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The extreme positive Indian Ocean Dipole (pIOD) in 2019 was followed by tropical Indian Ocean (TIO) basin‐wide warming in summer 2020, which contributed to severe flooding in the Yangtze River basin. Here, the potential relationship between extreme pIOD and subsequent summer TIO basin‐wide warming is explored using observations and model outputs, revealing that this sequential co‐occurrence is significantly influenced by Pacific SST conditions. Extreme pIODs that coincide with El Niño tend to be followed by TIO basin‐wide warming, whereas those cooccurring with neutral or La Niña conditions are comparatively less likely to do so. This is because El Niño can trigger anomalous anticyclone over the southeastern TIO, thereby maintaining and reinforcing the extreme pIOD‐related warm SST anomalies over the southwestern TIO, which subsequently induces SST warming over the northern TIO in summer. Our findings highlight the important modulation role of Pacific SST conditions, with significant implications for regional climate predictions.

Since the 20th century, accompanied by a long-term warming trend, the global surface air temperature (SAT) has exhibited distinct interdecadal oscillations. The period from 1910 to 2012 can be divided into four phases, including two rapid warming (1910–1945 and 1975–1998) and two warming slowdown (1940–1975 and 1998–2012) periods. This study explores the spatiotemporal characteristics of the interdecadal trends in global SAT under the influence of sea surface temperature (SST) on a multi-basin scale. Here, we have accumulated the numerical simulated SAT anomalies under the forcing of historical SST in the selected ocean basins. The results indicate that multi-basin SSTs collectively govern the spatiotemporal variations and interdecadal trends of SATs during rapid warming periods. SSTs in the Indian Ocean, North Atlantic, and western Pacific can affect the spatiotemporal interdecadal trends of SAT during 1940–1975. SSTs in the eastern tropical Pacific and North Pacific can modify the SAT spatiotemporal trends during 1998–2012. Considering the nonlinear interactions between different oceanic regions, the SAT forced by the collective SSTs in the six ocean basins shows high consistency with observation. This indicates that the combined effects of SSTs in the six ocean basins are key reasons for global SAT interdecadal change in 1910–2012.

The Indian Ocean Dipole (IOD) can affect the El Niño–Southern Oscillation (ENSO) state of the following year, in addition to the well-known preconditioning by equatorial Pacific Warm Water Volume (WWV), as suggested by a study based on observations over the recent satellite era (1981–2009). The present paper explores the interdecadal robustness of this result over the 1872–2008 period. To this end, we develop a robust IOD index, which well exploits sparse historical observations in the tropical Indian Ocean, and an efficient proxy of WWV interannual variations based on the temporal integral of Pacific zonal wind stress (of a historical atmospheric reanalysis). A linear regression hindcast model based on these two indices in boreal fall explains 50 % of ENSO peak variance 14 months later, with significant contributions from both the IOD and WWV over most of the historical period and a similar skill for El Niño and La Niña events. Our results further reveal that, when combined with WWV, the IOD index provides a larger ENSO hindcast skill improvement than the Indian Ocean basin-wide mode, the Indian Monsoon or ENSO itself. Based on these results, we propose a revised scheme of Indo-Pacific interactions. In this scheme, the IOD–ENSO interactions favour a biennial timescale and interact with the slower recharge-discharge cycle intrinsic to the Pacific Ocean.

The sea surface temperature anomaly (SSTA) in the North Indian Ocean (NIO) region associated with Indian Ocean Basin Mode (IOBM) is well‐known as a key factor in impacting the Tibetan Plateau summer precipitation (TPSP). However, either the commonly used IOBM index or the basin‐mean index of SSTA in the NIO region captures only a small portion of TPSP variability, making it underrated in indicating the TPSP. In this study, we demonstrate a significant and predictable relationship between the NIO SSTA and TPSP, when further considering the NIO pattern diversity. This relationship can be depicted by two physics‐based indices accounting for the diverse NIO patterns, which can effectively capture their distinct spatial features and associated impacts on the TPSP. Such an extended diversity view of NIO provides potential predictability of the TPSP.

