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ENSO and greenhouse warming
Abstract
The El Nino/Southern Oscillation (ENSO) is the dominant climate phenomenon affecting extreme weather conditions worldwide. Its response to greenhouse warming has challenged scientists for decades, despite model agreement on projected changes in mean state. Recent studies have provided new insights into the elusive links between changes in ENSO and in the mean state of the Pacific climate. The projected slow-down in Walker circulation is expected to weaken equatorial Pacific Ocean currents, boosting the occurrences of eastward-propagating warm surface anomalies that characterize observed extreme El Nino events. Accelerated equatorial Pacific warming, particularly in the east, is expected to induce extreme rainfall in the eastern equatorial Pacific and extreme equatorward swings of the Pacific convergence zones, both of which are features of extreme El Nino. The frequency of extreme La Nina is also expected to increase in response to more extreme El Ninos, an accelerated maritime continent warming and surface-intensified ocean warming. ENSO-related catastrophic weather events are thus likely to occur more frequently with unabated greenhouse-gas emissions. But model biases and recent observed strengthening of the Walker circulation highlight the need for further testing as new models, observations and insights become available.
... The intensity of ENSO is known to be highly uncertain based on climate model projections [8][9][10][11][12] . This uncertainty stems not only from a balance of amplifying and damping feedbacks that govern ENSO and are influenced by climate change 10 , but also from the uncertainty of future anthropogenic aerosol and greenhouse gas (GHG) emissions 13 . ...
... We probe the impacts of anthropogenic aerosols and GHGs on extreme ENSO events because, as per Ref. 9., higher GHG concentrations in future would increase the likelihood of more frequent and intense ENSO events. Furthermore, it has been established that the tropics have a convection temperature threshold 31 . ...
El Niño/Southern Oscillation variability has conspicuous impacts on ecosystems and severe weather. Here, we probe the effects of anthropogenic aerosols and greenhouse gases on El Niño/Southern Oscillation variability during the historical period using a broad set of climate models. Increased aerosols significantly amplify El Niño/Southern Oscillation variability primarily through weakening the mean advection feedback and strengthening the zonal advection and thermocline feedbacks, as linked to a weaker annual cycle of sea surface temperature in the eastern equatorial Pacific. They prevent extreme El Niño events, reduce interannual sea surface temperature skewness in the tropical Pacific, influence the likelihood of El Niño/Southern Oscillation events in April and June and allow for more El Niño transitions to Central Pacific events. While rising greenhouse gases significantly reduce El Niño/Southern Oscillation variability via a stronger sea surface temperature annual cycle and attenuated thermocline feedback. They promote extreme El Niño events, increase SST skewness, and enlarge the likelihood of El Niño/Southern Oscillation peaking in November while inhibiting Central Pacific El Niño/Southern Oscillation events.
... Similarly, changes in the Indian Ocean SST may alter easterly winds and accelerate warming in the western basin, although the frequency and amplitude of the IOD may remain unchanged (Cai et al., 2013). The SST changes are expected to significantly influence weather patterns in Indonesia (Cai et al., 2015). ...
... It is observed that SST increases are more significant in the central and eastern Pacific compared to the western Pacific. This finding is consistent with the research conducted by (Cai et al., 2015). The changes are expected to be more pronounced under the more extreme scenario (SSP5-8.5) ...
Indonesia, as a maritime continent, is vulnerable to environmental disasters such as floods and landslides due to extreme rainfall. This study aims to identify changes in the influence of ENSO and IOD on extreme rainfall across Indonesia, specifically during the September-October-November period. We used rainfall and sea surface temperature data from the CMIP6 climate model for the historical period (1985-2014), near-future (2031-2060), and far-future (2061-2090) projections under SSP2-4.5 and SSP 5-8.5 climate scenarios. The relation between rainfall dan ENSO/IOD was simply defined by linear regression approach. We analyzed the change of influence by comparing the historical and the future condition. The results indicated that the changes in the teleconnection of ENSO and IOD to extreme rainfall in future is consistently negative, except for Java (near-future) and Kalimantan and southern Sumatra (far-future). Our finding revealed that significant changes in the teleconnection varied throughout maritime continent. The maximum change was found in Northern Kalimantan, which reached values of -80 mm/°C due to ENSO and -180 mm/°C due to IOD for near future. These findings highlight the spatial variability in teleconnection changes across Indonesia, underscoring the need for region-specific climate adaptation measures in response to evolving extreme rainfall patterns.
... Figure 1b presents the differences in regressed variable fields between the two periods. The variations in SST anomalies across the equatorial CEP are not significant, indicating that the ENSO intensity remains relatively unchanged, resembling the patterns observed in global warming scenarios [62][63][64][65][66][67] . Compared to the SST anomalies, the positive precipitation anomalies in this region are considerably enhanced, suggesting a southeastward shift of the hook-like positive precipitation pattern, which likely influences the subsequent teleconnection impacts 32,63,65 . ...
... The variations in SST anomalies across the equatorial CEP are not significant, indicating that the ENSO intensity remains relatively unchanged, resembling the patterns observed in global warming scenarios [62][63][64][65][66][67] . Compared to the SST anomalies, the positive precipitation anomalies in this region are considerably enhanced, suggesting a southeastward shift of the hook-like positive precipitation pattern, which likely influences the subsequent teleconnection impacts 32,63,65 . Over the WNP region, there is a significant intensification of the anomalous anticyclone, accompanied by enhanced local negative precipitation anomalies. ...
... The periodic swing in SSTs anomalies between positive to negative extremes leads to two anomalous conditions known as El Niño (warm) and La Niña (cold) events, and the cycle often lasts over 2-7 years. The circulation of SSTs and ENSO events is often accompanied by extremes in local weather patterns such as temperatures, monsoons, and precipitation across the globe [5]. Although ENSO is originated from the central Pacific Ocean, it has farreaching consequences around the world. ...
... In our study, the following sensitivity analyses were applied to validate the chosen parameters: (1) changing the maximum number of lag months (0, 1, 2, 3) for the effect of ENSO on BD, (2) changing the degrees of freedom (14)(15)(16) for the time effect, and (3) changing the df (3)(4)(5) for each meteorological factors in the DLNM model. In order to test the stability of ENSO index in the study, we also performed sensitivity analyses by replacing ENSO indices Niño 3.4 into Niño 3 and Niño 4. Results of these analyses are shown in the Additional file Tables S2 and Figure S9-S10. ...
Background
Increasingly intense weather anomalies associated with interannual climate variability patterns, like El Niño-southern oscillation (ENSO), could exacerbate the occurrence and transmission of infectious diseases. However, research in China remains limited in understanding the impacts and intermediate weather changes of ENSO on bacillary dysentery (BD). This study aimed to reveal the relationship between ENSO, weather conditions, and the incidence of BD, and to identify the potential meteorological pathways moderated by ENSO in the ENSO-BD connections.
Methods
BD disease data and meteorological data, as well as ENSO index, from 2005 to 2020 were obtained for 95 cities in the Yangtze River Basin. We first established the associations between ENSO events and BD, ENSO and weather, as well as weather and BDs using two-stage statistical models. Then, we applied a causal mediation analysis to identify the specific meteorological changes in the ENSO-BD relationship.
Results
In the Yangtze River Basin, both El Niño (IRR: 1.06, 95%CI: 1.04 ~ 1.08) and La Niña (IRR: 1.03, 95%CI: 1.02 ~ 1.05) events were found to increase the risk of BD. Variations of ENSO index were associated with changes in local weather conditions. Both the increases in regional temperatures and rainfall were associated with a higher risk of BD. In the casual mediation analyses, we identified that higher temperatures and excessive rainfall associated with La Niña and El Niño events mediated the ENSO’s effect on BD, with mediation proportions of 38.58% and 34.97%, respectively.
Conclusions
Long-term climate variability, like ENSO, can affect regional weather conditions and lead to an increased risk of BD. We identified the mediating weather patterns in the relationship between ENSO and BD, which could improve targeted health interventions and establish an advanced early warning system in response to the BD epidemic.
... We apply the LIM-based algorithm for causal analysis to study the causal relation between two major climate phenomena the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). ENSO is an interannual climate phenomenon involved in the ocean-atmosphere interaction over the tropical Pacific Ocean [16]. It has been shown that ENSO can influence local weather patterns, increasing disaster risks like droughts and floods in an extreme ENSO event [16,17]. ...
... ENSO is an interannual climate phenomenon involved in the ocean-atmosphere interaction over the tropical Pacific Ocean [16]. It has been shown that ENSO can influence local weather patterns, increasing disaster risks like droughts and floods in an extreme ENSO event [16,17]. Detecting extreme ENSO events requires observations from both the atmosphere and oceans, but the average sea surface temperature (SST) over several regions of the tropical Pacific Ocean has been identified as being important for monitoring such events. ...
Causality analysis is a powerful tool for determining cause-and-effect relationships between variables in a system by quantifying the influence of one variable on another. Despite significant advancements in the field, many existing studies are constrained by their focus on unidirectional causality or Gaussian external forcing, limiting their applicability to complex real-world problems. This study proposes a novel data-driven approach to causality analysis for complex stochastic differential systems, integrating the concepts of Liang-Kleeman information flow and linear inverse modeling. Our method models environmental noise as either memoryless Gaussian white noise or memory-retaining Ornstein-Uhlenbeck colored noise, and allows for self and mutual causality, providing a more realistic representation and interpretation of the underlying system. Moreover, this LIM-based approach can identify the individual contribution of dynamics and correlation to causality. We apply this approach to re-examine the causal relationships between the El Ni\~{n}o-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD), two major climate phenomena that significantly influence global climate patterns. In general, regardless of the type of noise used, the causality between ENSO and IOD is mutual but asymmetric, with the causality map reflecting an ENSO-like pattern consistent with previous studies. Notably, in the case of colored noise, the noise memory map reveals a hotspot in the Ni\~no 3 region, which is further related to the information flow. This suggests that our approach offers a more comprehensive framework and provides deeper insights into the causal inference of global climate systems.
... Changing climate state of the tropical equatorial Pacific Ocean strongly influences ENSO variability and associated feedback processes (Collins et al., 2010;Hua et al., 2015;McPhaden et al., 2006;Sun et al., 2014). Changes in tropical equatorial Pacific SSTs associated with La Niña (El Niño) like conditions are generally governed by strengthened (weakened) Walker circulation (WC) because of strong ocean-atmosphere coupling (Bjerknes, 1969;Cai et al., 2015;Falster et al., 2023;Philander, 1989). To explore the physical mechanisms associated with reduced ENSO variability during the onset of the 4.2 ka event, we quantify changes in the Pacific WC using sea-level pressure (SLP) from the TraCE-21 ka all-forcing simulations (Liu et al., 2009). ...
... In contrast, the tropical SLP shows patterns opposite to those of the present during the onset of the 4.2 ka event and thus an intensification of the WC (Figures 7c and 7d). Given the influence of the mean state in the tropical Pacific on ENSO variability, we suggest that such an intensification of the WC might have contributed to a La Niña-like state, leading to a (Bjerknes, 1969;Cai et al., 2015). ...
Atmosphere‐ocean dynamics in the tropics play a key role in global climate change. An abrupt cooling event that occurred between 4500 and 3900a BP, known as the 4.2 ka event, has long been believed to be linked to changes in sea surface temperatures (SSTs) associated with intensified El Niño and Southern Oscillation (ENSO) variability. However, the precise timing and amplitude of ENSO variability during the 4.2 ka event remain uncertain, largely due to the lack of resolution in records from the ENSO‐sensitive regions. Here we present a 104‐year‐long monthly resolved coral record from the South China Sea that spans from 4400 to 4300 years BP, corresponding to the onset of the 4.2 ka event. Using the Sr/Ca paleo‐thermometry, we show a significant decrease in ENSO variability during this time interval compared to the modern period. The ENSO events decrease in the frequency from one every 3.5 years during the modern era to one every 5.6 years during the onset of the 4.2 ka event, with weaker magnitude in the latter period. This reduction in ENSO variability is largely associated with an intensification of the Pacific Walker circulation. We therefore suggest that ENSO variability was a response to, not a driver of, the development of the 4.2 ka event.
... This phenomenon is also linked to heightened rainfall in the BCS during negative IOD occurrences. These ENSO (El Niño-Southern Oscillation) and IOD (Indian Ocean Dipole) phenomena are expected to undergo changes due to climate change [13,14,38]. Climate change is projected to intensify both La Niña and El Niño events, and, under its influence, extreme El Niño, La Niña, and IOD events will occur more frequently [13,39,40]. ...
