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ENSO as an Integrating Concept in Earth Science
Abstract
The El Niño–Southern Oscillation (ENSO) cycle of alternating warm El Niño and cold La Niña events is the dominant year-to-year
climate signal on Earth. ENSO originates in the tropical Pacific through interactions between the ocean and the atmosphere,
but its environmental and socioeconomic impacts are felt worldwide. Spurred on by the powerful 1997–1998 El Niño, efforts
to understand the causes and consequences of ENSO have greatly expanded in the past few years. These efforts reveal the breadth
of ENSO's influence on the Earth system and the potential to exploit its predictability for societal benefit. However, many
intertwined issues regarding ENSO dynamics, impacts, forecasting, and applications remain unresolved. Research to address
these issues will not only lead to progress across a broad range of scientific disciplines but also provide an opportunity
to educate the public and policy makers about the importance of climate variability and change in the modern world.
... The El Niño-Southern Oscillation (ENSO) is the most significant source of interannual climate variability, originating from large-scale coupled interactions between the ocean and atmosphere in the tropical Pacific. ENSO has received significant scientific attention due to its far-reaching impacts on global climate (McPhaden et al., 2006;Timmermann et al., 2018;Wallace et al., 1998). The rapid growth of ENSO events is largely attributed to positive ocean-atmosphere feedback, known as the Bjerknes feedback, in the equatorial Pacific, where a weakening of the zonal sea surface temperature (SST) gradient drives westerly wind anomalies, further reducing the SST gradient and amplifying the system (Bjerknes, 1969). ...
... The upper ocean heat content (OHC) is a valuable precursor for ENSO SST development, as the accumulation of the warm water usually leads SST variations by several months (McPhaden et al., 2006;Meinen & McPhaden, 2000;Zhang et al., 2019). Previous studies have shown that El Niño events can be predicted 6-9 months in advance, primarily due to the slow exchange of OHC between the equatorial and off-equatorial Pacific Ocean (Cane & Zebiak, 1985;Wyrtki, 1985;Zebiak, 1989). ...
... Based on the recharge oscillator theory (Jin, 1997;Meinen & McPhaden, 2000), the precondition of oceanic recharged state (i.e., the buildup of subsurface warm water), plays a crucial role in the subsequent development of El Niño events. In particular, the oceanic recharge state around February has been closely linked to the amplitude of the ensuing El Niño (e.g., Lai et al., 2015;McPhaden, 1999;McPhaden et al., 2006;Xuan et al., 2022). To investigate the potential relationship between the Pacific oceanic recharge state and the timing of El Niño onset, the temporal evolution of OHC anomalies during early-and late-onset El Niño events is displayed in Figure 2a. ...
El Niño is generally phase‐locked to the boreal winter but displays significant variability in its onset timing, contributing to its diverse climate impacts. The physical mechanisms driving this variability remain inadequately understood. This study demonstrates that onset of El Niño events can occur over a broad range of months from March to September, with its onset timing closely linked to the precondition of oceanic recharged state and the occurrence of westerly wind bursts (WWBs) in the preceding spring. A stronger recharged state and increased frequency of WWBs promote earlier onset by efficiently transporting warm water to the equatorial eastern Pacific. Supporting evidence from MIROC6 simulations and a conceptual model underscores the crucial roles of both the recharged state and WWBs in determining the timing of El Niño onset. These results enhance our understanding of El Niño dynamics and hold important implications for seasonal climate prediction.
... El fenómeno conocido como El Niño-Oscilación Sur (ENOS) se refiere a un ciclo climático caracterizado por variaciones periódicas de la temperatura superficial del mar y de la presión atmosférica en el océano Pacífico ecuatorial. Este fenómeno incluye las fases de El Niño, La Niña y la Oscilación del Sur, impactando significativamente en el clima global (McPhaden et al., 2006). ...
... En contraste, La Niña representa condiciones más frías que lo normal, que a menudo conllevan efectos opuestos, como sequías en el sur de América y lluvias intensas en el Pacífico occidental. La fase neutral se refiere a las condiciones 'normales' que no se inclinan hacia ninguno de los extremos de temperatura (Cai et al., 2020;McPhaden et al., 2006). ...
The hydrological regime of Rapa Nui was modeled to assess the influence of the El Niño–Southern Oscillation (ENSO) on the island's water availability. A detailed review of conceptual hydrological models led to the selection and implementation of TOPMODEL in Matlab-Simulink. The model was applied to the Hanga Roa watershed using hydroclimatological and geospatial data from the 1970–2023 period.
Simulations evaluated the behavior of variables such as precipitation, groundwater recharge, runoff, and potential evaporation under different ENSO phases. Hydrological deficits were observed during both La Niña and El Niño events, suggesting a complex system response to interannual climate variability. La Niña tended to reduce precipitation and recharge during winter, while some El Niño events were also associated with dry conditions.
The model was adapted for long-term simulations through parameter calibration based on local conditions. Despite limitations such as limited observational data and the assumption of spatial homogeneity, the results support the hypothesis that ENSO affects the island's hydrological regime. The findings highlight the need to account for climate variability in water resource management strategies for vulnerable island environments like Rapa Nui.
... ENSO 是地球上最为显著、重要的气候现象，驱动着全球气候变率 (Philander et al., 1984;McPhaden et al., 2006;Ropelewski and Halpert, 1987) (Eisenman et al., 2005;Vecchi et al., 2006;Alexander et al., 2002;Lau and Nath, 1994;Klein et al., 1999) Guilyardi et al., 2003;Luo et al., 2003;Luo et al., 2005b) (Madec et al., 1998)，并网格采用 ORCA2 (Madec and Imbard, 1996) 等, 2020;He et al., 2023;Luo et al., 2008) (Luo et al., 2005a;Pacanowski, 1987 Kumar and Hoerling, 2000)。受限有限的计算资源，Hydra-SINTEX 大气分量个数设定为 ...
气候变率很大程度上受到海气相互作用的影响，然而大气内部信号多大程度上影响气候变率，尤其是在海表温度的变率尚待研究。本文以标准耦合模式（即SINTEX-F）为基础开发新的同一大气模式分量交互式集合耦合模式（即Hydra-SINTEX），从而尽可能客观、科学地滤去大气内部信号，进而通过对比标准耦合模式（控制试验）和同一大气模式分量交互式集合模式集合平均（控制试验）结果来分析纯大气内部信号对气候变率的影响。本文首先明确大气内部信号的分布并量化外强迫信号与大气内部信号的相对重要性，评估纯大气内部信号对气候系统平均态和气候变率的影响，并着重以大气内部信号对海表温度变率的影响为例，挑选海气耦合相对较强的东印度洋地区（印度洋偶极子关键区）和海气耦合相对较弱的北太平洋副热带地区，探讨纯大气内部信号对热带和中纬度地区海表温度变率的影响及其可能物理机制。研究结果表明：
（1）大气内部信号的空间分布与大气内部信号和外部强迫的相对重要性具有相当的不均一性。从中高纬度相较低纬度地区，大气内部信号和大气内部信号相对外部强迫对气候变率的影响更强。从低层至高层大气的垂直分布上看，大气内部信号和大气内部信号相对外部强迫重要性呈现为热带地区逐渐由弱变强，而中纬度地区呈现为逐渐减弱的特征。
（2）降水，2米气温，海表温度，海表盐度的气候态和气候变率在SINTEX-F中模拟能力良好。去除大气内部信号后，降水，2米气温，海表温度，海表盐度气候态差异不明显，然而其气候变率大大减小，且大气内部信号对不同空间区域、变量的影响存在差异。
（3）去除大气内部信号后，东印度洋SST变率相关的印度洋偶极子指数变率和谱振幅显著降低。印度洋偶极子的强度和事件间离散度显著减弱，并伴随着印度洋偶极子模态非对称性的减弱。然而印度洋偶极子事件的季节锁相现象未受大气内部信号的影响，秋季仍按是印度洋偶极子事件的成熟期。
（4）pIOD和nIOD事件的混合层收支分析表明，线性平流项促进混合层温度倾向的发展，而非线性平流项促进pIOD事件发展，却阻碍nIOD事件发展。去除大气内部信号后，混合层温度倾向项和线性平流项减少48~58%，非线性平流项几乎完全去除，并伴随IOD事件不对称性的降低。此外pIOD和nIOD事件中各项事件间离散度表明SINTEX-F中pIOD事件的混合层温度倾向项的离散度略大于nIOD事件。去除大气内部信号后，混合层温度倾向项离散度减少约60~67%，且pIOD和nIOD事件间离散度差异不大。
（5）去除大气内部信号后，经由中纬度大气过程（即PNA作用）和ENSO遥相关作用对副热带北太平洋海温变率的影响显著减弱且大小类似。然而不同ENSO或PNA位相下的对海温变率的影响存在差异，其中纯厄尔尼诺遥相关作用相较纯拉尼娜遥相关作用及其纯PNA负位相相较纯PNA正位相减弱得更强，揭示大气内部信号在不同ENSO和PNA相位下对SST变率的影响是非线性的。
（6）北太平洋副热带地区的混合层热收支分析表明纯厄尔尼诺事件和纯PNA正事件下的负混合层温度倾向来源于线性V平流项和线性W平流项。去除大气内部信号后，线性V平流项的减少程度在纯厄尔尼诺事件显著高于纯PNA正事件。而表现正混合层温度倾向的纯拉尼娜事件和纯PNA负事件中，纯拉尼娜事件下海温异常的发展归咎为线性W平流项和地表热通量项，纯PNA负事件则归咎为线性V平流项。去除大气内部信号后，各项强度减弱。此外各项离散度表明SINTEX-F中纯ENSO和纯PNA事件下混合层温度倾向离散度大值在同一水平。去除大气内部信号后，混合层温度倾向离散度显著减弱，但不同事件下各个收支项存在差异，说明大气内部信号的影响具有非线性的特点。
本研究成果丰富了我们对大气内部信号影响气候变率，尤其是海温变率的理解，这对未来提升气候预测能力有着较好的指导意义。
... El Niño-Southern Oscillation (ENSO) and the Atlantic Niño/Niña are the dominant interannual modes in the equatorial Pacific and Atlantic, respectively, driving pronounced influences in global climate Lubbecke et al., 2018;McPhaden et al., 2006;Philander et al., 1984;Richter & Tokinaga, 2021;Xie & Carton, 2004). Development of these two modes is mainly facilitated by the Bjerknes feedback (Bjerknes, 1969;Zebiak, 1993), with ENSO typically peaking in boreal winter while the Atlantic Niño/Niña in boreal summer (June, July, and August; JJA). ...
Plain Language Summary
In the 21st century, variability of the Pacific El Niño‐Southern Oscillation (ENSO) and the Atlantic Niño/Niña is projected to respond oppositely, with an increase for the former while a decrease for the latter. In this study, we find a weakening of the Atlantic Meridional Overturning Circulation (AMOC) under greenhouse warming contributes to such opposite responses via modulating the equatorial mean climate and thus the Bjerknes feedback. On one hand, the weakened AMOC induces a subsurface cooling in the western Pacific in contrast to an intense subsurface warming over the entire equatorial Atlantic, leading to a strengthened oceanic stratification in the Pacific, in comparison to an insignificantly enhancement in the Atlantic. On the other hand, the weakened AMOC contributes to a Niño‐like sea surface temperature warming in both basins, which shifts the Pacific deep convection eastward, while barely influences the Atlantic northern‐hemisphere‐located deep convection. The above differentials in change of oceanic stratification and deep convection contribute to opposite responses of ENSO and the Atlantic Niño/Niña to greenhouse warming.
... The El Niño-Southern Oscillation (ENSO) is the major interannual oscillation in the tropical Pacific (McPhaden et al., 2006;Timmermann et al., 2018). It arises from anomalous warming in the eastern tropical Pacific surface, which is amplified by oceanic zonal circulation driven by eastward wind-stress anomalies, a process known as the Bjerknes feedback (Bjerknes, 1969;Wyrtki, 1975). ...
Numerical experiments from phase II of the Ocean Model Intercomparison Project (OMIP2) generally underestimate the asymmetric temperature response to interannual changes in the wind‐stress over the equatorial western Pacific subsurface. Despite the knowledge that such a bias may be directly behind the general lack of asymmetry in model‐simulated El Niño‐Southern Oscillation (ENSO), its causes remain unknown. Here we report that a weaker response in the zonal currents to wind forcing in these models results in a biased response in the vertical motion which in turn causes weaker asymmetric temperature responses through the contribution of the vertical motion to the advective heating (dynamic heating). This finding underscores the critical importance of accurately modeling the zonal currents—a previously less noticed element in the modeling effort—to better capture the asymmetric responses in the tropical western Pacific to external wind forcing and thereby improving simulations of ENSO by coupled climate models.
... The El Niño-Southern oscillation (ENSO) is the primary mode of interannual variability within the climate system and whether El Niño (warm) or La Niña (cool) conditions develop each year is of significant scientific and societal interest. As a strongly coupled air-sea phenomenon which peaks in boreal winter, ENSO events drive a large-scale reorganisation of the entire tropical climate and influence the mid-latitudes through extratropical teleconnections (Horel and Wallace 1981, McPhaden et al 2006, Deser et al 2017, Ayarzagüena et al 2018, Timmermann et al 2018, Scaife et al 2024. In addition to affecting the climate in many regions (e.g. ...
Interannual forecasts provide skilful predictions of El Niño-Southern oscillation (ENSO) up to a year in advance, however our understanding of what drives the ensemble skill and diversity of outcomes across members is limited. Using a fully coupled ocean–atmosphere ensemble forecasting system, we investigate the causality of regional perturbations on the evolution of ENSO at interannual timescales. Using forecasts initialised on 1 November 2009, transplanting more realistic cooler conditions in the South Pacific across ensemble members on 1 January 2010 significantly cools the resulting 2010/2011 winter ENSO one year later. The imposed perturbations migrate equatorward via wind–evaporation–sea surface temperature feedback and significantly alter tropical zonal gradients during late spring and summer. This drives the ensemble towards La Niña conditions, in line with observations. Repeating the experiment with warmer South Pacific conditions, results in the reverse signal and warms ENSO one year later. Across the experiments we find an almost four-fold increase in probability of La Niña and a three-fold decrease in probability of El Niño, demonstrating that long lead regional perturbations can systematically tip the climate system between ENSO states. Predicted surface conditions are significantly impacted across many parts of the world and the forecast global annual mean surface temperature for 2010 is significantly cooled, resulting in better agreement with observations. Our results demonstrate sensitivity of ENSO evolution and the global climate system to specific regional perturbations and provide new insights for interannual climate prediction.
