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ABSTRACT Marine Heat Extremes (MHEs) are events of anomalously high Sea Surface Temperature (SST) during which SST values exceed a certain pre‐defined threshold. These MHEs have profound influence over weather patterns, air‐sea interaction and the health of marine ecosystems. This study investigates the long‐term evolution of MHEs in the Northern Indian Ocean (NIO) from 1900 to 2020. We utilised two normalised indices, the Normalised Extreme Frequency Index (NEFI) for frequency and the Normalised Extreme Heat Index (NEHI) for the intensity of MHEs, to objectively compare the MHE attributes across different periods and regions of the NIO. The analysis reveals non‐linearly increasing NEFI, with the Western Equatorial Indian Ocean (WEIO) experiencing the fastest rise, followed by the Eastern Equatorial Indian Ocean (EEIO), Arabian Sea (AS) and Bay of Bengal (BoB). MHE intensity shows exponential growth, with its mean‐based regimes becoming shorter and shifting more frequently. A new regime has been emerging since the last decade. Analysis of the spatial extent of the MHEs indicates that the WEIO is the fastest‐growing region of the NIO. Similar observations were found upon removing sub‐decadal variabilities, which include the potential effects of El Niño‐Southern Oscillation and Indian Ocean Dipole, highlighting the long‐term warming associated with global warming. The study also links the increasing mean SST to the rising frequency and intensity of MHEs, which is predominantly driven by the net surface heat‐flux, which is a combined effect of local and pantropical air‐sea interaction. The surface warming is outpacing subsurface warming, thereby strengthening thermal stratification over time, potentially impacting vertical mixing and upwelling, which can, in turn, lead to further surface warming. [ABSTRACT FROM AUTHOR]

The Bay of Bengal (BoB) tropical cyclones (TCs) and the Tibetan Plateau vortices (TPVs) are two crucial weather systems influencing the Tibetan Plateau (TP). Their synergistic effects can lead to widespread heavy precipitation events on the TP. In this study, we employ the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model to track the trajectory of water vapor transport during three large-scale precipitation events on the TP under the combined influence of BoB TCs and TPVs. The results indicate that low-level water vapor from the BoB under the influence of BoB TCs was cyclonically entangled into the cyclonic circulation, lifted and transported northward by southwesterly flow to the southeastern part of the TP, which contributes to the moistening of the entire troposphere there. Additionally, convergence of the cyclonic circulation of the TPVs on the northern TP further transports water vapor collected in the southeastern TP northward, conducive to the maintenance and development of precipitation systems, thus inducing widespread heavy precipitation events over the TP. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: Studying the monthly variations in the surface features of the Bay of Bengal is a complex task that involves numerous large-scale ocean-atmosphere dynamics. This study identified the bay’s changing circulation patterns over recent decades as a crucial study area requiring in-depth research. Understanding the changes in circulation patterns provides valuable insights into the Bay dynamics. It helps identify the potential impacts of climate change, ocean currents, and other factors on the bay’s ecosystem. This study aims to understand the seasonal variability of the Bay of Bengal’s surface circulation features using a high-resolution numerical Coastal and Regional Ocean Community simulations model. METHODS: To conduct the study in the Bay of Bengal, the Coastal and Regional Ocean Community model, a numerical ocean model, was utilized. The high-resolution numerical model for ocean circulation is three-dimensional and uses hydrostatic primitive equations in generalized curvilinear coordinates. Simulations were conducted over 8 years using a grid comprising 256 x 249 horizontal surface points to model a range of ocean-atmospheric parameters. This grid provided an approximate resolution of 10 kilometers.FINDINGS: The findings are based on the model’s enhanced performance compared to previous study results. It was observed that the sea surface temperature remains above 28 degrees Celsius throughout the bay except in winter. During the monsoon season, surface salinity was observed to be reduced in the Bay of Bengal’s northern region and western and eastern boundaries. Surface eddies along the western bay extend to deep waters before the onset of monsoon. The net heat flux in the bay has been determined as positive before monsoon, negative post-monsoon, and mixed during the monsoon season.CONCLUSION: This analysis focuses on the ocean surface layer with more prominent dynamics. Various surface parameters were calculated, and discussions on surface temperature, salinity, D20, D26, and net heat flux across seasons have been presented.

