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Chlorophyll-a can be used as a proxy for phytoplankton and thus is an essential water quality parameter. The presence of phytoplankton in the ocean causes selective absorption of light by chlorophyll-a pigment resulting in change of the ocean color that can be identified by ocean color remote sensing. The accuracy of chlorophyll-a concentration (Chl-a) estimated from remote sensing sensors depends on the bio-optical algorithm used for the retrieval in specific regional waters. In this work, it is attempted to estimate Chl-a from two currently active satellite sensors with relatively good spatial resolutions considering ocean applications. Suitability of two standard bio-optical Ocean Color (OC) Chlorophyll algorithms, OC-2 (2-band) and OC-3 (3-band) in estimating Chl-a for turbid waters of the northern coastal Bay of Bengal is assessed. Validation with in-situ data showed that OC-2 algorithm gives an estimate of Chl-a with a better correlation of 0.795 and least bias of 0.35 mg/m3. Further, inter-comparison of Chl-a retrieved from the two sensors, Landsat-8 OLI and Sentinel-2 MSI was also carried out. The variability of Chl-a during winter, pre-monsoon, and post-monsoon seasons over the study region were inter-compared. It is observed that during pre-monsoon and post-monsoon seasons, Chl-a from MSI is over estimated compared to OLI. This work is a preliminary step toward estimation of Chl-a in the coastal oceans utilizing available better spatially resolved sensors.

Tropical regions experience a diverse range of dense clouds, posing challenges for the daily reconstruction of chlorophyll-a concentration data. This underscores the pressing need for a practical method to reconstruct daily-scale chlorophyll-a concentrations in such regions. While traditional data reconstruction methods focus on single variables and rely on specific factors to infer missing data at specific locations, these single-variable methods may falter when applied to tropical oceans due to the scarcity of available data. Fortunately, all oceanographic variables undergo similar atmospheric and marine dynamic processes, creating internal relationships between them. This allows for the reconstruction of missing data through correlations between variables. Thus, this study introduces a multivariate reconstruction approach using the extended data interpolating empirical orthogonal function (ExDINEOF) method to reconstruct missing daily-scale chlorophyll-a concentration data. The ExDINEOF method considers the simultaneous relationships among multiple variables for data reconstruction in tropical oceans. To verify the method's robustness, missing data were reconstructed during the formation and passage of severe tropical cyclone Hudhud through the Bay of Bengal. The results demonstrate that ExDINEOF outperforms traditional data reconstruction methods, exhibiting favorable spatial distribution and enhanced accuracy within the dynamic tropical marine environment. Furthermore, an assessment of marine physical environmental factors associated with chlorophyll-a concentration data provides additional evidence for the ExDINEOF method's accuracy. Notably, the ExDINEOF method offers comprehensive spatial distribution aligned with underlying physical mechanisms governing phytoplankton distribution patterns, detailed phytoplankton growth, bloom, extinction variations in time series, satisfactory accuracy, and comprehensive local-level details.

Tropical shallow-water habitats represent the marine environments with the greatest biodiversity; however, these habitats are the most vulnerable to climate warming. Corals, seagrasses, and macroalgae play a crucial role in the structure, functions, and processes of the coastal ecosystems. Understanding their growth and physiological responses to elevated temperature and interspecific sensitivity is a necessary step to predict the fate of future coastal community. Six species representatives, including Pocillopora acuta, Porites lutea, Halophila ovalis, Thalassia hemprichii, Padina boryana, and Ulva intestinalis, collected from Phuket, Thailand, were subjected to stress manipulation for 5 days. Corals were tested at 27, 29.5, 32, and 34.5°C, while seagrasses and macroalgae were tested at 27, 32, 37, and 42°C. After the stress period, the species were allowed to recover for 5 days at 27°C for corals and 32°C for seagrasses and macroalgae. Non-destructive evaluation of photosynthetic parameters (Fv/Fm, Fv/F0, ϕPSII and rapid light curves) was carried out on days 0, 3, 5, 6, 8, and 10. Chlorophyll contents and growth rates were quantified at the end of stress, and recovery periods. An integrated biomarker response (IBR) approach was adopted to integrate the candidate responses (Fv/Fm, chlorophyll content, and growth rate) and quantify the overall temperature effects. Elevated temperatures were found to affect photosynthesis, chlorophyll content, and growth rates of all species. Lethal effects were detected at 34.5°C in corals, whereas adverse but recoverable effects were detected at 32°C. Seagrasses and macroalgae displayed a rapid decline in photosynthesis and lethal effects at 42°C. In some species, sublethal stress manifested as slower growth and lower chlorophyll content at 37°C, while photosynthesis remained unaffected. Among all, T. hemprichii displayed the highest thermotolerance. IBR provided evidence that elevated temperature affected the overall perf

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.