... Climate change is projected to intensify both La Niña and El Niño events, and, under its influence, extreme El Niño, La Niña, and IOD events will occur more frequently [13,39,40]. This study highlights These ENSO (El Niño-Southern Oscillation) and IOD (Indian Ocean Dipole) phenomena are expected to undergo changes due to climate change [13,14,38]. Climate change is projected to intensify both La Niña and El Niño events, and, under its influence, extreme El Niño, La Niña, and IOD events will occur more frequently [13,39,40]. ...
Turbidity serves as a crucial indicator of coastal water health and productivity. Twenty years of remote sensing data (2003–2022) from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) satellite were used to analyze the spatial and temporal variations in turbidity, as measured by total suspended matter (TSM), in the Berau Coastal Shelf (BCS), East Kalimantan, Indonesia. The BCS encompasses the estuary of the Berau River and is an integral part of the Coral Triangle, renowned for its rich marine and coastal habitats, including coral reefs, mangroves, and seagrasses. The aim of this research is to comprehend the seasonal and interannual patterns of turbidity and their associations with met-ocean parameters, such as wind, rainfall, and climate variations like the El Niño–Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). The research findings indicate that the seasonal spatial pattern of turbidity is strongly influenced by monsoon winds, while its temporal patterns are closely related to river discharge and rainfall. The ENSO and IOD climate cycles exert an influence on the interannual turbidity variations, with turbidity values decreasing during La Niña and negative IOD events and conversely increasing during El Niño and positive IOD events. Furthermore, the elevated turbidity during negative IOD and La Niña coincides with rising temperatures, potentially acting as a compound stressor on marine habitats. These findings significantly enhance our understanding of turbidity dynamics in the BCS, thereby supporting the management of marine and coastal ecosystems in the face of changing climatic and environmental conditions.
... • C), strong EI Niño (ONI = 1.5-1.9 • C), very strong EI Niño (ONI ≥ 2 • C), weak La Niña (ONI = −0.5 to −0.9 • C), moderate La Niña (ONI = −1 to −1.4 • C), strong La Niña (ONI = −1.5 to −1.9 • C), very strong La Niña (ONI ≤ −2 • C) [59][60][61][62][63]. We characterized the pCO 2 sw and FCO 2 dynamics during these ENSO events in the four representative regions including warm pool, cold tongue, as well as the tropical North and South Pacific (Boxes 1-4 in Figure 1), and we also analyzed the data series specifically in Niño 3, Niño 3.4, and Niño 4. It should be noted that regions of Niño 3 and Niño 3.4 fall entirely in the cold tongue region, while Niño 4 partially covered both the warm pool and cold tongue region. ...
The equatorial Pacific serves as the world’s largest oceanic source of CO2. The contrasting ocean environment in the eastern (i.e., upwelling) and western (i.e., warm pool) regions makes it difficult to fully characterize its CO2 dynamics with limited in situ observations. In this study, we addressed this challenge using monthly surface partial pressure of CO2 (pCO2sw) and air-sea CO2 fluxes (FCO2) data products reconstructed from satellite and reanalysis data at a spatial resolution of 1° × 1° in the period of 1982–2021. We found that during the very strong El Niño events (1997/1998, 2015/2016), both pCO2sw and FCO2 showed a significant decrease of 41–58 μatm and 0.5–0.8 mol·m⁻²·yr⁻¹ in the eastern equatorial Pacific, yet they remained at normal levels in the western equatorial Pacific. In contrast, during the very strong La Niña events (1999/2000, 2007/2008, and 2010/2011), both pCO2sw and FCO2 showed a strong increase of 40–48 μatm and 1.0–1.4 mol·m⁻²·yr⁻¹ in the western equatorial Pacific, yet with little change in the eastern equatorial Pacific. In the past 40 years, pCO2sw in the eastern equatorial Pacific was increasing at a higher rate (2.32–2.51 μatm·yr⁻¹) than that in the western equatorial Pacific (1.75 μatm·yr⁻¹), resulting in an accelerating CO2 outgassing (at a rate of 0.03 mol·m⁻²·yr⁻²) in the eastern equatorial Pacific. We comprehensively analyzed the potential effects of different factors, such as sea surface temperature, sea surface wind speed, and ΔpCO2 in driving CO2 fluxes in the equatorial Pacific, and found that ΔpCO2 had the highest correlation (R ≥ 0.80, at p ≤ 0.05), highlighting the importance of accurate estimates of pCO2sw from satellites. Further studies are needed to constrain the retrieval accuracy of pCO2sw in the equatorial Pacific from satellite remote sensing.
... The index mentioned, as stated by Aguilar et al. (2012), is extensively utilized in the field of remote sensing (Rouse et al., 1973). NDVI , a very effective measure of vegetation and greenness, is utilized for evaluating the ecological environment (Cai et al., 2015), capturing vegetation phenology (Hmimina et al., 2013;Vrieling et al., 2018), and determining land cover. It is extensively employed for monitoring the land cover dynamics (Baeza & Paruelo, 2020;Huang et al., 2018). ...
Revealing the status of forests is important for sustainable forest management. The basis of the concept lies in meeting the needs of future generations and today’s generations in the management of forests. The use of remote-sensing (RS) technologies and geographic information systems (GIS) techniques in revealing the current forest structure and in long-term planning of forest areas with multipurpose planning techniques is increasing day by day. Significant technological advances are in allowing programmers to modernize how they manage data. Sentinel-2, which is a relatively new addition to Earth observing satellites, is a new-generation satellite that has enabled classification and monitoring of land cover change with high precision at ease. Visible R, G, B, and near-infrared (NIR) bands have offered exceptional 10-m spatial reasolution, making them suitable for vegetation monitoring along with the additional 20-m bands to spare especially in chlorophyll content analyses. On the contrary, Landsat-8 and ASTER which have been longer lasting in Earth observation were rougher results especially in forestry studies. In this study, Landsat-8 and ASTER satellite images were compared against the Sentinel-2 images as a reference in conjunction with GIS techniques to monitor and assess the impact of various logging procedures, including selective logging and regeneration silviculture. The investigation employed a range of plant vegetation indices, including NDVI, GNDVI, and SAVI, to evaluate the efficacy of image resolution in detecting forest cover changes in the Kastamonu region, where the timber production is the hightest in Turkey. For selective and regeneration activities, satellite images were taken pre-harvesting and immediately post-harvesting, and index maps were produced. NDVI, GNDVI, and SAVI indices were the most accurate indicators of green vegetation change in the Sentinel-2A imagery. Similarly, for the Landsat-8 imagery, the SAVI, NDVI, and GNDVI indices were found to be satisfactory indicators. As for ASTER imagery, the success sequance was like SAVI, GNDVI, and NDVI. Based on the findings of this study, it has been noted that the ASTER imagery closeness to Sentinel-2A was more remarkable in detecting changes in green vegetation in forested areas. The data derived from ASTER imageries demonstrated superior efficacy compared to Landsat-8 in generating forest cover maps, owing to their proximity to those produced by Sentinel-2. The findings also indicated that ASTER imagery, with suitable spatial and spectral resolution, could still be utilized as efficienly as Landsats to generate forest cover density maps and monitor long-term forest conservation practices, particularly in professionally managed forests. Thus, this methodology demonstrated the capacity for efficient worldwide forest management.
... South Africa's geographical position exposes it to the weather phenomenon of the El Niño-Southern Oscillation 7 . The effects of this are likely to intensify due to climate change, and lead to more severe droughts and heavier summer rainfall and flooding 7,8 . Consequently, climate change poses a serious and current threat to the country's food security and its attempts to achieve the Sustainable Development Goal of Zero Hunger (SDG 2) 9 . ...
This series of five policy briefs draws on research conducted by South African and United Kingdom- based researchers within the SHEFS consortium. The series seeks to encourage policy makers working on the commercial broiler chicken system in South Africa to adopt a broad systems-based perspective in their work.
This brief highlights the system’s impact on the environment, and its vulnerability to climate change.
... Especially for the equatorial CP region, an obvious increase in precipitation anomalies is observed, leading to a reduction of SWR into ocean surface, thereby favoring the accelerated decay of local SST during the JF(1) period. However, similar to previous conclusions, the changes of El Niño-related SST anomalies are not evident [56][57][58] (Fig. S11b). ...
... However, many important phenomena are influenced by changing external factors, resulting in time-dependent governing rules. Examples include collective motion of particles and organisms in response to changes in their environment 4,5 , neuronal dynamics under stimuli 6,7 , mixing and coherent structure formation under a time-dependent fluid flow 8,9 , and the variability of the Earth's climate under natural and anthropogenic forcings 10,11 . In response, at the beginning of the previous decade, extensions of operator-theoretic techniques to non-autonomous dynamics were developed 12,13 , enabling the analysis of a much wider class of systems. ...
An important problem in modern applied science is characterizing the behavior of systems with complex internal dynamics subjected to external forcings from their environment. While a great variety of techniques has been developed to analyze such non-autonomous systems, many approaches rely on the availability of ensembles of experiments or simulations in order to generate sufficient information to encapsulate the external forcings. This makes them unsuitable to study important classes of natural systems such as climate dynamics where only a single realization is observed. Here, we show that operator-theoretic techniques previously developed to identify slowly decaying observables of autonomous dynamical systems provide a powerful means for identifying trends and persistent cycles of non-autonomous systems using data from a \emph{single} trajectory of the system. Using systematic mathematical analysis and prototype examples, we demonstrate that eigenfunctions of Koopman and transfer operators provide coordinates that simultaneously capture nonlinear trends and coherent modes of internal variability. In addition, we apply our framework to two real-world examples from present and past climate dynamics: Variability of sea surface temperature (SST) over the industrial era and the mid-Pleistocene transition (MPT) of Quaternary glaciation cycles. Our results provide a nonparametric representation of SST and surface air temperature (SAT) trends over the industrial era, while also capturing the response of the seasonal precipitation cycle to these trends. In addition, our paleo-climate analysis reveals the dominant glaciation cycles over the past 3 million years and the MPT with a high level of granularity.
... Most 5-year flood events occurring in winter could be linked to increased Gulf of Mexico winter storms, which brought heavier precipitation as they moved northward, particularly during strong El Niño years [62][63][64][65]. In the centralto-west regions, a combination of several circulation patterns appears to influence flood-generating mechanisms [66][67][68][69][70]. McCabe and Wolock (2014) [71] found both positive and negative correlations between streamflow variations and large-scale climate patterns, including NINO3.4 sea surface temperatures, the Pacific Decadal Oscillation (PDO), the Atlantic Multi-decadal Oscillation (AMO), the Pacific North American Index (PNA), and the North Atlantic Oscillation (NAO). ...
Accurately estimating flood levels is essential for effective infrastructure design, reservoir management, and flood risk mapping. Traditional methods for predicting these levels often rely on annual maximum flood (AMF) data, which may not always fit well to statistical models. To improve these estimates, we tested an approach that considers floods in relation to annual climate conditions-specifically, average, wet, and dry years-using daily streamflow data. We examined how well the Log Pearson Type III (LP3) distribution, a commonly used statistical model in flood frequency analysis, estimates flood levels when applied to these customized datasets instead of standard AMF data. Our study included over 70 years of data from 2028 basins across the United States, with drainage areas ranging from small (4.0 km 2) to large (50,362 km 2). We found that in some regions, LP3 better estimated frequent floods (recurrence interval of 2 to 25 years) when applied to AMF data. However, for less frequent, larger floods (recurrence interval of 50 to 200 years), the LP3 model worked better when applied to datasets representing wet or dry years. This approach could lead to more reliable flood predictions, which would benefit infrastructure planning and flood preparedness efforts.
... For instance, Schurer et al. [40] demonstrated how the NAO significantly affects winter precipitation patterns across the North Atlantic region, altering storm tracks and precipitation distribution. Similarly, Cai et al. [41] explored the role of ENSO in modulating precipitation in the Pacific and adjacent regions, emphasizing its influence on seasonal variability and extreme weather events. For instance, the observed decreasing trends in some seasons (e.g., winter and spring) align with Huang et al. [39], who reported a significant decrease in PRE over global semi-arid lands. ...
