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A negative Indian Ocean Dipole (IOD) event is under way. The IOD index has been very close to or exceeded negative IOD thresholds (i.e., at or below −0.4 °C) over the past eight weeks. All climate model outlooks surveyed indicate that negative IOD conditions are likely to continue into late spring. A negative IOD event is associated with above average winter-spring rainfall for much of Australia.

◆ Observational data analysis indicates that cold water brought up by coastal upwelling south of Java can trigger the onset of Indian Ocean Dipole (IOD). ◆ A method to accurately determine coastal upwelling signal based on satellite chlorophyll-a data was developed and used for analysis in areas with limited observations. ◆ As IOD affects the global climate, including summer weather in Japan, the findings of this study are expected to help improve the predictability of both the global climate and IOD.

Marine ecosystems are experiencing rapid shifts under climate change scenarios and baleen whales are vulnerable to environmental change, although not all impacts are yet clear. We identify how the migration behaviour of the Chagos whale, likely a pygmy blue whale (Balaenoptera musculus brevicauda), has changed in association with shifts in environmental factors. We used up to 18 years of continuous underwater acoustic recordings to analyse the relationships between whale acoustic presence and sea surface temperature (SST), chlorophyll-a concentration, El-Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD). We compared these relationships between two independent sites Diego Garcia southeast (DGS) and Diego Garcia northwest (DGN) where Chagos whales are detected and are suspected to move interannually across the Chagos-Laccadive ridge. We showed that the number of whale songs detected increased on average by 7.7% and 12.6% annually at DGS and DGN respectively. At the DGS site, Chagos whales shifted their arrival time earlier by 4.2 ± 2.0 days/year ± SE and were detected for a longer period by 7.3 ± 1.2 days/year ± SE across 18 years. A larger number of songs were detected during periods of higher chlorophyll-a concentration, and with positive IOD phases. At the DGN site, we did not see an earlier shift in arrival and songs were not detected for a longer period across the 13 years. Whale presence at DGN had a weaker but opposite relationship with chlorophyll-a and IOD. The oceanic conditions in the Indian Ocean are predicted to change under future climate scenarios and this will likely influence Chagos whale migratory behaviour. Understanding how environmental factors influence whale movement patterns can help predict how whales may respond to future environmental change. We demonstrate the value of long-term acoustic monitoring of marine fauna to determine how they may be affected by changing environmental conditions.

Shifts in phytoplankton phenology were observed in the Strait of Malacca (SM) and Sunda Shelf (SS), which were speculated to be potentially related to global warming and climate anomaly events. Such interactions between phytoplankton structure and physico-chemical factors were less known in narrow straits. Therefore, the spatial distribution pattern and diversity of surface phytoplankton assemblage, local hydrology, and nutrient regimes were investigated over the SM and SS (South China Sea, SCS) during 2017 and 2018 pre-monsoon season (spring). Diatoms, dinoflagellates, and cyanobacteria were representatives of microphytoplankton in the survey area. Total phytoplankton abundance peaked near Singapore Strait (SGS) and diminished toward SS. From the lower ratio of diatoms to dinoflagellates (<3) in SS, we deduced lower carbon pump efficiency here. In agreement with the modeled results proposed previously, cold conditions (negative Indian Ocean Dipole, IOD) were more suitable for high diatom (especially centric forms) abundance, while warm scenarios (positive IOD/El Niño period as in 2017) seemed to favor dinoflagellates and/or cyanobacteria. Specifically, diatom proportion increased by 30% and dinoflagellate, cyanobacteria reduced by 71%, 75% in response to shifts of climate anomaly from 2017 cruise to 2018 cruise. This study between field microalgae and physical and chemical conditions would be helpful to launch large-scale climate model, biogeochemistry, and carbon cycling in future research.

