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Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The observed Southern Ocean sea surface temperature (SST) has experienced prominent inter-decadal variability nearly in phase with the Inter-decadal Pacific Oscillation (IPO), but less associated with the Atlantic Multidecadal Variability (AMV), challenging the prevailing view of Pacific-Atlantic synergistic effects. Yet, the mechanisms of distinct trans-hemispheric connections to the Southern Ocean remain indecisive. Here, by individually constraining the observed cold-polarity and warm-polarity IPO and AMV SSTs in a climate model, we show that the IPO is influential in initiating a basin-wide Southern Ocean response, with the AMV secondary. A tropical Pacific-wide cooling triggers a basin-scale Southern Ocean cold episode through a strong Rossby wave response to the north-to-south cross-equatorial weakened Hadley circulation. By contrast, due to the competing role of tropical Pacific cooling, an Atlantic warming partly cools the Southern Ocean via a weak Rossby wave response to the south-to-north cross-equatorial enhanced Hadley circulation. Conversely, tropical Pacific warming leads to a warm Southern Ocean episode. Our findings highlight that properly accounting for the tropical Pacific SST variability may provide a potential for skillful prediction of Southern Ocean climate change and more reliable estimates of climate sensitivity, currently overestimated by the misrepresented Southern Ocean warming. [ABSTRACT FROM AUTHOR]

The influence of Atlantic Niño on the following El Niño–Southern Oscillation becomes significant since mid‐1970s. However, exact mechanisms for this inter‐decadal change are still unclear. Here, we perform a set of model pacemaker experiments to probe the relative contributions of the changes in the Atlantic Niño itself and the mean‐state under global warming. The results suggest that the warmer background of the tropical Atlantic plays an essential role in enhancing local mean precipitation, inducing stronger divergence and low‐level easterlies in the Pacific. Under a favorable condition in the Pacific, even a weak Atlantic Niño‐related warming could promote the development of La Niña through cross‐basin Walker circulation and the Indian Ocean‐relayed Kelvin wave response. In contrast, the Atlantic Niño pattern change itself induces feeble convection anomalies in the western Atlantic, which cannot induce significant atmospheric response in the Pacific. These results imply an important modulation of global warming on the inter‐basin connection. Plain Language Summary: Climate phenomena in the three tropical oceans are tightly inter‐connected through atmospheric and oceanic pathways. The observations show that the influence of equatorial Atlantic sea surface temperature (SST) on the evolution of the following El Niño–Southern Oscillation displays a noticeable multi‐decadal change. The inter‐basin influence is negligible in early decades but becomes statistically significant since mid‐1970s. To understand this multi‐decadal change, the changes in the remote impacts of the tropical Atlantic Niño are divided into those related to the changes in the Atlantic Niño itself and the background mean SST. By comparing their relative contributions, we find the warmer climatological mean SST excites incremental precipitation around the western tropical Atlantic and Intertropical Convergence Zone (ITCZ), amplifying inter‐basin Walker circulation and the Indian Ocean relayed effect, and thus can more easily promote the evolution of La Niña in the following seasons. In contrast, despite the Atlantic Niño pattern broadens westwards in the recent decades, its induced‐feeble positive convection anomalies in the western Atlantic scarcely induce the atmospheric response over the tropical Pacific. Our results stress the vital role of the multi‐decadal SST warming in the tropical Atlantic and provide a plausible explanation for the multi‐decadal strengthening of this inter‐basin connection in recent decades. Key Points: The correlation between summer Atlantic Niño and the following El Niño–Southern Oscillation (ENSO) becomes significantly negative since 1976The warming‐induced tropical Atlantic mean‐state change, rather than the Atlantic Niño change itself, dominantly modulates the inter‐basin impact on ENSOThe climatological sea surface temperature/precipitation strengthened in the tropical Atlantic is important to exert the influence on ENSO [ABSTRACT FROM AUTHOR]