BACKGROUND AND OBJECTIVES: The innovativeness of this study lies in achieving a comprehensive understanding of the seasonal variations and oceanic characteristics of the Bay of Bengal by addressing the complex interplay of large-scale ocean-atmosphere dynamics. The study aimed to understand the upper ocean characteristics of the Bay of Bengal by analyzing the surface variables such as salinity and temperature using a high-resolution model simulation. To accomplish this, advanced high-resolution numerical simulations were employed, utilizing the coastal and regional ocean community model. This model was crucial for investigating and analyzing the circulation features throughout the entire Bay of Bengal, contributing knowledge and insights about the coastal and regional oceanographic community. METHODS: To investigate the temporal variability of the upper ocean in the Bay of Bengal, climatological simulations were performed over eight years using the coastal and regional ocean community model. Including a three-year spin-up phase facilitated the adjustment of the model to initial conditions and the attainment of equilibrium, ensuring its fidelity to realworld conditions. The follow-up analyses and comparisons were performed five years after the spin-up phase. The primary objective of this study was to examine the temporal evolution of the kinetic energy throughout the eight-year simulation. The volume-averaged kinetic energy was computed, revealing a gradual increase throughout the simulation, with particularly pronounced enhancements observed during the monsoon period. A Taylor diagram was used for predicting the model with the other data sets. FINDINGS: The analysis is performed above the surface and sub-surface oceanic layers with prominent dynamics. The temperature and salinity for the surface and sub-surface layers were validated and analyzed for their seasonal variations. The simulations were validated against the existing satellite, reanalysis, and in situ data. CONCLUSION: The innovativeness of this study lies in its successful demonstration of the seasonal variability of temperature and salinity in the Bay of Bengal. Through extensive validations, it establishes the model to accurately simulate the climatological surface features of the Bay of Bengal. This study highlights the effectiveness of numerical models when combined with observations, and the data were reanalyzed, showcasing their utility as valuable tools for studying oceanic conditions. The utilization of a Taylor diagram further supports the validation and excellent performance of the model compared to other available datasets. During the simulation, there is a high correlation (0.96) between the evolution of the salinity and temperature values obtained from the model and the corresponding data from the World Ocean Atlas. This indicates a strong agreement between the model-based simulations and the assimilated data, as supported by the notable correlation values of 0.96 for salinity and temperature. These findings reinforce the existing knowledge regarding the influential role of monsoon winds in shaping the circulation patterns within the Bay of Bengal. Overall, this study contributes to advancing our understanding of the ocean dynamics of the region and underscores the importance of considering seasonal variations for comprehensive oceanographic research, coastal management, climate modeling, and future studies in the Bay of Bengal. [ABSTRACT FROM AUTHOR]