Detailed ocean currents in the southeastern tropical Indian Ocean adjacent to southern Sumatran and Javan coasts have not been fully explained because of limited observations. In this study, zonal current characteristics in the region have been studied using simulation results of a 1/8∘ global hybrid coordinate ocean model from 1950 to 2013. The simulated zonal currents across three meridional sections were then investigated using an empirical orthogonal function (EOF), where the first three modes account for 75 %-98 % of the total variance. The first temporal mode of EOF is then investigated using ensemble empirical mode decomposition (EEMD) to distinguish the signals. This study has revealed distinctive features of currents in the South Java Current (SJC) region, the Indonesian Throughflow (ITF)-South Equatorial Current (SEC) region, and the transition zone between these regions. The vertical structures of zonal currents in southern Java and offshore Sumatra are characterized by a one-layer flow. Conversely, a two-layer flow is observed in the nearshore and transition regions of Sumatra. Current variation in the SJC region has peak energies that are sequentially dominated by semiannual, intraseasonal, and annual timescales. Meanwhile, the transition zone is characterized by semiannual and intraseasonal periods with pronounced interannual variations. In contrast, interannual variability associated with El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) modulates the prominent intraseasonal variability of current in the ITF-SEC region. ENSO has the strongest influence at the outflow ITF, while the IOD's strongest influence is in southwestern Sumatra, with the ENSO (IOD) leading the current by 4 months (1 month). Moreover, the contributions (largest to smallest) of each EEMD mode at the nearshore of Java and offshore Sumatra are intraseasonal, semiannual, annual, interannual, and long-term fluctuations. The contribution of long-term

The study of ocean bottom pressure (OBP) helps to understand the changes in the sea level budget and ocean deep circulation. In this study, the characteristics and mechanisms of interannual OBP variability in the Southern Indian Ocean are examined using Gravity Recovery and Climate Experiment (GRACE) satellite data from 2003 to 2016. Results show that there are two energetic OBP centers in the Southern Indian Ocean (50°-60°S, 40°-60°E and 45°-60°S, 80°-120°E). The OBP magnitudes at two centers have strong variability on interannual time scales, and their values are larger during austral summer (NDJF) and winter (JJAS). Atmospheric forcing plays an important role in local OBP variability. The high (low) sea level pressure (SLP) over the Southern Indian Ocean benefits positive (negative) OBP anomalies via the convergence (divergence) of Ekman transport driven by local wind. Such SLP anomalies are related to the Southern Annular Mode (SAM), Southern Oscillation (SO) and Indian Ocean dipole (IOD). SAM can influence the OBP changes in both austral summer and winter, while SO and IOD have positive correlations with OBP variability during austral summer and austral winter, respectively. These results are validated by a mass-conservation ocean model, which further confirms the importance of atmospheric forcing on the interannual OBP variations.

Oceans across the globe are warming rapidly and marine ecosystems are changing as a result. However, there is a lack of information regarding how blue whales are responding to these changing environments, especially in the Southern Hemisphere. This is because long term data are needed to determine whether blue whales respond to variability in environmental conditions. Using over 16 years of passive acoustic data recorded at Cape Leeuwin, we investigated whether oceanic environmental drivers are correlated with the migration patterns of eastern Indian Ocean (EIO) pygmy blue whales off Western Australia. To determine which environmental variables may influence migration patterns, we modelled the number of acoustic call detections of EIO pygmy blue whale calls with broad and fine scale environmental variables. We found a positive correlation between total annual whale call detections and El Niño Southern Oscillation (ENSO) cycles and the Indian Ocean Dipole (IOD), with more whale calls detected during La Niña years. We also found that monthly whale call detections correlated with sea surface height around the hydrophone and chlorophyll-a concentration at a prominent blue whale feeding aggregation area (Bonney Upwelling) where whales feed during the summer before migrating up the west Australian coast. At the interannual scale, ENSO had a stronger relationship with call detections than IOD. During La Niña years, up to ten times more EIO pygmy blue whale calls were detected than in neutral or El Niño years. This is likely linked to changes in productivity in the feeding areas of the Great Australian Bight and Indian Ocean. We propose that in lower productivity years whales either skipped migration or altered their habitat use and moved further offshore from the hydrophones and therefore were not detected. The frequency and intensity of ENSO events are predicted to increase with climate change, which is likely to impact the productivity of the areas used by blue whale