Deep learning (DL) has achieved notable success in El Niño‐Southern Oscillation (ENSO) forecasts. Most DL‐based models focused on forecasting ENSO indices while the zonal distribution of sea surface temperature anomalies (SSTA) over the equatorial Pacific was overlooked. To provide accurate predictions for the SSTA zonal pattern, this study developed a model through leveraging the merits of the cosine distance in constructing the convolutional neural network. This model can skillfully predict the SSTA zonal pattern over the equatorial Pacific 1 year in advance, remarkably outperforming current dynamical models. Moreover, the physical interpretation of the model prediction reveals that the sources for ENSO predictability at different lead times are distinct. For the 10‐month‐lead predictions, the precursors in the north Pacific, south Pacific and tropical Atlantic play critical roles in determining the model behaviors; while for the 16‐month‐lead predictions, the initial signals in the tropical Pacific associated with the discharge‐recharge cycle are essential. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) is the most prominent climate phenomenon in the Earth system. It significantly affects the worldwide weather and climate via teleconnections. Numerous studies have reported that the ENSO teleconnection and its impacts largely depend on the zonal distribution of SSTA over the equatorial Pacific. Thus, the ENSO forecast with the specific SSTA zonal pattern is important for anticipating the severity of ENSO‐related disasters and mitigating the potential socio‐economic impacts. However, current dynamical models have difficulties in accurately predicting the SSTA zonal pattern, while most of deep learning models only provide predictions of ENSO indices. Hence, we developed a deep learning model based on the convolutional neural network which can effectively predict the SSTA zonal pattern 1 year in advance. Moreover, we investigate the interpretability of this model by analyzing activation maps. The results suggest that crucial factors captured by this model at different lead times are physically reasonable, which verify the credibility of this model. Key Points: We develop a deep learning model that can skillfully predict the explicit sea surface temperature anomalies (SSTA) zonal pattern over the equatorial Pacific 1 yr aheadPhysical interpretation shows that the source of 10‐month‐lead prediction stems from the Pacific Meridional Mode, South Pacific quadrupole, and tropical Atlantic SSTAThe main source of 16‐month‐lead forecast comes from discharge/recharge cycles, implying distinct prediction sources at different lead times [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Prediction skill for the seasonal tropical cyclone (TC) activity in the Northern Hemisphere is investigated using the coupled climate forecast system (version 1.0) of Nanjing University of Information Science and Technology (NUIST-CFS1.0). This assessment is based on the seven-month (May to November) hindcasts consisting of nine ensemble members during 1982–2019. The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere. The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations, although the seasonal mean TC frequency and accumulated cyclone energy (ACE) are underestimated in all basins due to the low resolution (T106) of the atmospheric component in the model. NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic (NA) and eastern North Pacific (ENP), which have a good relationship with indexes based on the sea surface temperature. In the western North Pacific (WNP), NUIST-CFS1.0 can closely capture ACE, which is significantly correlated with the El Niño—Southern Oscillation (ENSO), while it has difficulty forecasting the interannual variation of TC frequency in this area. When the WNP is further divided into eastern and western subregions, the model displays improved TC activity forecasting ability. Additionally, it is found that biases in predicted TC genesis locations lead to inaccurately represented TC—environment relationships, which may affect the capability of the model in reproducing the interannual variations of TC activity. [ABSTRACT FROM AUTHOR]