BACKGROUND AND OBJECTIVES: The innovativeness of this study lies in achieving a comprehensive understanding of the seasonal variations and oceanic characteristics of the Bay of Bengal by addressing the complex interplay of large-scale ocean-atmosphere dynamics. The study aimed to understand the upper ocean characteristics of the Bay of Bengal by analyzing the surface variables such as salinity and temperature using a high-resolution model simulation. To accomplish this, advanced high-resolution numerical simulations were employed, utilizing the coastal and regional ocean community model. This model was crucial for investigating and analyzing the circulation features throughout the entire Bay of Bengal, contributing knowledge and insights about the coastal and regional oceanographic community.METHODS: To investigate the temporal variability of the upper ocean in the Bay of Bengal, climatological simulations were performed over eight years using the coastal and regional ocean community model. Including a three-year spin-up phase facilitated the adjustment of the model to initial conditions and the attainment of equilibrium, ensuring its fidelity to real-world conditions. The follow-up analyses and comparisons were performed five years after the spin-up phase. The primary objective of this study was to examine the temporal evolution of the kinetic energy throughout the eight-year simulation. The volume-averaged kinetic energy was computed, revealing a gradual increase throughout the simulation, with particularly pronounced enhancements observed during the monsoon period. A Taylor diagram was used for predicting the model with the other data sets.FINDINGS: The analysis is performed above the surface and sub-surface oceanic layers with prominent dynamics. The temperature and salinity for the surface and sub-surface layers were validated and analyzed for their seasonal variations. The simulations were validated against the existing satellite, reanalysis, and in situ data.CONCLUSIONS: The innovativeness of this study lies in its successful demonstration of the seasonal variability of temperature and salinity in the Bay of Bengal. Through extensive validations, it establishes the model to accurately simulate the climatological surface features of the Bay of Bengal. This study highlights the effectiveness of numerical models when combined with observations, and the data were reanalyzed, showcasing their utility as valuable tools for studying oceanic conditions. The utilization of a Taylor diagram further supports the validation and excellent performance of the model compared to other available datasets. During the simulation, there is a high correlation (0.96) between the evolution of the salinity and temperature values obtained from the model and the corresponding data from the World Ocean Atlas. This indicates a strong agreement between the model-based simulations and the assimilated data, as supported by the notable correlation values of 0.96 for salinity and temperature. These findings reinforce the existing knowledge regarding the influential role of monsoon winds in shaping the circulation patterns within the Bay of Bengal. Overall, this study contributes to advancing our understanding of the ocean dynamics of the region and underscores the importance of considering seasonal variations for comprehensive oceanographic research, coastal management, climate modeling, and future studies in the Bay of Bengal.

BACKGROUND AND OBJECTIVES: Studying the monthly variations in the surface features of the Bay of Bengal is a complex task that involves numerous large-scale ocean-atmosphere dynamics. This study identified the bay's changing circulation patterns over recent decades as a crucial study area requiring in-depth research. Understanding the changes in circulation patterns provides valuable insights into the Bay dynamics. It helps identify the potential impacts of climate change, ocean currents, and other factors on the bay's ecosystem. This study aims to understand the seasonal variability of the Bay of Bengal's surface circulation features using a high-resolution numerical Coastal and Regional Ocean Community simulations model. METHODS: To conduct the study in the Bay of Bengal, the Coastal and Regional Ocean Community model, a numerical ocean model, was utilized. The high-resolution numerical model for ocean circulation is three-dimensional and uses hydrostatic primitive equations in generalized curvilinear coordinates. Simulations were conducted over 8 years using a grid comprising 256 x 249 horizontal surface points to model a range of ocean-atmospheric parameters. This grid provided an approximate resolution of 10 kilometers. FINDINGS: The findings are based on the model's enhanced performance compared to previous study results. It was observed that the sea surface temperature remains above 28 degrees Celsius throughout the bay except in winter. During the monsoon season, surface salinity was observed to be reduced in the Bay of Bengal's northern region and western and eastern boundaries. Surface eddies along the western bay extend to deep waters before the onset of monsoon. The net heat flux in the bay has been determined as positive before monsoon, negative post-monsoon, and mixed during the monsoon season. CONCLUSION: This analysis focuses on the ocean surface layer with more prominent dynamics. Various surface parameters were calculated, and discussions on surface temperature, salinity, D20, D26, and net heat flux across seasons have been presented. [ABSTRACT FROM AUTHOR]