Citation: Ogunrinde, A.T.; Adeyeri, O.E.; Xian, X.; Yu, H.; Jing, Q.; Faloye, O.T. Long-Term Spatiotemporal Trends in Precipitation, Temperature, and Evapotranspiration Across Arid Asia and Africa. Water 2024, 16, 3161. Abstract: This study examines trends in precipitation (PRE), maximum temperature (TMAX), minimum temperature (TMIN), and potential evapotranspiration (PET) using the Modified Mann-Kendall test and Sen's slope estimator between 1901 and 2022 in the arid lands of Central Asia, West Asia and North Africa. The results reveal complex spatial and temporal climate change patterns across the study area. Annual PRE shows a slight negative trend (Z = −0.881, p = 0.378), with significant decreases from 1951-2000 (Z = −3.329, p = 0.001). The temperatures exhibit strong warming trends (TMIN: Z = 9.591, p < 0.001; TMAX: Z = 8.405, p < 0.001). PET increased significantly (Z = 6.041, p < 0.001), with acceleration in recent decades. Spatially, precipitation decreased by 10% in maximum annual values, while PET increased by 10-15% in many areas. Temperature increases of 2-3 • C were observed, with TMAX rising from 36-39 • C to 39-42 • C in some MENA regions. Seasonal analysis shows winter precipitation decreasing significantly in recent years (Z = −1.974, p = 0.048), while summer PET shows the strongest increasing trend (Z = 5.647, p < 0.001). Spatial analysis revealed clear latitudinal gradients in temperature and PET, with higher values in southern regions. PRE patterns were more complex, with coastal and mountainous areas receiving more precipitation. The combination of rising temperatures, increasing PET, and variable PRE trends suggest an overall intensification of aridity in many parts of the region. This analysis provides crucial insights into the climate variability of these water-scarce areas, emphasizing the need for targeted adaptation strategies in water resource management, agriculture, and ecosystem conservation.
... Finally, while ENSO is a well-known driver of warming in the Northeast Pacific, our analysis more specifically relates the likelihood of occurrence and intensity of MHWs in that region to the presence of CP El Niño conditions in the tropical Pacific, especially the longer-lasting conditions. Recent research indicates that the duration and strength of El Niño and La Niña events may increase due to climate change (Cai et al., 2015;Trenberth, 2020). The data generated by long LIM simulations produced several thousand ENSO events of durations longer than 13 months, which offer valuable insights into their potential impacts. ...
Plain Language Summary
Marine heatwaves (MHWs) are periods of prolonged, extremely warm ocean temperatures that have caused widespread ecological and socioeconomic impacts worldwide. The predictability of these events can be improved if we can find connections between regional events and larger climatic drivers, such as El Niño‐Southern Oscillation (ENSO). Both the positive phase of ENSO, El Niño, and its negative phase, La Niña, have been linked to MHWs in various parts of the world. However, not all El Niño and La Niña events are the same, leading to uncertainty in the relationship between ENSO and MHWs. Due to the limited duration of the observational record, a major issue arises with the lack of examples of different types of El Niño and La Niña events in observations. To overcome this challenge, we utilized 10,000 years of simulated data from a near‐global linear inverse model to generate many more samples of possible global ocean temperature configurations. We find strong differences between regional MHWs and different types of El Niño and La Niña events. In some regions, the probability of MHWs is 12 times more likely under long‐lasting El Niño events.
... Due to their subtropical to midlatitude setting, variability is expected to be mainly influenced by the tropics and via annular variability modes. Nevertheless, tropically forced variability primarily arises from the Pacific, and hence, it is not surprising that the North American West Coast and Chile are primarily affected (Cai et al. 2015). Although the El Niño-Southern Oscillation (ENSO) induced variability is global, the other MCRs are in locations remote from the tropical Pacific and/or near nodal lines in ENSO-teleconnections (Taschetto et al. 2020). ...
Mediterranean climate‐type regions (MCRs) are characterised by warm‐to‐hot dry summers and mild‐wet winters. These regions are typically found on the western or southern edges of continents, for example, in the Mediterranean Basin, the west coast of North and South America, southern Africa and southwest Australia. The MCRs are vulnerable to climate variability and change related to their unique characteristics, such as pronounced rainfall seasonality and prolonged hot and dry summers. Based on historical observations and CMIP6 climate projections, we apply an empirical bio‐climatic assessment of how the geographic distribution of MCRs has changed during the last century and how these zones will be further impacted under continued warming. Results indicate a poleward and eastward expansion of MCRs in the Mediterranean Basin, North America‐California and South America‐Central Chile regions. For parts of Southern Africa and Southern Australia, a retreat of the MCR margins and an expansion of more arid climate zones are projected. These shifts are particularly profound according to high emission and radiative forcing pathways and future scenarios. The warming in MCRs is projected to accelerate (e.g., mean regional warming of up to 5.5°C under a 4°C global warming scenario), and precipitation will decrease by about 5%–10% for every additional degree of global warming. One exception is the California MCR, where rainfall will likely increase. Such changes can challenge water resources, food security and other aspects of human livelihood and ecosystems in these unique geographical zones.
... Still, correlations have been found between NE Pacific MHWs and ENSO and other large-scale climate modes such as the PDO, Interdecadal Pacific Oscillation, and North Pacific Gyre Oscillation (Holbrook et al., 2019;Joh & Di Lorenzo, 2017;Ren et al., 2023). Understanding the mechanisms that connect ENSO to MHWs is important because ENSO events are anticipated to change in a future climate, including the possibility of increased El Niño and La Niña occurrence and intensity (Cai et al., 2015;Maher et al., 2023). ...
We use moored observations in 80 m water depth at the NH‐10 site along the historic Newport Hydrographic Line from 1999 to 2021 to calculate water temperature anomalies at the surface, near surface, and bottom. Analysis is focused on the subsurface temporal and spatial characteristics of marine heatwaves (MHWs) during 2014–2016 and 2019–2020 on the continental shelf and slope. Warm anomalies extend throughout the water column in fall/winter 2014–2016 when winds are predominantly downwelling‐favorable, while the 2019–2020 period is characterized by shallower summer and fall anomalies on the shelf. Sustained temperature anomalies during the bottom MHW in late 2016 are the largest in the NH‐10 time series. Analysis of temporal patterns in wind stress during MHW and non‐MHW periods shows the onset of upwelling‐favorable winds interrupts warm events. Indices of cumulative upwelling and annual spring transition dates reveal the spring transition was unusually late in 2014, with only five years with later spring transitions since the upwelling index record began in 1967. In 2015 and 2019, in contrast, spring transition is close to the climatological mean of April 15. In 2016 and 2020, anomalous warming is observed when cumulative upwelling decreases after an early spring transition.
... A natural flood pulse is essential for maintaining environmental heterogeneity, the exchange of functional traits among environments, and ecosystem functions in the Paraná floodplain (Pineda et al. 2019;Diniz et al. 2023). Another point to be considered is that extreme droughts are expected to increase with climate change (Cai et al. 2015;Cavalcantti et al. 2015), which can aggravate this scenario. Predation and spatial components were important for explaining this low functional beta diversity. ...
Floodplains are among the most biodiverse systems on the planet and offer several ecosystem services; however, they are threatened by anthropic actions such as dam construction. We investigated zooplankton taxonomic and functional β-diversity, environmental heterogeneity, and the drivers of β-diversity in response to the hydrological period in the Amazon (without dams) and Paraná (with several dams) floodplains. We also discuss the implications of biodiversity-environment relationships for ecological conservation. We sampled 36 lakes during the drought and rainy periods (72 samples). The 180 zooplankton taxa found were classified into six functional traits. We calculated taxonomic and functional β-diversity (total, replacement, and richness) and the importance of different drivers (physical-chemical variables, food availability, predation, and spatial component). We also determined the environmental heterogeneity in each floodplain and hydrological period. The functional and taxonomic β diversity of the zooplankton community exhibited different patterns in response to the hydrological period. The Amazon floodplain presented greater environmental heterogeneity but not greater beta diversity. The Paraná floodplain presented the lowest functional β diversity during the drought period, where predation and the spatial component were the variables that most explained this variation. A greater contribution of replacement, regardless of the hydrological period, should lead to efforts to preserve as many lakes as possible in both floodplains, as they present unique compositions of species and traits. We emphasize the need to plan conservation strategies in these floodplains, especially considering that dams can lead to homogeneous environmental and biological conditions.
... In addition, natural variability is affected by anthropogenic drivers [47,51]. Many studies suggest that it is likely that the ENSO will intensify [52,53], as will the positive phase of the annular modes [54,55]. These changes in natural variability over the next century can have repercussions on future coastal hazards [56], as well as on the spatial regions defined in this work. ...
Both seasonal and extreme climate conditions are influenced by long-term natural internal variability. However, in general, long-term hazard variation has not been incorporated into coastal risk assessments. There are coastal regions of high interest, such as urban areas, where a large number of people are exposed to hydrometeorological hazards, and ecosystems, which provide protection, where long-term natural variability should be considered a design factor. In this study, we systematized climate analysis to identify high-interest regions where hazard long-term variability should be considered in risk assessment, disaster reduction, and future climate change adaptation and protection designs. To achieve this goal, we examined the effect of the leading modes of climate variability (Arctic Oscillation, Southern Annular Mode, and El Niño–Southern Oscillation) on the variation in the recurrence of extreme coastal hazard events, including as a first step sea surface temperature, winds, and waves. Neglecting long-term variability could potentially lead to the underperformance of solutions, or even irreversible damage that compromises the conditions of ecosystems for which nature-based solutions are designed.
... Accurate prediction of global sea surface temperature at sub-seasonal to seasonal (S2S) timescale is critical for drought and flood forecasting, as well as for improving disaster preparedness in human society [1,2,3] . Government departments or academic studies normally use physics-based numerical models to predict S2S sea surface temperature and corresponding climate indices, such as El Niño-Southern Oscillation. ...
Accurate prediction of global sea surface temperature at sub-seasonal to seasonal (S2S) timescale is critical for drought and flood forecasting, as well as for improving disaster preparedness in human society. Government departments or academic studies normally use physics-based numerical models to predict S2S sea surface temperature and corresponding climate indices, such as El Ni\~no-Southern Oscillation. However, these models are hampered by computational inefficiencies, limited retention of ocean-atmosphere initial conditions, and significant uncertainty and biases. Here, we introduce a novel three-dimensional deep learning neural network to model the nonlinear and complex coupled atmosphere-ocean weather systems. This model incorporates climatic and temporal features and employs a self-attention mechanism to enhance the prediction of global S2S sea surface temperature pattern. Compared to the physics-based models, it shows significant computational efficiency and predictive capability, improving one to three months sea surface temperature predictive skill by 13.7% to 77.1% in seven ocean regions with dominant influence on S2S variability over land. This achievement underscores the significant potential of deep learning for largely improving forecasting skills at the S2S scale over land.
... Looking forward over the 21 st century, the interannual and decadal variability of Walker Circulation in a warming climate remains an open question, given the discrepancy between observations (L' Heureux et al., 2013;Vecchi et al., 2006) and model predictions (Cai et al., 2015a;Heede and Fedorov, 2023). However, recent work (Cai et al., 2021;Cai et al., 2018;Cai et al., 2015b) suggests that La Niña events will become both stronger and more frequent across the 21 st century. ...
... Seasonal variability, spanning 4-12 months, reflects the primary signals of seasonal changes and the annual cycle [5][6][7][8]. The El Niño/Southern Oscillation (ENSO), with 2-7-year cycles, is one of the main drivers of global climate variability on an interannual time scale on an annual basis [9][10][11][12]. In particular, the quasi-biweekly oscillation (QBWO, 10-20 days) and intraseasonal oscillation (ISO, 30-90 days) serve as the bridge linking low-frequency climate variability with synoptic weather systems. ...
The atmosphere exhibits variability across different time scales. Currently, in the field of atmospheric science, statistical filtering is one of the most widely used methods for extracting signals on certain time scales. However, signal extraction based on traditional statistical filters may be sensitive to missing data points, which are particularly common in meteorological data. To address this issue, this study applies a new type of temporal filters based on a one-dimensional convolution neural network (1D-CNN) and examines its performance on reducing such uncertainties. As an example, we investigate the advantages of a 1D-CNN bandpass filter in extracting quasi-biweekly-to-intraseasonal signals (10–60 days) from temperature data provided by the Hong Kong Observatory. The results show that the 1D-CNN achieves accuracies similar to a 121-point Lanczos filter. In addition, the 1D-CNN filter allows a maximum of 10 missing data points within the 60-point window length, while keeping its accuracy higher than 80% (R2 > 0.8). This indicates that the 1D-CNN model works well even when missing data points exist in the time series. This study highlights another potential for applying machine learning algorithms in atmospheric and climate research, which will be useful for future research involving incomplete time series and real-time filtering.
