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The Indian Ocean Dipole (IOD) and El Niño-Southern Oscillation (ENSO) are the primary climatic modes that profoundly impact physical and biological processes in the Northern Indian Ocean (NIO). IOD- and ENSO-related vertical phytoplankton anomalies, however, remain poorly understood. Using the three-dimensional Chlorophyll a concentration dataset generated by a machine learning model, this study examines IOD- and ENSO-linked vertical phytoplankton anomalies over the entire euphotic layer (0-100 m) in the NIO during 2000-2019. Results reveal that IOD and ENSO trigger significant opposite changes in phytoplankton at 0-50 m and 50-100 m. The effects of IOD and ENSO on the vertical structure of phytoplankton are generally asymmetric, with anomalies at 0-50 m being significantly larger than that at 50-100 m. During summer and fall, the significant vertical phytoplankton anomalies in the Central Arabian Sea (CAS), Southern Tip of India (STI), and the Eastern Equatorial Indian Ocean (EEIO), are primarily related to IOD forcing. IOD-linked negative (positive) phytoplankton anomalies at 0-50 m (50-100 m) are driven by the westward propagating downwelling Rossby waves. During winter and spring, due to the local wind anomalies and shallower thermocline, the Seychelles-Chagos Thermocline Ridge (SCTR) is the only region where ENSO exhibits greater positive effects on phytoplankton at 50-100 m than IOD. Different from IOD, the ENSO-related wind reversal impedes subsurface upwelling in the STI and EEIO, thereby constraining vertical biological activity. These findings could shed light on how phytoplankton will respond to changing ocean dynamics under global warming.

The interannual-decadal variability in the upper-ocean salinity of the southeast Indian Ocean (SEIO) was found to be highly correlated with the El Niño-Southern Oscillation (ENSO). Based on multisource data, this study revealed that this ENSO-like salinity variability mainly resides in the domain between 13°S-30°S and 100°E-120°E, and at depths above 150 m. This variability is principally driven by meridional geostrophic velocity (MGV), which changes with the zonal pattern of the sea surface height (SSH). Previous studies have reported that the variability in the SSH in the south Indian Ocean is principally driven by local-wind forcing and eastern-boundary forcing. Here the eastern-boundary forcing denotes the influence of SSH anomaly radiated from the western coast of Australia. A recent study emphasized the contribution of local-wind forcing in salinity variability in the SEIO, for its significant role in generation of the zonal dipole pattern of SSH anomaly in the south Indian Ocean, which was considered to be responsible for the anomalous MGV in the SEIO. While our results revealed a latitudinal difference between the domain where the SSH dipole pattern exists (north of 20°S) and the region in which the ENSO-like salinity variability is strongest (20°S-30°S), suggesting that this salinity variability cannot be attributed entirely to the SSH dipole pattern. Our further investigation shows that, the MGV in the SEIO changes with local zonal SSH gradient that principally driven by eastern-boundary forcing. In combination with the strong meridional salinity gradient, the boundary-driven MGV anomalies cause significant meridional salinity advection and eventually give rise to the observed ENSO-like salinity variability. This study revealed the leading role of eastern-boundary forcing in interannual variability of the upper-ocean salinity in the SEIO.

Phytoplankton biomass, quantified as the concentration of chlorophyll-a (CHL), is the base of the marine food web that supports fisheries production in the Bay of Bengal (BoB). Nutrients from river discharge, the ocean subsurface layer, and the atmosphere have been reported to determine CHL in the BoB. Which source of nutrients mainly determines CHL in different parts of the bay has not been determined. Furthermore, how climate variations influence nutrient inputs from different sources and their impacts on CHL have not been detailed. To address these questions, we used relationships between satellite-derived CHL and in situ river discharge data (a proxy for river-borne nutrients) from 1997 to 2016, physical variables, and modeled dust deposition (DD), a proxy for atmosphere-borne nutrients. Nutrients supplied from the ocean subsurface layer were assessed based on variations in physical parameters (i.e., wind stress curl, sea surface height anomaly, and sea surface temperature). We found that nutrients from the Ganges and Brahmaputra Rivers were important for CHL along the northern coast of the bay. By increasing rainfall and river discharge, La Niña extended high-CHL waters further southward. Nutrients from the ocean subsurface layer determine CHL variations mainly in the southwestern bay. We suggest that the variations in the supply of nutrients from the subsurface layer are related to the generation of mesoscale cyclonic eddies during La Niña, a negative Indian Ocean Dipole, or both. Climate-driven cyclonic eddies together with cyclones can intensify Ekman divergence and synergistically lead to a pronounced increase in CHL in the southwestern bay. Nutrients from the atmosphere mainly determine CHL in the central/eastern BoB. We further suggest that DD in the central/eastern BoB is influenced by ENSO with a 6-7-month time lag. CHL in the central/eastern bay responds to the ENSO 6-7 months after the ENSO peak because of the 6-7-month lag between ENSO and DD

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

East Asian summer monsoon (EASM) is one of the most dominant climate systems in East Asia. The anomalous EASM can cause the extreme high temperature, flood or drought. And El Niño-Southern Oscillation (ENSO), the dominating mode in the tropical Pacific, is the most important factor affecting EASM. Understanding the processes for interannual to interdecadal variability of EASM-ENSO relationship is crucial.

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

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.

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.

Tropical Indo-Pacific climate shifts to a more El Niño-like state.

Unprecedented warm sea surface temperature (SST) anomalies were observed off the west coast of Australia in February-March 2011. Peak SST during a 2-week period were 5°C warmer than normal, causing widespread coral bleaching and fish kills. Understanding the climatic drivers of this extreme event, which we dub "Ningaloo Niño", is crucial for predicting similar events under the influence of global warming. Here we use observational data and numerical models to demonstrate that the extreme warming was mostly driven by an unseasonable surge of the poleward-flowing Leeuwin Current in austral summer, which transported anomalously warm water southward along the coast. The unusual intensification of the Leeuwin Current was forced remotely by oceanic and atmospheric teleconnections associated with the extraordinary 2010-2011 La Niña. The amplitude of the warming was boosted by both multi-decadal trends in the Pacific toward more La Niña-like conditions and intraseasonal variations in the Indian Ocean.

Climat : record en vue pour 2015.

Climat : record en vue pour 2015.

Preliminary findings of a comprehensive scientific survey examining the impact of the climate change-related 2016 mass bleaching in the Maldives indicate that all reefs surveyed were affected by the event. Approximately 60% of all coral colonies assessed - and up to 90% in some sites - were bleached.

Preliminary findings of a comprehensive scientific survey examining the impact of the climate change-related 2016 mass bleaching in the Maldives indicate that all reefs surveyed were affected by the event. Approximately 60% of all coral colonies assessed - and up to 90% in some sites - were bleached.

Here's a simple backyard science experiment for you to try, which has global implications.

Maldives: In a Troubled Paradise, Time Runs Out on Environmental Deadline.

Climate Change Impacts Countered By Stricter Fisheries Management.

Climate Change Impacts Countered By Stricter Fisheries Management.

El Niño threatens southern Africa with yet another drought.

El Niño threatens southern Africa with yet another drought.

El Niño, one of three strongest recorded, brings high drought risk for Australia.

El Niño, one of three strongest recorded, brings high drought risk for Australia.

This summer's sea temperatures were the hottest on record for Australia: here's why.

This summer's sea temperatures were the hottest on record for Australia: here's why.

El Niño in the Pacific has an impact on dolphins over in Western Australia.

Massive mangrove die-off on Gulf of Carpentaria worst in the world, says expert.