Previous studies have demonstrated that the tropical Indian Ocean basin mode (IOB) favors the phase transition of ENSO; however, they have not differentiated the two types of ENSO. This study reports that the boreal winter-spring IOB appears more likely to induce the central-Pacific (CP) ENSO than the eastern-Pacific ENSO one year later based on observation data and CMIP5 simulations. We find a strong asymmetry in the forcing of the IOB on the CP ENSO. The impact of IOB warming on CP La Niña events is more significant than the impact of IOB cooling on CP El Niño events. IOB warming during late winter to early spring produces easterly wind anomalies over the western equatorial Pacific and an anomalous descending motion of the Walker circulation near the dateline, inducing cooling in the central Pacific during the subsequent summer to winter. This suggests that interbasin interactions with the tropical Indian Ocean, in addition to the northern tropical Atlantic Ocean, are capable of generating CP La Niña events. Most CMIP5 models generally capture the negative IOB-CP ENSO lagged correlation. However, the cooling center and sinking branch of the anomalous Walker circulation in the Pacific Ocean forced by the IOB warming are weaker and shifted eastward in the multimodel ensemble than in the observations. Additionally, the observed asymmetry of the IOB impact on the CP ENSO is not captured by the CMIP5 models. This study indicates that improving the simulation of the IOB as a contributor to ENSO diversity remains a challenge.

Low-frequency changes in the tropical Indian Ocean surface temperature have previously been investigated in the context of the Indian Ocean basin-wide (IOBM) and dipole (IOD) modes. The IOBM and IOD are the leading eigenmodes estimated from a traditional anomaly of SST. This approach ignores the possibility of multiple seasonal cycles (SCs) having different geographic patterns and interannually modulating amplitudes. The analyses presented here are anchored on the four sets of multivariate seasonal cycles independently extracted from the monthly observations of sea surface temperature (SST), surface wind, and surface pressure variations. We show that the secular warming, encapsulated by the monotonic variations of the first SC of SST (SST–SC1), differs from the previous linear trend patterns and has the most significant variance in the Indian Ocean Warm Pool (IOWP). Hence, these warming tendencies quantify the monotonic expansion rates of IOWP. The most significant interannual responses of Indian Ocean SST to remote forces (such as El Niño and La Niña) are also captured by SST–SC1. Unlike the traditional IOBM but similar to SST–SC1’s secular warming, these remotely forced interannual signals also have considerable variances in IOWP. The interannual variations in SST’s third seasonal cycle (i.e., SST–SC3) inherit SST–SC3’s dipole pattern but diverge from classical IOD in many aspects and are predominantly controlled by local processes. However, they are insufficient to account for the total interannual signals on their own. The collective interannual variations of four seasonal cycles—with significant variances off Africa’s eastern shores—demonstrate basin-wide unipolar patterns. Hence, SST interannual signals in the north-western Indian Ocean and the constantly growing warming in the IOWP influence climate and weather over countries surrounding the Indian Ocean. Thus, this study offers a simple way to separate three types of climate signals: secular, internal, and remotely induced climate fluctuations.

This paper identifies the seasonal relationships between monsoon activities over South China (SC) in winter and summer, which can help improve seasonal predictability. A predefined unified monsoon index that can well represent monsoon characteristics in both winter and summer over SC is employed. A time series of this unified monsoon index in summer and winter, and a lead-lag correlation analysis of the unified monsoon index, found that from summer to winter, monsoon activities tend to have an out-of-phase relationship (weak summer with strong winter monsoons or strong summer with weak winter), while from winter to summer, they tend to be in-phase (weak winter with weak summer or strong winter with strong summer). The composite difference between strong and weak winter monsoons shows that in the preceding summer of strong winter monsoons, monsoon activities tend to be weak, due to the influence of developing La Niña-like events; in the ensuing summer, monsoon activities tend to be strong, modulated by an anomalous cyclone over the western North Pacific (WNP), which is triggered by that La Niña-like pattern over the East Pacific. From summer to winter, the Indian Ocean dipole (IOD) mode is evident over the Indian Ocean (IO); from winter to summer, the Indian Ocean Basin (IOB) mode is dominant, which confirms the important role of the IO in these seasonal relationships of monsoon activities. A negative IOD pattern acts together with La Niña-like forcing, enhances northerly anomalies over East Asia, strengthens winter monsoon winds, and thus enhances the out-of-phase relationship. IOB cooling can capture the anomalous signal of El Niño–Southern Oscillation (ENSO) and favor the persistence of an anomalous cyclone over the WNP until the following summer (“capacitor effect”), which is important for the in-phase relationship. These roles are also further verified by numerical experiments that prescribe ENSO-like, IOD-like, and IOB-like heat source anomalies over the Pacific and IO in an anomalous atmospheric general circulation model.