... Heede and Fedorov (2023) studied the response of ENSO to global warming using data from 20 models and four different scenarios, and found that most models showed enhanced ENSO sea surface temperature changes. Extreme El Niño and La Niña events may occur more frequently, and ENSO related catastrophic weather events may occur more frequently (Cai et al. 2015). Occurrence of them can cause anomalies in atmospheric circulation, leading to changes in weather events and driving the formation and development of extreme weather events such as extreme heat waves (Luo et al., 2019) and extreme precipitation (Li et al. 2019). ...
By using ERA5 reanalysis data, this paper combined existing research definitions of gale processes to analyze the variation characteristics of gale processes occurring in the South China Sea region, and to study the response of the gale process to East Pacific sea surface temperature. The results indicate that the gale process shows the significant annual variation and the most frequent in winter and least frequent in summer. While there is no significant trend in the frequency of gale processes in each season. There is a significant negative correlation between the frequency of gale process and the East Pacific sea surface temperature in spring, autumn, and winter. When the sea surface temperature in the eastern Pacific rises abnormally, the frequency of gale processes in the South China Sea decreases. When abnormally high, the frequency of gale process in the South China Sea increases. In summer, this relationship is the opposite. When sea surface temperature is abnormal, the anomalous anticyclone triggered in the western Pacific, and has a weakening effect on the prevailing winds in the South China Sea, leading to a reduction in high wind speed and gale events, thereby reducing the frequency of gale process.
... How ENSO responds to a warming climate has been an important issue in recent decades (Timmermann et al. 1999;Yeh et al. 2009;Collins et al. 2010;Cai et al. 2015Cai et al. , 2021. Under global warming, the oceanic and atmospheric mean states in the tropical Pacific will undergo a series of significant changes, regulating the coupled ocean-atmosphere feedbacks that change the characteristics of ENSO. ...
El Niño‒Southern Oscillation (ENSO) is the leading mode of interannual ocean‒atmosphere coupling in the tropical Pacific, greatly influencing the global climate system. Seasonal phase locking, which means that ENSO events usually peak in boreal winter, is a distinctive feature of ENSO. In model future projections, the ENSO sea surface temperature (SST) amplitude in winter shows no significant change with a large intermodel spread. However, whether and how ENSO phase locking will respond to global warming are not fully understood. In this study, using CESM large ensemble (CESM-LE) projections, we found that the seasonality of ENSO events, especially its peak phase, has advanced under global warming. This phenomenon corresponds to the seasonal difference in the changes in the ENSO SST amplitude with an enhanced (weakened) amplitude from boreal summer to autumn (winter). Mixed layer ocean heat budget analysis revealed that the advanced ENSO seasonality is due to intensified positive meridional advective and thermocline feedback during the ENSO developing phase, and intensified negative thermal damping during the ENSO peak phase. Furthermore, the seasonal variation in the mean El Niño-like SST warming in the tropical Pacific favors a weakened zonal advective feedback in boreal autumn-winter and earlier decay of ENSO. The advance of the ENSO peak phase is also found in most CMIP5/6 models that simulate the seasonal phase locking of ENSO well in the present climate. Thus, even though the amplitude response in the winter shows no model consensus, ENSO also significantly changes during different stages under global warming.
... forecasts are for a turnabout of the El Niño to neutral or La Niña conditions over 2024 (https://www.climate.gov/newsfeatures/blogs/enso/april-2024-enso-update-gone-fishing), suggesting that the probability of another global warming spike in number of El Niños and long La Niñas due to greenhouse gas warming (Cai et al., 2015;DiNezio et al., 2012;Vecchi et al., 2008). If the probability of spikes given these ENSO events remains the same, this would imply that in the future, the 120 number of global warming spikes increases or decreases depending on ENSO frequency changes (Eq. ...
Global-mean surface temperature rapidly increased 0.27 ± 0.05 K from 2022 to 2023. Such an interannual global warming spike is not unprecedented in the observational record with previous instances occurring in 1956–57 and 1976–77. However, why global warming spikes occur is unknown and the rapid global warming of 2023 has led to concerns that it could have been externally driven. Here we show that climate models that are subject only to internal variability can generate such spikes, but they are an uncommon occurrence (𝑝 = 2.6 ± 0.1 %). However, when a prolonged La Niña immediately precedes an El Niño in the simulations, as occurred in nature in 1956–57, 1976–77, 2022–23, such spikes become much more common (𝑝 = 16.5 ± 0.6 %). Furthermore, we find that nearly all simulated spikes (94 %) are associated with El Niño occurring that year. Thus, our results underscore the importance of El Niño/Southern Oscillation in driving the occurrence of global warming spikes such as the one in 2023, without needing to invoke anthropogenic forcing, such as changes in atmospheric concentrations of greenhouse gases or aerosols, as an explanation.
Heat waves have emerged as one of the most severe and destructive meteorological phenomena, significantly threatening human health, agricultural productivity, and ecosystems due to their increasing frequency, duration, and intensity. In India, these extreme events predominantly occur during the pre-monsoon months (March to mid-June), with recent years (2016, 2019, 2022, and 2023) showing a clear intensification in their occurrence. This study aims to explore the dynamics of heat waves, synoptic conditions, surface land-atmosphere interactions, and regional variations in recent years across India, utilizing maximum temperature data from the India Meteorological Department (IMD) and heat wave indices to evaluate their intensity and impact. Analysis of maximum temperature data and heatwave indices highlights a notable rise in heatwave frequency and duration, particularly in northern and central India. The 2-meter (2 m) temperature anomaly in north, central, and southern India exceeded 2.5°C, while the 925hPa temperature showed significant warming trends in north and northwest India. The analysis of the spatial distribution of the planetary boundary layer (PBL) and total cloud cover (TCC) indicates reduced cloud cover and an increased PBL, intensifying heat wave conditions across north and central regions. The warm air advection and sinking air in the descending limb of the Walker circulation ensured a stable and drier atmosphere, favoring heatwave conditions. Moreover, a persistent anticyclonic circulation and its associated high-pressure system enabled heat-trapping within the atmosphere, leading to prolonged and intensified heat wave conditions. The study indicates a shift in the position and strength of the subtropical jet stream (STJ) during these years, highlighting its significant role in developing and intensifying heat waves.
Full article is available here:
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Ocean carbon uptake is crucial to mitigate carbon emissions due to human activities. The internal variability in air-sea CO2 fluxes (FCO2) significantly affects the carbon budget assessment, especially in the tropical Pacific. However, the Coupled Model Intercomparison Project fails to capture real-world interannual variability of FCO2, especially in the tropical Pacific. Based on observed sea surface temperature (SST) in the eastern tropical Pacific, the Pacific Ocean–Global Atmosphere (POGA) experiment reproduces real-world interannual variability in FCO2 consistent with observations in the tropical Pacific. The results show that this variability is dominated by El Niño-Southern Oscillation (ENSO) events by Bjerknes feedback. Dynamic and thermodynamic decompositions further support the nonthermal processes that dominate the interannual variability of FCO2, with stronger upwelling bringing higher dissolved inorganic carbon (DIC) from the subsurface to the surface, increasing the FCO2, and vice versa for downwelling. However, the SST thermal effect is opposite in phase to FCO2 changes, partly offsetting the effects of dynamic processes. Using the observed SST, the POGA experiment also extends the FCO2 datasets to the 1930s, partially overcoming the limitation of observations, and helping us understand interannual to decadal variability and vertical physical processes.
Given its impact on enhanced melting of the Greenland ice sheet, it is crucial to assess changes in frequency and characteristics of summer Greenland blocking. Indeed, the occurrence of such atmospheric pattern has seen a marked increase in recent decades: however, the observed trend is not captured by any simulation from state-of-the-art global climate models. It is therefore paramount to determine whether the lack of trend is caused by a misrepresentation of key physical mechanisms in climate models or whether such trend is mainly attributable to decadal variability, or both. Here we investigate Greenland blocking characteristics in reanalysis (ERA5) and ECMWF seasonal forecasts (SEAS5.1), showing that about 10 % of the 1000 permutations of SEAS5.1 runs can simulate a 43-year trend equal or larger to the ERA5 one: this suggests that the initialization and the higher model resolution contribute to a more realistic representation of the blocking dynamics than in freely-evolving climate runs. To further investigate these aspects, we apply the Peter and Clark momentary conditional independence (PCMCI) algorithm to assess monthly causal pathways. Results show that while the relationship among Arctic temperature, snow cover, Atlantic multidecadal variability and Greenland blocking is consistent both in ERA5 and SEAS5.1, the effect of early snow melt over North America on Greenland blocking is mostly absent in SEAS5.1. Therefore, while it is possible that the observed trend is due to internal decadal variability, the misrepresentation of the snow cover processes may explain the difficulty that SEAS5.1 has in reproducing the observed trend. This deficit in representing the snow impact on the atmospheric circulation might also be the culprit of the missing trend in climate models, raising the question whether long-term projections underestimate a future increase in Greenland blocking and ice melt.
El Niño–Southern Oscillation (ENSO) is a prominent climate phenomenon affecting precipitation patterns across much of the world. Regional ENSO‐precipitation teleconnections are often asymmetric such that the precipitation response to El Niño is stronger or weaker than the response to La Niña. Better understanding of asymmetry in teleconnections can improve the predictability of climate extremes during ENSO events. In this study, we assess the capability of 50 state‐of‐the‐art climate models and a reanalysis against observational data in simulating seasonal differences in asymmetric response of precipitation to ENSO. The analysis is performed across 46 sub‐continental scale regions, using a precipitation composite technique for deriving the asymmetric component of precipitation response. Significant regional and seasonal diversity is found in the asymmetric response to ENSO, both in observations and models. Model performance in simulating the nature of teleconnections is higher than the performance in simulating the associated asymmetry. Model performance in capturing the regional diversity of asymmetry is highest in austral spring. The model biases in asymmetry are related to the inability of the models to accurately simulate the skewness of the heavy tailed local precipitation distributions and Niño3.4 SST distributions. In regions outside the Pacific and Indian Ocean basins, model bias in the skewness of local precipitation variability plays a larger role in model asymmetry bias. This analysis contributes to better understanding the fidelity of CMIP6 models in capturing asymmetry in teleconnections across different seasons and regions which are critical for making skillful projections of floods and droughts in a warming climate.
Climate-driven warming and changes in major ocean currents enable poleward larval transport and range expansions of many marine species. Here, we report the population genetic structure of the gastropod Kelletia kelletii , a commercial fisheries species and subtidal predator with top-down food web effects, whose populations have recently undergone climate-driven northward range expansion. We used reduced representation genomic sequencing (RAD-seq) to genotype 598 adults from 13 locations spanning approximately 800 km across the historical and expanded range of this species. Analyses of 40747 single nucleotide polymorphisms (SNPs) showed evidence for long-distance dispersal of K. kelletii larvae from a central historical range site (Point Loma, CA, USA) hundreds of km into the expanded northern range (Big Creek, CA), which seems most likely to result from transport during an El Niño-Southern Oscillation (ENSO) event rather than consistent on-going gene flow. Furthermore, the high genetic differentiation among some sampled expanded-range populations and their close genetic proximity with distinct populations from the historical range suggested multiple origins of the expanded-range populations. Given that the frequency and magnitude of ENSO events are predicted to increase with climate change, understanding the factors driving changes in population connectivity is crucial for establishing effective management strategies to ensure the persistence of this and other economically and ecologically important species.
Future changes to the year-to-year swings between active and inactive North Atlantic tropical cyclone (TC) seasons have received little attention, yet may have great societal implications in areas prone to hurricane landfalls. This work investigates past and future changes in North Atlantic TC activity, focusing on interannual variability and evaluating the contributions from anthropogenic forcing. We show that interannual variability of Atlantic TC activity has already increased, evidenced by an increase in the occurrence of both extremely active and inactive TC seasons. TC-resolving general circulation models project a 36% increase in the variance of North Atlantic TC activity, measured by accumulated cyclone energy, by the middle of the 21st century. These changes are the result of increased variability in vertical wind shear and atmospheric stability, in response to enhanced Pacific-to-Atlantic interbasin sea surface temperature variations. Robust anthropogenic-forced intensification in the variability of Atlantic TC activity will continue in the future, with important implications for emergency planning and societal preparedness.
