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In 2023, the development of El Niño is poised to drive a global upsurge in surface air temperatures (SAT), potentially resulting in unprecedented warming worldwide. Nevertheless, the regional patterns of SAT anomalies remain diverse, obscuring where historical warming records may be surpassed in the forthcoming year. Our study underscores the significant influence of El Niño and the persistence of climate signals on the inter-annual variability of regional SAT, both in amplitude and spatial distribution. The likelihood of global mean SAT exceeding historical records, calculated from July 2023 to June 2024, is estimated at 90%, contingent upon annual-mean sea surface temperature anomalies in the eastern equatorial Pacific exceeding 0.6 °C. Regions particularly susceptible to recording record-high SAT include coastal and adjacent areas in Asia such as the Bay of Bengal and the South China Sea, as well as Alaska, the Caribbean Sea, and the Amazon. This impending warmth heightens the risk of year-round marine heatwaves and escalates the threat of wildfires and other negative consequences in Alaska and the Amazon basin, necessitating strategic mitigation measures to minimize potential worst-case impacts.
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Multi-year El Niño events induce severe and persistent floods and droughts worldwide, with significant socioeconomic impacts, but the causes of their long-lasting behaviors are still not fully understood. Here we present a two-way feedback mechanism between the tropics and extratropics to argue that extratropical atmospheric variability associated with the North Pacific Oscillation (NPO) is a key source of multi-year El Niño events. The NPO during boreal winter can trigger a Central Pacific El Niño during the subsequent winter, which excites atmospheric teleconnections to the extratropics that re-energize the NPO variability, then re-triggers another El Niño event in the following winter, finally resulting in persistent El Niño-like states. Model experiments, with the NPO forcing assimilated to constrain atmospheric circulation, reproduce the observed connection between NPO forcing and the occurrence of multi-year El Niño events. Future projections of Coupled Model Intercomparison Project phases 5 and 6 models demonstrate that with enhanced NPO variability under future anthropogenic forcing, more frequent multi-year El Niño events should be expected. We conclude that properly accounting for the effects of the NPO on the evolution of El Niño events may improve multi-year El Niño prediction and projection.
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The record-breaking mei-yu in the Yangtze-Huaihe River valley (YHRV) in 2020 was characterized by an early onset, a delayed retreat, a long duration, a wide meridional rainbelt, abundant precipitation, and frequent heavy rainstorm processes. It is noted that the East Asian monsoon circulation system presented a significant quasi-biweekly oscillation (QBWO) during the mei-yu season of 2020 that was associated with the onset and retreat of mei-yu, a northward shift and stagnation of the rainbelt, and the occurrence and persistence of heavy rainstorm processes. Correspondingly, during the mei-yu season, the monsoon circulation subsystems, including the western Pacific subtropical high (WPSH), the upper-level East Asian westerly jet, and the low-level southwesterly jet, experienced periodic oscillations linked with the QBWO. Most notably, the repeated establishment of a large southerly center, with relatively stable latitude, led to moisture convergence and ascent which was observed to develop repeatedly. This was accompanied by a long-term duration of the mei-yu rainfall in the YHRV and frequent occurrences of rainstorm processes. Moreover, two blocking highs were present in the middle to high latitudes over Eurasia, and a trough along the East Asian coast was also active, which allowed cold air intrusions to move southward through the northwestern and/or northeastern paths. The cold air frequently merged with the warm and moist air from the low latitudes resulting in low-level convergence over the YHRV. The persistent warming in the tropical Indian Ocean is found to be an important external contributor to an EAP/PJ-like teleconnection pattern over East Asia along with an intensified and southerly displaced WPSH, which was observed to be favorable for excessive rainfall over YHRV.
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El Niño-Southern Oscillation (ENSO) is the dominant interseasonal-interannual variability in the tropical Pacific and substantial efforts have been dedicated to predicting its occurrence and variability because of its extensive global impacts. However, ENSO predictability has been reduced in the 21st century, and the impact of extratropical atmosphere on the tropics has intensified during the past 2 decades, making the ENSO more complicated and harder to predict. Here, by combining tropical preconditions/ocean-atmosphere interaction with extratropical precursors, we provide a novel approach to noticeably increase the ENSO prediction skill beyond the spring predictability barrier. The success of increasing the prediction skill results mainly from the longer lead-time of the extratropical-tropical ocean-to-atmosphere interaction process, especially for the first 2 decades of the 21st century.