... The El Niño Southern Oscillation (ENSO) is the most important climate phenomenon through ocean-atmosphere interaction over the equatorial Pacific, early illuminated by Bjerknes 1 and Wyrtki 2 , which influences global climate patterns, ecosystem, agriculture, and human society [3][4][5][6] . ENSO is characterized by its two-phase oscillation between El Niño and La Niña events, recurring with a periodicity of 2-7 years. ...
... Wind-generated waves play an important role in ocean circulation and global environment systems through redistribution of air-sea energy and momentum fluxes at the upper ocean and lower atmosphere (Babanin, 2023;Casas-Prat et al., 2024). As the most prominent climate mode, the El Niño-Southern Oscillation (ENSO), originating from coupled ocean-atmosphere processes in the tropical Pacific, can reorganize the global weather and climate with far-reaching social and economic impacts (McPhaden et al., 2006;Timmermann et al., 2018). During El Niño winters, the warmer sea surface temperature (SST) in the central and eastern Pacific can strengthen extratropical cyclones (ETCs) in the North Pacific and shift their tracks southward by modulating the atmospheric baroclinicity via atmospheric teleconnections (Eichler & Higgins, 2006;M. ...
Plain Language Summary
Multimodal seas, comprising independent wave systems of distinct origins, produce a complex wave climate with strong spatial variations around the Pacific Islands. The El Niño‐Southern Oscillation (ENSO) significantly affects ocean conditions and weathers across the Pacific. In‐depth understanding of localized ENSO impacts on ocean waves around islands, like Hawaii, is lacking. Here we analyzed 41 years of high‐resolution model wave data to understand how ENSO influences wave patterns across the Hawaiian Islands. The north and west‐facing shores exposed to northwest swells experience the largest interannual variation, with increases in amplitude and frequency of large events during El Niño winters. While the trade wind waves show moderate correlation with ENSO, seas mainly driven by local winds, show little variation between El Niño and La Niña phases. These findings underscore the importance of high‐resolution wave data in revealing various levels of ENSO influence from shore to shore. Based on the ENSO‐wave connection, we develop a semi‐empirical model to reconstruct seasonal wave statistics as a function of the ENSO index with promising results for regions experiencing hazardous winter swells. The semi‐empirical wave model can predict severe wave conditions seasons in advance to improve coastal safety and help inform decision‐making for coastal management.
... El Niño-Southern Oscillation (ENSO) is the strongest interannual climate variability on our planet 1,2 . It exerts strong impacts on regional climate and society worldwide [3][4][5] through atmospheric teleconnection 6 . ...
Improving the prediction skill of El Niño-Southern Oscillation (ENSO) is of critical importance for society. Over the past half-century, significant improvements have been made in ENSO prediction. Recent studies have shown that deep learning (DL) models can substantially improve the prediction skill of ENSO compared to individual dynamical models. However, effectively integrating the strengths of both DL and dynamical models to further improve ENSO prediction skill remains a critical topic for in-depth investigations. Here, we show that these DL forecasts, including those using the Convolutional Neural Networks and 3D-Geoformer, offer comparable ENSO forecast skill to dynamical forecasts that are based on the dynamic-model mean. More importantly, we introduce a combined dynamical-DL forecast, an approach that integrates DL forecasts with dynamical model forecasts. Two distinct combined dynamical-DL strategies are proposed, both of which significantly outperform individual DL or dynamical forecasts. Our findings suggest the skill of ENSO prediction can be further improved for a range of lead times, with potentially far-reaching implications for climate forecasting.
... The risk of simultaneous crop failures across several major breadbasket 3 regions, known as synchronous failures, has caused growing concerns about the stability of the global food supply 4,5 . Climate oscillations, the main drivers of interannual climate variations on the global land surface 6 , explain yield variations over two-thirds of global cropland 7 and are regarded as important drivers of synchronous crop failures across breadbaskets 8 . Consequently, many scientists [7][8][9] and insurance companies 10 consider climate oscillation to be a reliable proxy for forecasting variations in global food production. ...
Large-scale climate oscillations are recognized as skilful predictors of variations in global and regional crop yield. However, the mechanisms linking climate oscillations to crop yield variations remain unclear and are widely assumed to result from crop physiological responses to oscillation-induced local climate variations. Here we assessed the pattern of oscillation-induced yield variations in China over the past four decades and found that El Niño/Southern Oscillation (ENSO) is the primary climatic oscillation associated with extreme yield anomalies, particularly in southern China. These ENSO-related extreme yield anomalies are driven not only by local climate anomalies but also by greater occurrences of crop pests and diseases. Interestingly, the greater occurrence of crop pests is not triggered by local climate anomalies but is linked to ENSO-forced climate anomalies in mainland Southeast Asia, the source region of these pests, fuelled by the ENSO-driven circulation pattern facilitating their migration to China. Given the projected increase in the frequency of ENSO events in a warming future, effectively mitigating such oscillation-induced crop failures requires cross-border collaboration between the source and receiving countries of crop pests.
... The El Niño cycle is the dominant driver of year-to-year global climate variability (e.g., Lin & Qian, 2019;McPhaden et al., 2006;Timmermann et al., 2018). It is a coupled ocean-atmosphere phenomenon (Bjerknes, 1969) with three phases, which are characterized by the presence of anomalously warm (El Niño), anomalously cold (La Niña), or normal (neutral) sea surface temperatures in the central and eastern tropical Pacific Ocean. ...
This paper explores the potential of a hybrid modeling approach that combines machine learning (ML) with conventional physics‐based modeling for weather prediction beyond the medium range. It extends the work of Arcomano et al. (2022, https://doi.org/10.1029/2021ms002712), which tested the approach for short‐ and medium‐range weather prediction, and the work of Arcomano et al. (2023, https://doi.org/10.1029/2022gl102649), which investigated its potential for climate modeling. The hybrid model used for the forecast experiments of the paper is based on the low‐resolution, simplified parameterization atmospheric general circulation model SPEEDY. In addition to the hybridized prognostic variables of SPEEDY, the model has three purely ML‐based prognostic variables: the 6 hr cumulative precipitation, the sea surface temperature, and the heat content of the top 300 m deep layer of the ocean (a new addition compared to the model used in Arcomano et al., 2023, https://doi.org/10.1029/2022gl102649). The model has skill in predicting the El Niño cycle and its global teleconnections with precipitation for 3–7 months depending on the season. The model captures equatorial variability of the precipitation associated with Kelvin and Rossby waves and MJO. Predictions of the precipitation in the equatorial region have skill for 15 days in the East Pacific and 11.5 days in the West Pacific. Though the model has low spatial resolution, for these tasks it has prediction skill comparable to what has been published for high‐resolution, purely physics‐based, conventional, operational forecast models.
... Over the past few decades, numerous studies have explored the relationship between sea surface temperature 39 (SST) and various atmospheric phenomena (e.g., Xie 2023). For instance, the impact of large-scale, persistent 40 SST anomalies in equatorial oceans on global atmospheric circulation and extreme weather events is well-41 documented (e.g., McPhaden et al., 2006;Saji et al., 1999). Similarly, it is widely recognized that SST 42 patterns can influence the intensities and tracks of both tropical and extratropical cyclones (e.g., Emanuel 43 1986; Nakamura et al., 2004). ...
The effects of extratropical sea surface temperature (SST) heterogeneity on various atmospheric phenomena have received much attention recently. In this study, the effects of SST anomalies on heavy precipitation that occurred in northern Kyushu Island, Japan, in August 2021 are investigated with a convection–permitting regional atmospheric model. The mid–August SST anomalies are found to provide the following favorable conditions for the intense precipitation. Mesoscale cyclones and associated moisture fluxes intensified over a warm SST anomaly in the northern East China Sea (ECS). The vertical shear of horizontal winds also intensified over a pair of warm and cool SST anomalies in the eastern ECS. The SST anomaly in the western subtropical North Pacific affected static stability of the air parcels entering the precipitation area. The air parcels became more unstable even though they passed over the cool SST anomalies south of the precipitation area. This seemingly counterintuitive result can be explained by the stability of the atmospheric boundary layer (ABL) and the height of the air parcels. The less unstable ABL over the cool SST anomaly kept the air parcels at lower altitudes, and thus they tended to be more susceptible to the influence of heat fluxes from the sea surface and therefore becoming more unstable. The results of this study thus provide a new insight into the role of the complex SST distribution during heavy precipitation events in extratropics, suggesting the need for further studies to deepen our understanding of the atmospheric responses to the extratropical SST.
... El Niño-Southern Oscillation (ENSO) is a periodic phenomenon that occurs every 3-7 years and involves changes in the sea surface temperature of the Central and Eastern Pacific Ocean [3]. ENSO consists of 3 phases namely El Niño, La Niña, and neutral which typically last 1 year each [6]. El Niño is the warm phase where there is higher than average sea surface temperature in the Central and Eastern Pacific Ocean while La Niña is the cold phase where there is lower than average sea surface temperature in the Central and Eastern Pacific Ocean. ...
In this chapter, we explore the application of machine learning (ML) and deep learning (DL) techniques to forecast commodity price volatility, emphasizing the integration of climatic data and financial variables. We use an XAI method, namely the Shapley interpretation method, to explain the impact of different variables on the agricultural price risk. As a preliminary consideration, agricultural businesses are supposed to be significantly influenced by environmental factors, particularly climatic anomalies such as El Niño and La Niña. Therefore, understanding their impact is crucial for effective market prediction and risk management. We discuss various predictive models, including time series analysis, machine learning models, and recurrent neural networks (RNNs) , highlighting their ability to handle large datasets and complex patterns. This chapter provides a comprehensive overview of how advanced computational methods can enhance the accuracy of volatility forecasts, to show the substantial benefits for farmers, investors, and policymakers. By integrating diverse data sources, including historical price data and environmental indicators, while illustrating the potential of ML and DL to study commodity trading and financial planning, we observe that climate features do not persistently rank among the top predictors of agricultural price risk in the US market. This might look surprising at first, as the common belief is the great influence of climate on any aspect of agriculture. This can be interpreted as a sign of adequately manageable risk in commodity market prices against natural phenomena.
... El Niño-Southern Oscillation (ENSO) is the most significant interannual variation signal in the tropical Pacific climate system. ENSO cold and warm events trigger significant anomalies in the tropical Pacific sea surface temperature (SST) and abnormal changes in ocean circulation, which have important effects on the Pacific Ocean and even on the global climate [13,[24][25][26]. Compared with the Pacific Ocean, the tropical Indian Ocean has a smaller sea temperature variability but has equally significant zonal anomaly changes. ...
As important components of the equatorial current system in the Indian Ocean, Wyrtki jets (WJs) play a significant role in distributing heat and matter in the East and West Indian Oceans. By dividing the El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) events into several phases, we find that the spring branch exhibits positive (negative) anomalies during the El Niño (La Niña) decaying phase, while the fall branch exhibits negative (positive) anomalies during the El Niño (La Niña) developing phase. The spring and fall branches are characterized by negative (positive) anomalies under the influence of positive (negative) dipole events, and these anomalies are particularly pronounced during fall. This study systematically analyzes the characteristics of WJs under the interactions between the Indo-Pacific ocean and the atmosphere, based on the phase-locking characteristics of ENSO, and reveals the regulatory mechanisms underlying their different response patterns.
... To address this question, we start by comparing trends in year-round zonal-260 mean heatwave frequency in ERA5 from 1979 to 2022 between the Northern Hemisphere (NH) extratropics, the tropics, and the SH extratropics (Fig. 7a). Poleward of about 20°N, the NH has experienced a gradual increase in heatwave frequency 1983, 1987, 1998, 2010, 2015-16, and 2019-21 are associated with El Niño events in the tropical Pacific (e.g., McPhaden et al., 2006). The SH, on the other hand, shows a broad mid-latitude minimum in heatwave 265 frequency, much clearer than the NH, and a poleward migration of this SH minimum (Fig. 7a). ...
Recent decades have seen a global increase in hot temperature extremes, yet the role of changes in the atmospheric circulation in driving this trend remains unclear. To better understand how atmospheric dynamics control extreme weather, we explore a mechanism that relates mid-latitude heatwave frequency to the storm track position in a suite of idealized model experiments with the dry dynamical core of the ICON model. The underlying relationship between the zonal phase speed of synoptic-scale waves, the latitude of the storm track, and the strength of the eddy-driven jet is assessed through spectral analysis of upper-tropospheric meridional wind. By comparing our experiments to reanalysis data, we find evidence that observed trends in the Southern Hemisphere circulation have contributed towards reducing the persistence of austral mid-latitude hot temperature extremes. This mechanism may also be relevant for the future evolution of extreme events in the Northern Hemisphere, where we see the joint influence of Arctic Amplification and the expansion of the tropics.
... The Southern Annular Mode (SAM) is the primary climate variability mode in the Southern Hemisphere, reflecting circulation changes between high and mid-latitudes driven by atmospheric pressure gradients (Marshall 2003, Fogt andMarshall 2020). The El Niño-Southern Oscillation (ENSO), the strongest interannual climate fluctuation originating in the Tropical Pacific Ocean, influences global climates through teleconnections (Trenberth 1997, McPhaden et al 2006. The Pacific South America (PSA) pattern consists of two modes: PSA1, often associated with ENSO events on an interannual scale, and PSA2, generally associated with other tropical oceanic fluctuations (Mo and Paegle 2001, Ding et al 2011, Irving and Simmonds 2016. ...