The interactions between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are known to have great implications for global climate variability and seasonal climate predictions. Observational analysis suggests that the ENSO–IOD inter‐basin connection is time‐varying and related to the Atlantic Multidecadal Oscillation (AMO) with weakened ENSO–IOD relationship corresponding to AMO warm phases. A suite of Atlantic pacemaker simulations successfully reproduces the decadal fluctuations in ENSO–IOD relationship and its link to the AMO. The warm sea surface temperature (SST) anomalies associated with the AMO drive a series of Indo‐Pacific mean climate changes through tropical‐wide teleconnections, including the La Niña‐like mean SST cooling over the central Pacific and the deepening of mean thermocline depth in the eastern Indian Ocean. By modulating ocean–atmosphere feedback strength, those mean state changes decrease both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing, therefore decoupling the IOD from ENSO. Plain Language Summary: The El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) are two most important interannual climate signals exciting world‐wide climate and socioeconomic impacts. Their interactions are known to have great implications for global climate variability and seasonal climate predictions. However, the ENSO–IOD relationship is time‐varying and show prominent decadal fluctuations. Such changes in ENSO–IOD relationship are associated with the decadal variation in IOD teleconnections and predictability. The prediction skill of IOD is high when the ENSO–IOD relationship is strong, and vice versa. But it remains unknown what controls the decadal modulation of Indo‐Pacific inter‐basin connection. Our findings suggest that the Atlantic Multidecadal Oscillation (AMO) may modulate the ENSO–IOD inter‐basin connection. The AMO sea surface temperature anomalies drive a series of Indo‐Pacific mean climate changes through tropical‐wide teleconnections. Those mean state changes further influence both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing, thereby modulating the ENSO–IOD relationship. This study advances our understandings on inter‐basin and cross‐scale interactions in the climate system. Key Points: The inter‐basin connection between El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole is time‐varying and controlled by the remote Atlantic Multidecadal Oscillation (AMO)The AMO sea surface temperature anomalies drive a series of Indo‐Pacific mean climate changes through tropical‐wide teleconnectionsThe AMO induced mean state changes influence both ENSO amplitude and the Indian Ocean sensitivity to ENSO forcing [ABSTRACT FROM AUTHOR]

Currently, the Arctic is undergoing a significant warming, which has exerted widespread impacts on global climate. Although many mechanisms responsible for the Arctic warming have been proposed, the impacts of the multi‐decadal change of tropical sea surface temperature receive little attention. Here we use numerical experiments to elucidate that the Indian Ocean (IO) warming may contribute to the Arctic warming. Through enhancing the Atlantic Meridional Overturning Circulation, the IO warming remotely induces more ocean heat transport from the North Atlantic to the Arctic. The resulted upper ocean warming dominates the surface warming in the Arctic. Additionally, despite the net negative contribution of the atmospheric heat transport, more warm air is conveyed into the Kara Seas, North Eurasia, and North America sectors, contributing to the local warming. The results propose a new mechanism to interpret the Arctic warming and indicate the important remote impacts of the tropical IO warming. Plain Language Summary: The Arctic warming is a significant phenomenon in the context of global warming, which not only impacts the local ecosystem but also influences global climate. Improved understanding of its causes is important to the protection of the Arctic ecosystem and the forecast of global climate. Although many previous studies have proposed various mechanisms to interpret the Arctic warming, its causes are still not fully understood. In this study, we find that the Indian Ocean (IO) warming is also a possible contributor to the Arctic warming. Through enhancing the Atlantic Meridional Overturning Circulation, the IO warming remotely induces more ocean heat transport from the North Atlantic to the Arctic and then contributes to the Arctic warming. Additionally, the southerly winds in the high latitudes in response to the IO warming, transport more warm air into the Kara Seas, North Eurasia and North America and contributes to the local warming. The present study indicates the IO warming may also contribute to the Arctic warming. A better understanding of the remote impacts of tropical oceans may foster the comprehensive understanding of the complicated reasons for the Arctic warming. Key Points: Rapid warming in the Indian Ocean (IO) may contribute