The El Niño–Southern Oscillation (ENSO), originating in the central and eastern equatorial Pacific, is a defining mode of interannual climate variability with profound impact on global climate and ecosystems. However, an understanding of how the ENSO might have evolved over geological timescales is still lacking, despite a well-accepted recognition that such an understanding has direct implications for constraining human-induced future ENSO changes. Here, using climate simulations, we show that ENSO has been a leading mode of tropical sea surface temperature (SST) variability in the past 250 My but with substantial variations in amplitude across geological periods. We show this result by performing and analyzing a series of coupled time-slice climate simulations forced by paleogeography, atmospheric CO 2 concentrations, and solar radiation for the past 250 My, in 10-My intervals. The variations in ENSO amplitude across geological periods are little related to mean equatorial zonal SST gradient or global mean surface temperature of the respective periods but are primarily determined by interperiod difference in the background thermocline depth, according to a linear stability analysis. In addition, variations in atmospheric noise serve as an independent contributing factor to ENSO variations across intergeological periods. The two factors together explain about 76% of the interperiod variations in ENSO amplitude over the past 250 My. Our findings support the importance of changing ocean vertical thermal structure and atmospheric noise in influencing projected future ENSO change and its uncertainty.
Global-mean surface temperature rapidly increased 0.29 ± 0.04 K from 2022 to 2023. Such a large interannual global warming spike is not unprecedented in the observational record, with a previous instance occurring in 1976–1977. However, why such large global warming spikes occur is unknown, and the rapid global warming of 2023 has led to concerns that it could have been externally driven. Here we show that climate models that are subject only to internal variability can generate such spikes, but they are an uncommon occurrence (p= 1.6 % ± 0.1 %). However, when a prolonged La Niña immediately precedes an El Niño in the simulations, as occurred in nature in 1976–1977 and 2022–2023, such spikes become much more common (p= 10.3 % ± 0.4 %). Furthermore, we find that nearly all simulated spikes (p= 88.5 % ± 0.3 %) are associated with El Niño occurring that year. Thus, our results underscore the importance of the El Niño–Southern Oscillation in driving the occurrence of global warming spikes such as the one in 2023, without needing to invoke anthropogenic forcing, such as changes in atmospheric concentrations of greenhouse gases or aerosols, as an explanation.
Ocean-driven ice loss from the West Antarctic Ice Sheet is a significant contributor to sea-level rise. Recent ocean variability in the Amundsen Sea is controlled by near-surface winds. We combine palaeoclimate reconstructions and climate model simulations to understand past and future influences on Amundsen Sea winds from anthropogenic forcing and internal climate variability. The reconstructions show strong historical wind trends. External forcing from greenhouse gases and stratospheric ozone depletion drove zonally uniform westerly wind trends centred over the deep Southern Ocean. Internally generated trends resemble a South Pacific Rossby wave train and were highly influential over the Amundsen Sea continental shelf. There was strong interannual and interdecadal variability over the Amundsen Sea, with periods of anticyclonic wind anomalies in the 1940s and 1990s, when rapid ice-sheet loss was initiated. Similar anticyclonic anomalies probably occurred prior to the 20th century but without causing the present ice loss. This suggests that ice loss may have been triggered naturally in the 1940s but failed to recover subsequently due to the increasing importance of anthropogenic forcing from greenhouse gases (since the 1960s) and ozone depletion (since the 1980s). Future projections also feature strong wind trends. Emissions mitigation influences wind trends over the deep Southern Ocean but has less influence on winds over the Amundsen Sea shelf, where internal variability creates a large and irreducible uncertainty. This suggests that strong emissions mitigation is needed to minimise ice loss this century but that the uncontrollable future influence of internal climate variability could be equally important.
In the present study, we developed and validated an experimental life support system (ELSS) designed to investigate coral reef associated bacterial communities. The microcosms in the ELSS consisted of coral reef sediment, synthetic seawater, and specimens of five benthic reef species. These included two hard corals Montipora digitata and Montipora capricornis, a soft coral Sarcophyton glaucum, a zoanthid Zoanthus sp., and a sponge Chondrilla sp.. Physicochemical parameters and bacterial communities in the ELSS were similar to those observed at shallow coral reef sites. Sediment bacterial evenness and higher taxonomic composition were more similar to natural-type communities at days 29 and 34 than at day 8 after transfer to the microcosms, suggesting microbial stabilization after an initial recovery period. Biotopes were compositionally distinct but shared a number of ASVs. At day 34, sediment specific ASVs were found in hosts and visa versa. Transplantation significantly altered the bacterial community composition of M. digitata and Chondrilla sp., suggesting microbial adaptation to altered environmental conditions. Altogether, our results support the suitability of the ELSS developed in this study as a model system to investigate coral reef associated bacterial communities using multi-factorial experiments.
El Niño–Southern Oscillation (ENSO) exhibits a considerable asymmetry in sea surface temperature anomalies (SSTa), as El Niño events tend to be stronger and centered further east than La Niña events. Here, we analyze ENSO asymmetry in observations and preindustrial control integrations of 32 models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Observations indicate a significant link between strong eastern Pacific (EP) El Niño events and the ENSO amplitude and asymmetry. The large CMIP6 database confirms this strong link. Most CMIP6 models suffer from an equatorial Pacific cold SST bias. This cold tongue bias hinders the southward migration of the ITCZ toward the equator over the eastern equatorial Pacific, which is characteristic of strong EP El Niño events in observations. Therefore, many models underestimate the eastern equatorial Pacific rainfall anomalies and simulate a wind stress feedback over the western Pacific that is too weak and too far west. As a result, the cold tongue bias exerts a strong control on the climate models’ ability to generate strong EP El Niño events and therefore on the ENSO overall amplitude and asymmetry. We discuss the relevance of these results in view of a potential increase of strong EP El Niño events under global warming.
Significance Statement
El Niño and La Niña are asymmetric, as El Niño events tend to be stronger and further east than La Niña events. Due to an equatorial Pacific cold tongue bias with too cold SSTs, the simulation of ENSO asymmetry is degraded in many climate models participating in CMIP6. Here, we show how the cold tongue bias influences ENSO asymmetry. The cold bias hampers the simulation of strong eastern Pacific El Niños by making it more difficult for SST to exceed the threshold for deep atmospheric convection over the eastern equatorial Pacific. Recent research indicates that climate models with a realistic ENSO asymmetry agree on the projected ENSO under global warming. The results of this study suggest that reducing the cold tongue bias has the potential to enhancing the reliability of future ENSO projections.
The present investigation attempted to understand the intensity, frequency and spatial coverage of rainfall, runoff, groundwater and agricultural droughts in the semi-arid region of Maharashtra during 1981–2014. For this, various indices similar to Standardized Precipitation Index (SPI) (probabilistic nature) were applied. The linear regression, partial correlation and Student’s t-Test techniques were also used to evaluate inter-connections in hydro-meteorological and agricultural droughts. The hydrological deficiencies mimic the pattern of meteorological droughts in the study area with respect to coverage and intensity. Moderate hydro-meteorological droughts occurred frequently (once in 3 to 4 years). Additionally, the research highlighted an increase in the frequency and intensity of hydrological droughts during the post-1990 period, possibly linked to anthropogenic interventions (dam constructions and irrigation expansion). Despite El Niño events resulting in below-average rainfall, runoff, and groundwater levels in the study area, other phenomena such as Equatorial Indian Ocean Monsoon Oscillation (EQUINOO) / Indian Ocean Dipole (IOD) may have played a crucial role in major drought occurrences in 1986, 2003, and 2012 (events that happen once in > 30 years). The hydro-meteorological droughts lead to agricultural droughts, as they significantly affect the rainfed and irrigated crops in terms of productivity and cropped area. This effect was particularly notable during severe and region-wide droughts in 1985-86, 2002-03, and 2011-12. Furthermore, the investigation suggested that the study area is likely to experience hydro-meteorological deficiencies with ~ 25% probability between 2029 and 2050, coupled with a significant temperature rise (by 1.05 °C). This projected scenario could exacerbate water scarcity and agricultural distress in the future (up to 2050).
A notable anomalous lower-tropospheric anticyclone appears over the western North Pacific (WNP) during post-El Niño summer, exerting a profound influence on the East Asia summertime climate. Here, we employ a suite of global climate model projections under symmetric CO 2 ramp-up (RU) and ramp-down (RD) scenarios to reveal the asymmetric response of the WNP anticyclone (WNPAC). Our results demonstrate a progressive strengthening of the WNPAC with rising CO 2 concentrations, a trend that persists as CO 2 declines, followed by gradual recovery, and the anomalous anticyclone fails to return to its initial state when CO 2 concentrations return to pre-industrial levels, attributed to Indo-Pacific zonal SST gradient variations. In contrast to the CO 2 RU phase, the increased zonal SST gradient is witnessed in the CO 2 RD phase, favoring anomalous moisture convergence over the Maritime Continent (MC). This strengthens the WNPAC through Kelvin wave-induced Ekman divergence or local Hadley circulation adjustment. The increased zonal SST gradient is associated with strengthened SST warming in the MC and accelerated decay of El Niño-related positive SST anomalies in the equatorial Central Pacific, ultimately attributed to a climatological equatorial Pacific El Niño-like warming pattern driving intricate air-sea interactions and processes. Our findings indicate that the overshoot of the WNPAC during the CO 2 RD phase may exacerbate the flood and high temperature risks in densely populated East Asia.
The deep ocean, a vast thermal reservoir, absorbs excess heat under greenhouse warming, which ultimately regulates the Earth’s surface climate. Even if CO2 emissions are successfully reduced, the stored heat will gradually be released, resulting in a particular pattern of ocean warming. Here, we show that deep ocean warming will lead to El Niño-like ocean warming and resultant increased precipitation in the tropical eastern Pacific with southward shift of the intertropical convergence zone. Consequently, the El Niño-Southern Oscillation shifts eastward, intensifying Eastern Pacific El Niño events. In particular, the deep ocean warming could increase convective extreme El Niño events by 40 to 80% relative to the current climate. Our findings suggest that anthropogenic greenhouse warming will have a prolonged impact on El Niño variability through delayed deep ocean warming, even if CO2 stabilization is achieved.
The 2022 Yangtze mega-flash drought is characterized by strong intensity and rapid development both in time and space, accompanied by a persistent anticyclonic circulation anomaly. However, the causes of the extreme event remain elusive given the multiscale nature of drought. Here we presented a brief overview for the oceanic and terrestrial causes of the mega-flash drought during the summer of 2022, and estimated the risk in a changing climate. Using the soil moisture percentile as the drought index, it was found that the drought expanded to the entire Yangtze River basin within two months, with 80% of basin under severe drought conditions at the end of August. Both the intensity and onset speed of the 2022 mega-flash drought were ranked as the first during the past 62 years, with return periods of 86 and 259 years, respectively. The results of composite analysis showed that the spring La Niña can facilitate the abrupt change from a wet/normal condition in May–June to drought in July–August over the Yangtze River basin, which was beneficial for the increase of flash drought intensity and onset speed in 2022. The analysis through the linear regression also indicated that the unprecedented intensity was associated with the negative phase of the Pacific Decadal Oscillation. Quantified by a coupling strength index for soil moisture and vapor pressure deficit, it was found that there was a strong land-atmosphere coupling over the Yangtze River basin during July–August 2022. The attribution by using CMIP6 climate models suggested that land-atmosphere coupling increased the risks of flash drought intensity and onset speed like 2022 by 61%±6% and 64%±7% under natural climate forcings, and the synergy of coupling and anthropogenic climate change would increase the risks by 75%±22% and 85%±12%. Our findings emphasized the role of land-atmosphere coupling combined with anthropogenic climate change in intensifying flash droughts.
El Nino events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on subdecadal timescales. Understanding changes in the frequency or characteristics of El Nino events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies(1-5) show that the canonical El Nino has become less frequent and that a different kind of El Nino has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Nino, termed the central Pacific El Nino (CP-El Nino; also termed the dateline El Nino(2), El Nino Modoki(3) or warm pool El Nino(5)), differs from the canonical eastern Pacific El Nino (EP-El Nino) in both the location of maximum SST anomalies and tropical-midlatitude teleconnections. Here we show changes in the ratio of CP-El Nino to EP-El Nino under projected global warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set(6). Using calculations based on historical El Nino indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Nino compared to the EP-El Nino. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Nino to EP-El Nino, the occurrence ratio of CP-El Nino/EP-El Nino is projected to increase as much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.