Stable water isotopes data extracted from polar ice/firn cores provides valuable climate information. This study presents isotopic time series from a shallow firn core (∼9 m deep) in the Möller Ice Stream basin, Weddell Sea sector, Antarctica. We investigated the relationships between water isotopic ratios (δs; i.e., δ¹⁸O and δD), d-excess data, hemispheric and regional meteorological data, large-scale atmospheric modes, specifically the Southern Annular Mode (SAM) and Pacific South America pattern (PSA), as well as the position and depth of the Amundsen Sea Low (ASL). The interannual variability of δs from 1999–2014 is largely explained by changes in SAM and PSA phases and the ASL response. Positive δs anomalies are associated with (1) warming in the Antarctic Peninsula, southern tip of South America, and high latitudes of the western Southern Atlantic Ocean; (2) northerly flow of heat and moisture from the Antarctic Peninsula and the Weddell Sea sector; (3) establishment of positive geopotential anomalies over the southeast of South America and New Zealand, and negative geopotential anomalies over the ASL region; and, to a lesser extent, (4) the decrease in sea ice in the Weddell Sea sector. Although the δs reflect large-scale atmospheric forcing, it is important to note that core-based studies may have biases and limited regional representation. This underscores the need for further ice core research to refine these connections at the basin scale and improve regional climate reconstructions.
... Hal ini menyebabkan perubahan dinamika atmosfer dan oseanografi (Aldrian dan Susanto, 2003;Labania et al., 2019). Perubahan dinamika tersebut terjadi tidak hanya di dalam Samudra Pasifik tropis namun terjadi juga di luar Samudra Pasifik tropis, yang berdampak pada habitat darat dan laut, ketersediaan air, ketahanan pangan, ekonomi, dan stabilitas sosial (McPhaden et al., 2006;Santoso et al., 2017). Parameter fisis oseanografi yang dipengaruhi variabilitas iklim ENSO adalah parameter angin dan gelombang (Joseph dan Kumar, 2021;Labania et al., 2019;Shuzong et al., 2017). ...
North Halmahera and Morotai are strategic regions in the North Maluku Islands, Indonesia, rich in marine biodiversity and with great potential in the maritime, trade, and fisheries sectors. These regions serve as crucial routes for maritime transportation and regional trade, making accurate information about the physical conditions of the sea, particularly wave height, essential for ensuring the safety and security of shipping lanes. This study aims to analyze the impact of the El-Nino Southern Oscillation (ENSO) phenomenon on ocean wave heights in the waters of North Halmahera and Morotai during the period from 2012 to 2021. Additionally, the study measures the correlation between the Southern Oscillation Index (SOI) and Significant Wave Height (SWH). The data used in this study include wave data from the Marine Copernicus platform and SOI data obtained from http://www.bom.gov.au/climate/enso/soi/. Three observation stations were selected in the waters of North Halmahera and Morotai to monitor changes and variations in SWH during the ENSO phenomenon. A correlation analysis was conducted to determine the relationship between SOI values and SWH at each observation station. The results indicate that during the El-Nino phase, wave heights decreased significantly at several stations, particularly at stations 1 and 3, with a negative correlation between SOI and SWH. Conversely, during the La-Nina phase, wave heights increased, especially at stations 2 and 3, showing a stronger positive correlation. The relationship between SOI and SWH varied depending on location and time period. This study concludes that ENSO has a significant impact on the variation in wave heights in the waters of North Halmahera and Morotai. These findings are important for supporting maritime safety and managing maritime activities in the region.
... y la ocurrencia de eventos extremos aproximadamente cada 10 años(McPhaden et al., 2006), se alinea con las fluctuaciones observadas en los regímenes de crecimiento de la anchoveta, donde se identificaron fluctuaciones significativas en sus anomalías, con ciclos detectados en escalas de ~ 9, 3 y 5 años. Estas anomalías fueron especialmente pronunciadas en tres períodos:197031990, con mayor magnitud entre 1981 y 1985; 199032000, con mayor magnitud entre 1995 y 2000; y 200032022, destacando en este último un rango mayor entre 2010 y 2022 (Figura 30). ...
Somatic growth is a key process in stock assessment, as it affects biomass, size composition, natural mortality, and productivity. However, in practice, growth is often perceived as invariant over time without considering its relationship with extrinsic factors (such as density dependence and environmental factors) and intrinsic factors (such as physiological integrity). This study aims to quantify the growth of anchovy in the north-central stock, analyze its interannual variability, and explain this variability in terms of environmental and condition-related variables. To estimate anchovy growth, the von Bertalanffy Growth Function (VBGF) was applied using the ELEFAN routine, which estimated growth parameters (K and L∞) from length-frequency data. Various optimization algorithms (ELEFAN/RSA, ELEFAN/SA, ELEFAN/GA) and bootstrapping were used to assess the uncertainty of the results. A time series analysis identified trends and breakpoints, while a wavelet analysis examined short- and long-term fluctuations. The results showed that both parameters followed normal distributions, with average values of 18.50 ± 0.542 cm for L∞ and 0.890 ± 0.102 year⁻¹ for K. Significant fluctuations in growth parameters highlighted the influence of phenomena such as the El Niño-Southern Oscillation on interannual and multi-decadal growth regimes. These fluctuations reflect the high variability of the ecosystem and the phenotypic plasticity of anchovy in response to changing environmental conditions. Furthermore, the study revealed that environmental scenarios characterized by increased temperature and reduced primary productivity negatively affect the asymptotic length of anchovy, suggesting that somatic growth is redirected toward early reproduction as an adaptive strategy under unfavorable conditions. Additionally, the anchovy growth rate was found to be linked to zooplankton availability, which impacts its condition factor. The positive relationship between the growth rate and zooplankton levels indicates that higher availability of this resource supports somatic growth. In summary, variability in the somatic growth of anchovy, alongside other stock attributes, could significantly influence stock status and catches. Incorporating this variability into stock assessment and fishery management models will improve the accuracy of biological and population status estimates for anchovy, ultimately enabling better management of its fishery.
... From (McPhaden, Zebiak and Glantz, 2006), we note that the periodicity in the smoothed spectra coincide with cyclical climatic events measured by ENSO. This despite accounting for SOI in stage one. ...
... As a crucial component of the climate system, the ocean profoundly influences global climate through the exchange of heat, momentum, and matter with the atmosphere [1][2][3]. Meanwhile, the latest ocean state serves as a crucial foundation for short-term climate forecasts due to its large heat capacity and slower changes compared to atmospheric processes [4][5][6]. Particularly for a climate forecast with a lead time of more than three months, indicative signals mostly come from the ocean state [7][8][9]. Therefore, the sea surface temperature (SST), as a key variable representing ocean conditions, has been an essential input physical variable for statistical climate forecast systems [10][11][12]. ...
Statistical climate forecast systems typically do not use preceding global gridded sea surface temperature (SST) data directly; instead, they extract a single predictor (e.g., the Niño3.4 index) or multiple predictors (e.g., time series of several SST spatial modes). In this study, four different SST predictor extracting methods (one single-predictor method and three multiple-predictor methods) are comparatively analyzed within the same climate forecast platform incorporating either the linear regression (LR) model or the neural network (NN) forecast model. Rolling forecast experiments with the LR model show that, compared to a single strong SST predictor, only multiple predictors with more high-quality information (high signal-to-noise ratio) could improve the forecast skill. Sensitivity experiments also show that the influence of multiple-predictor extracting methods on forecast skill from the NN model is much weaker than that from the LR model. Moreover, whether or not multiple SST predictors are orthogonal might also affect the forecast skill. The above analyses provide a reference for establishing statistical climate forecast system based on preceding SST data.
... It has been pointed out that the tropical ocean-atmosphere interactions have played crucial roles in influencing the decadal to centennial scale hydroclimate fluctuation in the monsoonaffected areas (Li et al., 2024;Wang et al., 2000). The El Niño-Southern Oscillation (ENSO) event has been recognized as the most important climate phenomenon among them, closely mirroring the latitudinal sea surface temperature gradient between the western and central-eastern Pacific basin (McPhaden et al., 2006). The ENSO-related response in the monsoon system is via the largescale latitudinal migration in the Walker circulation over the tropical ocean (Kumar et al., 1999;Wang et al., 2000). ...
Identifying the late Holocene Indian summer monsoon (ISM) changes and their possible forcing mechanisms provides an important perspective for understanding the current monsoon shifts driven by anthropogenic climate change within a natural baseline. In this study, we present a well-dated, ca. 4.0 ka grain-size sensitive component record from Lake MangCo, located in the southeastern Tibetan Plateau. The record depicts late Holocene ISM evolution and centennial-scale precipitation events superimposed on millennial-scale climate changes. The results indicate that precipitation was relatively high during the first half of the late Holocene, likely before 2.0 cal ka BP, followed by a period of relatively reduced precipitation thereafter, which indicates that the Northern Hemisphere summer insolation (NHSI) has primarily controlled ISM intensity. A slight increasing trend in ISM strength since 1.1 cal ka BP was observed, which may correspond to the reported “2.0-kyr-shift” and could be related to warming tropical temperatures. Three low precipitation intervals, occurring at ∼1.1, 2.0, and 3.2 cal ka BP, align well with known centennial-scale ISM weakening events during the late Holocene, such as the Medieval Warm Period (MWP) and the “2.0-ka-dry-event.” Our findings further validate the climatic effects of tropical ocean–atmospheric interactions in the Pacific and Indian Ocean basins on ISM variabilities at centennial timescales.
... However, ENSO flavors varied greatly from one to another (e.g., Fu et al., 1986;Capotondi et al., 2020;Geng and Jin, 2023;Timmermann et al., 2018;Wang and Ren, 2020) over the past millennium (Yan et al., 2011). due mainly to the complex tropical three-ocean interactions and the changing tropicalextratropical interplay under greenhouse warming (e.g., Cai et al., 2021;Jia et al., 2019Jia et al., , 2021Min and Zhang, 2024;Wang, 2019;Wang and Wang, 2021;Yang and Huang, 2021;Zhang et al., 2021Zhang et al., , 2023 El Niño-Southern Oscillation (ENSO), alternating irregularly between El Niño (warm) and La Niña (cold) sea surface temperature (SST) conditions in the tropical Pacific, is the most prominent interannual signal in the atmospheric and oceanic climate systems (e.g., Alizadeh, 2022;Cai et al., 2018;Yeh et al., 2018;Wang et al., 1999;McPhaden et al., 2006;Pathirana et al., 2023). It severely disrupts global weather and climate patterns Yeh et al., 2018), and thereby ecosystems, agriculture, water availability, hydro-power production, food security, Arctic sea-ice loss, and even economical and social stability (e.g., Cai et al., 2021;Chu et al., 2021;Iizumi et al., 2014;Ng et al., 2017;Hu et al., 2016aHu et al., , 2016bSantoso et al., 2017), by modulating large-scale atmospheric circulation, highlighting the ). ...
https://authors.elsevier.com/a/1knb42weQ%7ElMu （A personalized URL providing 50 days' free access to this article before May 07, 2025）
El Niño-Southern Oscillation (ENSO) exhibits a wide range of spatial patterns, causing distinct global impacts. Over the past decades, various ENSO indices have been proposed to capture its diversity. Although the classification systems for ENSO flavors differ by definition methodology, it has generally been categorized into two distinct eastern Pacific (EP) and central Pacific (CP) types. However, how different indices characterize these ENSO flavors remains unclear. Here, we reveal the significant differences among these ENSO indices in terms of locally explained variance, type, frequency, and the phase. Specifically, some ENSO indices capture more signals in the equatorial EP or CP, but some others explain relatively insufficient local explanatory variance in the tropical EP and CP, respectively. Moreover, different definition methodologies can result in varying ENSO frequencies identified, even under the same identification criteria and classification process. The most notable discrepancies are observed among CP El Niño and EP La Niña flavors. Furthermore, we discuss the macro-regulation of the Pacific Decadal Oscillation phase on the frequency of each ENSO flavor with different definition. Our findings indicate that each index processes unique characteristics, yet none can comprehensively describe all aspects of ENSO complexity. This highlights the need to consider multiple indices for a comprehensive understanding of ENSO.
... Despite scientists' decades of endeavor, prediction of ENSO accurately still remains as a challenge [2,3]. However, duo to existence of frequent and recursive factors in ENSO and its connection to oceanic variability it can be concluded that this phenomenon is predictable [4]. ...
Ability of predicting climate phenomena enables international organization and governments to manage natural disasters such as droughts. El Niño Sothern Oscillation (ENSO) is one the most influential and crucial phenomenon follows with large scale climatic events and can be used for predicting droughts and floods all around the world. Due to such a great importance, a new Convolutional Neural Network method based on augmented data (ACNN) for predicting ENSO on a relatively long period is developed in this research. The method is developed based on CNN to forecast ENSO six month earlier. Sea Surface Temperature (SST) anomaly maps are given to the model as the predictors and Niño 3.4 Index is the predictand. The method applies convolutional tensors to extract features from the maps, and delivers them to a fully connected neural network to discover connections between Niño Index and the features. A tricky augmentation process is used to increase the number of input data to compensate lack of observations. The model's skill correlation is over 0.83 for January-February-March season, while, the original CNN method' correlation is 0.71. The model can be executed on GPUs of a laptop without any need to super computers. The feature that makes it a great tool for predicting ENSO even for research institutions in low income countries.
... It can be argued that Pacific SST-SIC variability within the NAO-linked pair, resembles with the impact of El Nino Southern Oscillation (ENSO), which is the dominant mode of interannual variability in the Pacific realm (McPhaden et al. 2006;Timmermann et al. 2018;Vaideanu et al. 2023a). The central Pacific mode of ENSO which could be recognized in the SST pattern of the third pair (Fig. 1f) can be interpreted as a response of the Tropical Pacific to the dominant mode of North Atlantic SST variability (Dima et al. 2015). ...
