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Flinders University oceanography experts have described a new kind of cyclone in the Indian Ocean near Sumatra after observing satellite surface winds in the region.

◆ 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.

Whale sharks off the western coast of India have suffered high levels of fishing pressure in the past, and today continue to be caught in small-scale fisheries as by-catch. Additionally, coastlines in this region host very large and growing human populations that are undergoing rapid development. This exacerbates ongoing anthropogenic threats to this species such as pollution, habitat loss, and ship traffic. For these reasons, there is an urgent need for data on movement patterns of whale sharks in this region of the Indian Ocean. Here, we address this issue by providing the first data on the horizontal movements of whale sharks tagged in the northern Arabian Sea off the western coast of the Indian state of Gujarat. From 2011 to 2017, eight individuals, ranging from 5.4 to 8 m were tagged and monitored using satellite telemetry. Tag retention varied from 1 to 137 days, with the sharks traveling distances of 34 - ∼2,230 km. Six of the eight individuals remained close to their tagging locations, although two sharks displayed wide ranging movements into the Arabian Sea, following frontal zones between water masses of different sea surface temperatures. We explore the relationship between the movement patterns of these whale sharks and the physical and biological processes of the region.

It's visible in satellite images from just off Sri Lanka's coast: a thin grey film that snakes three kilometres out to sea before disappearing into the waves.

A few weeks after IDAI which wreaked havoc on central Mozambique (and eastern Zimbabwe), the country is dealing with another unprecedented event. Tropical Cyclone Kenneth made landfall in northern Mozambique on 25 April, near the border with Tanzania, in an area where no tropical cyclone has been observed since the satellite era. There is no record of two storms of such intensity striking Mozambique in the same season. It has now weakened into a depression.

Recent literature on the impact of cyclones on mangrove forest productivity indicates that nutrient fertilizations aided by tropical cyclones enhance the productivity of mangrove forests. We probe the implications of these predictions in the context of Indian mangroves to propose potential future directions for mangrove research in the subcontinent. First, we look at the time series trend (2000-2020) in satellite-derived gross primary productivity (GPP) datasets for seven mangrove forests across the country's coastline. Second, we compare seasonal changes in soil nutrient levels for a specific site to further the arguments proposed in the literature and investigate the role of potential drivers of mangrove productivity. We find overall increasing trends for GPP over the past two decades for all seven mangrove sites with seasonal fluctuations closely connected to the tropical storm activities for three sites (Bhitarkanika, Pichavaram, and Charao). Additionally, organic carbon and nitrogen levels showed no significant trend, but phosphorus levels were higher during the post-monsoon-winter period for Bhitarkanika. Our findings expand the predictions of previous studies that emphasized the role of storm-induced nutrient fluxes and freshwater supply as primary drivers of productivity gradients in mangroves. Our study provides insights on how mangrove productivity may change with fluctuating frequency and magnitude of cyclones under a changing climate, implying the need for more mechanistic studies in understanding the long-term impact on mangrove productivity in the region.

Human activities in the oceans increase the extinction risk of marine megafauna. Interventions require an understanding of movement patterns and the spatiotemporal overlap with threats. We analysed the movement patterns of 33 white sharks (Carcharodon carcharias) satellite-tagged in South Africa between 2012 and 2014 to investigate the influence of size, sex and season on movement patterns and the spatial and temporal overlap with longline and gillnet fisheries and marine protected areas (MPAs). We used a hidden Markov model to identify 'resident' and 'transient' movement states and investigate the effect of covariates on the transition probabilities between states. A model with sex, total length and season had the most support. Tagged sharks were more likely to be in a resident state near the coast and a transient state away from the coast, while the probability of finding a shark in the transient state increased with size. White sharks moved across vast areas of the southwest Indian Ocean, emphasising the need for a regional management plan. White sharks overlapped with longline and gillnet fisheries within 25% of South Africa's Exclusive Economic Zone and spent 15% of their time exposed to these fisheries during the study period. The demersal shark longline fishery had the highest relative spatial and temporal overlap, followed by the pelagic longline fishery and the KwaZulu-Natal (KZN) shark nets and drumlines. However, the KZN shark nets and drumlines reported the highest white shark catches, emphasising the need to combine shark movement and fishing effort with reliable catch records to assess risks to shark populations accurately. White shark exposure to shark nets and drumlines, by movement state, sex and maturity status, corresponded with the catch composition of the fishery, providing support for a meaningful exposure risk estimate. White sharks spent significantly more time in MPAs than expected by chance, likely due to increased prey abundance