to the Arctic warming through both oceanic and atmospheric pathwaysMore ocean heat is transported from the North Atlantic to the Arctic due to enhanced Atlantic Meridional Overturning Circulation in response to the IO warmingSoutherly winds in the high latitudes in response to the IO warming convey more warm air into parts of the Arctic [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The recently discovered Chile Niño/Niña is an intrinsic coupled climate mode in the southeast Pacific, which influences both regional climate and marine ecosystem. Using Scale Interaction Experiment‐Frontier version 2 seasonal prediction system, it is shown that the Chile Niño/Niña can be skillfully predicted up to 3‐month lead. Although the occurrences and related climate impacts of the Chile Niño/Niña are captured by the prediction system, the predicted magnitudes are weaker than observations in the ensemble mean. Further analyses of the inter‐member relationships indicate that the Chile Niño/Niña predictability depends on how well the coastal ocean‐atmosphere‐land positive feedback among alongshore surface winds, coastal upwelling and the sea surface temperature anomalies is captured. The insufficient reproduction of this essential feedback is responsible for the underestimated magnitude. Therefore, accurately predicting the Chile Niño/Niña remains a challenge. Improving model resolution and ensemble size may be a key to enhancing prediction skills of the coastal climate modes along the eastern boundary upwelling systems. Plain Language Summary: The Chile Niño/Niña is an El Niño–Southern Oscillation‐like phenomenon off northern Chile, which is generated by intrinsic coastal air‐sea‐land interaction. The occurrences of Chile Niño/Niña not only influence the production of marine ecosystem, but also exert impacts on terrestrial climate over the South America. For example, an off‐Chile sea surface temperature warm event induced catastrophic floods over Chile's Atacama Desert in March 2015, causing huge casualties and economic losses. Therefore, skillfully predicting the Chile Niño/Niña is crucial for mitigating climate disasters to benefit the livelihood of people. Based on a state‐of‐the‐art seasonal prediction system, the Chile Niño/Niña and associated climate impacts are found to be predictable one season ahead. We also found that the key to predict the Chile Niño/Niña lies in the realistic simulation of coastal ocean‐atmosphere‐land positive feedback in the southeast Pacific. Our study discusses the predictability of the Chile Niño/Niña for the first time, which may contribute to improving the seasonal prediction of coastal climate modes discovered in the eastern boundary upwelling regions of the major oceans. Establishing an early warning system for such a climate mode may contribute to reducing the socioeconomic losses. Key Points: As an intrinsic coastal climate mode, the Chile Niño/Niña has noticeable impacts on regional climate and marine ecosystemThe occurrences of Chile Niño/Niña events are found to be predictable up to 3 months ahead for the first timeThe Chile Niño/Niña predictability is underpinned by the coastal ocean‐atmosphere‐land positive feedback [ABSTRACT FROM AUTHOR]

Extreme El Niño events severely disrupt the global climate, causing pronounced socio-economic losses. A prevailing view is that extreme El Niño events, defined by total precipitation or convection in the Niño3 area, will increase 2-fold in the future. However, this projected change was drawn without removing the potential impacts of Coupled Model Intercomparison Project phase 5 (CMIP5) models' common biases. Here, we find that the models' systematic biases in simulating tropical climate change over the past century can reduce the reliability of the projected change in the Pacific sea surface temperature (SST) and its related extreme El Niño frequency. The projected Pacific SST change, after removing the impacts of 13 common biases, displays a 'La Niña-like' rather than 'El Niño-like' change. Consequently, the extreme El Niño frequency, which is highly linked to the zonal distribution of the Pacific SST change, would remain mostly unchanged under CMIP5 warming scenarios. This finding increases confidence in coping with climate risks associated with global warming. [ABSTRACT FROM AUTHOR]