Arctic sea ice plays a pivotal role in shaping the climate system at high latitudes, acting as both an indicator and driver of climate change processes in this sensitive region. Its seasonal variability and long-term decline have far-reaching implications for global climate dynamics, regional ecosystems, and human activities. While climate models indicate clear evidence of human-induced sea ice decline, quantification of the relative contributions of forcing factors in relation to climate-system internal processes remains uncertain. Here, we tackle this uncertainty by employing a combination of statistical analyses on observational data, highlighting the distinct fingerprints of increased atmospheric CO2 concentration as external forcing, the Atlantic Multidecadal Oscillation (AMO) as well as the North Atlantic Oscillation (NAO), as modes of internal variability, on global sea surface temperature (SST) and Arctic sea ice concentration (SIC) since 1950. Our analyses reveal that rising atmospheric CO2 concentrations are by far the dominant causal factor for SIC variability, while AMO and NAO also play a significant role in either exacerbating or mitigating sea ice loss. Since mid-1980s, the positive trend of the AMO has amplified the declining trend in Arctic sea ice, with its effects being roughly half as large as the effect of rising CO2 concentrations. Linear regression analyses shed light on the physical processes linking the drivers of Arctic sea ice decline both during phases of sea-ice accumulation and melting. Causal links between increasing atmospheric CO2 concentrations, the AMO, the NAO, on the one hand, and observed global SST—Arctic SIC patterns on the other are also established. Observation-based coupled SST-SIC interactions underline the past evolution of Arctic sea ice and emphasize the important roles of these drivers in shaping its current and future evolution.
Possible links between the Earth’s surface temperature and solar variability are investigated using uni- and bivariate wavelet methods, in an attempt to attribute the fluctuations of the global mean surface temperature (GMST). Time-varying strengths of oscillations on different time scales in time series for several sets of GMST and solar activity indices are evaluated using continuous wavelet transform. Furthermore, possible relationships on different time scales between the GMST and solar activity time series are investigated using cross wavelet transform and wavelet coherence analyses. The results show that for the most prominent oscillations of solar activity on the ∼11-year scale, no statistically significant response is found in any of the temperature time series. Little evidence is found supporting the postulated link on the ∼60-year time scale between surface temperature and solar activity. The ∼60-year oscillations in the climate system likely stem from internal variabilities of the coupled ocean-atmosphere system, especially the variabilities in the North Atlantic and the associated variabilities in the western tropical Pacific, rather than solar variability. The latitudinal differences in temperature response to solar activity depend on time scales. Our findings do not support the notion that solar variability has been playing a dominant role in recent climate change.
Observations reveal a strong correlation between the magnitude of El Niño and the displacement of the eastern edge of the western Pacific warm pool (WPWP). In Part I, this relationship was examined in the Coupled Model Intercomparison Project Phase 6 (CMIP6) models using their historical simulations, and it was found to be comparable to that in the observations. The present study extends the analysis to future projections under two Shared Socioeconomic Pathway (SSP) scenarios—SSP245 and SSP585—to assess whether this strong relationship persists under global warming. It is found that El Niño magnitude and WPWP boundary displacement in most models under global warming are as strongly correlated as in the observations and their historical simulations. Moreover, most models project that stronger El Niño events will be accompanied by a greater eastward displacement of the WPWP boundary. For models with a positive response, the ensemble projects an increase in El Niño magnitude of 0.21 ± 0.03 °C (0.20 ± 0.03 °C) under the SSP245 (SSP585) scenario, accompanied by an eastward displacement of the WPWP by 11.7 ± 1.3° (11.1 ± 1.0°) in longitude. These results further support the notion that El Niño is a consequence of the eastward extension of the WPWP.
Observations indicate that the Indian Ocean Dipole (IOD) in autumn is an important precursor to the El Niño-Southern Oscillation (ENSO) 14 months later. Our study explores the performance of CMIP5 and CMIP6 models in simulating this IOD-ENSO relationship. The models exhibit significant spread in the IOD-ENSO relationship, which can be attributable to the diversity in the simulated mean precipitation over the tropical south Pacific Ocean (TSPO) and Indian Ocean (TSIO). Models with higher mean precipitation over the tropical south Pacific Ocean produce stronger surface easterly (westerly) wind anomalies over the western-central equatorial Pacific in response to the negative (positive) IOD event via modulating the tropical Walker circulation. Stronger surface easterly wind anomalies over the western-central equatorial Pacific cause more warm water to be accumulated in the western tropical Pacific through strengthened anticyclonic wind stress curl and westward downwelling Rossby waves, providing favorable conditions for the El Niño occurrence. Furthermore, higher mean precipitation enhances the air-sea interaction over the tropical Pacific, which is also favorable for ENSO development. Mean precipitation over the tropical Indian Ocean also contributes to the coupling feedback within the Indian Ocean, but this effect is relatively small. Further analysis shows that the prediction skill of the Niño-3.4 index according to the IOD index 14 months earlier reaches 0.6 with a lead time of 14 months for the high-correlation models, whereas for the low-correlation models, it starts to decline from May of the following year and drops to 0.4 at the peak of ENSO. This suggests that the physical connection between IOD and ENSO should be carefully considered when using predictors outside the tropical Pacific to forecast ENSO.
Review articles are vital in synthesizing existing research, identifying knowledge gaps, and informing future research directions. In the context of disasters, reviews help uncover relationships, intricacies, and nexus among different hazard types, concepts, and thematic areas. However, existing reviews tend to adopt a segmented approach, focusing on individual disasters, with limited efforts toward comprehensive meta-reviews across multiple disaster types. This study conducted a meta-review, or review of reviews, on six major disasters: droughts, earthquakes, floods, heatwaves, hurricanes, and wildfires. A total of 26,076 review articles were retrieved from the Scopus database. Bibliometric analysis, review trend analysis, keyword mapping, and citation analysis were performed to explore the landscape of disaster-related review literature. The analysis revealed a consistent increase in published review articles, particularly on floods, droughts, and earthquakes. A total of 962 authors from 160 distinct Institutions globally contributed to the disaster reviews domain. Reviews on droughts, heatwaves, and wildfires received the highest citation counts. Most reviews were published in English and Chinese. Keyword analysis highlighted resilience and adaptation as recurrent terms across all disaster types, underscoring their central role in disaster risk reduction and vulnerability mitigation. The findings indicate a growing global interest in synthesizing disaster research through reviews, especially for specific hazards. However, the limited number of integrated meta-reviews indicates the need for more holistic approaches. The observed interconnections among different disasters suggest that a collective, cross-hazard perspective is crucial to understanding complex disaster dynamics and enhancing resilience, adaptation, and sustainability strategies.
The El Niño Southern Oscillation (ENSO) during the Early Eocene Climatic Optimum (EECO, 56–48 million years ago) is investigated using a multi-model ensemble of deep-time climate simulations. We reveal that ENSO sea surface temperature variability during the EECO had significantly longer periodicity and stronger amplitude than present-day conditions. These changes are attributed to intensified ocean-atmosphere feedback processes and enhanced in-phase tropical inter-basin interactions within a broader ocean basin compared to the present-day. Sensitivity experiments in coupled ocean-atmosphere models suggest that tectonic changes, particularly the expansion of the tropical ocean basin, play a dominant role in amplifying ENSO variability and extending its periodicity, while stronger inter-basin connections further enhance ENSO amplitude. Elevated atmospheric CO2 levels, though driving substantial mean-state changes, partially offset the tectonic influence on ENSO variability by modifying feedback processes. These findings underscore the role of tropical ocean basin geometry and atmospheric CO2 levels in shaping ENSO variability, offering insights into past climate dynamics and implications for future projections under sustained global warming.
O objetivo deste trabalho foi comparar as produtividades de caroço, pluma e semente de algodão entre os eventos El Niño, La Niña e Neutro do fenômeno El Niño Oscilação Sul (ENOS), nos estados do Paraná, São Paulo e Minas Gerais. Foram utilizadas séries históricas de produtividades de caroço, pluma e semente de algodão dos estados do Paraná, São Paulo e Minas Gerais dos anos agrícolas de 1976/77 a 2022/23. Os dados do fenômeno ENOS, foram obtidos no site da National Oceanic and Atmospheric Administration - NOAA. Após a remoção da tendência tecnológica, em cada estado, foram comparadas as médias de produtividades de caroço, pluma e semente entre os eventos El Niño, La Niña e Neutro, por meio do teste t de Student a 5% de significância. No estado do Paraná, as produtividades de caroço, pluma e semente de algodão não diferem entre os eventos La Niña e Neutro e são superiores ao El Niño. Nos estados de São Paulo e Minas Gerais não há diferença nas produtividades de caroço, pluma e semente de algodão entre os eventos El Niño, La Niña e Neutro.
This study investigates the impacts of climate variability on hydrological extremes-droughts and floods-in the context of a changing climate. Using historical climate and hydrological data (1980-2020) alongside key climate indices, including the El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO), we analyze trends in temperature, precipitation, and streamflow, and their linkages to extreme events. Results reveal a significant rise in mean temperatures (0.25°C per decade) and declining precipitation, exacerbating drought frequency and intensity, while amplifying flood magnitudes during extreme rainfall periods. El Niño phases correlate strongly with prolonged droughts, whereas La Niña phases drive flood occurrences. Hydrological modeling using the Soil and Water Assessment Tool (SWAT) demonstrates robust performance (Nash-Sutcliffe Efficiency [NSE] = 0.76 in calibration), projecting a tripling of drought and flood events by 2100 under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios. Geospatial vulnerability assessments identify regions with high exposure and low adaptive capacity, underscoring the need for integrated water management and climate-resilient infrastructure. This research highlights the critical role of climate variability in shaping hydrological risks and advocates for adaptive strategies to mitigate socio-environmental impacts in vulnerable regions.
Climate records have been broken with alarming regularity in recent years, but the events of 2023–2024 were exceptional even when accounting for recent climatic trends. Here we quantify these events across multiple variables and show how excess energy accumulation in the Earth system drove the exceptional conditions. Key factors were the positive decadal trend in Earth’s Energy Imbalance (EEI), persistent La Niña conditions beginning in 2020, and the switch to El Niño in 2023. Between 2022 and 2023, the heating from EEI was over 75% larger than during the onset of similar recent El Niño events. We show further how regional processes shaped distinct patterns of record-breaking sea surface temperatures in individual ocean basins. If the recent trend in EEI is maintained, we argue that natural fluctuations such as ENSO cycles will increasingly lead to amplified, record-breaking impacts, with 2023–2024 serving as a glimpse of future climate extremes.
El Niño induced equatorial precipitation centers shift to different longitudinal positions during Eastern Pacific (EP) and Central Pacific (CP) El Niño events, resulting in distinct global climate responses. However, it remains unexplored how EP and CP El Niño forced precipitation changes may differ under global warming. Here, we find that the longitudinal separation of precipitation centers in EP and CP El Niño events is projected to increase under global warming. Specifically, the precipitation anomalies during EP El Niño events will shift further eastward, while those during CP El Niño will intensify in their original positions. This change is attributed to the amplified equatorial thermocline feedback as the mean thermocline shoals. A more meridionally confined El Niño structure under global warming generates extra boundary layer moisture convergence in situ. This intensifies the precipitation anomalies in CP El Niño but shifts the precipitation center eastward towards the maximum sea surface temperature anomaly center in EP El Niño. The projected increased longitudinal separation of precipitation centers suggests that the differences in global climate impacts between EP and CP El Niño events will intensify under global warming. The El Niño-Southern Oscillation (ENSO), the strongest air-sea interaction mode of the climate system 1-4 , leads to year-to-year climate anomalies all around the world. It affects many aspects of human activities and natural systems, such as water resources, fishing, agriculture, finance, coastal erosion , land and marine ecosystems 3,5-10. These global climate impacts of ENSO are forced mainly through anomalous tropical convective heating and its excited atmospheric teleconnections 3,5,6,11-16. ENSO-related teleconnections and global climate variations are complicated by a diversity of ENSO spatial patterns 14,17-25. Two typical types of El Niño, eastern Pacific (EP) and central Pacific (CP) El Niño, named after the central positions of their sea surface temperature (SST) anomalies, drive tropical precipitation and its associated convective heating anomalies with remarkable longitudinal shifts. Correspondingly, the anomalous Walker Circulation and the Pacific-North American (PNA) teleconnection pattern associated with CP El Niño are shifted westward relative to those associated with EP El Niño 14,17-19,24,26-28. As a result, different climate impacts of two types of El Niño are also observed in Asia and Australian monsoon domain 19,29 , North America 26,27 , South America 12,15 and polar region 25,30. ENSO is projected to undergo significant changes under global warming according to state-of-the-art coupled climate system models 31-44. Most climate models project an El Niño-like warming pattern in the background mean state of tropical Pacific, while observational records show a La Niña-like mean state change over the past century. Uncertainty in the change in the background mean state introduces additional complexity and uncertainty in ENSO projections 41,45,46. Compared with large uncertainties in the variation of ENSO intensity influenced by internal variability and
This chapter comprehensively explores climate change, tracing its natural cycles over millions of years and the accelerated impacts of human activities since the Industrial Revolution. It begins by outlining Earth’s historical climatic variations, driven by factors such as Milankovitch cycles, tectonic shifts, and feedback mechanisms. Key epochs, like the Pliocene Warm Period and the Pleistocene glaciations, highlight the natural drivers of global temperature fluctuations and their ecological and geological consequences. The chapter then shifts to anthropogenic influences, emphasizing the role of greenhouse gas emissions from fossil fuel combustion, industrial processes, and deforestation. Empirical evidence underscores the unprecedented rate of global warming since the twentieth century, marked by rising temperatures, extreme weather events, and melting ice sheets. It discusses climate models, feedback mechanisms, and future projections, warning of severe socio-economic and ecological impacts. Finally, the chapter examines historical civilizations affected by climatic shifts and contemporary vulnerabilities, emphasizing the urgency for mitigation and adaptation strategies to address this global challenge.