El Niño-Southern Oscillation (ENSO) induces climate anomalies around the globe. Atmospheric general circulation model simulations are used to investigate how ENSO-induced teleconnection patterns during boreal winter might change in response to global warming in the Pacific-North American sector. As models disagree on changes in the amplitude and spatial pattern of ENSO in response to global warming, for simplicity the same sea surface temperature (SST) pattern of ENSO is prescribed before and after the climate warming. In a warmer climate, precipitation anomalies intensify and move eastward over the equatorial Pacific during El Niño because the enhanced mean SST warming reduces the barrier to deep convection in the eastern basin. Associated with the eastward shift of tropical convective anomalies, the ENSO-forced Pacific-North American (PNA) teleconnection pattern moves eastward and intensifies under the climate warming. By contrast, the PNA mode of atmospheric internal variability remains largely unchanged in pattern, suggesting the importance of tropical convection in shifting atmospheric teleconnections. As the ENSO-induced PNA pattern shifts eastward, rainfall anomalies are expected to intensify on the west coast of North America, and the El Niño-induced surface warming to expand eastward and occupy all of northern North America. The spatial pattern of the mean SST warming affects changes in ENSO teleconnections. The teleconnection changes are larger with patterned mean warming than in an idealized case where the spatially uniform warming is prescribed in the mean state. The results herein suggest that the eastward-shifted PNA pattern is a robust change to be expected in the future, independent of the uncertainty in changes of ENSO itself.
El Niño-Southern Oscillation (ENSO) consists of irregular episodes of warm El Niño and cold La Niña conditions in the tropical Pacific Ocean1, with significant global socio-economic and environmental impacts1. Nevertheless, forecasting ENSO at lead times longer than a few months remains a challenge2, 3. Like the Pacific Ocean, the Indian Ocean also shows interannual climate fluctuations, which are known as the Indian Ocean Dipole4, 5. Positive phases of the Indian Ocean Dipole tend to co-occur with El Niño, and negative phases with La Niña6, 7, 8, 9. Here we show using a simple forecast model that in addition to this link, a negative phase of the Indian Ocean Dipole anomaly is an efficient predictor of El Niño 14 months before its peak, and similarly, a positive phase in the Indian Ocean Dipole often precedes La Niña. Observations and model analyses suggest that the Indian Ocean Dipole modulates the strength of the Walker circulation in autumn. The quick demise of the Indian Ocean Dipole anomaly in November–December then induces a sudden collapse of anomalous zonal winds over the Pacific Ocean, which leads to the development of El Niño/La Niña. Our study suggests that improvements in the observing system in the Indian Ocean region and better simulations of its interannual climate variability will benefit ENSO forecasts.
The global climate during 1998 was affected by opposite extremes of the ENSO cycle, with one of the strongest Pacific warm episodes (El Niño) in the historical record continuing during January-early May and Pacific cold episode (La Niña) conditions occurring from July-December. In both periods, regional temperature, rainfall, and atmospheric circulation patterns across the Pacific Ocean and the Americas were generally consistent with those observed during past warm and cold episodes. Some of the most dramatic impacts from both episodes were observed in the Tropics, where anomalous convection was evident across the entire tropical Pacific and in most major monsoon regions of the world. Over the Americas, many of the El Niño- (La Niña-) related rainfall anomalies in the subtropical and extratropical latitudes were linked to an extension (retraction) of the jet streams and their attendant circulation features typically located over the subtropical latitudes of both the North Pacific and South Pacific. The regions most affected by excessive El Niño-related rainfall included 1) the eastern half of the tropical Pacific, including western Ecuador and northwestern Peru, which experienced significant flooding and mudslides; 2) southeastern South America, where substantial flooding was also observed; and 3) California and much of the central and southern United States during January-March, and the central United States during April-June. El Niño-related rainfall deficits during 1998 included 1) Indonesia and portions of northern Australia; 2) the Amazon Basin, in association with a substantially weaker-than-normal South American monsoon circulation; 3) Mexico, which experienced extreme drought throughout the El Niño episode; and 4) the Gulf Coast states of the United States, which experienced extreme drought during April-June 1998. The El Niño also contributed to extreme warmth across North America during January-May. The primary La Niña-related precipitation anomalies included 1) increased rainfall across Indonesia, and a nearly complete disappearance of rainfall across the east-central equatorial Pacific; 2) above-normal rains across northwestern, eastern, and northern Australia; 3) increased monsoon rains across central America and Mexico during October-December; and 4) dryness across equatorial eastern Africa. The active 1998 North Atlantic hurricane season featured 14 named storms (9 of which became hurricanes) and the strongest October hurricane (Mitch) in the historical record. In Honduras and Nicaragua extreme flooding and mudslides associated with Hurricane Mitch claimed more than 11 000 lives. During the peak of activity in August-September, the vertical wind shear across the western Atlantic, along with both the structure and location of the African easterly jet, were typical of other active seasons. Other regional aspects of the short-term climate included 1) record rainfall and massive flooding in the Yangtze River Basin of central China during June-July; 2) a drier and shorter-than-normal 1997/98 rainy season in southern Africa; 3) above-normal rains across the northern section of the African Sahel during June-September 1998; and 4) a continuation of record warmth across Canada during June-November. Global annual mean surface temperatures during 1998 for land and marine areas were 0.56°C above the 1961-90 base period means. This record warmth surpasses the previous highest anomaly of +0.43°C set in 1997. Record warmth was also observed in the global Tropics and Northern Hemisphere extratropics during the year, and is partly linked to the strong El Niño conditions during January-early May.
It has been previously proposed that two El Niño (EN) regimes, strong and moderate, exist but the historical observational record is too short to establish this conclusively. Here, 1200 years of simulations with the GFDL CM2.1 model allowed us to demonstrate their existence in this model and, by showing that the relevant dynamics are also evident in observations, we present a stronger case for their existence in nature. In CM2.1, the robust bimodal probability distribution of equatorial Pacific sea surface temperature (SST) indices during EN peaks provides evidence for the existence of the regimes, which is also supported by a cluster analysis of these same indices. The observations agree with this distribution, with the EN of 1982-1983 and 1997-1998 corresponding to the strong EN regime and all the other observed EN to the moderate regime. The temporal evolution of various indices during the observed strong EN agrees very well with the events in CM2.1, providing further validation of this model as a proxy for nature. The two regimes differ strongly in the magnitude of the eastern Pacific warming but not much in the central Pacific. Observations and model agree in the existence of a finite positive threshold in the SST anomaly above which the zonal wind response to warming is strongly enhanced. Such nonlinearity in the Bjerknes feedback, which increases the growth rate of EN events if they reach sufficiently large amplitude, is very likely the essential mechanism that gives rise to the existence of the two EN regimes. Oceanic nonlinear advection does not appear essential for the onset of strong EN. The threshold nonlinearity could make the EN regimes very sensitive to stochastic forcing. Observations and model agree that the westerly wind stress anomaly in the central equatorial Pacific in late boreal summer has a substantial role determining the EN regime in the following winter and it is suggested that a stochastic component at this time was key for the development of the strong EN towards the end of 1982.
The El Nino/Southern Oscillation is Earth's most prominent source of interannual climate variability, alternating irregularly between El Nino and La Nina, and resulting in global disruption of weather patterns, ecosystems, fisheries and agriculture(1-5). The 1998-1999 extreme La Nina event that followed the 1997-1998 extreme El Nino event(6) switched extreme El Nino-induced severe droughts to devastating floods in western Pacific countries, and vice versa in the southwestern United States(4,7). During extreme La Nina events, cold sea surface conditions develop in the central Pacific(8,9), creating an enhanced temperature gradient from the Maritime continent to the central Pacific. Recent studies have revealed robust changes in El Nino characteristics in response to simulated future greenhouse warming(10-12), but how La Nina will change remains unclear. Here we present climate modelling evidence, from simulations conducted for the Coupled Model Intercomparison Project phase 5 (ref. 13), for a near doubling in the frequency of future extreme La Nina events, from one in every 23 years to one in every 13 years. This occurs because projected faster mean warming of the Maritime continent than the central Pacific, enhanced upper ocean vertical temperature gradients, and increased frequency of extreme El Nino events are conducive to development of the extreme La Nina events. Approximately 75% of the increase occurs in years following extreme El Nino events, thus projecting more frequent swings between opposite extremes from one year to the next.
El Niño Southern Oscillation (ENSO) is a naturally occurring mode of tropical Pacific variability, with global impacts on society and natural ecosystems. While it has long been known that El Niño events display a diverse range of amplitudes, triggers, spatial patterns, and life cycles, the realization that ENSO's impacts can be highly sensitive to this event-to-event diversity is driving a renewed interest in the subject. This paper surveys our current state of knowledge of ENSO diversity, identifies key gaps in understanding, and outlines some promising future research directions.
The destructive environmental and socio-economic impacts of the El Niño/Southern Oscillation (ENSO) demand an improved understanding of how ENSO will change under future greenhouse warming. Robust projected changes in certain aspects of ENSO have been recently established. However, there is as yet no consensus on the change in the magnitude of the associated sea surface temperature (SST) variability, commonly used to represent ENSO amplitude, despite its strong eeects on marine ecosystems and rainfall worldwide. Here we show that the response of ENSO SST amplitude is time-varying, with an increasing trend in ENSO amplitude before 2040, followed by a decreasing trend thereafter. We attribute the previous lack of consensus to an expectation that the trend in ENSO amplitude over the entire twenty-first century is unidirectional, and to unrealistic model dynamics of tropical Pacific SST variability. We examine these complex processes across 22 models in the Coupled Model Intercomparison Project phase 5 (CMIP5) database, forced under historical and greenhouse warming conditions. The nine most realistic models identified show a strong consensus on the time-varying response and reveal that the non-unidirectional behaviour is linked to a longitudinal difference in the surface warming rate across the Indo-Pacific basin. Our results carry important implications for climate projections and climate adaptation pathways.
The Indian Ocean dipole is a prominent mode of coupled ocean-atmosphere variability, affecting the lives of millions of people in Indian Ocean rim countries. In its positive phase, sea surface temperatures are lower than normal off the Sumatra-Java coast, but higher in the western tropical Indian Ocean. During the extreme positive-IOD (pIOD) events of 1961, 1994 and 1997, the eastern cooling strengthened and extended westward along the equatorial Indian Ocean through strong reversal of both the mean westerly winds and the associated eastward-flowing upper ocean currents. This created anomalously dry conditions from the eastern to the central Indian Ocean along the Equator and atmospheric convergence farther west, leading to catastrophic floods in eastern tropical African countries but devastating droughts in eastern Indian Ocean rim countries. Despite these serious consequences, the response of pIOD events to greenhouse warming is unknown. Here, using an ensemble of climate models forced by a scenario of high greenhouse gas emissions (Representative Concentration Pathway 8.5), we project that the frequency of extreme pIOD events will increase by almost a factor of three, from one event every 17.3 years over the twentieth century to one event every 6.3 years over the twenty-first century. We find that a mean state change--with weakening of both equatorial westerly winds and eastward oceanic currents in association with a faster warming in the western than the eastern equatorial Indian Ocean--facilitates more frequent occurrences of wind and oceanic current reversal. This leads to more frequent extreme pIOD events, suggesting an increasing frequency of extreme climate and weather events in regions affected by the pIOD.
Errors of coupled general circulation models (CGCMs) limit their utility for climate prediction and projection. Origins of and feedback for tropical biases are investigated in the historical climate simulations of 18 CGCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5), together with the available Atmospheric Model Intercomparison Project (AMIP) simulations. Based on an intermodel empirical orthogonal function (EOF) analysis of tropical Pacific precipitation, the excessive equatorial Pacific cold tongue and double intertropical convergence zone (ITCZ) stand out as the most prominent errors of the current generation of CGCMs. The comparison of CMIP-AMIP pairs enables us to identify whether a given type of errors originates from atmospheric models. The equatorial Pacific cold tongue bias is associated with deficient precipitation and surface easterly wind biases in the western half of the basin in CGCMs, but these errors are absent in atmosphere-only models, indicating that the errors arise from the interaction with the ocean via Bjerknes feedback. For the double ITCZ problem, excessive precipitation south of the equator correlates well with excessive downward solar radiation in the Southern Hemisphere (SH) midlatitudes, an error traced back to atmospheric model simulations of cloud during austral spring and summer. This extratropical forcing of the ITCZ displacements is mediated by tropical ocean-atmosphere interaction and is consistent with recent studies of ocean-atmospheric energy transport balance.