◆ 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.

COrona VIrus Disease (COVID) 2019 pandemic forced most countries to go into complete lockdown and India went on complete lockdown from 24th March 2020 to 8th June 2020. To understand the possible implications of lockdown, we analyze the long-term distribution of Net Primary Productivity (NPP) in the North Indian Ocean (NIO) and the factors that influence NPP directly and indirectly, for the period 2003-2019 and 2020 separately. There exists a seasonal cycle in the relationship between Aerosol Optical Depth (AOD), Chlorophyll-a (Chl-a) and NPP in agreement with the seasonal transport of aerosols and dust into these oceanic regions. In Arabian Sea (AS), the highest Chl-a (0.58 mg/m3), NPP (696.57 mg/C/m2/day) and AOD (0.39) are observed in June, July, August, and September (JJAS). Similarly, maximum Chl-a (0.48 mg/m3) and NPP (486.39 mg/C/m2/day) are found in JJAS and AOD (0.27) in March, April, and May (MAM) in Bay of Bengal. The interannual variability of Chl-a and NPP with wind speed and Sea Surface Temperature (SST) is also examined, where the former has a positive and the latter has a negative feedback to NPP. The interannual variability of NPP reveals a decreasing trend in NPP, which is interlinked with the increasing trend in SST and AOD. The analysis of wind, SST, Chl-a, and AOD for the pre-lockdown, lockdown, and post lockdown periods of 2020 is employed to understand the impact of COVID-19 lockdown on NPP. The assessment shows the reduction in AOD, decreased wind speeds, increased SST and reduced NPP during the lockdown period as compared to the pre-lockdown, post-lockdown and climatology. This analysis is expected to help to understand the impact of aerosols on the ocean biogeochemistry, nutrient cycles in the ocean biogeochemical models, and to study the effects of climate change on ocean ecosystems.

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

To clarify the changes in phytoplankton community and influencing factors in short-term nutrient-addition experiments in the Equatorial Eastern Indian Ocean, we conducted three experiments (one in situ-like experiment, one on-deck experiment with deep seawater, and one on-deck experiment with surface seawater). Our findings indicate that when nutrients were added, there was a more significant increase in the chlorophyll a (chl a) concentrations of microphytoplankton (>20 μm) compared to those of nanophytoplankton (2-20 μm) and picophytoplankton (<20 μm phytoplankton. Furthermore, bottle effects should be considered when conducting incubation experiments.

Ocean primary production is the basis of the marine food web, sustaining life in the ocean via photosynthesis, and removing carbon dioxide from the atmosphere. Recently, a small but significant decrease in global marine primary production has been reported based on ocean color data, which was mostly ascribed to decreases in primary production in the northern Indian Ocean, particularly in the Bay of Bengal. Available reports on primary production from the Bay of Bengal (BoB) are limited, and due to their spatial and temporal variability difficult to interpret. Primary production in the BoB has historically been described to be driven by diatom and chlorophyte clades, while only more recent datasets also show an abundance of smaller cyanobacterial primary producers visually difficult to detect. The different character of the available datasets, i.e., direct counts, metagenomic and biogeochemical data, and satellite-based ocean color observations, make it difficult to derive a consistent pattern. However, making use of the most highly resolved dataset based on satellite imaging, a shift in community composition of primary producers is visible in the BoB over the last 2 decades. This shift is driven by a decrease in chlorophyte abundance and a coinciding increase in cyanobacterial abundance, despite stable concentrations of total chlorophyll. A similar but somewhat weaker trend is visible in the Arabian Sea, where satellite imaging points towards decreasing abundances of chlorophytes in the north and increasing abundances of cyanobacteria in the eastern parts. Statistical analysis indicated a correlation of this community change in the BoB to decreasing nitrate concentrations, which may provide an explanation for both the decrease in eukaryotic nitrate-dependent primary producers and the increase in small unicellular cyanobacteria related to Prochlorococcus, which have a comparably higher affinity to nitrate. Changes in community composition of primary producers and an