Environmental changes greatly affect fish body condition, but impacts on many species are often unknown. We investigated the relative condition factor (Kn) of Conger myriaster in relation to abiotic/biotic variables in Haizhou Bay, southwestern Yellow Sea, China. We developed generalized additive mixed models (GAMMs) to analyze the time-lag effects of their responses to external factors and statistically evaluated their influence on Kn in newly recruited and juvenile individuals. Accordingly, we predicted the Kn under future climate projections for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5. The results revealed a 5-month lag for both life stages to the El Niño 3.4 index (equatorial Pacific sea surface temperature anomalies), a 1–2 week lag for sea surface temperature, and no lag for food availability. El Niño 3.4 was the primary driver for newly recruited individuals, while sea temperature was most influential for juveniles. Food availability significantly impacted Kn for both stages. Predictive models suggest a thermally induced Kn decline for newly recruited individuals across all climate scenarios. Juveniles showed more resilience to global warming with stable Kn values across all scenarios until 2040, followed by rapid declines under SSP3-7.0/SSP5-8.5 scenarios. Our findings demonstrate life-stage-specific time-lag responses to environmental shifts in C. myriaster.
The recharge oscillator (RO) is a simple mathematical model of the El Niño Southern Oscillation (ENSO). In its original form, it is based on two ordinary differential equations that describe the evolution of equatorial Pacific sea surface temperature and oceanic heat content. These equations make use of physical principles that operate in nature: (a) the air‐sea interaction loop known as the Bjerknes feedback, (b) a delayed oceanic feedback arising from the slow oceanic response to winds within the equatorial band, (c) state‐dependent stochastic forcing from fast wind variations known as westerly wind bursts (WWBs), and (d) nonlinearities such as those related to deep atmospheric convection and oceanic advection. These elements can be combined at different levels of RO complexity. The RO reproduces ENSO key properties in observations and climate models: its amplitude, dominant timescale, seasonality, and warm/cold phases amplitude asymmetry. We discuss the RO in the context of timely research questions. First, the RO can be extended to account for ENSO pattern diversity (with events that either peak in the central or eastern Pacific). Second, the core RO hypothesis that ENSO is governed by tropical Pacific dynamics is discussed from the perspective of influences from other basins. Finally, we discuss the RO relevance for studying ENSO response to climate change, and underline that accounting for ENSO diversity, nonlinearities, and better links of RO parameters to the long term mean state are important research avenues. We end by proposing important RO‐based research problems.
Global warming has emerged as a significant environmental challenge for humanity, particularly in climate-sensitive regions such as the Chinese Loess Plateau (CLP). Climate changes in this region are thought to have led to an increase in extreme weather events, adversely affecting ecosystems and agricultural development. This study uses spruce tree-ring samples to reconstruct precipitation data for the western CLP (WCLP) since 1598 CE. The resulting record accounts for 49 % of the variation in instrumental precipitation from July of the previous year to June of the current year. Through this reconstruction, we document occurrences of extreme drought and wet events over the past 426 years, record significant historical drought events in WCLP, reveal climatic driving mechanisms on different timescales, and analyze recent trends of increasing precipitation. This study contributes to a deeper understanding of the climatic history of the WCLP and provides scientific foundations for future climate predictions and regional sustainable development.
I developed Lagrangian climate models to analyze global sulfur emissions and model their chemistry and transport in the troposphere. This research significantly improved model predictions and contributed to our understanding of aerosol-cloud interactions.
Observational records during the past several decades show a marked increase in boreal winter extreme US hydroclimate events, with extreme floods and droughts becoming more common. Coincidentally, El Niño-Southern Oscillation (ENSO), a key driver of US precipitation and associated extreme hydroclimate on interannual time scales, has also increased in amplitude and is projected to continue increasing throughout the 21st century. This study examines future changes in ENSO and its impacts on the US winter extreme hydroclimate events (e.g., drought and flood) by using a large ensemble simulation. Results in this study show that both the amplitude of ENSO and ENSO-induced atmospheric teleconnections are projected to strengthen, leading to a significant increase in US precipitation variability and extreme hydroclimate events, albeit with notable regional differences. Signal-to-noise ratio analysis shows that the ENSO signal explains a significantly increased fraction of the total variance in US winter precipitation compared to non-ENSO factors (i.e., noise), suggesting a growing role of ENSO in future US extreme hydroclimate events. Further analysis shows that while both the increase in ENSO amplitude and the atmospheric response to ENSO have a similar impact on the hydroclimate over the Southeast and Southwest US, the amplification of the atmospheric response to ENSO plays a more dominant role in the Northeast US.
In recent years, the expansion of renewable energy technologies has been remarkable on a global scale. Wind energy, in particular, has played a crucial role in the pursuit of decarbonizing the energy matrix. However, it is important to recognize that the construction and operation of wind farms have significant impacts on the environment and local climate, altering the properties of the land surface and disturbing the interactions between the surface and the atmosphere. This study is dedicated to investigating the effects of the growth and installation of wind farms on land surface temperature (LST) and vegetation in the Caatinga biome of Rio Grande do Norte (RN), a region particularly vulnerable to climate change. Geolocation data of wind turbines located in RN, provided by the Agência Nacional de Energia Elétrica (ANEEL), were used. The turbines were grouped into 34 clusters using the DBSCAN method. LST and vegetation data were obtained from the MODIS sensor aboard the Aqua and Terra satellites over the period from 2004 to 2023 for LST and 2022 for vegetation, using both day and night measurements. These data were compared with reference values extracted from the Açu National Forest. The results pointed to a trend of nighttime warming and a decrease in the Enhanced Vegetation Index (EVI) values over the years. These analyses offer a more comprehensive understanding of the environmental impacts associated with wind farms, considering the specific context of the Caatinga and its interactions with climate change.
El Niño–Southern Oscillation (ENSO) is an oscillation of the ocean–atmosphere system in the tropical Pacific, which is argued to be energized by high-frequency stochastic atmospheric disturbances. Among these disturbances, westerly wind bursts (WWBs) play a crucial role in the development of El Niño by generating eastward-propagating downwelling Kelvin waves and suppressing the thermocline in the central-eastern equatorial Pacific. The present work elucidates distinct seasonal evolutions of WWBs during cyclic and noncyclic El Niño events, and their association with the local sea surface temperature anomalies (SSTAs). For noncyclic El Niño events, WWBs prevail over the western-central equatorial Pacific during spring of the developing year, accompanied by local warming SSTAs. In contrast, active WWBs cannot be observed until the developing summer for cyclic El Niño events. Significant differences in high-frequency WWBs and associated local deep convection appear in the developing spring season of noncyclic and cyclic El Niño events. These differences are closely linked to local SSTAs in the western-central equatorial Pacific via the stimulation of atmospheric deep convection, preceding the full manifestation of ENSO-associated large-scale SSTAs in the central-eastern tropical Pacific. The observed difference in WWBs for noncyclic and cyclic El Niño events and its association with the western-central equatorial Pacific SSTAs is realistically reproduced in a coupled general circulation model. This study enhances our comprehension of El Niño development by illustrating the intricate connection between WWBs and El Niño evolution from the ENSO cycle perspective.
This paper presents an attempt to recover the space–time structure of fluxes of CO 2 to the atmosphere over the period 1980–1995 from atmospheric concentration and isotopic composition measurements. The technique used is Bayesian synthesis inversion in which sources are aggregated into large regions and their strengths adjusted to match observed concentrations. The sources are constrained by prior estimates based on a priori knowledge. The input data are atmospheric CO 2 concentration measurements from the NOAA/CMDL network, 13CO 2 composition and O 2 /N 2 ratios measured at Cape Grim, Tasmania by CSIRO Atmospheric Research. The primary findings are a relatively large long-term mean ocean uptake of CO 2 , and seasonal fluxes over land with similar integrated magnitude, but smaller peak amplitude, compared with those derived by Fung and co-workers. Predicted interannual variability is smaller than reported in previous studies. The largest contributor is the oceanic tropics where fluxes vary on the time scale of the southern oscillation. There is evidence of longer timescale variation in land uptake. Increases in ocean uptake and northern land uptake in the early 1990s are consistent with a response to the Mt. Pinatubo eruption.
The development of seasonal-to-interannual climate predictions has spurred widespread claims that the dissemination of such forecasts will yield benefits for society. Based on the use as well as non-use of forecasts in the Peruvian fishery during the 1997–98 El Niño event, we identify: (1) potential constraints on the realization of benefits, such as limited access to and understanding of information, and unintended reactions; (2) the need for an appropriately detailed definition of societal benefit, considering whose welfare counts as a benefit among groups such as labor, industry, consumers, citizens of different regions, and future generations. We argue that consideration of who benefits, and an understanding of potential socioeconomic constraints and how they might be addressed, should be brought to bear on forecast dissemination choices. We conclude with examples of relevant dissemination choices made using this process.
Experiments with Whole Atmosphere Community Climate Model (WACCM) under perpetual January conditions indicate that stratospheric sudden warmings (SSWs) are twice as likely to occur in El Niño winters than in La Niña winters, in basic agreement with the limited observational dataset. Tropical SST anomalies that mimic El Niño and La Niña lead to changes in the shape of probability distribution functions (PDFs) of stratospheric day-to-day variability, resulting in a warmer pole and weaker vortex on average for El Niño conditions. The tropical SST forcing induces a response similar to the observed response in the enhancement of the planetary wave of zonal wavenumber 1 (wave 1) and the weakening of wave 2 in the upper troposphere and stratosphere of high latitudes. The enhanced wave 1 contributes to a shift of the PDFs of poleward eddy heat flux in the lower stratosphere, or wave forcing entering the stratosphere. The shift of the PDFs includes an increase of strong wave events that induce more frequent SSWs.
As part of the Palmer Long-Term Ecological Research (LTER) program, the size structure of the population of Antarctic krill found between Anvers and Adelaide Islands west of the Antarctic Peninsula has been analyzed for patterns in recruitment success. The data were from a series of 11 cruises, 1 in spring (November 199 1) and 10 in summer (January 1993 to January 2002). A maximum-likelihood fitting procedure was used to fit a mixture of normal distributions to the length-density distributions derived from net data. The recruitment index was calculated as the proportion of age-class 1 krill of the total. Antarctic krill in the Palmer LTER region showed a pattern of episodic recruitment, with 2 strong year classes in succession followed by 3 or 4 moderate or poor year classes. The 2 strong year classes represented 85 to 90% of the krill caught for 5 or 6 yr, and as the absolute abundance of the year class declined due to mortality, so did the abundance of Antarctic krill in the region. The recruitment index was positively correlated with the absolute value of a seasonal El Nino/Southern Oscillation (ENSO) index, with strongest recruitment during the neutral or moderate periods of ENSO. The mechanism underlying the strong link between the recruitment index and ENSO is most likely the effects of seasonal sea-ice dynamics on both reproduction and winter-over survival of the resulting larvae as previously documented.
Beginning from the hypothesis by Bjerknes [1969] that ocean-atmosphere interaction was essential to the El Nino-Southern Oscillation (ENSO) phenomenon, the Tropical Ocean-Global Atmosphere (TOGA) decade has not only confirmed this but has supplied detailed theory for mechanisms setting the underlying period and possible mechanisms responsible for the irregularity of ENSO. Essentials of the theory of ocean dynamical adjustment are reviewed from an ENSO perspective. Approaches to simple atmospheric modeling greatly aided development of theory for ENSO atmospheric feedbacks but are critically reviewed for current stumbling blocks for applications beyond ENSO. ENSO theory has benefitted from an unusually complete hierarchy of coupled models of various levels of complexity. Most of the progress during the ENSO decade came from models of intermediate complexity, which are sufficiently detailed to compare to observations and to use in prediction but are less complex than coupled general circulation models. ENSO theory in simple models lagged behind ENSO simulation in intermediate models but has provided a useful role in uniting seemingly diverse viewpoints. The process of boiling ENSO theory down to a single consensus model of all aspects of the phenomenon is still a rapidly progressing area, and theoretical limits to ENSO predictability are still in debate, but a thorough foundation for the discussion has been established in the TOGA decade.
[1] The origins of the delayed increases in global surface temperature accompanying El Niño events and the implications for the role of diabatic processes in El Niño–Southern Oscillation (ENSO) are explored. The evolution of global mean surface temperatures, zonal means and fields of sea surface temperatures, land surface temperatures, precipitation, outgoing longwave radiation, vertically integrated diabatic heating and divergence of atmospheric energy transports, and ocean heat content in the Pacific is documented using correlation and regression analysis. For 1950–1998, ENSO linearly accounts for 0.06°C of global surface temperature increase. Warming events peak 3 months after SSTs in the Niño 3.4 region, somewhat less than is found in previous studies. Warming at the surface progressively extends to about ±30 ° latitude with lags of several months. While the development of ocean heat content anomalies resembles that of the delayed oscillator paradigm, the damping of anomalies through heat fluxes into the atmosphere introduces a substantial diabatic component to the discharge and recharge of the ocean heat content. However, most of the delayed warming outside of the tropical Pacific comes from persistent changes in atmospheric circulation forced from the tropical Pacific. A major part of the ocean heat loss to the atmosphere is through evaporation and thus is realized in the atmosphere as latent
Previous studies by the authors have described the composite global marine surface anomalies of ENSO warm (El Niño) events and cold (La Niña) events. Here the similarities and differences in these life cycles are examined. Qualitatively different behavior between warm events and cold events exists in the tropical Indian and Atlantic Oceans and in the extratropical Pacific. Even in the tropical Pacific statistically significantly different behavior is found in some variables for particular regions and phases of the life cycles. A single-mode regression analysis of the ENSO signal is done; the patterns are very similar to those of previously published ENSO EOF and regression analyses. The authors describe how the regression patterns obscure many of the interesting life cycles and life cycle differences of cold events and warm events. Most of the regression structures outside of the tropical Pacific are not statistically significant because of such differences. ENSO models should be evaluated against their ability to reproduce the observed cold event and warm event life cycles and not just single EOF or regression mode patterns.