This work investigates the teleconnection patterns over the North Pacific/North America sector and regional rainfall variability over the southwestern USA during boreal autumn, associated with two types of El Nino. These two types, called cold tongue (CT) and warm pool (WP) El Ninos, have an opposing impact on atmospheric circulation over the eastern North Pacific. When CT El Nino occurs, a strong cyclonic anomaly tends to appear over the North Pacific, and the associated southwesterly winds bring unusually moist air and thereby enhance rainfall over the southwestern USA. However, during WP El Nino autumns, a tripolar anomaly develops over the North Pacific. The associated northerly and northeasterly winds transport unusually dry air to the southwestern USA causing a reduction in rainfall. In this region, the rainfall response to WP El Nino is similar to that of La Nina, but opposite to that of CT El Nino. Since the early 1990s, the WP El Nino event has occurred more frequently, while the CT El Nino events has become less. The La Nina events remain roughly unchanged in terms of the zonal location. Autumn rainfall deficits over the southwestern USA have also been more frequent after the 1990s. The El Nino regime change thus appears to contribute to a decadal difference in the regional autumn rainfall.
Observations and climate simulations exhibit epochs of extreme El Niño/Southern Oscillation (ENSO) behavior that can persist for decades. Previous studies have revealed a wide range of ENSO responses to forcings from greenhouse gases, aerosols, and orbital variations – but they have also shown that interdecadal modulation of ENSO can arise even without such forcings. The present study examines the predictability of this intrinsically-generated component of ENSO modulation, using a 4000-year unforced control run from a global coupled GCM (GFDL-CM2.1) with a fairly realistic representation of ENSO. Extreme ENSO epochs from the unforced simulation are reforecast using the same ("perfect") model, but slightly-perturbed initial conditions. These 40-member reforecast ensembles display potential predictability of the ENSO trajectory, extending up to several years ahead. However, no decadal-scale predictability of ENSO behavior is found. This indicates that multidecadal epochs of extreme ENSO behavior can arise not only intrinsically, but delicately, and entirely at random. Previous work had shown that CM2.1 generates strong, reasonably-realistic, decadally-predictable high-latitude climate signals, as well as tropical and extratropical decadal signals that interact with ENSO. However, those slow variations appear not to lend significant decadal predictability to this model's ENSO behavior, at least in the absence of external forcings. While the potential implications of these results are sobering for decadal predictability, they also suggest an expedited approach to model evaluation and development – in which large ensembles of short runs are executed in parallel, to quickly and robustly evaluate simulations of ENSO. Further implications are discussed for decadal prediction, attribution of past and future ENSO variations, and societal vulnerability.
El Niño events, the warm phase of the El Niño/Southern
Oscillation (ENSO), are known to affect other tropical ocean basins
through teleconnections. Conversely, mounting evidence suggests that
temperature variability in the Atlantic Ocean may also influence ENSO
variability. Here we use reanalysis data and general circulation models
to show that sea surface temperature anomalies in the north tropical
Atlantic during the boreal spring can serve as a trigger for ENSO
events. We identify a subtropical teleconnection in which spring warming
in the north tropical Atlantic can induce a low-level cyclonic
atmospheric flow over the eastern Pacific Ocean that in turn produces a
low-level anticyclonic flow over the western Pacific during the
following months. This flow generates easterly winds over the western
equatorial Pacific that cool the equatorial Pacific and may trigger a La
Niña event the following winter. In addition, El Niño
events led by cold anomalies in the north tropical Atlantic tend to be
warm-pool El Niño events, with a centre of action located in the
central Pacific, rather than canonical El Niño events. We suggest
that the identification of temperature anomalies in the north tropical
Atlantic could help to forecast the development of different types of El
Niño event.
It is vital to understand how the El Niño-Southern Oscillation
(ENSO) has responded to past changes in natural and anthropogenic
forcings, in order to better understand and predict its response to
future greenhouse warming. To date, however, the instrumental record is
too brief to fully characterize natural ENSO variability, while large
discrepancies exist amongst paleo-proxy reconstructions of ENSO. These
paleo-proxy reconstructions have typically attempted to reconstruct the
full temporal variability of ENSO, rather than focusing simply on its
variance. Here a new approach is developed that synthesizes the
information on common low frequency variance changes from various proxy
datasets to obtain estimates of ENSO variance. The method is tested
using surrogate data from two coupled general circulation model (CGCM)
simulations. It is shown that in the presence of dating uncertainties,
synthesizing variance information provides a more robust estimate of
ENSO variance than synthesizing the raw data than identifying its
running variance. We also examine whether good temporal correspondence
between proxy data and instrumental ENSO records implies a good
representation of ENSO variance. A significant improvement in
reconstructing ENSO variance changes is found when combining several
proxies from diverse ENSO-teleconnected source regions, rather than by
relying on a single well-correlated location, suggesting that ENSO
variance estimates provided derived from a single site should be viewed
with caution. Finally, identifying the common variance signal in a
series of existing proxy based reconstructions of ENSO variability over
the last 600 yr we find that the common ENSO variance over the period
1600-1900 was considerably lower than during 1979-2009.
Climate models participating in the third Coupled Model Inter Comparison
Project (CMIP3) suggest a significant increase in the transport of the
New Guinea Coastal Undercurrent (NGCU) and the Equatorial Undercurrent
(EUC, in the central and western Pacific) and a decrease in the Mindanao
current and the Indonesian Throughflow. Most models also project a
reduction in the strength of the equatorial Trade winds. Typically, on
ENSO time scales, a weakening of the equatorial easterlies would lead to
a reduction in EUC strength in the central Pacific. The strengthening of
the EUC projected for longer timescales, can be explained by a robust
projected intensification of the south-easterly trade winds and an
associated off-equatorial wind-stress curl change in the Southern
Hemisphere. This drives the intensification of the NGCU and greater
water input to the EUC in the west. A 1½-layer shallow water
model, driven by projected wind stress trends from the CMIP3 models
demonstrates that the projected circulation changes are consistent with
a purely wind driven response. While the equatorial winds weaken for
both El Niño events and in the projections, the ocean response
and the mechanisms driving the projected wind changes are distinct from
those operating on interannual timescales.
Changes to the El Niño/Southern Oscillation (ENSO) and its
atmospheric teleconnections under climate change are investigated using
simulations conducted for the Coupled Model Intercomparison Project
(CMIP5). The overall response to CO2 increases is determined
using 27 models, and the ENSO amplitude change based on the multi-model
mean is indistinguishable from zero. However, changes between ensembles
run with a given model are sometimes significant: for four of the eleven
models having ensemble sizes larger than three, the 21st century change
to ENSO amplitude is statistically significant. In these four models,
changes to SST and wind stress do not differ substantially from those in
the models with no ENSO response, indicating that mean changes are not
predictive of the ENSO sensitivity to climate change. Also, ocean
vertical stratification is less (more) sensitive to CO2 in
models where ENSO strengthens (weakens), likely due to a regulation of
the subsurface temperature structure by ENSO-related poleward heat
transport. Atmospheric teleconnections also show differences between
models where ENSO amplitude does and does not respond to climate change;
in the former case El Niño/La Niña-related sea level
pressure anomalies strengthen with CO2, and in the latter
they weaken and shift polewards and eastwards. These results illustrate
the need for large ensembles to isolate significant ENSO climate change
responses, and for future work on diagnosing the dynamical causes of
inter-model teleconnection differences.
The El Niño/Southern Oscillation (ENSO) is the Earth's most prominent source of interannual climate variability, exerting profound worldwide effects. Despite decades of research, its behaviour continues to challenge scientists. In the eastern equatorial Pacific Ocean, the anomalously cool sea surface temperatures (SSTs) found during La Niña events and the warm waters of modest El Niño events both propagate westwards, as in the seasonal cycle. In contrast, SST anomalies propagate eastwards during extreme El Niño events, prominently in the post-1976 period, spurring unusual weather events worldwide with costly consequences. The cause of this propagation asymmetry is currently unknown. Here we trace the cause of the asymmetry to the variations in upper ocean currents in the equatorial Pacific, whereby the westward-flowing currents are enhanced during La Niña events but reversed during extreme El Niño events. Our results highlight that propagation asymmetry is favoured when the westward mean equatorial currents weaken, as is projected to be the case under global warming. By analysing past and future climate simulations of an ensemble of models with more realistic propagation, we find a doubling in the occurrences of El Niño events that feature prominent eastward propagation characteristics in a warmer world. Our analysis thus suggests that more frequent emergence of propagation asymmetry will be an indication of the Earth's warming climate.
The idea that global warming leads to more extreme weather and climate
variations has become engrained in popular and scientific minds. For
hydroclimate, or P-E, variability,there are good reasons to believe this
may actually be the case. As the atmosphere warms and can hold more
moisture circulation anomalies can converge or diverge more moisture
and, hence, intensify the resulting P-E anomalies. Examining the
simulations of the IPCC AR4 models it is shown that interannual
variability of P-E increases almost everywhere with a few notable
exceptions such as some subtropical regions and much of the tropical and
subtropical Americas. Over North America the variance increases most in
the mid to subpolar latitudes. The dominant potentially-predictable mode
of internannual P-E variability is the El Nino-Southern Oscillation
(ENSO). ENSO-driven interannual P-E variability clearly increases in
amplitude in the tropical Pacific but elsewhere the changes are more
complex. This is not surprising in that ENSO-driven P-E anomalies are
primarily caused by circulation anomalies combining with the
climatological humidity field. As climate warms and the specific
humidity increases this term leads to an intensification of ENSO-driven
P-E variability. However, ENSO-driven circulation anomalies also change,
in some regions amplifying, but in others opposing and even
overwhelming, the impact of rising specific humidity. ENSO-driven P-E
variability weakens over southwestern North America although the changes
do not reach statistical significance. Over South America there is
statistically significant weakening of the ENSO-dirven P-E variability
over northeast Brazil and a strengthening over southeastern Brazil.
These spatially variable changes can be related to changes in the
ENSO-driven circulation anomalies, the causes of which are analyzed
using idealized experiments with atmosphere models.
Large discrepancies exist between twentieth-century tropical Indo-Pacific sea surface temperature trends determined from present reconstructions. These discrepancies prevent an unambiguous verification and validation of climate models used for projections of future climate change. Here we demonstrate that a more consistent and robust trend among all the reconstructions is found by filtering each data set to remove El Niño/Southern Oscillation (ENSO), which is represented not by a single-index time series but rather by an evolving dynamical process. That is, the discrepancies seem to be largely the result of different estimates of ENSO variability in each reconstruction. The robust ENSO-residual trend pattern represents a strengthening of the equatorial Pacific temperature gradient since 1900, owing to a systematic warming trend in the warm pool and weak cooling in the cold tongue. Similarly, the ENSO-residual trend in sea-level pressure represents no weakening of the equatorial Walker circulation over the same period. Additionally, none of the disparate estimates of post-1900 total eastern equatorial Pacific sea surface temperature trends are larger than can be generated by statistically stationary, stochastically forced empirical models that reproduce ENSO evolution in each reconstruction.
The El Niño–Southern Oscillation (ENSO) exhibits well-known asymmetries: 1) warm events are stronger than cold events, 2) strong warm events are more likely to be followed by cold events than vice versa, and 3) cold events are more persistent than warm events. Coupled GCM simulations, however, continue to underestimate many of these observed features.
To shed light on these asymmetries, the authors begin with a widely used delayed-oscillator conceptual model for ENSO and modify it so that wind stress anomalies depend more strongly on SST anomalies (SSTAs) during warm conditions, as is observed. Then the impact of this nonlinearity on ENSO is explored for three dynamical regimes: self-sustained oscillations, stochastically driven oscillations, and self-sustained oscillations disrupted by stochastic forcings. In all three regimes, the nonlinear air–sea coupling preferentially strengthens the feedbacks (both positive and delayed negative) during the ENSO warm phase—producing El Niños that grow to a larger amplitude and overshoot more rapidly and consistently into the opposite phase, than do the La Niñas. Finally, the modified oscillator is applied to observational records and to control simulations from two global coupled ocean–atmosphere–land–ice models [Geophysical Fluid Dynamics Laboratory Climate Model version 2.1 (GFDL CM2.1) and version 2.5 (GFDL CM2.5)] to elucidate the causes of their differing asymmetries.
Due to errors in complex coupled feedbacks that compensate differently
in different global climate models, as well as nonlinear nature of El
Niño-Southern Oscillation (ENSO), there remain difficulties in
detecting and evaluating the reason for the past and future changes in
the ENSO amplitude, σniño. Here we use physics
parameter ensembles, in which error compensation was eliminated by
perturbing model parameters, to explore relationships between mean
climate and variability. With four such ensembles we find a strong
relationship between σniño and the mean
precipitation over the eastern equatorial Pacific (P¯nin˜o).