A planned artificial reef (AR) deployment program as part of a fisheries enhancement might be a useful tool for managers to supplement traditional ways to utilize available space and augment local productivity. Several AR deployment initiatives have been carried out globally, but they are rarely subjected to a rigorous site selection process. We created a site selection procedure in this study that includes systematic stages including exclusion mapping, underwater visual transect, benthic composition, seawater quality, and comparative visual mapping. This research focused on restoring the fishing grounds for artisanal fishermen by deploying AR along the southeast coast of India. The results of each stage in the procedure enabled us to choose suitable locations at a target depth with low wave action, no slope, and a good substrate capable of supporting an AR. Analysis of variance (ANOVA-one way) showed significant (p < 0.05) spatial variation for depth, slope, seawater current, salinity, chlorophyll-a, benthic density, and diversity. The geographical information system (GIS) based model output showed space allocation for AR deployment. The GIS methodology for site selection was developed to be easily adaptable to the demands of diverse artificial reef programs. The integrated strategy has proven to be a successful regulatory intervention for AR deployment practices in order to facilitate coastal restoration and management.

Microzooplankton (MZP) are an important part of the microbial food web and play a pivotal role in connecting the classic food chain with the microbial loop in the marine ecosystem. They may play a more important role than mesozooplankton in the lower latitudes and oligotrophic oceans. In this article, we studied the species composition, dominant species, abundance, and carbon biomass of MZP, including the relationship between biological variables and environmental factors in the eastern equatorial Indian Ocean during the spring intermonsoon. We found that the MZP community in this ocean showed a high species diversity, with a total of 340 species. Among these, the heterotrophic dinoflagellates (HDS) (205 species) and ciliates (CTS) (126 species) were found to occupy the most significant advantageous position. In addition, CTS (45.3%) and HDS (39.7%) accounted for a larger proportion of the population abundance, while HDS (47.1%) and copepod nauplii (CNP) (46.4%) made a larger contribution to the carbon biomass. There are significant differences in the ability of different groups of MZP to assimilate organic carbon. In this sea area, MZP are affected by periodic currents, and temperature is the main factor affecting the distribution of the community. The MZP community is dominated by eurytopic species and CNP. CTS are more sensitive to environmental changes than HDS, among which Ascampbelliella armilla may be a better habitat indicator species. In low-latitude and oligotrophic ocean areas, phytoplankton with smaller cell diameters were found to occupy a higher proportion, while there was no significant correlation between the total concentration of integrated chlorophyll a and the biological variables of MZP. Therefore, we propose that the relationship between size-fractionated phytoplankton and MZP deserves further study. In addition, the estimation of the carbon biomass of MZP requires the establishment of more detailed experimental methods to reflect the real situ

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

The unprecedented nationwide lockdown due to the 'coronavirus disease 2019' (COVID-19) affected humans and the environment in different ways. It provided an opportunity to examine the effect of reduced transportation and other anthropogenic activities on the environment. In the current study, the impact of lockdown on chlorophyll-a (Chl-a) concentration, an index of primary productivity, over the northern Indian Ocean (IO), is investigated using the observations and a physical-biogeochemical model. The statistics of model validation against observations shows a correlation coefficient of 0.85 (0.89), index of agreement as 0.90 (0.91). Root mean square error of 0.45°C (0.50°C) for sea surface temperature over the Bay of Bengal (BoB) (Arabian Sea, AS) is observed. The model results are analyzed to understand the upper-oceanic physical and biological processes during the lockdown. A comparison of the observed and model-simulated data during the lockdown period (March-June, 2020) and pre-pandemic period (March-June, 2019) shows significant differences in the physical (temperature and salinity) and biogeochemical (Chl-a concentration, nutrient concentration, and dissolved oxygen) parameters over the western AS, western BoB, and regions of Sri Lanka. During the pandemic, the reduced anthropogenic activities lead to a decrease in Chl-a concentration in the coastal regions of western AS and BoB. The enhanced aerosol/dust transport due to stronger westerly winds enhanced phytoplankton biomass in the western Arabian Sea (WAS) in May-June of the pandemic period.

