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The South China Sea (SCS) summer monsoon (SCSSM) and Western North Pacific tropical cyclones (TCs) are both tropical systems that interact with each other on multiple scales. This study examines the differences in TCs activity characteristics between anomalous strong and weak SCSSM years, and explores the possible mechanisms behind these differences through the coupling relationship between tropical atmospheric circulation and oceanic surface conditions. Results show that the destructiveness of TCs over the Western North Pacific is stronger during weak SCSSM years than in strong years, whereas the opposite occurs for TCs over the SCS. The interaction between the tropical Indo-Pacific ocean and atmosphere plays a key role in the relationship between SCSSM intensity and TCs activity. In strong (weak) SCSSM years, the sea surface temperature anomaly (SSTA) in the tropical Pacific Ocean tends to correspond to a La Niña-like (El Niño-like) distribution, whereas the tropical Indian Ocean shows an Indian Ocean dipole-negative (positive) phase distribution. Moreover, Walker circulations in both the Indian and Pacific Oceans are coupled during these years, which creates a seesaw-like relationship in the conditions for TCs formation between the SCS and the Western Pacific Ocean. During weak SCSSM years, the formation and activity of TCs over the SCS are suppressed due to the weakened water vapor transport caused by abnormal easterly winds from the eastern Indian Ocean to the southern SCS. Meanwhile, the higher SSTA in the Western Pacific Ocean enhances the TCs activity. In strong SCSSM years, the enhanced monsoon drives a stronger monsoon trough, improving the convective environment over the SCS, whereas in contrast, the Western Pacific Ocean is covered by colder water, resulting in poorer conditions for TCs genesis. [ABSTRACT FROM AUTHOR]

The Southern Indonesian (SI) region is known for its high-intensity coastal upwelling caused by monsoonal wind. Interannual phenomena such as El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) also influence upwelling activity in this region. This study analyzed the relationship between upwelling intensity (UI sst) and those variables and their impact on oceanographic features such as Sea Surface Temperature (SST) and chlorophyll-a concentration. We used satellite imagery data, including SST from the National Oceanic and Atmospheric Administration (NOAA) and chlorophyll-a from MODIS, to analyze the aforementioned issue. To identify the impact of wind patterns on coastal upwelling, we analyzed using zonal wind stress from ERA-5 Data. Quantification of UI sst is defined as the SST gradient between the coastal and open ocean waters. Linear and partial correlation analysis between UI sst with the Ocean Niño Index (ONI) and Dipole Mode Index (DMI) were conducted to see the influence of ENSO and IOD phenomena. Anomaly analysis was also conducted on SST, chlorophyll-a concentration, zonal windstress and UI sst to see how large the values were during the years of the ENSO and IOD events. Upwelling in the SI region typically occurs during southeast monsoon (SEM) periods, starting earlier in the East side (Nusa Tenggara Islands) and moving towards the West side (South Coast of Java). The correlation analysis (both linear and partial) indicates that the IOD has a stronger influence on UI sst in the SI region compared to ENSO, especially during June to October (SEM periods). This finding is confirmed by anomaly analysis, which reveals significant changes in SST, chlorophyll-a concentration, zonal windstress, and UI sst during ENSO and IOD events. The magnitude of the anomalies is generally stronger during IOD events than those observed under ENSO conditions. • Remote sensing satellite data can identify the variability of upwelling phenomena in the Southern Indonesian (SI) seas. • The strength of upwelling intensity in SI is strongly influenced by Interannual phenomena such as the ENSO and IOD. • Sea Surface Temperature and Chlorophyll-a anomalies confirm the influence of changes in upwelling intensity by ENSO and IOD. • IOD has a stronger influence than ENSO on Upwelling intensity in the SI Region. [ABSTRACT FROM AUTHOR]

The recharge oscillator mechanism suggests that a strong El Niño event can trigger a following La Niña event that sometimes lasts for two or even three years through warm water volume preconditioning within the tropical Pacific. However, a prominent and persistent “double-dip” La Niña event appeared in the boreal winters of 2020/2021 and 2021/2022 without any significant El Niño preconditioning. Here we explore the possibility that tropical basin interactions may have initiated and helped to prolong La Niña conditions over the 2-year period 2020–2022. This period was preceded by a strong positive Indian Ocean Dipole (IOD) during the boreal fall of 2019 that gave way to basin-scale warming in the Indian Ocean in early 2020 and a notable tropical Atlantic warming in the boreal winter of 2019/2020. Later, a strong Atlantic Niño developed in the boreal summer of 2021. Using composite analyses to characterize earlier double-dip La Niñas, we argue the unusual sequence of events in 2019–2021 in the Indian and Atlantic Oceans may have energized and sustained the 2020–2022 La Niña event without any significant warm water volume preconditioning within the tropical Pacific.