This involves a two-way interaction, in which the wetter mean state with
greater P¯nin˜o acts to increase the ENSO amplitude by
strengthening positive coupled feedbacks. Such a relationship is also
identified in 11 single-model historical climate simulations in the
Coupled Model Intercomparison Project phase 5 despite mean precipitation
biases apparently masking the relationship in the multi-model ensemble
(MME). Taking changes in σniño and
P¯nin˜o between pre-industrial and recent periods eliminates
the bias, and therefore results in a robust
σniño-P¯nin˜o connection in
MME, which suggests a 10-15% increase in the ENSO amplitude since
pre-industrial era mainly due to changing mean state. However, the
σniño-P¯nin˜o connection is
less clear for their future changes, which are still greatly uncertain.
Climate model experiments are analyzed to elucidate if and how the changes in mean climate in response to doubling of atmospheric CO2 (2xCO2) influence ENSO. The processes involved the development, transition, and decay of simulated ENSO events are quantified through a multimodel heat budget analysis. The simulated changes in ENSO amplitude in response to 2xCO2 are directly related to changes in the anomalous ocean heat flux convergence during the development, transition, and decay of ENSO events. The weakening of the Walker circulation and the increased thermal stratification, both robust features of the mean climate response to 2xCO2, play opposing roles in ENSO–mean climate interactions. Weaker upwelling in response to a weaker Walker circulation drives a reduction in thermocline-driven ocean heat flux convergence (i.e., thermocline feedback) and, thus, reduces the ENSO amplitude. Conversely, a stronger zonal subsurface temperature gradient, associated with the increased thermal stratification, drives an increase in zonal-current-induced ocean heat flux convergence (i.e., zonal advection feedback) and, thus, increases the ENSO amplitude. These opposing processes explain the lack of model agreement in whether ENSO is going to weaken or strengthen in response to increasing greenhouse gases, but also why ENSO appears to be relatively insensitive to 2xCO2 in most models.
The amplitude of the El Niño-Southern Oscillation (ENSO) is known
to fluctuate in long records derived from observations and general
circulation models (GCMs), even when driven by constant external
forcings. This involves an interaction between the ENSO cycle and the
background mean state, which affects the climatological precipitation
over the eastern equatorial Pacific. The changes in climatological
rainfall may be ascribed to several factors: changes in mean sea surface
temperature (SST), changes in SST variability, and changes in the
sensitivity of precipitation to SST. We propose a method to separate
these effects in model ensembles. A case study with a single GCM
demonstrates that the method works well, and suggests that each factor
plays a role in changing mean precipitation. Applying the method to 16
pre-industrial control simulations archived in the Coupled Model
Intercomparison Project phase 5 (CMIP5) reveals that the inter-model
diversity in mean precipitation arises mostly from differences in the
mean SST and atmospheric sensitivity to SST, rather than from
differences in ENSO amplitude.
This study examines preindustrial simulations from Coupled Model Intercomparison Project, phase 3 (CMIP3), models to show that a tendency exists for El Niñ o sea surface temperature anomalies to be located farther eastward than La Niñ a anomalies during strong El Niñ o–Southern Oscillation (ENSO) events but farther westward than La Niñ a anomalies during weak ENSO events. Such reversed spatial asymmetries are shown to force a slow change in the tropical Pacific Ocean mean state that in return modulates ENSO amplitude. CMIP3 models that produce strong reversed asymmetries experience cyclic modulations of ENSO intensity, in which strong and weak events occur during opposite phases of a decadal variability mode associated with the residual effects of the reversed asymmetries. It is concluded that the reversed spatial asymmetries enable an ENSO–tropical Pacific mean state interaction mechanism that gives rise to a decadal modulation of ENSO intensity and that at least three CMIP3 models realistically simulate this interaction mechanism.
Extreme El Niño (e.g., 1983/1983 and 1997/1998) causes severe weather and climate impacts globally, but the associated dynamics is not fully understood. The present study shows that advection of mean temperature by anomalous eastward zonal current plays an important role in producing such extreme events especially during the early part of the developing period. While the climatological direction of the upper oceanic current in the equatorial Pacific is westward, at times the direction reverses. These eastward current events are well distinguished from the normal, westward conditions. The upper-layer zonal current in the equatorial Pacific is basically in geostrophic balance and forced by wind stress. However, in the case of the eastward zonal current events, persistent westerly winds are observed in the Western Pacific, and the current becomes synchronized with the westerly wind stress above. The advection of the mean temperature by the anomalous zonal current in the early developing period always precedes strong El Niño, though it does not significantly contribute to the growth of La Niña, neutral, and moderate El Niño; and is the major contributor of asymmetry in the early developing phase.
We analyse the ability of CMIP3 and CMIP5 coupled ocean–atmosphere general circulation models (CGCMs) to simulate the tropical Pacific mean state and El Niño-Southern Oscillation (ENSO). The CMIP5 multi-model ensemble displays an encouraging 30 % reduction of the pervasive cold bias in the western Pacific, but no quantum leap in ENSO performance compared to CMIP3. CMIP3 and CMIP5 can thus be considered as one large ensemble (CMIP3 + CMIP5) for multi-model ENSO analysis. The too large diversity in CMIP3 ENSO amplitude is however reduced by a factor of two in CMIP5 and the ENSO life cycle (location of surface temperature anomalies, seasonal phase locking) is modestly improved. Other fundamental ENSO characteristics such as central Pacific precipitation anomalies however remain poorly represented. The sea surface temperature (SST)-latent heat flux feedback is slightly improved in the CMIP5 ensemble but the wind-SST feedback is still underestimated by 20–50 % and the shortwave-SST feedbacks remain underestimated by a factor of two. The improvement in ENSO amplitudes might therefore result from error compensations. The ability of CMIP models to simulate the SST-shortwave feedback, a major source of erroneous ENSO in CGCMs, is further detailed. In observations, this feedback is strongly nonlinear because the real atmosphere switches from subsident (positive feedback) to convective (negative feedback) regimes under the effect of seasonal and interannual variations. Only one-third of CMIP3 + CMIP5 models reproduce this regime shift, with the other models remaining locked in one of the two regimes. The modelled shortwave feedback nonlinearity increases with ENSO amplitude and the amplitude of this feedback in the spring strongly relates with the models ability to simulate ENSO phase locking. In a final stage, a subset of metrics is proposed in order to synthesize the ability of each CMIP3 and CMIP5 models to simulate ENSO main characteristics and key atmospheric feedbacks.
Canonical El Niño has a warming center in the eastern Pacific (EP), but in recent decades, El Niño warming center tends to occur more frequently in the central Pacific (CP). The definitions and names of this new type of El Niño, however, have been notoriously diverse, which makes it difficult to understand why the warming center shifts. Here, we show that the new type of El Niño events is characterized by: 1) the maximum warming standing and persisting in the CP and 2) the warming extending to the EP only briefly during its peak phase. For this reason, we refer to it as standing CP warming (CPW). Global warming has been blamed for the westward shift of maximum warming as well as more frequent occurrence of CPW. However, we find that since the late 1990s the standing CPW becomes a dominant mode in the Pacific; meanwhile, the epochal mean trade winds have strengthened and the equatorial thermocline slope has increased, contrary to the global warming-induced weakening trades and flattening thermocline. We propose that the recent predominance of standing CPW arises from a dramatic decadal change characterized by a grand La Niña-like background pattern and strong divergence in the CP atmospheric boundary layer. After the late 1990s, the anomalous mean CP wind divergence tends to weaken the anomalous convection and shift it westward from the underlying SST warming due to the suppressed low-level convergence feedback. This leads to a westward shift of anomalous westerly response and thus a zonally in-phase SST tendency, preventing eastward propagation of the SST anomaly. We anticipate more CPW events will occur in the coming decade provided the grand La Niña-like background state persists.
Precipitation changes over the Indo-Pacific during El Niño events
are studied using an Atmospheric General Circulation Model forced with
sea-surface temperature (SST) anomalies and changes in atmospheric
CO2 concentrations. Linear increases in the amplitude of the
El Niño SST anomaly pattern trigger nonlinear changes in
precipitation amounts, resulting in shifts in the location and
orientation of the Intertropical Convergence Zone (ITCZ) and the South
Pacific Convergence Zone (SPCZ). In particular, the maximum
precipitation anomaly along the ITCZ and SPCZ shifts eastwards, the ITCZ
shifts south towards the equator, and the SPCZ becomes more zonal.
Precipitation in the equatorial Pacific also increases nonlinearly. The
effect of increasing CO2 levels and warming SSTs is also
investigated. Global warming generally enhances the tropical Pacific
precipitation response to El Niño. The precipitation response to
El Niño is found to be dominated by changes in the atmospheric
mean circulation dynamics, whereas the response to global warming is a
balance between dynamic and thermodynamic changes. While the dependence
of projected climate change impacts on seasonal variability is
well-established, this study reveals that the impact of global warming
on Pacific precipitation also depends strongly on the magnitude of the
El Niño event. The magnitude and structure of the precipitation
changes are also sensitive to the spatial structure of the global
warming SST pattern.
The Pacific Walker circulation is a large overturning cell that spans
the tropical Pacific Ocean, characterized by rising motion (lower
sea-level pressure) over Indonesia and sinking motion (higher sea
level-pressure) over the eastern Pacific. Fluctuations in the Walker
circulation reflect changes in the location and strength of tropical
heating, so related circulation anomalies have global impacts. On
interannual timescales, the El Niño/Southern Oscillation accounts
for much of the variability in the Walker circulation, but there is
considerable interest in longer-term trends and their drivers, including
anthropogenic climate change. Here, we examine sea-level pressure trends
in ten different data sets drawn from reanalysis, reconstructions and in
situ measurements for 1900-2011. We show that periods with fewer in situ
measurements result in lower signal-to-noise ratios, making assessments
of sea-level pressure trends largely unsuitable before about the 1950s.
Multidecadal trends evaluated since 1950 reveal statistically
significant, negative values over the Indonesian region, with weaker,
positive trends over the eastern Pacific. The overall trend towards a
stronger, La Niña-like Walker circulation is nearly concurrent
with the observed increase in global average temperatures, thereby
justifying closer scrutiny of how the Pacific climate system has changed
in the historical record.
It is vital to understand how the El Niño–Southern Oscillation (ENSO) has responded to past changes in natural and anthropogenic forcings, in order to better understand and predict its response to future greenhouse warming. To date, however, the instrumental record is too brief to fully characterize natural ENSO variability, while large discrepancies exist amongst paleo-proxy reconstructions of ENSO. These paleo-proxy reconstructions have typically attempted to reconstruct ENSO's temporal evolution, rather than the variance of these temporal changes. Here a new approach is developed that synthesizes the variance changes from various proxy data sets to provide a unified and updated estimate of past ENSO variance. The method is tested using surrogate data from two coupled general circulation model (CGCM) simulations. It is shown that in the presence of dating uncertainties, synthesizing variance information provides a more robust estimate of ENSO variance than synthesizing the raw data and then identifying its running variance. We also examine whether good temporal correspondence between proxy data and instrumental ENSO records implies a good representation of ENSO variance. In the climate modeling framework we show that a significant improvement in reconstructing ENSO variance changes is found when combining information from diverse ENSO-teleconnected source regions, rather than by relying on a single well-correlated location. This suggests that ENSO variance estimates derived from a single site should be viewed with caution. Finally, synthesizing existing ENSO reconstructions to arrive at a better estimate of past ENSO variance changes, we find robust evidence that the ENSO variance for any 30 yr period during the interval 1590–1880 was considerably lower than that observed during 1979–2009.
Despite the continued increase in atmospheric greenhouse gas concentrations, the annual-mean global temperature has not risen in the twenty-first century, challenging the prevailing view that anthropogenic forcing causes climate warming. Various mechanisms have been proposed for this hiatus in global warming, but their relative importance has not been quantified, hampering observational estimates of climate sensitivity. Here we show that accounting for recent cooling in the eastern equatorial Pacific reconciles climate simulations and observations. We present a novel method of uncovering mechanisms for global temperature change by prescribing, in addition to radiative forcing, the observed history of sea surface temperature over the central to eastern tropical Pacific in a climate model. Although the surface temperature prescription is limited to only 8.2% of the global surface, our model reproduces the annual-mean global temperature remarkably well with correlation coefficient r = 0.97 for 1970-2012 (which includes the current hiatus and a period of accelerated global warming). Moreover, our simulation captures major seasonal and regional characteristics of the hiatus, including the intensified Walker circulation, the winter cooling in northwestern North America and the prolonged drought in the southern USA. Our results show that the current hiatus is part of natural climate variability, tied specifically to a La-Niña-like decadal cooling. Although similar decadal hiatus events may occur in the future, the multi-decadal warming trend is very likely to continue with greenhouse gas increase.