The occurrence of the 2017/2018 La Niña, following a weak‐to‐neutral La Niña in boreal winter 2016/2017, was surprising. Based on observational records and multiple linear regression analysis for the Pacific zonal wind tendency (dU/dt), this study investigates possible reasons why the La Niña condition suddenly happened in late 2017. Similar to previous four double‐peaked La Niña events (1983–1985, 1998–2000, 2007–2009, and 2010–2012), we find that the multiyearly persistent easterly anomaly in the central equatorial Pacific is a key condition to the development of the second La Niña. The occurrence of the 2017/2018 La Niña results from large warm sea surface temperature (SST) anomalies in the tropical Indian and Atlantic Oceans that act to force the persistent easterly anomaly in the Pacific via modifying the Walker Circulations. About 24% of the variance of the Pacific dU/dt can be statistically explained by the tropical Indian Ocean and Atlantic SST anomalies. Plain Language Summary: The 2017/2018 La Niña appears to be surprising, given that an El Niño‐like condition has already developed in the first half of 2017 but actually in opposite to most models' forecasts that issued a false alarm of an El Niño. Previous studies suggested that both the tropical Indian and Atlantic Oceans have exhibited a rapid warming in recent decades, which have caused an easterly trend in the central Pacific. In this study, we examine the possible contributions of the tropical Indian Ocean and Atlantic SSTs to the occurrence of the second La Niña in 2017/2018. Our results highlight the importance of the SST warming in the tropical Indian and Atlantic Oceans for the occurrence of the second La Niña under rapid SST warming in the two basins during recent decades. Key Points: Persistent easterly anomaly in the central equatorial Pacific is a key condition to the occurrence of the second La NiñaRapid SST warming in the tropical Indian and Atlantic Oceans acts to strengthen the persistent easterly anomalyAbout 24% of the variance of the dU/dt in the central equatorial Pacific during 1980‐2017 can be explained by the IO and AO SSTAs [ABSTRACT FROM AUTHOR]

El Niño and La Niña, the warm and cold phases of El Niño–Southern Oscillation (ENSO), cause significant year-to-year disruptions in global climate, including in the atmosphere, oceans, and cryosphere. Australia is one of the countries where its climate, including droughts and flooding rains, is highly sensitive to the temporal and spatial variations of ENSO. The dramatic impacts of ENSO on the environment, society, health, and economies worldwide make the application of reliable ENSO predictions a powerful way to manage risks and resources. An improved understanding of ENSO dynamics in a changing climate has the potential to lead to more accurate and reliable ENSO predictions by facilitating improved forecast systems. This motivated an Australian national workshop on ENSO dynamics and prediction that was held in Sydney, Australia, in November 2017. This workshop followed the aftermath of the 2015/16 extreme El Niño, which exhibited different characteristics to previous extreme El Niños and whose early evolution since 2014 was challenging to predict. This essay summarizes the collective workshop perspective on recent progress and challenges in understanding ENSO dynamics and predictability and improving forecast systems. While this essay discusses key issues from an Australian perspective, many of the same issues are important for other ENSO-affected countries and for the international ENSO research community. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, precipitation outputs from retrospective seasonal forecasts made by nine General Circulation Models ( GCMs) are used to investigate historical Indian summer monsoon seasonal rainfall variability and predictability over India. The observed data is taken from the India Meteorological Department whereas GCMs are obtained from the International Research Institute for Climate and Society, Columbia University, the National Center for Environmental Prediction, and the Japan Agency for Marine Earth Science and Technology. The study focusses on June- September precipitation hindcasts initialized from the 1 May. First, the mean climatology, variance of interannual variability ( IAV), and long-term trends for the nine GCMs were evaluated. Then Empirical Orthogonal Function ( EOF) is used to extract major climate modes and spectral analyses method is used to investigate the temporal properties of the leading principal components. It is found that the models are able to reproduce the climatology and IAV to varying degrees. The EOF and spectral analyses of models hindcast reveal that these models are capable of predicting the observed precipitation variability to some extent. In order to study the remote response, the correlation co-efficient between model predicted rainfall and sea surface temperature ( SST) have been calculated. The results suggest that the models show exaggerated remote response to ENSO SST forcing and the Indian Ocean Dipole Mode index has less predictive skill compared to ENSO. The correlation values between the model predicted Monsoon Hadley Index ( MHI) and observed MHI reveals that only a few of them could exhibit large scale circulation features well. [ABSTRACT FROM AUTHOR]