The present study focuses on climatological distributions of Monsoon Depressions (MDs) during different phases of Monsoon Intraseasonal Oscillation (MISO) and their relationship with different observed meteorological and oceanic parameters from buoys. The MISO is represented as a cyclic process with eight phases to show the northward propagation of the rainfall band. Almost 60% of MDs occur during the third and fourth phases of MISO over the north Bay of Bengal (BoB) and central India. Interestingly, a similar climatological composite of SST for different MISO phases does not precisely match the spatial precipitation pattern over the BoB. Instead, the oscillation is shown over a confined area near the east coast and to the north of 15 ∘ N. The lagged (6–12 days) impact of SST is well recognized in central and west BoB. The characteristics of MISO are explained through a detailed investigation of two contrasting years (2017 and 2018) in terms of the number of MDs. The analysis showed possible impacts of intensity and track of depressions on the MISO in terms of its intensity and successive phases. The intraseasonal signal of surface salinity is mostly negative during the weak phases of MISO (7, 8, and 1) with a slight lag (10–15 days) because of a freshwater flux resulting from the previous wet period. Similarly, during the active phases (phase 3 to phase 6), the salinity signal becomes positive for the lagged impact of higher evaporation during the current and prior phases. A consecutive repetition of phases 4 to 6, associated with different MDs concurrence with increasing ocean heat content (OHC), is noted during both years. The ISO in subsurface (25–60 m) temperature is stronger in 2018, and upward propagation of temperature anomaly helps in formations of more depressions than in 2017. In addition, six years (2013–2018) of subsurface temperature showed that MDs formation followed the warmer subsurface. The ISO signals for different meteorological parameters, Air Temperature, Sea Level Pressure, and Wind Speed are comparatively stronger (by amplitude) in 2018 than in 2017, resulting in higher variability of MISO and more MDs. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau uplift has induced the formation of the largest sediment source-sink system in the northeast Indian Ocean, which has become an ideal region for investigating land-sea interaction processes. However, many questions regarding sediment transport patterns and their controlling factors at different time scales remain unanswered. Therefore, in the present study, a gravity core named BoB-79, based on the southern Bay of Bengal (BoB) was selected to investigate sediment provenance shift and its corresponding mechanism to sedimentary environment change since the last glacial maximum (LGM). The clay mineral compositions are analyzed and the whole core sediments reveal a feature dominated by illite (~55%), followed by chlorite (~24%) and kaolinite (~17%), and the content of smectite (~4%) is the lowest. A trigonometric analysis of provenance discrimination of clay minerals showed that the Himalayas, together with the Indian Peninsula, represent the main sources of southern BoB sediments, and the last glacial period might have been controlled by the dominant Himalayan provenance, with an average contribution of approximately 90%. However, as a secondary source, the influence of the Indian Peninsula increased significantly during the Holocene, and its mean contribution was 24%, thus, indicating that it had a crucial effect on the evolution process of BoB. The sediment transportation pattern changed significantly from the LGM to the Holocene: in the last glacial period, the low sea level exposed the shelf area that caused the Ganges River connected with the largest submarine canyon in BoB named Swatch of No Ground (SoNG), and the Himalayan materials could be transported to the BoB directly under a strong turbidity current, thereby forming the deep sea deposition center with a sedimentation rate of 4.5 cm/kyr. Following Holocene, the sea level increased significantly, and the materials from multiple rivers around the BoB were directly imported into the continental shelf area. The intensive Indian summer monsoon dominated the transportation process of the terrestrial materials, thereby forming a deposition center in the shallow water area of the continental shelf northeast Indian Ocean; subsequently, the material flux relative to the input to the deep sea area decreased significantly, and the sedimentation rate in the southern BoB decreased to 1.7 cm/kyr.

The seasonal and inter-annual variability of Total Alkalinity (TA) concentration was studied in the Bay of Bengal from 2003 to 2019 by using MODIS-Aqua derived sea surface temperature (SST) and sea surface salinity (SSS) products. The satellite derived TA showed a positive relationship with in-situ TA with (R2 = 0.67, RMSE = ±27.53 μMol/kg, SEE = ±32.16 and uncertainty error = 2287μMol/kg). The seasonal SST, SSS and TA portray the clear seasonal pattern between the seasons without any rapid change increase or decrease in trend observed over the years. In contrast to other seasons, the spring inter-monsoon was observed to have a warm surface water temperature with high salinity and TA. Strong wind and excessive cloud cover during the summer monsoon result in the reduction of ocean surface heat, which favours sea surface cooling and shallow mixed layer depth, resulting in low SST, SSS, and TA compared to the spring inter-monsoon. During fall inter-monsoon, the reversal of East India coastal current directs warm water from north to south and the weak wind that prevails in this region enhances stratification. During winter, low-saline water compensates the static stability loss by thermal inversion from the sea surface resulting in surface cooling with coldest SST, low SSS and TA during this period.