Most climate forecast agencies failed to make successful predictions of the strong 2020/2021 La Niña event before May 2020. The western equatorial Pacific warm water volume (WWV) before the 2020 spring failed to predict this La Niña event because of the near neutral state of the equatorial Pacific Ocean in the year before. A strong Indian Ocean Dipole (IOD) event took place in the fall of 2019, which is used as a precursor for the La Niña prediction in this study. We used observational data to construct the precursory relationship between negative sea level anomalies (SLA) in the southeastern tropical Indian Ocean (SETIO) in boreal fall and negative Niño 3.4 sea surface temperature anomalies index one year later. The application of the above relation to the prediction of the 2020/2021 La Niña was a great success. The dynamics behind are the Indo-Pacific "oceanic channel" connection via the Indian Ocean Kelvin wave propagation through the Indonesian seas, with the atmospheric bridge playing a secondary role. The high predictability of La Niña across the spring barrier if a positive IOD should occur in the previous year suggests that the negative SETIO SLA in fall is a much better and longer predictor for this type of La Niña prediction than the WWV. In comparison, positive SETIO SLA lead either El Niño or La Niña by one year, suggesting uncertainty of El Niño predictions.

In recent years, enormous socioeconomic damage has been wreaked by recurrent abnormal weather events around the world. The seedbed for this abnormal weather is climate variability events on a massive spatiotemporal scale - those that cover thousands of kilometers and continue over months and years. Here we will review an article featured on the cover of the November 28, 2013 issue of Nature Geoscience on research predicting how a climate variability event in the tropical Indian Ocean, known as the Indian Ocean Dipole (IOD), will change with global warming in the future.

The Arabian Gulf comprises one of the world's most unique and fragile marine ecosystems; it is susceptible to the adverse effects of climate change due to its shallow depth and its location within an arid region that witnesses frequent severe atmospheric events. To reproduce these effects in numerical models, it is important to obtain a better understanding of the region's sea surface temperature (SST) variability patterns, as SST is a major driver of circulation in shallow environments. To this end, here, empirical orthogonal function (EOF) decomposition analysis was conducted to investigate interannual to multi-decadal SST variability in the Gulf from 1982 to 2020, using daily Level 4 Group for High Resolution SST (GHRSST) data. In this way, three dominant EOF modes were identified to contribute the Gulf's SST variability. Significant spatial and temporal correlations were found suggesting that throughout the 39-year study period, SST variability could be attributed to atmospheric changes driven by the El Nio-Southern Oscillation (ENSO), Atlantic Multi-decadal Oscillation (AMO), and Indian Ocean Dipole (IOD) climate modes. Spatial and temporal analyses of the dataset revealed that the average SST was 26.7°C, and that the warming rate from 1982 to 2020 reached up to 0.59°C/decade. A detailed examination of SST changes associated with heat exchange at the air-sea interface was conducted using surface heat fluxes from fifth generation (ERA5) European Centre for Medium-Range Weather Forecasts (ECMWF). Despite the SST warming trend, the accumulation of heat during the study period is suggesting that there was an overall loss of heat (cooling). This cooling reverted into heating in 2003 and has since been increasing.

Dipole: the 'Indian Niño' that has brought devastating drought to East Africa.

Iodine affects the radiative budget and the oxidative capacity of the atmosphere and is consequently involved in important climate feedbacks. A fraction of the iodine emitted by oceans ends up in aerosols, where complex halogen chemistry regulates the recycling of iodine to the gas-phase where it effectively destroys ozone. The iodine speciation and major ion composition of aerosol samples collected during four cruises in the East and West Pacific and Indian Oceans was studied to understand the influences on iodine's gas-aerosol phase recycling. A significant inverse relationship exists between iodide (I-) and iodate (IO3-) proportions in both fine and coarse mode aerosols, with a relatively constant soluble organic iodine (SOI) fraction of 19.8% (median) for fine and coarse mode samples of all cruises combined. Consistent with previous work on the Atlantic Ocean, this work further provides observational support that IO3- reduction is attributed to aerosol acidity, which is associated to smaller aerosol particles and air masses that have been influenced by anthropogenic emissions. Significant correlations are found between SOI and I-, which supports hypotheses that SOI may be a source for I-. This data contributes to a growing observational dataset on aerosol iodine speciation and provides evidence for relatively constant proportions of iodine species in unpolluted marine aerosols. Future development in our understanding of iodine speciation depends on aerosol pH measurements and unravelling the complex composition of SOI in aerosols.