In light of the growing recognition of the role of surface temperature variations in the Indian Ocean for driving global climate variability, the predictive skill of the sea surface temperature (SST) anomalies associated with the Indian Ocean dipole (IOD) is assessed using ensemble seasonal forecasts from a selection of contemporary coupled climate models that are routinely used to make seasonal climate predictions. The authors assess predictions from successive versions of the Australian Bureau of Meteorology Predictive Ocean-Atmosphere Model for Australia (POAMA 15b and 24), successive versions of the NCEP Climate Forecast System (CFSv1 and CFSv2), the ECMWF seasonal forecast System 3 (ECSys3), and the Frontier Research Centre for Global Change system (SINTEX-F) using seasonal hindcasts initialized each month from January 1982 to December 2006. The lead time for skillful prediction of SST in the western Indian Ocean is found to be about 5-6 months while in the eastern Indian Ocean it is only 3-4 months when all start months are considered. For the IOD events, which have maximum amplitude in the September-November (SON) season, skillful prediction is also limited to a lead time of about one season, although skillful prediction of large IOD events can be longer than this, perhaps up to about two seasons. However, the tendency for the models to overpredict the occurrence of large events limits the confidence of the predictions of these large events. Some common model errors, including a poor representation of the relationship between El Niño and the IOD, are identified indicating that the upper limit of predictive skill of the IOD has not been achieved. [ABSTRACT FROM AUTHOR]

The Indian summer monsoon rainfall has complex, regionally heterogeneous, interannual variations with huge socioeconomic impacts, but the underlying mechanisms remain uncertain. The upwelling along the Somalia and Oman coasts starts in late spring, peaks during the summer monsoon, and strongly cools the sea surface temperature (SST) in the western Arabian Sea. They restrict the westward extent of the Indian Ocean warm pool, which is the main moisture source for the monsoon rainfall. Thus, variations of the Somalia–Oman upwelling can have significant impacts on the moisture transport toward India. Here the authors use both observations and an advanced coupled atmosphere–ocean general circulation model to show that a decrease in upwelling strengthens monsoon rainfall along the west coast of India by increasing the SST along the Somalia–Oman coasts, and thus local evaporation and water vapor transport toward the Indian Western Ghats (mountains). Further observational analysis reveals that such decreases in upwelling are caused by anomalously weak southwesterly winds in late spring over the Arabian Sea that are due to warm SST/increased precipitation anomalies over the Seychelles–Chagos thermocline ridge of the southwestern Indian Ocean (and vice versa for years with strong upwelling/weak west Indian summer monsoon rainfall). The latter SST/precipitation anomalies are often related to El Niño conditions and the strength of the Indonesian–Australian monsoon during the previous winter. This sheds new light on the ability to forecast the poorly predicted Indian monsoon rainfall on a regional scale, helped by a proper ocean observing/forecasting system in the western tropical Indian Ocean. [ABSTRACT FROM AUTHOR]