Human activities in the oceans increase the extinction risk of marine megafauna. Interventions require an understanding of movement patterns and the spatiotemporal overlap with threats. We analysed the movement patterns of 33 white sharks (Carcharodon carcharias) satellite-tagged in South Africa between 2012 and 2014 to investigate the influence of size, sex and season on movement patterns and the spatial and temporal overlap with longline and gillnet fisheries and marine protected areas (MPAs). We used a hidden Markov model to identify 'resident' and 'transient' movement states and investigate the effect of covariates on the transition probabilities between states. A model with sex, total length and season had the most support. Tagged sharks were more likely to be in a resident state near the coast and a transient state away from the coast, while the probability of finding a shark in the transient state increased with size. White sharks moved across vast areas of the southwest Indian Ocean, emphasising the need for a regional management plan. White sharks overlapped with longline and gillnet fisheries within 25% of South Africa's Exclusive Economic Zone and spent 15% of their time exposed to these fisheries during the study period. The demersal shark longline fishery had the highest relative spatial and temporal overlap, followed by the pelagic longline fishery and the KwaZulu-Natal (KZN) shark nets and drumlines. However, the KZN shark nets and drumlines reported the highest white shark catches, emphasising the need to combine shark movement and fishing effort with reliable catch records to assess risks to shark populations accurately. White shark exposure to shark nets and drumlines, by movement state, sex and maturity status, corresponded with the catch composition of the fishery, providing support for a meaningful exposure risk estimate. White sharks spent significantly more time in MPAs than expected by chance, likely due to increased prey abundance

Accurately estimating the ocean's subsurface thermohaline structure is essential for advancing our understanding of regional and global ocean dynamics. In this study, we propose a novel neural network model based on Convolutional Block Attention Module-Convolutional Neural Network (CBAM-CNN) to simultaneously estimate the ocean subsurface thermal structure (OSTS) and ocean subsurface salinity structure (OSSS) in the tropical Indian Ocean using satellite observations. The input variables include sea surface temperature (SST), sea surface salinity (SSS), sea surface height anomaly (SSHA), eastward component of sea surface wind (ESSW), northward component of sea surface wind (NSSW), longitude (LON), and latitude (LAT). We train and validate the model using Argo data, and compare its accuracy with that of the original Convolutional Neural Network (CNN) model using root mean square error (RMSE), normalized root mean square error (NRMSE), and determination coefficient (R²). Our results show that the CBAM-CNN model outperforms the CNN model, exhibiting superior performance in estimating thermohaline structures in the tropical Indian Ocean. Furthermore, we evaluate the model's accuracy by comparing its estimated OSTS and OSSS at different depths with Argo-derived data, demonstrating that the model effectively captures most observed features using sea surface data. Additionally, the CBAM-CNN model demonstrates good seasonal applicability for OSTS and OSSS estimation. Our study highlights the benefits of using CBAM-CNN for estimating thermohaline structure and offers an efficient and effective method for estimating thermohaline structure in the tropical Indian Ocean.

The seasonality of eddy kinetic energy (EKE) is analyzed in the north Indian Ocean by adopting high-resolution ocean reanalysis data. Significant eddy energy can be mainly spotted in six regions, including the Somali Current (SC) region, the Gulf of Aden, the Laccadive Sea, the east of Sri Lanka, the East Indian Coastal Current (EICC) region, and the northwest of Sumatra. As the most energetic region, the EKE averaged above 200 m could exceed 0.15 m2·s-2 in the SC region, whereas the mean EKE above 200 m is less than 0.04 m2·s-2 in the other regions. The barotropic and baroclinic instabilities are vital to eddy energy, and the contribution of each term in the barotropic/baroclinic equations varies with season and region. In the SC region and EICC region, EKE is primarily generated by barotropic conversion due to the sharp velocity shear caused by the strong SC during the summer monsoon and the EICC from March to June. For the other regions, the leading source of EKE is the eddy potential energy (EPE), which is extracted from available potential energy of mean flow via baroclinic conversion, and then the EPE is converted into EKE through vertical density flux. Once generated, EKE will be redistributed by pressure work and advection via eddy energy flux, which varies in sync with the monthly variation of total EKE, transporting EKE to the adjacent region or deeper layer. From the vertical aspect, eddy energy conversions are more prominent above 200 m. The maximal EKE and barotropic conversion mostly occur at the surface, whereas the EPE and baroclinic conversion may have two peaks, which lie at the surface and in the thermocline. Using the satellite altimeter data and wind data, we further investigate the impact of geostrophic eddy wind work, which reveals a slightly dampening effect to EKE in the north Indian Ocean.