A multi-model ensemble-based system for seasonal-to-interannual prediction has been developed in a joint European project known as DEMETER (Development of a European Multimodel Ensemble Prediction System for Seasonal to Interannual Prediction). The DEMETER system comprises seven global atmosphere–ocean coupled models, each running from an ensemble of initial conditions. Comprehensive hindcast evaluation demonstrates the enhanced reliability and skill of the multimodel ensemble over a more conventional single-model ensemble approach. In addition, innovative examples of the application of seasonal ensemble forecasts in malaria and crop yield prediction are discussed. The strategy followed in DEMETER deals with important problems such as communication across disciplines, downscaling of climate simulations, and use of probabilistic forecast information in the applications sector, illustrating the economic value of seasonal-to-interannual prediction for society as a whole.
http://journals.ametsoc.org/doi/abs/10.1175/BAMS-85-6-853
Climatic changes associated with the El Nino Southern Oscillation (ENSO) can have a dramatic impact on terrestrial ecosystems worldwide, but especially on arid and semiarid systems, where productivity is strongly limited by precipitation. Nearly two decades of research, including both short-term experiments and long-term studies conducted on three continents, reveal that the initial, extraordinary increases in primary productivity percolate up through entire food webs, attenuating the relative importance of top-down control by predators, providing key resources that are stored to fuel future production, and altering disturbance regimes for months or years after ENSO conditions have passed. Moreover, the ecological changes associated with ENSO events have important implications for agroecosystems, ecosystem restoration, wildlife conservation, and the spread of disease. Here we present the main ideas and results of a recent symposium on the effects of ENSO in dry ecosystems, which was convened as part of the First Alexander von Humboldt International Conference on the El Nino Phenomenon and its Global Impact.
A hierarchy of EI Niiio-Southern Oscillation (ENSO) prediction schemes has been developed during the Tropical Ocean-Global Atmosphere (TOGA) program which includes statistical schemes and physical mOdels. The statistical models are, in general, based on linear statistical techniques and can be classified into models which use atmospheric (sea level pressure or surface wind) or oceanic (Sea swface temperatUre or a measure of upper ocean heat content) quantities or a combination of oceanic and atmospheric quantities as predictors. The physical models consist of coupled QCean-atmosphere mOdels of varying degrees of complexity, ranging from simplified coupled models c¥-the "shallow water" type to coupled general circulation models. All models, statistical and physical, perform considerably better than the persistence forecast in predicting typical indices of ENSO on lead times of 6 to 12 months. The TOGA program can be regarded as a success from this perspective. However, despite the demonstrated predictability, little is known about ENSO predictability limits and the predictability of phenomena outside the tropical Pacific. Furthermore, the predictability of anomalous features known to be associated with ENSO (e.g., Indian monsoon and Sahel rainfall, southern African drought, and off.,equatorial sea surface temperatUre) needs to be addressed in more detail. As well, the relative importance of different physical mechanisms (in the ocean or atmosphere) has yet to be established A seasonal dependence m predictability is seen in many models, but the processes responsible for it are not fully understood, and its meaning is still a matter of scientific discussion. Likewise, a marked decadal variation in skill is observed, and the reasons for this are still under investigation. FinallY, the different prediction models yield similar skills, although they are initialized quite differently. The reasons for these differences are also unclear.
The European Centre for Medium-Range Weather Forecasts (ECMWF) has made seasonal forecasts since 1997 with ensembles of a coupled ocean-atmosphere model (S1). In January 2002, a new version (S2) was introduced. For the calibration of these models, hindcasts have been performed starting in 1987, so that 15 years of hindcasts and forecasts are now available for verification.
Seasonal predictability is to a large extent due to the El Niño - Southern Oscillation (ENSO) climate oscillations. ENSO predictions of the ECMWF models are compared with those of statistical models, some of which are used operationally. The relative skill depends strongly on the season. The dynamical models are better at forecasting the onset of El Niño or La Niña in boreal spring to summer. The statistical models are comparable at predicting the evolution of an event in boreal fall and winter.
The modelled El Niño–mean state–seasonal cycle interactions in 23 coupled ocean–atmosphere GCMs, including the recent IPCC
AR4 models, are assessed and compared to observations and theory. The models show a clear improvement over previous generations
in simulating the tropical Pacific climatology. Systematic biases still include too strong mean and seasonal cycle of trade
winds. El Niño amplitude is shown to be an inverse function of the mean trade winds in agreement with the observed shift of
1976 and with theoretical studies. El Niño amplitude is further shown to be an inverse function of the relative strength of
the seasonal cycle. When most of the energy is within the seasonal cycle, little is left for inter-annual signals and vice
versa. An interannual coupling strength (ICS) is defined and its relation with the modelled El Niño frequency is compared
to that predicted by theoretical models. An assessment of the modelled El Niño in term of SST mode (S-mode) or thermocline
mode (T-mode) shows that most models are locked into a S-mode and that only a few models exhibit a hybrid mode, like in observations.
It is concluded that several basic El Niño–mean state–seasonal cycle relationships proposed by either theory or analysis of
observations seem to be reproduced by CGCMs. This is especially true for the amplitude of El Niño and is less clear for its
frequency. Most of these relationships, first established for the pre-industrial control simulations, hold for the double
and quadruple CO2 stabilized scenarios. The models that exhibit the largest El Niño amplitude change in these greenhouse gas (GHG) increase
scenarios are those that exhibit a mode change towards a T-mode (either from S-mode to hybrid or hybrid to T-mode). This follows
the observed 1976 climate shift in the tropical Pacific, and supports the—still debated—finding of studies that associated
this shift to increased GHGs. In many respects, these models are also among those that best simulate the tropical Pacific
climatology (ECHAM5/MPI-OM, GFDL-CM2.0, GFDL-CM2.1, MRI-CGM2.3.2, UKMO-HadCM3). Results from this large subset of models suggest
the likelihood of increased El Niño amplitude in a warmer climate, though there is considerable spread of El Niño behaviour
among the models and the changes in the subsurface thermocline properties that may be important for El Niño change could not
be assessed. There are no clear indications of an El Niño frequency change with increased GHG.
The Pacific Decadal Oscillation (PDO) has been described by some as a long-lived El Niño-like pattern of Pacific climate variability, and by others as a
blend of two sometimes independent modes having distinct spatial and temporal characteristics of North Pacific sea surface
temperature (SST) variability. A growing body of evidence highlights a strong tendency for PDO impacts in the Southern Hemisphere,
with important surface climate anomalies over the mid-latitude South Pacific Ocean, Australia and South America. Several independent
studies find evidence for just two full PDO cycles in the past century: “cool” PDO regimes prevailed from 1890–1924 and again
from 1947–1976, while “warm” PDO regimes dominated from 1925–1946 and from 1977 through (at least) the mid-1990's. Interdecadal
changes in Pacific climate have widespread impacts on natural systems, including water resources in the Americas and many
marine fisheries in the North Pacific. Tree-ring and Pacific coral based climate reconstructions suggest that PDO variations—at
a range of varying time scales—can be traced back to at least 1600, although there are important differences between different
proxy reconstructions. While 20th Century PDO fluctuations were most energetic in two general periodicities—one from 15-to-25
years, and the other from 50-to-70 years—the mechanisms causing PDO variability remain unclear. To date, there is little in
the way of observational evidence to support a mid-latitude coupled air-sea interaction for PDO, though there are several
well-understood mechanisms that promote multi-year persistence in North Pacific upper ocean temperature anomalies.
A semiparametric approach for forecasting streamflow at multiple gaging locations on a river network conditional on climate precursors is developed. The strategy considers statistical forecasts of annual or seasonal streamflow totals at each of the sites and their disaggregation to monthly or higher resolution flows using a k nearest neighbor resampling approach that maintains space-time consistency across the sites and subperiods. An application of the approach to forecasting inflows at six reservoirs in the state of Ceara in northeastern Brazil is presented. The climate precursors used are the NINO3 index for the El Niño-Southern Oscillation and an equatorial Atlantic sea surface temperature index. Forecasts of January through December streamflow are made at three lead times: in January of the same year and in October and July of the preceding year. The skill of the ensemble forecasts generated is evaluated on subsets of the historical data not used for model building. Correlations with the equatorial Atlantic index and with NINO3 translate into useful streamflow forecasts for the next 18 months of reservoir operation and water management.
Westerly wind bursts (WWBs) in the equatorial Pacific occur during the development of most El Niño events and are believed to be a major factor in ENSO’s dynamics. Because of their short time scale, WWBs are normally considered part of a stochastic forcing of ENSO, completely external to the interannual ENSO variability. Recent observational studies, however, suggest that the occurrence and characteristics of WWBs may depend to some extent on the state of ENSO components, implying that WWBs, which force ENSO, are modulated by ENSO itself.
Satellite and in situ observations are used here to show that WWBs are significantly more likely to occur when the warm pool is extended eastward. Based on these observations, WWBs are added to an intermediate complexity coupled ocean–atmosphere ENSO model. The representation of WWBs is idealized such that their occurrence is modulated by the warm pool extent. The resulting model run is compared with a run in which the WWBs are stochastically applied. The modulation of WWBs by ENSO results in an enhancement of the slow frequency component of the WWBs. This causes the amplitude of ENSO events forced by modulated WWBs to be twice as large as the amplitude of ENSO events forced by stochastic WWBs with the same amplitude and average frequency. Based on this result, it is suggested that the modulation of WWBs by the equatorial Pacific SST is a critical element of ENSO’s dynamics, and that WWBs should not be regarded as purely stochastic forcing. In the paradigm proposed here, WWBs are still an important aspect of ENSO’s dynamics, but they are treated as being partially stochastic and partially affected by the large-scale ENSO dynamics, rather than being completely external to ENSO.
It is further shown that WWB modulation by the large-scale equatorial SST field is roughly equivalent to an increase in the ocean–atmosphere coupling strength, making the coupled equatorial Pacific effectively self-sustained.
Despite the impact of El Nino-Southern Oscillation (ENSO) events on climate in the Indo-Pacific region, models linking ENSO-based climate variability to Indonesian cereal production are not well developed. This study measures connections among sea-surface temperature anomalies (SSTAs), rainfall, and Indonesian rice and corn production from 1971 to 1998. Year-to-year August SSTA fluctuations explain about half the interannual variance in paddy production during the main (wet) season. These effects are cumulative for rice: during strong El Nino years, wet season production shortfalls are not made up subsequently. For corn, the cumulative area sown is actually higher in El Nino years than La Nina years. Indonesia's paddy production varies on average by 1.4 million tons for every 1°C change in August SSTAs. The paper illustrates how an SSTA model might assist policy makers with budgetary processes, and private sector cereal traders with framing production expectations.
Figs (Ficus spp.) and their species-specific pollinators, the fig wasps (Agaonidae), have coevolved one of the most intricate interactions found in nature, in which the fig wasps, in return for pollination services, raise their offspring in the fig inflorescence. Fig wasps, however, have very short adult lives and hence are dependent on the near-continuous production of inflorescences to maintain their populations. From January to March 1998 northern Borneo suffered a very severe drought linked to the El Niño-Southern Oscillation event of 1997-1998. This caused a substantial break in the production of inflorescences on dioecious figs and led to the local extinction of their pollinators at Lambir Hills National Park, Sarawak, Malaysia. Most pollinators had not recolonized six months after the drought and, given the high level of endemism and wide extent of the drought, some species may be totally extinct. Cascading effects on vertebrate seed dispersers, for which figs are often regarded as keystone resources, and the tree species dependent on their services are also likely. This has considerable implications for the maintenance of biodiversity under a scenario of climate change and greater climatic extremes.
The El Niño-Southern Oscillation (ENSO) is the most potent source of interannual climate variability. Uncertainty surrounding the impact of greenhouse warming on ENSO strength and frequency has stimulated efforts to develop a better understanding of the sensitivity of ENSO to climate change. Here we use annually banded corals from Papua New Guinea to show that ENSO has existed for the past 130,000 years, operating even during "glacial" times of substantially reduced regional and global temperature and changed solar forcing. However, we also find that during the 20th century ENSO has been strong compared with ENSO of previous cool (glacial) and warm (interglacial) times. The observed pattern of change in amplitude may be due to the combined effects of ENSO dampening during cool glacial conditions and ENSO forcing by precessional orbital variations.
In 1997-98, fires associated with an exceptional drought caused by the El Niño/Southern Oscillation (ENSO) devastated large areas of tropical rain forests worldwide. Evidence suggests that in tropical rainforest environments selective logging may lead to an increased susceptibility of forests to fire. We investigated whether this was true in the Indonesian fires, the largest fire disaster ever observed. We performed a multiscale analysis using coarse- and high-resolution optical and radar satellite imagery assisted by ground and aerial surveys to assess the extent of the fire-damaged area and the effect on vegetation in East Kalimantan on the island of Borneo. A total of 5.2 +/- 0.3 million hectares including 2.6 million hectares of forest was burned with varying degrees of damage. Forest fires primarily affected recently logged forests; primary forests or those logged long ago were less affected. These results support the hypothesis of positive feedback between logging and fire occurrence. The fires severely damaged the remaining forests and significantly increased the risk of recurrent fire disasters by leaving huge amounts of dead flammable wood.
There is now ample evidence of the ecological impacts of recent climate change, from polar terrestrial to tropical marine environments. The responses of both flora and fauna span an array of ecosystems and organizational hierarchies, from the species to the community levels. Despite continued uncertainty as to community and ecosystem trajectories under global change, our review exposes a coherent pattern of ecological change across systems. Although we are only at an early stage in the projected trends of global warming, ecological responses to recent climate change are already clearly visible.
This paper assesses the major impacts on human lives and the economy of the United States resulting from weather events attributed to El Niño 1997-98. Southern states and California were plagued by storms, whereas the northern half of the nation experienced much above normal cold season temperatures and below normal precipitation and snowfall. Losses included 189 lives, many due to tornadoes, and the major economic losses were property and crop damages from storms, loss of business by the recreation industry and by snow removal equipment/supplies manufacturers and sales firms, and government relief costs. Benefits included an estimated saving of 850 lives because of the lack of bad winter weather. Areas of major economic benefits (primarily in the nation's northern sections) included major reductions in expenditures (and costs) for natural gas and heating oil, record seasonal sales of retail products and homes, lack of spring flood damages, record construction levels, and savings in highway-based and airline transportation. Further, the nation experienced no losses from major Atlantic hurricanes. The net economic effect was surprisingly positive and less government relief was needed than in prior winters without El Niño influences. The estimated direct losses nationally were about 19 billion The highly accurate long-range predictions issued by the Climate Prediction Center in the summer of 1997 for the winter conditions led to some major benefits. For example, the predictions led California to conduct major mitigation efforts and the results suggest these led to a major reduction in losses. Several utilities in the northern United States used the winter forecasts to alter their strategy for purchasing natural gas, leading to major savings to their customers.