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The possible factors associated with the shortening of lead time between ocean warm water volume (WWV) variability along the equatorial Pacific and El Niño-Southern Oscillation (ENSO) variability after 2000 are documented. It is shown that the shortening of lead time is due to frequency increases of both WWV and ENSO. During 1979-99 the dominant frequencies were 1.5-3.5 years for both the Niño3.4 and WWV indices. In contrast, during 2000-16, both indices had a relatively flatter spectrum and were closer to a white noise process with a relative maximum at 1.5-2.0 years for the Niño3.4 index and 0.8-1.3 years for the WWV index. The frequency change of ENSO and WWV were linked to a westward shift of the Bjerknes feedback region. The results here are consistent with previous argument that the westward shift of the air-sea coupling region will cause an increase of ENSO frequency, as the corresponding zonal advection feedback reduces the period and growth of coupled instability, thus favoring more frequent and weak El Niño events.
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The most predictable components of the El Niño-Southern Oscillation (ENSO) evolution in real-time multi-model predictions are identified by applying an empirical orthogonal function analysis of the model data that maximizes the signal-to-noise ratio (MSN EOF). The normalized Niño3.4 index is analyzed for nine 3-month overlapping seasons. In this sense, the first most predictable component (MSN EOF1) is the decaying phase of ENSO during the Northern Hemisphere spring, followed by persistence through autumn and winter. The second most predictable component of ENSO evolution, with lower prediction skill and smaller explained variance than MSN EOF1, corresponds to the growth during spring and then persistence in summer and autumn. This result suggests that decay phase of ENSO is more predictable than the growth phase. Also, the most predictable components and the forecast skills in dynamical and statistical models are similar overall, with some differences arising during spring season initial conditions. Finally, the reconstructed predictions, with only the first two MSN components, show higher skill than the model raw predictions. Therefore this method can be used as a diagnostic for model comparison and development, and it can provide a new perspective for the most predictable components of ENSO.
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The 2014 El Niño, anticipated to be a strong event in early 2014, turned out to be fairly weak. In early 2014, the tropical Pacific exhibited persistent negative SST anomalies in the southeastern Pacific and positive SST anomalies in north, following the pattern of the Southern Pacific Meridional Mode. In this study, we explored the role of the off-equatorial SST anomalies in the 2014 prediction. Our experiments show that 40% of the amplitude error at the peak phase could be attributed to the lack of prediction of negative SST anomalies in the southeastern Pacific. However, the impact of this model error is partially compensated by the absence of the positive SST anomalies in the tropical western North Pacific in the model. The model response to the amplitude of negative southeastern Pacific SST anomalies is nonlinear in terms of equatorial warming, because the enhanced meridional pressure gradient forces very strong meridional winds without accelerating the zonal wind component near the equator. Our study suggests that reliable forecasts of ENSO strongly rely on correctly modeling the meridional SST gradient, as well as its delicate feedback with the zonal (ENSO) mode.
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According to the classical theories of ENSO, subsurface anomalies in ocean thermal structure are precursors for ENSO events and their initial specification is essential for skillful ENSO forecast. Although ocean salinity in the tropical Pacific (particularly in the western Pacific warm pool) can vary in response to El Niño events, its effect on ENSO evolution and forecasts of ENSO has been less explored. Here we present evidence that, in addition to the passive response, salinity variability may also play an active role in ENSO evolution, and thus important in forecasting El Niño events. By comparing two forecast experiments in which the interannually variability of salinity in the ocean initial states is either included or excluded, the salinity variability is shown to be essential to correctly forecast the 2007/08 La Niña starting from April 2007. With realistic salinity initial states, the tendency to decay of the subsurface cold condition during the spring and early summer 2007 was interrupted by positive salinity anomalies in the upper central Pacific, which working together with the Bjerknes positive feedback, contributed to the development of the La Niña event. Our study suggests that ENSO forecasts will benefit from more accurate salinity observations with large-scale spatial coverage.