Monthly composites of remote sensing reflectance at 555 nm wavelength (Rrs555) from ocean color imagery of the MODIS sensor onboard the Aqua platform were used to characterize the spatial and temporal variability of coastal plume in the Sofala Bank and its relation to river discharge, local rainfall, and wind speed. To achieve the objective, maps of monthly composites of Rrs555 over the Sofala Bank were inspected and statistical analysis was performed, including correlation, analysis of variance, and wavelet coherence between environmental variables and both plume area and Rrs555. Climatology of Rrs555 revealed that both plume dispersion and Rrs555 values are higher during June to December and lower during January to May. A positive correlation (r = 0.77) between wind speed and monthly time series of Rrs555, and a negative correlation between the Zambezi river discharge (r = −0.21) and rainfall (r = −0.67) with Rrs555 were found. These results suggest that variation of suspended matter in the Sofala Bank is mainly controlled by erosion and re-suspension by winds rather than the input of terrigenous matter by the Zambezi River discharge and rainfall, assuming that Rrs555 can be a valid proxy for the inorganic suspended matter. The southern portion of the Sofala Bank (i.e., near the mouths of the Pungue and Buzi Rivers) presented higher values of Rrs555 if compared to the center region near Zambezi river mouth and the northern region near Licungo river mouth. The higher Rrs555 values in the southern region might be associated with higher re-suspension rates due to increased tide mixing, dredging activities, and the shallower nature of bathymetry in the southern region. The dominance of wind in controlling the variability of suspended sediments and the eventual relatively greater contribution of Pungue and Buzi River than the Zambezi in supplying sediments could represent an evidence of weakening of Zambezi River supply of sediments, a process that might have start

Coastal waters are inherently dynamic due to river discharge, industrial effluents, shipping, dredging, waste dumping, and sewage disposal. Population growth in urban cities, climate change and variability, and changes in land-use practices all contribute to pressure on coastal water quality (SKOVSKI et al., 2012; MILLER and HUTCHINS, 2017; KUMAR et al., 2020; Vijay PRAKASH et al., 2021). Anthropogenic activity is evident around these estuaries and coastal and open ocean environments. Hence, it is important to assess the water quality on a regular basis and provide mitigation measures for coastal pollution (YUVARAJ et al., 2018). Improving water quality and variability in coastal waters is necessary and should be prioritized. Observational programs, which are more expensive and time-consuming, aid in understanding the status of water quality and its trends. Many countries have coastal programs that use predictive systems to inform the public and stakeholders about coastal health. Hydrodynamic processes are an integral part of complex surface water systems. The main factor that determines the concentration of pollutants is hydrodynamic transport, which includes advection, dispersion, vertical mixing, and convection (James, 2002). The flow and circulation patterns have a great influence not only on the distribution of temperature, nutrients, and dissolved oxygen (DO) but also on the aggregation and distribution of sediments and pollutants. When a load of pollutants is discharged into coastal waters, it is affected by the fate and transportation processes that change its concentration. Several studies have been conducted to evaluate the coastal water quality spatiotemporally along the east coast of Indian coastal waters using site-specific data and model configuration (PANDA et al., 2006; BHARAHTI et al., 2017; NAIK et al., 2020; MOHANTY et al., 2021). Through numerical modeling and remote sensing, estimation is user-friendly and low-cost in evaluating any water quali

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.

The Irrawaddy (IR) is the largest river discharging into the Andaman Sea and plays an important role in the salinity distribution and the mixed layer physics of the Andaman Sea. This study presents the first report of the IR plume pathways in the Andaman Sea during the summer monsoon and the mechanisms behind them. An ocean circulation model is employed to conduct idealized experiments in which the freshwater forcing, due to rivers other than IR as well as precipitation, are ignored. Our simulations reveal that, during the summer monsoon, the discharge from Irrawaddy spreads as a freshwater jet oriented towards southeast and accumulates over the shelf at the eastern coast of the Andaman Sea. Climatology of Chlorophyll-a concentration measured by satellite and surface currents from global ocean model reanalysis indicates the presence of the Irrawaddy freshwater jet during the summer monsoon. The evolution of surface salinity and currents along the jet suggests that the IR freshwater traps momentum imparted by winds. The momentum balance in the Irrawaddy jet is between Coriolis and wind friction term, indicating that the freshwater jet is completely driven by winds during the summer monsoon. Surface distribution of wind friction term also shows that the northwest-southeast orientation of the Irrawaddy jet is due to the southwesterly orientation of the summer monsoon winds. Further experiments with three different wind forcing scenarios (no winds, winds over the equator only, and winds over the Bay of Bengal only) reveal that the flow of Irrawaddy jet during the summer monsoon is completely controlled by the local winds.

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

Building better ocean and climate models with salinity data.

Cyclone's 'Overshooting Cloud Tops' Seen from Above.

Sentinel-2A is demonstrating how it can be used to help forecast ocean waves around our coasts: sunlight reflected from the water surface reveals complex waves as they encounter the coastline and seafloor off the tip of Dorre Island, Western Australia.

Sentinel-2A is demonstrating how it can be used to help forecast ocean waves around our coasts: sunlight reflected from the water surface reveals complex waves as they encounter the coastline and seafloor off the tip of Dorre Island, Western Australia.

University of Hawaii at Manoa's Philip THOMPSON of the Sea Level Center examined 25 years of interactions between the atmosphere and the ocean surface.

University of Hawaii at Manoa's Philip THOMPSON of the Sea Level Center examined 25 years of interactions between the atmosphere and the ocean surface.