The Indian summer monsoon (ISM) is one of the main components of the Asian summer monsoon. It is well known that one of the starting mechanisms of a summer monsoon is the thermal contrast between land and ocean and that sea surface temperature (SST) and moisture are crucial factors for its evolution and intensity. The Indian Ocean, therefore, may play a very important role in the generation and evolution of the ISM itself. A coupled general circulation model, implemented with a high-resolution atmospheric component, appears to be able to simulate the Indian summer monsoon in a realistic way. In particular, the features of the simulated ISM variability are similar to the observations. In this study, the relationships between the ISM and tropical Indian Ocean (TIO) SST anomalies are investigated, as well as the ability of the coupled model to capture those connections. The recent discovery of the Indian Ocean dipole mode (IODM) may suggest new perspectives in the relationship between ISM and TIO SST. A new statistical technique, the coupled manifold, is used to investigate the TIO SST variability and its relation with the tropical Pacific Ocean (TPO). The analysis shows that the SST variability in the TIO contains a significant portion that is independent from the TPO variability. The same technique is used to estimate the amount of Indian rainfall variability that can be explained by the tropical Indian Ocean SST. Indian Ocean SST anomalies are separated in a part remotely forced from the tropical Pacific Ocean variability and a part independent from that. The relationships between the two SSTA components and the Indian monsoon variability are then investigated in detail. [ABSTRACT FROM AUTHOR]

The Atlantic Niño/Niña, one of the dominant interannual variability in the equatorial Atlantic, exerts prominent influence on the Earth's climate, but its prediction skill shown previously was unsatisfactory and limited to two to three months. By diagnosing the recently released North American Multimodel Ensemble (NMME) models, we find that the Atlantic Niño/Niña prediction skills are improved, with the multi-model ensemble (MME) reaching five months. The prediction skills are season-dependent. Specifically, they show a marked dip in boreal spring, suggesting that the Atlantic Niño/Niña prediction suffers a "spring predictability barrier" like ENSO. The prediction skill is higher for Atlantic Niña than for Atlantic Niño, and better in the developing phase than in the decaying phase. The amplitude bias of the Atlantic Niño/Niña is primarily attributed to the amplitude bias in the annual cycle of the equatorial sea surface temperature (SST). The anomaly correlation coefficient scores of the Atlantic Niño/Niña, to a large extent, depend on the prediction skill of the Niño3.4 index in the preceding boreal winter, implying that the precedent ENSO may greatly affect the development of Atlantic Niño/Niña in the following boreal summer. [ABSTRACT FROM AUTHOR]

A new air‐sea coupled mode is discovered off the coast of northern Chile and named Chile Niño/Niña. It shows remarkable interannual variability in sea surface temperature (SST) with the peak in austral summer from January to March. The related warm (cold) SST anomalies are mainly generated by anomalous southward (northward) alongshore surface winds that suppress (enhance) the coastal upwelling and subsurface mixing and, in turn, reinforce the wind anomalies by heating (cooling) the overlying atmosphere and strengthening the anomalous cross‐shore pressure contrast. The positive feedback is called the coastal Bjerknes feedback in analogy to the equatorial Bjerknes feedback that is responsible for generation of El Niño–Southern Oscillation. The anomalous surface shortwave radiation through the SST‐low stratus cloud thermodynamic feedback and the variation in the mixed‐layer depth play positive roles in the evolution of Chile Niño (Niña). In contrast, the wind‐evaporation‐SST feedback plays almost no role in the evolution. Plain Language Summary: The coastal air‐sea coupled modes occur along eastern boundaries of most of major subtropical oceans and have noticeable biogeochemical impacts on marine ecosystems. However, no such phenomenon has been reported in the southeast Pacific so far. Here, by carefully removing the influence of El Niño–Southern Oscillation, we have discovered a new coastal climate mode off northern Chile and named it Chile Niño/Niña. The intrinsic climate mode along the coast is generated by the coastal Bjerknes feedback among alongshore surface winds, coastal upwelling, and the SST anomalies. The anomalous surface shortwave radiation and the variation in the mixed‐layer depth contribute to the evolution of Chile Niño/Niña. Our results reveal the existence and generation mechanism of Chile Niño/Niña for the first time, which advance our knowledge of ocean‐atmosphere‐land coupled interactions and may provide new insights into the research of marine ecology and blue economy. Key Points: A new intrinsic climate mode is discovered off the coast of northern Chile and named Chile Niño/Niña for the first timeThe coastal Bjerknes feedback involving the ocean‐atmosphere‐land interaction plays an essential role in generating Chile Niño/NiñaThe anomalous shortwave radiation by a stratus cloud feedback and variation of the mixed‐layer depth influence Chile Niño/Niña evolution [ABSTRACT FROM AUTHOR]