Satellite altimetry is an important technique to derive oceanic deflections of vertical (DOV). HaiYang-2A (HY-2A) is the first Chinese altimetry satellite launched in August 2011 to observe the global marine dynamic environment. To assess the reliability of DOVs derived from HY-2A geodetic mission data, the Bay of Bengal and its adjoining area (0°–23°N, 80°–100°E) are selected as the research area, and the accuracy of HY-2A/GM-derived DOVs is compared with that of DOVs determined from CryoSat-2-measured sea surface heights (SSHs) and SARAL/AltiKa (SARAL)-measured SSHs which are in the same period as HY-2A-measured SSHs. Compared with the along-track DOVs calculated from Sentinel-3B-measured SSHs (from cycle 20 to cycle 33), the RMS of differences for HY-2A-determined DOVs is 0.1 μrad smaller than that for SARAL-determined DOVs and CryoSat-2-determined DOVs. The differences of the along-track DOVs in the frequency domain are also analyzed by power spectral density. In addition, the XGM2019e model is adopted to evaluate the quality of the gridded DOVs model established by least-squares collocation method. Marine gravity anomaly models (SIO V30.1) and ship-borne gravity anomalies are also used to assess the accuracy of gravity anomalies derived from gridded DOVs. The whole results show that the accuracy of HY-2A-determined DOVs is coincident with that of CryoSat-2-determined DOVs and slightly lower than that of SARAL-determined DOVs. Therefore, HY-2A/GM altimetry data can be applied in establishing the global high-precision DOV model.

This study addresses the air–sea interaction processes and mixed layer variability, which cause the intraseasonal oscillations in the sea surface temperature (SST) during January 2013–December 2014 using the Regional Ocean Modeling System (ROMS). We have analyzed the SST variability at three locations—northern Bay of Bengal (BoB)/15°N, 90°E (R15), central BoB/12°N, 90°E (R12), and equatorial Indian Ocean (EIO)/0°N, 80.5°E (R0). During northeast monsoon (NEM) and southwest monsoon (SWM), intraseasonal SST variability is respectively controlled by the intense outgoing fluxes (sum of longwave radiation, latent heat flux, and sensible heat flux) and zonal wind stress. The intraseasonal SST variability in spring and fall is modulated by intense incoming shortwave radiation. There is a profound impact of mixed layer depth (MLD) variations on the intraseasonal SST oscillations in the BoB and EIO. At R15, and R12, deepened simulated MLD is associated with the lowered SST variability in the NEM and SWM. In spring and fall, the shallow MLD variability corresponds to higher intraseasonal SST variability at the buoy locations. In the northern BoB, ROMS cannot capture barrier layer (BL) and temperature inversion (TI) accurately in the winter and premonsoon season due to salinity bias, resulting in the difference between simulated and actual MLD. But the simulated MLD bias does not affect the intraseasonal SST structures in the NEM and pre-SWM. In the northern BoB, the proper representation of salinity structure may represent BL, TI, and MLD, accurately in the simulation during the winter and premonsoon season. [ABSTRACT FROM AUTHOR]