The response of El Niño to natural radiative forcing changes over the past 1000 yr is investigated based on numerical experiments employing the Zebiak-Cane model of the tropical Pacific coupled ocean-atmosphere system. Previously published empirical results demonstrating a statistically significant tendency toward El Niño conditions in response to past volcanic radiative forcing are reproduced in the model experiments. A combination of responses to past changes in volcanic and solar radiative forcing closely reproduces changes in the mean state and interannual variability in El Niño in past centuries recorded from fossil corals. The dynamics of El Niño thus appear to have played an important role in the response of the global climate to past changes in radiative forcing.
Hurricanes result in considerable damage in the United States. Previous work has shown that Atlantic hurricane landfalls in the United States have a strong relationship with the El Niño-Southern Oscillation phenomena. This paper compares the historical record of La Niña and El Niño events defined by eastern Pacific sea surface temperature with a dataset of hurricane losses normalized to 1997 values. A significant relationship is found between the ENSO cycle and U.S. hurricane losses, with La Niña years exhibiting much more damage. Used appropriately, this relationship is of potential value to decision makers who are able to manage risk based on probabilistic information.
This pedagogical note reminds the reader that the interpretation of climate records is dependent upon understanding the behavior of stochastic processes. In particular, before concluding that one is seeing evidence for trends, shifts in the mean, or changes in oscillation periods, one must rule out the purely random fluctuations expected from stationary time series. The example of the North Atlantic oscillation (NAO) is mainly used here: the spectral density is nearly white (frequency power law s-0.2) with slight broadband features near 8 and 2.5 yr. By generating synthetic but stationary time series, one can see exhibited many of the features sometimes exciting attention as being of causal climate significance. Such a display does not disprove the hypothesis of climate change, but it provides a simple null hypothesis for what is seen. In addition, it is shown that the linear predictive skill for the NAO index must be very slight (less than 3% of the variance). A brief comparison with the Southern Oscillation shows a different spectral distribution, but again a simulation has long periods of apparent systematic sign and trends. Application of threshold-crossing statistics (Ricean) shows no contradiction to the assumption that the Darwin pressure record is statistically stationary.
A 1000-yr integration of a coupled ocean atmosphere model (ECHO-G) has been analyzed to describe decadal to multidecadal variability in equatorial Pacific sea surface temperature (SST) and thermocline depth (Z20), and their relationship to decadal modulations of El Niño Southern Oscillation (ENSO) behavior. Although the coupled model is characterized by an unrealistically regular 2-yr ENSO period, it exhibits significant modulations of ENSO amplitude on decadal to multidecadal time scales.The authors' main finding is that the structures in SST and Z20 characteristic of tropical Pacific decadal variability (TPDV) in the model are due to an asymmetry between the anomaly patterns associated with the model's El Niño and La Niña states, with this asymmetry reflecting a nonlinearity in ENSO variability. As a result, the residual (i.e., the sum) of the composite El Niño and La Niña patterns exhibits a nonzero dipole structure across the equatorial Pacific, with positive perturbation values in the east and negative values in the west for SST and Z20. During periods when ENSO variability is strong, this difference manifests itself as a rectified change in the mean state.For comparison, a similar analysis was applied to a gridded SST dataset spanning the period 1871 1999. The data confirms that the asymmetry between the SST anomaly patterns associated with El Niño and La Niña for the model is realistic. However, ENSO in the observations is weaker and not as regular as in the model, and thus the changes due to ENSO asymmetries for the observations can only be detected in the Niño-12 region.
Analysis of a suite of atmospheric GCM experiments for 1950-94 shows that both the tropical and the extratropical wintertime climate respond nonlinearly with respect to opposite phases of ENSO. Such behavior is found to be reproducible among four different GCMs studied and confirms that several observed asymmetries in wintertime anomalies with respect to ENSO phases are symptomatic of nonlinearity rather than sampling error.Nonlinearity in the tropical Pacific rainfall response is related to an SST threshold for convection that leads to saturation at modestly cold SST forcing but a linear increase for warmer SST forcing. A spatial shift in the rainfall response is also a feature of the various GCMs' nonlinear behavior, that is, accentuated by the large zonal gradient of climatological SSTs across the equatorial Pacific and the fact that convection responds to the total rather than the anomalous SST.Regarding upper-tropospheric teleconnection responses over the Pacific-North American region, nonlinearity exists in both the strength of the midlatitude response and its spatial phase. The four GCMs are found to be unanimous in having a 500-mb height response whose amplitude is roughly double for extreme warm tropical Pacific SSTs as compared with extreme cold SST forcing. The longitudinal phase of the GCMs' teleconnections is also shifted eastward during warm events as compared with cold events, though this displacement is smaller than that observed.Further analysis of model simulations reveals that nonlinearity in climate responses emerges mainly for stronger ENSO events, and a predominantly linear response is found for weaker tropical Pacific SST forcing. In particular, climate simulations using both realistic and idealized SSTs indicate that tropical Pacific SST anomalies greater than one standard deviation of the interannual variation are required for initiating an appreciable nonlinear climate response.
In order to determine the interannual and decadal changes in the air-sea carbon fluxes of the equatorial Pacific, we developed seasonal and interannual relationships between the fugacity of CO2 (fCO2) and sea surface temperature (SST) from shipboard data that were applied to high-resolution temperature fields deduced from satellite data to obtain high-resolution large-scale estimates of the regional fluxes. The data were gathered on board research ships from November 1981 through June 2004 between 95°W and 165°E. The distribution of fCO2sw during five El Niño periods and four La Niña periods were documented. Observations made during the warm boreal winter-spring season and during the cooler boreal summer-fall season of each year enabled us to examine the interannual and seasonal variability of the fCO2sw-SST relationships. A linear fit through all of the data sets yields an inverse correlation between SST and fCO2sw, with both interannual and seasonal differences in slope. On average, the surface water fCO2 in the equatorial region has been increasing at a rate similar to the atmospheric CO2 increase. In addition, there appears to be a slight increase (~27%) in the outgassing flux of CO2 after the 1997-1998 Pacific Decadal Oscillation (PDO) regime shift. Most of this flux increase is due to increase in wind speeds after the spring of 1998, although increases in fCO2sw after 1998 are also important. These increases are coincident with the recent rebound of the shallow water meridional overturning circulation in the tropical and subtropical Pacific after the regime shift.
An overview is presented of the principal features of the El Niño–Southern Oscillation (ENSO) teleconnections in terms of regional patterns of surface temperature, precipitation and mid-tropospheric atmospheric circulation. The discussion is cast in the context of variations in the associations over time, with decadal scale changes emphasized. In the five decades or so for which we have adequate records to reliably analyse the global aspects of ENSO effects on regional climates around the world, we have witnessed one major decadal scale change in the overall pattern of sea-surface temperatures (SST) in the global ocean, and concomitant changes in the atmospheric response to those changes. The analysis underscores the connection between low frequency changes in tropical SST, ENSO and decadal scale changes in the general atmospheric circulation, pointing to the complex interplay between the canonical ENSO system, slow changes in SST in the Indo-Pacific over the last century, and long-term changes in the atmospheric circulation itself. Published in 2001 by John Wiley & Sons, Ltd.
El Niño events (warm) are often stronger than La Niña events (cold). This asymmetry is an intrinsic nonlinear characteristic of the El Niño-Southern Oscillation (ENSO) phenomenon. In order to measure the nonlinearity of ENSO, the maximum potential intensity (MPI) index and the nonlinear dynamic heating (NDH) of ENSO are proposed as qualitative and quantitative measures. The 1997/98 El Niño that was recorded as the strongest event in the past century and another strong El Nin̄o event in 1982/83 nearly reached the MPI. During these superwarming events, the normal climatological conditions of the ocean and atmosphere were collapsed completely. The huge bursts of ENSO activity manifested in these events are attributable to the nonlinear dynamic processes. Through a heat budget analysis of the ocean mixed layer it is found that throughout much of the ENSO episodes of 1982/83 and 1997/98, the DH strengthened these warm events and weakened subsequent La Nin̄a events. This led to the warm-cold asymmetry. It is also found that the eastward-propagating feature in these two El Niño events provided a favorable phase relationship between temperature and current that resulted in the strong nonlinear dynamical warming. For the westward-propagating El Nin̄o events prior to the late 1970s (e.g., 1957/58 and 1972/73 ENSOs) the phase relationships between zonal temperature gradient and current and between the surface and subsurface temperature anomalies are unfavorable for nonlinear dynamic heating, and thereby the ENSO events are not strong.
During the 1997–98 El Niño, the equatorial Pacific Ocean retained 0.7 × 1015 grams of carbon that normally would have been lost to the atmosphere as carbon dioxide. The surface ocean became impoverished
in plant nutrients, and chlorophyll concentrations were the lowest on record. A dramatic recovery occurred in mid-1998, the
system became highly productive, analogous to coastal environments, and carbon dioxide flux out of the ocean was again high.
The spatial extent of the phytoplankton bloom that followed recovery from El Niño was the largest ever observed for the equatorial
Pacific. These chemical and ecological perturbations were linked to changes in the upwelling of nutrient-enriched waters.
The description and explanation of these dynamic changes would not have been possible without an observing system that combines
biological, chemical, and physical sensors on moorings with remote sensing of chlorophyll.
A major accomplishment of the recently completed Tropical Ocean-Global Atmosphere (TOGA) Program was the development of an ocean observing system to support seasonal-to-interannual climate studies. This paper reviews the scientific motivations for the development of that observing system, the technological advances that made it possible, and the scientific advances that resulted from the availability of a significantly expanded observational database. A primary phenomenological focus of TOGA was interannual variability of the coupled ocean-atmosphere system associated with El Niño and the Southern Oscillation (ENSO). Prior to the start of TOGA, our understanding of the physical processes responsible for the ENSO cycle was limited, our ability to monitor variability in the tropical oceans was primitive, and the capability to predict ENSO was nonexistent. TOGA therefore initiated and/or supported efforts to provide real-time measurements of the following key oceanographic variables: surface winds, sea surface temperature, subsurface temperature, sea level and ocean velocity. Specific in situ observational programs developed to provide these data sets included the Tropical Atmosphere-Ocean (TAO) array of moored buoys in the Pacific, a surface drifting buoy program, an island and coastal tide gauge network, and a volunteer observing ship network of expendable bathythermograph measurements. Complementing these in situ efforts were satellite missions which provided near-global coverage of surface winds, sea surface temperature, and sea level. These new TOGA data sets led to fundamental progress in our understanding of the physical processes responsible for ENSO and to the development of coupled ocean-atmosphere models for ENSO prediction.
Critical reviews of forecasts of ENSO conditions, based on a set of 15 dynamical and statistical models, are given for the 1997-98 El Niño event and the initial stages of the 1998-99 La Niña. While many of the models forecasted some degree of warming one to two seasons prior to the onset of the El Niño in boreal spring of 1997, none predicted its strength until the event was already becoming very strong in late spring. Neither the dynamical nor the statistical models, as groups, performed significantly better than the other during this episode. The best performing statistical models and dynamical models forecast SST anomalies of about +1°C (vs 2.5°-3° observed) in the Niño 3.4 region prior to any observed positive anomalies. The most comprehensive dynamical models performed better than the simple dynamical models. Once the El Niño had developed in mid-1997, a larger set of models was able to forecast its peak in late 1997 and dissipation and reversal to cold conditions in late spring/early summer 1998. Overall, however, skill for these recent two years does not appear greater than that found over an earlier (1982-93) period. In both cases, median model correlation skill averaged over lead times of one to three seasons is near or just above 0.6.Because ENSO extremes usually develop in boreal spring or early summer and persist through the following winter, forecasting impact tendencies in extratropical North America for winter (when impacts are most pronounced) at 5 months of lead time is not difficult, requiring only good observations of the summer ENSO state and knowledge of the winter teleconnections. Because of the strength of the 1997-98 El Niño and the consequent skill of 5-month lead forecasts of U.S. winter 1997-98 impacts, the success of these forecasts was noticed to an unprecedented extent by the general public. However, forecasting impacts in austral winter that occur simultaneously with the initial appearance of an ENSO extreme (e.g., in Chile, Uruguay, Kiribati, Ecuador, and Peru) require forecasting the boreal spring/summer onset of ENSO events themselves at several months of lead time. This latter task is formidable, as evidenced by the fact that formal announcements of an El Niño did not occur until May, leaving little time for users in the above regions to prepare.Verbal summaries of ENSO forecasts issued to users worldwide during the 1997-98 El Niño event contained ambiguities. To address the needs for forecasts to be expressed verbally for nontechnical users and also to be precise enough for meaningful utility and verification, a simple numerically based verbal classification system for describing ENSO-related forecasts is presented.