This study applies WACCM, a stratosphere-resolving model to dissect the stratospheric responses in the northern winter extratropics to the imposed ENSO-related SST anomalies in the tropics. It is found that the anomalously warmer and weaker stratospheric polar vortex during warm ENSO is basically a balance of the opposite effects between the SST anomalies in the tropical Pacific (TPO) and that over the tropical Indian Ocean basin (TIO). Specifically, the ENSO-related SST anomalies over the TIO are to induce an anomalously colder and stronger stratospheric polar vortex during warm ENSO, which acts to partially cancel out the much stronger warmer and weaker polar vortex response to the SST anomalies over the TPO. Further analysis indicates that, while the SST forcing from the TPO contributes to the anomalously positive Pacific North America (PNA) pattern in the troposphere and the enhancement of the stationary wavenumber (WN)-1 in the stratosphere during warm ENSO, the TIO SST forcing is to induce an anomalously negative PNA and a reduction of both WN-1 and WN-2 in the stratosphere. Diagnosis of E–P flux confirms that, the anomalously upward propagation of stationary waves in the extratropics mainly lies over the western coast of North America during warm ENSO, which is mainly associated with the TPO-induced positive PNA response and is partially suppressed by the effect of the accompanying TIO SST forcing.

The oldest oceanic basin (160–180 Ma) in the western Pacific is the birthplace of the Pacific Plate and is thus essential for understanding the formation and evolution of the oceanic plate. However, the upper mantle structure beneath the region has not been thoroughly investigated because of the remoteness and difficulties of long‐term in situ seismic measurements at the ocean bottom. From 2018 to 2019, the Oldest‐1 experiment on the oldest seafloor was conducted as part of the international Pacific Array initiative. We present the first three‐dimensional P ‐wave velocity structure down to a depth of 350 km based on the relative travel time residuals of teleseismic earthquakes recorded by 11 broadband ocean‐bottom seismometers operated during the Oldest‐1 experiment. Our result shows a fast P ‐wave velocity anomaly ( V P perturbation of 2%–4% faster than average) at a depth of 95–185 km beneath the northeast of the study area. This structure is interpreted as evidence of dry, viscous, and rigid materials at depths below the lithosphere. Two slow anomalies ( V P perturbation of 2%–4% slower than average) are seen beneath the southwestern and eastern (the oldest seafloor >170 Ma) parts of the array site. The low‐velocity zones are found at depths of 95–305 km. The observed velocity structures can be indicative of plume activities that affected the upper mantle as the Pacific Plate migrated over hotspots from the southeast. Alternatively, the observed velocity features may provide seismic evidence for small‐scale sublithospheric convection. One‐year ocean‐bottom geophysical investigation on the oldest Pacific provides seismic mantle structure of the region Detailed 3‐D mantle structure implies complex evolution process of Pacific Plate Our model implies thermochemical modification of the upper mantle by plume interaction or small‐scale convection

In this study, we investigate the predictability of the tropical Indian Ocean (TIO) sea surface temperature anomalies (SSTA) using the recently released North American Multimodel Ensemble dataset (NMME). We place emphasis on the predictability of two interannual variability modes: the Indian Ocean Basin mode (IOBM) and the Indian Ocean Dipole (IOD). If defined by a 0.5 correlation skill, we find that the statistically skilful predictions correspond to an approximately 9- and 4-month lead for the two modes, respectively. We then applied a newly-developed predictability framework, i.e. Average Predictability Time method (APT), to explore the most potentially predictable mode (APT1) for the TIO SSTA. The derived APT1s correlate significantly to the IOBM and IOD, but are also characterised by several significant differences, which implies that there is a close link between the variability-related modes and the predictability-defined modes. Further analysis reveals that the predictability source of the IOBM-related APT1 originates from ENSO-induced thermocline variation over the southwest Indian Ocean, whereas wind-driven upwelling near Sumatra dominates IOD-related APT1. This study provides insights into the understanding of TIO SSTA predictability and offers a practical approach to obtain predictable targets to improve the TIO seasonal prediction skill.