in response to the occurrence of El Niño, but the increase in CO2 lagged behind the change in temperature by 5 months. This pattern was not observed for La Niña events. An increase in global CO2 emissions and a subsequent increase in global temperature proposed by IPCC were not observed, but an increase in global temperature, an increase in soil respiration, and a subsequent increase in global CO2 emissions were noticed. This natural process can be clearly detected during periods of increasing temperature specifically during El Niño events. The results cast strong doubts that anthropogenic CO2 is the cause of global warming.

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.

El Nino/La Nina事件对许昌气候的影响

根据1971～2009年期间发生的El Nino/La Nina事件和许昌市气象资料,利用统计分析的方法分析了1971年以来许昌气温、降水、旱涝灾害与El Nino/La Nina事件之间的关系,初步揭示了El Nino/La Nina事件对许昌气候的影响。结果表明,许昌市39年来温度和降水均有升高的趋势;厄尔尼诺年平均气温比正常年份高0.1℃,平均降水量比正常年份少34mm,厄尔尼诺次年降水增加,降水量多于正常年份35.3mm;拉尼娜年气温上升且波动较大,拉尼娜发生年平均气温比正常年份高0.3℃,拉尼娜年降水量多于正常年份2.3mm,拉尼娜次年降水量少于正常年份15.5mm;从气温来讲,拉尼娜年许昌气温的上升幅度要大于厄尔尼诺年气温的上升幅度。从降水量上来讲,厄尔尼诺年对许昌降水量的影响度要大于拉尼娜年对降水的影响度。El/La事件对许昌市旱涝灾害影响显著,拉尼娜年发生大涝灾害的几率较大。

El Niño事件消亡期亚洲季风区对流层上层经向热力差异的演变

采用NOAA1979—2019年的南方涛动SOI指数、GPCC降水数据和ERA5气温数据探究El Niño事件消亡期亚洲季风区对流层上层海陆热力差异的演变特征。El Niño事件衰减期按所处季节可分为春季型、秋季型和冬季型,其中冬季型衰减对季风区对流层上层经向热力差(TIup)的贡献最大,且热力差异在冬季达到最大;春季型衰减会使伴随长江中下游夏季降水增加,秋季型衰减会使长江中下游夏季降水减少,冬季型衰减会使华北大部分地区夏季降水增多,只有华南、西南及东北部分地区降水略有减小。

Understanding the Development of the 2018/19 Central Pacific El Niño

A central Pacific(CP)El Niño event occurred in 2018/19.Previous studies have shown that different mechanisms are responsible for different subtypes of CP El Niño events(CP-I El Niño and CP-II El Niño).By comparing the evolutions of surface winds,ocean temperatures,and heat budgets of the CP-I El Niño,CP-II El Niño,and 2018/19 El Niño,it is illustrated that the subtropical westerly anomalies in the North Pacific,which led to anomalous convergence of Ekman flow and surface warming in the central equatorial Pacific,played an important role in the 2018/19 El Niño event as well as in the CP-II El Niño.Although the off-equatorial forcing played a vital role,it is found that the equatorial forcing acted as a driving(damping)term in boreal spring(summer)of the 2018/19 El Niño.The 2018/19 El Niño provides a timely and vivid example that helps illustrate the proposed mechanism of the CP El Niño,which could be leveraged to improve El Niño predictability.

不同Niño指数对El Niño事件响应的差异性分析

ENSO事件是发生在热带太平洋地区、具有最强年际变化的全球尺度振荡信号。一方面直接使得赤道太平洋地区的天气出现异常,另一方面还会以遥相关的形式影响热带太平洋以外的地区,甚至影响了全球的天气变化,选取能够表明其特征的指标十分重要。不同类型El Niño事件对于各类Niño指数的响应也是不同的,东部型El Niño事件在Niño1 + 2指数、Niño3指数、Niño3.4指数的响应较为明显,在Niño4指数的响应较弱;而中部型El Niño事件相比较来说在Niño4指数和Niño3.4指数的响应较为明显,其中Niño3.4指数对于两类El Niño事件的响应表现较为突出。