In Australia, successful seasonal predictions of wet and dry conditions are achieved by utilizing the remote impact of sea surface temperature (SST) variability in tropical oceans, particularly the Pacific Ocean, on the seasonal timescale. Beyond seasonal timescales, however, it is still unclear which processes and oceans contribute to interannual-to-decadal wet/dry conditions in Australia. This research examines the interannual-to-decadal relationship between global SST anomalies (SSTAs) and Australian wet/dry variability by analyzing observational data and global climate model experiments conducted with the NCAR Community Earth System Model (CESM) and the Model for Interdisciplinary Research on Climate (MIROC). A 10-member ensemble simulation suite for 1960–2015 (CESM) and 1950–2010 (MIROC) is conducted by assimilating the observed three-dimensional ocean temperature and salinity anomalies into fully coupled global climate models. In both observational analyses and ocean assimilation experiments, the most dominant annual mean precipitation variability shows a clear relationship with SSTAs in the tropical Pacific and the Atlantic. Our partial ocean assimilation experiment, in which the ocean component of the CESM and MIROC are assimilated by the observed ocean temperature and salinity anomalies in the equatorial Pacific only, shows that the tropical Pacific SST variability is the main driver of Australian precipitation variability on the interannual-to-decadal timescales. However, our additional partial ocean assimilation experiment, in which the climate models incorporate the observed anomalies solely in the Atlantic ocean, demonstrates that the Atlantic Ocean can also affect Australian precipitation variability on the interannual-to-decadal timescale through changes in tropical Pacific SSTAs and the modulation of the global Walker circulation. Our results suggest that about a half of Australian interannual-to-decadal precipitation variability originates from the Atlantic Ocean. [ABSTRACT FROM AUTHOR]

Variations of East Asian westerly jet (EAJ) drastically affect the rainfall in southern China (SC) during Meiyu season. Previous studies conventionally focused on the entire EAJ's variations and their impacts. In this study, we find that the variations of EAJ eastern section (EAJE) and western section (EAJW) are mostly independent of each other. Moreover, the independent components of EAJE and EAJW's variations have different impacts on the rainfall in SC. Southward-displaced and intensified EAJE (SI-EAJE) and southward-displaced and weakened EAJW (SW-EAJW), the first two leading modes of EAJ variations, are associated with increased rainfall anomalies centred over central and southern parts of SC, respectively. Associated with the SI-EAJE (SW-EAJW), anomalous cold cyclone is centred around the Japan Sea (central China). The associated anomalous westerly wind and northward-decreasing (northwestward-decreasing) temperature centred over the central (southern) SC together induce midtropospheric warm advection and thus positive rainfall anomalies centred over the central (southern) SC. The anomalous circulations also cause moisture convergences roughly collocated with the anomalous warm advections over the SC, which intensifies the rainfall anomalies. Warm sea surface temperature anomalies in the equatorial central-eastern Pacific during boreal spring induce meridional teleconnection along the coastal East Asia in Meiyu season through suppressing the convective activities in the northwestern Pacific. The resultant SI-EAJE and associated anomalous circulations increase the rainfall over the central SC, and vice versa. Dipole of increased (decreased) spring snow anomalies on the eastern (western) Tibetan Plateau suppresses (intensifies) convective activities in Meiyu season. The resultant SW-EAJW and associated anomalous circulations increase the rainfall in the southern SC. • Interannual variations of EAJ eastern and western section are primarily independent. • The two EAJ sections cause different Meiyu rainfall anomalies in the southern China. • Thermal advection and moisture anomalies induce the different rainfall anomalies. • Variations of EAJ eastern section can be induced by preceding ENSO in boreal spring. • Dipole of spring snow anomalies on Tibetan Plateau changes the EAJ western section. [ABSTRACT FROM AUTHOR]