The primary focus of this review is tropical-extratropical interactions and especially the issues involved in determining the response of the extratropical atmosphere to tropical forcing associated with sea surface temperature (SST) anomalies. The review encompasses observations, empirical studies, theory and modeling of the extratropical teleconnections with a focus on developments over the Tropical Oceans-Global Atmosphere (TOGA) decade and the current state of understanding. In the tropical atmosphere, anomalous SSTs force anomalies in convection and large-scale overturning with subsidence in the descending branch of the local Hadley circulation. The resulting strong upper tropospheric divergence in the tropics and convergence in the subtropics act as a Rossby wave source. The climatological stationary planetary waves and associated jet streams, especially in the northern hemisphere, can make the total Rossby wave sources somewhat insensitive to the position of the tropical heating that induces them and thus can create preferred teleconnection response patterns, such as the Pacific-North American (PNA) pattern. However, a number of factors influence the dispersion and propagation of Rossby waves through the atmosphere, including zonal asymmetries in the climatological state, transients, and baroclinic and nonlinear effects. Internal midlatitude sources can amplify perturbations. Observations, modeling, and theory have clearly shown how storm tracks change in response to changes in quasi-stationary waves and how these changes generally feedback to maintain or strengthen the dominant perturbations through vorticity and momentum transports. The response of the extratropical atmosphere naturally induces changes in the underlying surface, so that there are changes in extratropical SSTs and changes in land surface hydrology and moisture availability that can feedback and influence the total response. Land surface processes are believed to be especially important in spring and summer. Anomalous SSTs and tropical forcing have tended to be strongest in the northern winter, and teleconnections in the southern hemisphere are weaker and more variable and thus more inclined to be masked by natural variability. Occasional strong forcing in seasons other than winter can produce strong and identifiable signals in the northern hemisphere and, because the noise of natural variability is less, the signal-to-noise ratio can be large. The relative importance of tropical versus extratropical SST forcings has been established through numerical experiments with atmospheric general circulation models (AGCMs). Predictability of anomalous circulation and associated surface temperature and precipitation in the extratropics is somewhat limited by the difficulty of finding a modest signal embedded in the high level of noise from natural variability in the extratropics, and the complexity and variety of the possible feedbacks. Accordingly, ensembles of AGCM runs and time averaging are needed to identify signals and make predictions. Strong anomalous tropical forcing provides opportunities for skillful forecasts, and the accuracy and usefulness of forecasts is expected to improve as the ability to forecast the anomalous SSTs improves, as models improve, and as the information available from the mean and the spread of ensemble forecasts is better utilized.
"Late Victorian Holocausts" focuses on three zones of drought and subsequent famine: India, Northern China and North-Eastern Brazil. All of these countries were effected by the same global climatic factors that caused massive crop failures, and all experienced brutal famines that decimated the populations. The effects of drought were magnified in each case because of singularly destructive policies promulgated by different ruling elites. The author, Mike Davis, argues that the seeds of underdevelopment in what later became known as "The Third World" were sown in this era of high imperialism, as the price for Capitalist modernization was paid in the currency of millions of peasants' lives.
After early ideas that saw El Niños as isolated events, the advent of coupled models brought the conception of ENSO as a cycle in which each phase led to the next in a self-sustained oscillation. Twenty-two years of observations that represent the El Niño and La Niña peaks (east Pacific SST) and the memory of the system (zonal mean warm water volume) suggest a distinct break in the cycle, in which the coupled system is able to remain in a weak La Niña state for up to two years, so that memory of previous influences would be lost. Similarly, while the amplitude of anomalies persists from the onset of a warm event through its termination, there is no such persistence across the La Niña break. These observations suggest that El Niños are in fact event-like disturbances to a stable basic state, requiring an initiating impulse not contained in the dynamics of the cycle itself.
This paper reviews our understanding of how the effects of the El Niño–southern oscillation (ENSO) might be transmitted from the tropical Pacific Ocean to the Antarctic, and examines the evidence for such signals in the Antarctic meteorological, sea ice, ice core and biological records. Many scientific disciples concerned with the Antarctic require an understanding of how the climatic conditions in the tropical and mid‐latitude regions affect the Antarctic, and it is hoped that this review will aid their work.
The most pronounced signals of ENSO are found over the southeast Pacific as a result of a climatological Rossby wave train that gives positive (negative) height anomalies over the Amundsen–Bellingshausen Sea during El Niño (La Niña) events. However, the extra‐tropical signature can sometimes show a high degree of variability between events in this area. In West Antarctica, links between ENSO and precipitation have shown variability on the decadal time scale. Across the continent itself, it is even more difficult to relate meteorological conditions to ENSO, yet analyses of the long meteorological records from the stations do indicate a distinct switch in sign of the pressure anomalies from positive to negative across the minimum in the southern oscillation index.
The oceanic signals of ENSO around the Antarctic are less clear, but it has been suggested that the Antarctic circumpolar wave could be forced by the phenomenon.
Ice‐core data offer the potential to help in understanding the long‐term relationship between ENSO and the climate of the Antarctic, but there are difficulties because of the need to smooth the ice‐core data to overcome the mixing of snow on the surface. Nevertheless, analysis of methylsulphonic acid in a South Pole core has shown high variability on ENSO time scales.
It is clear that some evidence of ENSO can be found in the Antarctic meteorological and ice‐core records; however, many of the relationships tend not to be stable with time, and we currently have a poor understanding of the transfer functions by which such signals arrive at the Antarctic from the tropical Pacific. Copyright © 2004 Royal Meteorological Society
The extent to which European seasonal precipitation is predictable is a topic of scientific and societal importance. Although the potential for seasonal prediction is much less over Europe than in the tropics, it is not negligible. Previous studies suggest that European seasonal precipitation skill may peak in the spring (March–April–May) period, this being the season when El Niño–Southern Oscillation (ENSO) teleconnections to the North Atlantic and European sector are at their strongest. Examination of the correlation significance and temporal stability of contemporaneous and lagged ENSO links to European and North African precipitation over 98 years confirms this to be the case. The strongest ENSO links are found across the central European region (45°N–55°N,35°E–5°W). These links are symmetric with the sign of ENSO. Using a linear statistical model employing temporally stable lagged ENSO and lagged local North Atlantic sea surface temperatures as predictors, we compute the forecast skill and significance of central European spring precipitation over 30 independent years. For early March forecasts our model skill is 14–18% better than climatology, which is significant at the 95% level. Copyright © 2002 Royal Meteorological Society
This review paper presents an assessment of the current state of knowledge and capability in seasonal climate prediction at the end of the 20th century. The discussion covers the full range of issues involved in climate forecasting, including (1) the theory and empirical evidence for predictability; (2) predictions of surface boundary conditions, such as sea surface temperatures (SSTs) that drive the predictable part of the climate; (3) predictions of the climate; and (4) a brief consideration of the application of climate forecasts. Within this context, the research of the coming decades that seeks to address shortcomings in each area is described. Copyright © 2001 Royal Meteorological Society
The DEMETER multi-model ensemble system is used to investigate the enhancement in seasonal predictability that can be achieved by calibrating single-model ensembles and combining them to issue multi-model predictions. The forecast quality of both deterministic and probabilistic predictions is assessed and compared to the skill of a simple multi-model ensemble where all the single models are equally weighted. Both calibration and combination are carried out using cross-validation. Single-model seasonal ensembles are calibrated using canonical correlation analysis for model adjustment and variance inflation for reliability enhancement. Results indicate that both model adjustment and inflation increase the skill of tropical predictions for single-model ensembles, provided that the training time series are long enough. Some improvements are also found for extratropical areas, although mostly due to an increase of reliability associated with the inflation. The beneficial impact of calibration is smaller for the simple multi-model than for the single-model ensembles due to the relatively high reliability of the former. The raw single-model predictions are also linearly combined using grid-point multiple linear regression to create an optimized multi-model system. Results indicate that the forecast quality of the simple multi-model ensemble is generally difficult to improve using multiple linear regression due to the lack of robustness of the regression coefficients. As in the case of the calibration, longer time series would be preferred to achieve a significant forecast quality improvement. Over the tropics, a multiple linear regression, that uses the principal components of the model anomalies for the target area as predictors indicates a substantial gain in skill even with the available sample size. The implications of these results in an operational context are discussed.
Maintaining a multi-model database over a generation or more of model development provides an important framework for assessing model improvement. Using control integrations, we compare the simulation of the El Nio/Southern Oscillation (ENSO), and its extratropical impact, in models developed for the 2007 Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report with models developed in the late 1990s [the so-called Coupled Model Intercomparison Project-2 (CMIP2) models]. The IPCC models tend to be more realistic in representing the frequency with which ENSO occurs, and they are better at locating enhanced temperature variability over the eastern Pacific Ocean. When compared with reanalyses, the IPCC models have larger pattern correlations of tropical surface air temperature than do the CMIP2 models during the boreal winter peak phase of El Nio. However, for sea-level pressure and precipitation rate anomalies, a clear separation in performance between the two vintages of models is not as apparent. The strongest improvement occurs for the modelling groups whose CMIP2 model tended to have the lowest pattern correlations with observations. This has been checked by subsampling the multi-century IPCC simulations in a manner to be consistent with the single 80-year time segment available from CMIP2. Our results suggest that multi-century integrations may be required to statistically assess model improvement of ENSO. The quality of the El Nio precipitation composite is directly related to the fidelity of the boreal winter precipitation climatology, highlighting the importance of reducing systematic model error. Over North America distinct improvement of El Nio forced boreal winter surface air temperature, sea-level pressure, and precipitation rate anomalies to occur in the IPCC models. This improvement is directly proportional to the skill of the tropical El Nio forced precipitation anomalies.
The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides global monthly measurements of both oceanic phytoplankton chlorophyll biomass and light harvesting by land plants. These measurements allowed the comparison of simultaneous ocean and land net primary production (NPP) responses to a major El Niño to La Niña transition. Between September 1997 and August 2000, biospheric NPP varied by 6 petagrams of carbon per year (from 111 to 117 petagrams of carbon per year). Increases in ocean NPP were pronounced in tropical regions where El Niño–Southern Oscillation (ENSO) impacts on upwelling and nutrient availability were greatest. Globally, land NPP did not exhibit a clear ENSO response, although regional changes were substantial.
For the last decade, climate scientists have improved their skill at predicting seasonal rainfall patterns in many parts of the world based on observations of sea surface temperatures. Making forecasts useful to decision-makers, especially subsistence farmers in developing countries, remains a significant challenge. In this paper, we discuss a set of six constraints limiting the usefulness of forecasts: credibility, legitimacy, scale, cognitive capacity, procedural and institutional barriers, and available choices. We identify how these constraints have in fact limited forecast use so far, and propose means of overcoming them. We then discuss a pilot project in Zimbabwe, where we test our proposals. Drawing from two years’ observation, we offer lessons to guide future efforts at effective forecast communication.
We review forecasts of the future of El Niño and the Southern Oscillation (ENSO), a coupled instability of the ocean–atmosphere system in the tropical Pacific with global impacts. ENSO in the modern world is briefly described, and the physics of the ENSO cycle is discussed. Particular attention is given to the Bjerknes feedback, the instability mechanism which figures prominently in ENSO past and future. Our knowledge of ENSO in the paleoclimate record has expanded rapidly within the last 5 yr. The ENSO cycle is present in all relevant records, going back 130 kyr. It was systematically weaker during the early and middle Holocene, and model studies indicate that this results from reduced amplification in the late summer and early fall, a consequence of the altered mean climate in response to boreal summer perihelion. Data from corals shows substantial decadal and longer variations in the strength of the ENSO cycle within the past 1000 yr; it is suggested that this may be due to solar and volcanic variations in solar insolation, amplified by the Bjerknes feedback. There is some evidence that this feedback has operated in the 20th century and some model results indicate that it will hold sway in the greenhouse future, but it is very far from conclusive. The comprehensive general circulation models used for future climate projections leave us with an indeterminate picture of ENSO's future. Some predict more ENSO activity, some less, with the highly uncertain consensus forecast indicating little change.
Oxygen minimum zones (OMZs) are widespread features in the most productive regions of the world ocean. A holistic view of benthic responses to OMZ conditions will improve our ability to predict ecosystem-level consequences of climatic trends that influence oxygen availability, such as global warming or ENSO-related events. Four stations off Callao, Peru (~12°S, Station A, 305 m; Station B, 562 m; Station C, 830 m and Station D, 1210 m) were sampled to examine the influence of the low bottom-water oxygen concentration and high organic-matter availability within the OMZ (O2 < 0.5 ml L−1) on sediments, benthic communities, and bioturbation. Sampling took place during early January 1998, an intense El Niño period associated with higher-than-normal levels of O2 on the shelf and upper slope.
The 1997-98 El Nino was, by some measures, the strongest on record, with major climatic impacts felt around the world. A newly completed tropical Pacific atmosphere-ocean sphere-ocean observing system documented this El Nino from its rapid onset to its sudden demise in greater detail than was ever before possible. The unprecedented measurements challenge existing theories about El Nino-related climate swings and suggest why climate forecast models underpredicted the strength of the El Nino before its onset.
Recent advances in observational and theoretical studies of El Niño have shed light on controversies concerning the possible
effect of global warming on this phenomenon over the past few decades and in the future. El Niño is now understood to be one
phase of a natural mode of oscillation—La Niña is the complementary phase—that results from unstable interactions between
the tropical Pacific Ocean and the atmosphere. Random disturbances maintain this neutrally stable mode, whose properties depend
on the background (time-averaged) climate state. Apparent changes in the properties of El Niño could reflect the importance
of random disturbances, but they could also be a consequence of decadal variations of the background state. The possibility
that global warming is affecting those variations cannot be excluded.
The Sea-viewing Wide Field-of-view Sensor (SeaWiFS) provides global monthly measurements of both oceanic phytoplankton chlorophyll biomass and light harvesting by land plants. These measurements allowed the comparison of simultaneous ocean and land net primary production (NPP) responses to a major El Niño to La Niña transition. Between September 1997 and August 2000, biospheric NPP varied by 6 petagrams of carbon per year (from 111 to 117 petagrams of carbon per year). Increases in ocean NPP were pronounced in tropical regions where El Niño-Southern Oscillation (ENSO) impacts on upwelling and nutrient availability were greatest. Globally, land NPP did not exhibit a clear ENSO response, although regional changes were substantial.
Evolution can be predicted in the short term from a knowledge of selection and inheritance. However, in the long term evolution is unpredictable because environments, which determine the directions and magnitudes of selection coefficients, fluctuate unpredictably. These two features of evolution, the predictable and unpredictable, are demonstrated in a study of two populations of Darwin's finches on the Galápagos island of Daphne Major. From 1972 to 2001, Geospiza fortis (medium ground finch) and Geospiza scandens (cactus finch) changed several times in body size and two beak traits. Natural selection occurred frequently in both species and varied from unidirectional to oscillating, episodic to gradual. Hybridization occurred repeatedly though rarely, resulting in elevated phenotypic variances in G. scandens and a change in beak shape. The phenotypic states of both species at the end of the 30-year study could not have been predicted at the beginning. Continuous, long-term studies are needed to detect and interpret rare but important events and nonuniform evolutionary change.