The existing oligotrophic conditions in the southwest tropical Indian Ocean (SWTIO) is believed to be one of the causes for low phytoplankton productivity (PP) observed in this area. Though many remote sensing based studies on PP have been carried out in SWTIO, studies on in situ estimation of PP and its cause(s) of variability are scarce. Thus, to understand the controlling environmental forcings on the variability in phytoplankton biomass (chlorophyll-a; Chl-a), community structure and productivity, time series (TS; @6 h intervals for 10 days; 1 station), plus point measurements (RT; 3 stations) were carried out in the SWTIO during the southwest monsoon (June) of 2014. Strong thermohaline stratification resulted in shallow (35-40 m) mixed layer (ML). Subsurface Chl-a maximum (SCM) was observed to oscillate within 40-60 m with majority of peaks at ∼50 m, and existed just beneath the ML depth. Light availability during sampling period was highly conducive for algal growth; nutrient ratios indicated N- and Si-limitation (N:P < 10; N:Si < 1 and SiO4 < 5 μM) suggesting unfavorable conditions for diatoms and/or silicoflagellates growth within the ML. Furthermore, HPLC-based pigments analysis confirmed dominance of nano-sized plankton (53%) followed by pico-plankton (25%) and micro-plankton (22%). Column integrated production (IPP) varied from 176 to 268 (241 ± 43 mgC m-2 d-1) and was relatively stable during the observation period, except a low value (19.4 E m-2 d-1) on 11 June, which was ascribed to the drastic dropdown in the daily incident PAR due to overcast sky. Vertical profiles of PP and Chl-a resembled each other and maximum PP usually corresponded with SCM depths. The Chl-a-specific PP (PB) was mostly higher within the ML and showed no surface photoinhibition, due to the dominance of smaller phytoplankton (less prone to pigment packaging effect) in the surface layer. Comparatively, higher PB within the ML is indicative of phytoplankton healthine

The Ninety East Ridge is a submarine north-south oriented volcanic ridge in the eastern Indian Ocean. Surface-layer ichthyoplankton collected in this area from September to October were identified by combined morphological and molecular (DNA barcoding) techniques, and their species composition, diversity, and abundance, and correlations with environmental variables were described. Collections comprised 109 larvae and 507 eggs, which were identified to 37 taxa in 7 orders, 20 families, and 27 genera, and were dominated by the order Perciformes and species Vinciguerria sp., Oxyporhamphus micropterus, and Decapterus macarellus. Species abundances at each station and of each species were relatively low, suggesting that this area or the time of sampling were not of major importance for fish spawning. Waters above Ninety East Ridge had lower species diversity but higher species richness than waters further offshore. A generalized additive model revealed that high abundance of ichthyoplanktonic taxa occurred in areas with low sea surface height and high sea surface salinity, temperature, and chlorophyll a concentration. Of these, sea surface height was most correlated with ichthyoplankton abundance. We provided baseline data on surface-dwelling ichthyoplankton communities in this area to aid in development of pelagic fishery resources in waters around the Ninety East Ridge.

The monsoon circulation in the Northern Indian Ocean (NIO) is unique since it develops in response to the bi-annual reversing monsoonal winds, with the ocean currents mirroring this change through directionality and intensity. The interaction between the reversing currents and topographic features have implications for the development of the Island Mass Effect (IME) in the NIO. The IME in the NIO is characterized by areas of high chlorophyll concentrations identified through remote sensing to be located around the Maldives and Sri Lanka in the NIO. The IME around the Maldives was observed to reverse between the monsoons to downstream of the incoming monsoonal current whilst a recirculation feature known as the Sri Lanka Dome (SLD) developed off the east coast of Sri Lanka during the Southwest Monsoon (SWM). To understand the physical mechanisms underlying this monsoonal variability of the IME, a numerical model based on the Regional Ocean Modeling System (ROMS) was implemented and validated. The model was able to simulate the regional circulation and was used to investigate the three-dimensional structure of the IME around the Maldives and Sri Lanka in terms of its temperature and velocity. Results revealed that downwelling processes were prevalent along the Maldives for both monsoon periods but was applicable only to latitudes above 4°N since that was the extent of the monsoon current influence. For the Maldives, atolls located south of 4°N, were influenced by the equatorial currents. Around Sri Lanka, upwelling processes were responsible for the IME during the SWM but with strong downwelling during the NEM. In addition, there were also regional differences in intra-seasonal variability for these processes. Overall, the strength of the IME processes was closely tied to the monsoon current intensity and was found to reach its peak when the monsoon currents were at the maximum.