The highly dynamic nature of the marine environment can have a substantial influence on the foraging behaviour and spatial distribution of marine predators, particularly in pelagic marine systems. However, knowledge of the susceptibility of benthic marine predators to environmental variability is limited. This study investigated the influence of local-scale environmental conditions and large-scale climate indices on the spatial distribution and habitat use in the benthic foraging Australian fur seal (Arctocephalus pusillus doriferus; AUFS). Female AUFS provisioning pups were instrumented with GPS or ARGOS platform terminal transmitter tags during the austral winters of 2001–2019 at Kanowna Island, south-eastern Australia. Individuals were most susceptible to changes in the Southern Oscillation Index that measures the strength of the El Niño Southern Oscillation, with larger foraging ranges, greater distances travelled and more dispersed movement associated with 1-yr lagged La Niña-like conditions. Additionally, the total distance travelled was negatively correlated with the current year sea surface temperature and 1-yr lagged Indian Ocean Dipole, and positively correlated with 1-yr lagged chlorophyll-a concentration. These results suggest that environmental variation may influence the spatial distribution and availability of prey, even within benthic marine systems.

Indian Ocean decadal sea-level variability is an active research area, with many unresolved questions due to inadequate observational coverage. In this study, we analyse 26 Coupled Model Intercomparison Project (CMIP) pre-industrial simulations and isolate two consistent modes of Indian Ocean variability, which collectively explain about 50% of the total decadal sea-level variance. With opposite sea-level signals in the southwestern and eastern Indian Ocean, the first mode is related to decadal modulation of the Indian Ocean Dipole (DIOD) and equatorial wind-driven dynamics. Though IOD is more independent of the El Niño–Southern Oscillation (ENSO) at decadal (r ~ 0.4) than interannual (r ~ 0.6) timescales, the DIOD–ENSO co-variability yields sea-level signals along the west coast of Australia, transmitted from the western Pacific via the Indonesian Throughflow. The second mode encompasses variability in the south Indian Ocean (SIODV), exhibiting a broad monopolar sea-level pattern east of Madagascar. In about half of the models, the SIODV is largely independent from DIOD (and decadal ENSO) and driven by south Indian Ocean wind-stress curl associated with meridional shifts in the Mascarene High (MH). In the other models, the SIODV lags the DIOD about 3 years. In those models, in addition to MH forcing, the DIOD-related alongshore wind stress off the northwest Australian coast triggers Rossby waves that also contribute to the SIODV, further west. The DIOD and MH forcing are mutually independent (r ~ 0.2). The results are broadly consistent with sea-level variations derived from the short altimeter data, despite an underestimation of the Oceanic bridge signals in CMIP models. [ABSTRACT FROM AUTHOR]

Highlights: [•] We modelled rainfall using multiple regression and Artificial Neural Networks for Victoria, Australia. [•] We examined combined lagged months of ENSO and IOD as potential predictors of spring rainfall. [•] Spring rainfall was predicted three years in advance with the developed models using ENSO–IOD lagged months. [•] ANN models proved to be more accurate than multiple regression models in terms of long term predictions. [ABSTRACT FROM AUTHOR]

The Madden–Julian oscillation (MJO) is the main component of intraseasonal variability of the tropical convection, with clear climatic impacts at an almost-global scale. Based on satellite observations, it is shown that there are two types of austral-summer MJO events (broadly defined as 30–120 days convective variability with eastward propagation of about 5 m/s). Equatorial MJO events have a period of 30–50 days and tend to be symmetric about the equator, whereas MJO events centered near 8°S tend to have a longer period of 55–100 days. The lower-frequency variability is associated with a strong upper-ocean response, having a clear signature in both sea surface temperature and its diurnal cycle. These two MJO types have different interannual variations, and are modulated by the Indian Ocean Dipole (IOD). Following a negative IOD event, the lower-frequency southern MJO variability increases, while the higher-frequency equatorial MJO strongly diminishes. We propose two possible explanations for this change in properties of the MJO. One possibility is that changes in the background atmospheric circulation after an IOD favour the development of the low-frequency MJO. The other possibility is that the shallower thermocline ridge and mixed layer depth, by enhancing SST intraseasonal variability and thus ocean–atmosphere coupling in the southwest Indian Ocean (the breeding ground of southern MJO onset), favour the lower-frequency southern MJO variability. [ABSTRACT FROM AUTHOR]