Coastal upwelling is an oceanographic process that brings cold, nutrient-rich waters to the ocean surface from depth. These nutrient-rich waters help drive primary productivity which forms the foundation of ecological systems and the fisheries dependent on them. Although coastal upwelling systems of the Western Indian Ocean (WIO) are seasonal (i.e., only present for part of the year) with large variability driving strong fluctuations in fish catch, they sustain food security and livelihoods for millions of people via small-scale (subsistence and artisanal) fisheries. Due to the socio-economic importance of these systems, an "Upwelling Watch" analysis is proposed, for producing updates/alerts on upwelling presence and extremes. We propose a methodology for the detection of coastal upwelling using remotely-sensed daily chlorophyll-a and Sea Surface Temperature (SST) data. An unsupervised machine learning approach, K-means clustering, is used to detect upwelling areas off the Somali coast (WIO), where the Somali upwelling - regarded as the largest in the WIO and the fifth most important upwelling system globally - takes place. This automatic detection approach successfully delineates the upwelling core and surrounds, as well as non-upwelling ocean regions. The technique is shown to be robust with accurate classification of out-of-sample data (i.e., data not used for training the detection model). Once upwelling regions have been identified, the classification of extreme upwelling events was performed using confidence intervals derived from the full remote sensing record. This work has shown promise within the Somali upwelling system with aims to expand it to the rest of the WIO upwellings. This upwelling detection and classification method can aid fisheries management and also provide broader scientific insights into the functioning of these important oceanographic features.

The Arabian Sea is a significant hypoxic region in world's oceans, characterized by the most extensive oxygen minimum zones (OMZs). Both physical and biological processes can alter the vertical and horizontal distribution of dissolved oxygen within the upper ocean and affect the spatial and temporal distribution of hypoxia within the OMZ. To identify the key physical and biological factors influencing the boundaries of oxycline, we analyzed an extensive dataset collected from the biogeochemical-Argo (BGC-Argo) floats during the period of 2010-2022. In particular, we investigated the impact of physical subduction events on the oxycline. Our results shows that the upper boundary of the oxycline deepened in summer and winter, and seemed to be controlled by the mixed layer depth. In contrast, it was shallower during spring and autumn, mainly regulated by the deep chlorophyll maximum. The lower boundary of the oxycline in the western Arabian Sea was predominantly controlled by regional upwelling and downwelling, as well as Rossby waves in the eastern Arabian Sea. Subduction patches originated from the Arabian Sea High Salinity Water (ASHSW) were observed from the BGC-Argo data, which were found to deepen the lower boundary of the oxycline, and increase the oxygen inventory within the oxycline by 8.3%, leading to a partial decrease in hypoxia levels.

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.

The Eastern Indian Ocean (EIO) is an ideal region to explore the variability and controlling mechanisms of the seawater carbonate system and their potential influence on global climate change due to the distinctive environmental features, while studies in the EIO is far from sufficient. The spatiotemporal distributions of pH, dissolved inorganic carbon (DIC), alkalinity (Alk), and partial pressure of carbon dioxide (pCO2) were investigated in the EIO during autumn 2020 and spring 2021. The respective quantitative contributions of different controlling processes to DIC were further delineated. Significant seasonal variations were observed in the study area. Overall, the surface pH was lower and DIC, Alk, and pCO2 were higher during spring 2021 than during autumn 2020. The pH generally decreased from east to west during autumn 2020, whereas it decreased from north to south during spring 2021. The low values of DIC and Alk that were detected in the Bay of Bengal in these two seasons were mainly attributed to the influence of river inputs. Coastal upwelling during monsoon periods led to higher pCO2 and DIC values near Sumatra and Sri Lanka during spring 2021. The relationships of carbonate system parameters with different types of nutrients and different sized chlorophyll-a in the two seasons indicated the shifts of nutrients utilized by the phytoplankton, and phytoplankton species dominated the carbonate system variabilities. In vertical profiles, carbonate system parameters showed strong correlations with other physical and biogeochemical parameters, and these correlations were more robust during spring 2021 than during autumn 2020. The average sea-air flux of CO2 was 10.00 mmol m−2 d−1 during autumn 2020 and was 16.00 mmol m−2 d−1 during spring 2021, which revealed that the EIO served as a CO2 source during the study period. In addition, the separation of different controlling processes of DIC indicated stronger mixing processes, less CaCO3 precipitation, m