The key role of oceans in the global climatic system can be accurately quantified by the measurement of CO $_{2}$ exchange across air–sea interface. The direction and magnitude of this CO $_{2}$ exchange are mainly governed by the gradient of partial pressure of carbon dioxide (pCO $_{2}$) at the air–sea interface. The sea surface pCO $_{2}$ is highly variable, primarily regulated by seasonal sea surface temperature (SST) and CO $_{2}$ (aqueous) concentration. In this paper, the moored pCO $_{2}$ observations from autonomous pCO $_{2}$ system deployed at 15  $^{\circ }$ N 90  $^{\circ }$ E in the Bay of Bengal (BOB) were used to derive CO $_{2}$ fluxes to examine variability over time scale at BOB. An attempt has also been made to develop a model using multiple linear regression (MLR) and support vector regression (SVR) to estimate the sea surface pCO $_{2}$ from space-based observations of SST and salinity. pCO $_{2}$ variability was primarily attributed to SST and CO $_{2}$ concentration changes. Derived fluxes showed that BOB is a net annual source (0.440 g-C/m $^{2}$ /year for year 2014) of CO $_{2}$ at mooring location with significant seasonality effects. For the estimation of surface pCO $_{2}$ , SVR model showed better results [root mean square error (RMSE) = 7.68 $\mu$ atm] in comparison to MLR model (RMSE = 12.36 $\mu$ atm). The seasonal climatological pCO $_{2}$ maps from September 2011 to February 2018 showed southward increase in pCO $_{2}$ in all seasons possibly due to southward increase in SST and less influence of river water. These pCO $_{2}$ maps can further be utilized in deriving CO $_{2}$ flux maps for BOB. [ABSTRACT FROM AUTHOR]

Abstract Hilsa (Tenualosa ilisha) or river shad is an anadromous fish species widely distributed in the North Indian Ocean, mainly in the Bay of Bengal (BoB). Hilsa is the national fish of Bangladesh and it contributes 10% of the total fish production of the country, with a market value of $1.74 billion. Hilsa also holds a very important place in the economics of West Bengal of India with 12.5% of the catch and also tops the marine capture in Myanmar. During the last two decades Hilsa production from inland waters has been stable, whereas marine yields in the BoB increased substantially. In order to sustainably manage the trans-boundary stock of Hilsa, the taxonomy, distribution, habitat, migration patterns, population dynamics, fisheries and socio-economics aspects of the fishery have been reviewed here. To achieve a successful trans-boundary management for the Hilsa stock, complete ban on undersize fishing, well-targeted temporal and spatial bans, creation of protected areas in strategic points, incentive for Hilsa fishers and ecological restoration of Hilsa habitats and more work on technological development of Hilsa aquaculture are recommended. Graphical abstract Unlabelled Image Highlights • Hilsa is widely distributed in south Asian countries, mainly in the Bay of Bengal, where six million people are engaged in Hilsa value chain • Hilsa in freshwater face challenges from overfishing and resource degradation. • Spatial and seasonal fishing bans and incentives for fishers are found as successful management measures. • To sustain the fishery, effective regional collaboration is necessary along with strict conservation measures. [ABSTRACT FROM AUTHOR]

In this paper, a study is presented on energetics of internal tides using available high temporal resolution in situ data collected during February 19–20, 2012 and MITgcm (M.I.T. General Circulation Model) model simulations in the western Bay of Bengal. The spectral estimate of density indicates that the peak estimate is associated with the semidiurnal frequency at all the depths. The vertical displacement of density, i.e., isopycnal displacement, suggests that about 20-m amplitude of semidiurnal internal tides exist in the pycnocline region in both observations and model simulations. After eliminating the barotropic signal, the baroclinic zonal and meridional components of velocity are found to be in the order of 0.3 and 0.4 m s−1, respectively. The energy flux calculated using the velocity-pressure correlation is predominantly seen in zonal direction from both observations and simulations. The peak magnitude of available potential energy is found to be of the order of 22 J m−3 in the pycnocline region for the semidiurnal tide. As expected, the horizontal kinetic energy values have the maximum at the surface layer. The computed barotropic forcing is found minimal over the shelf-break region as it is converted into internal tides. The internal tides are generated over the shelf-slope region and propagate toward the coast. The energy dissipation is seen to be maximum over the shelf-slope region causes mixing due to internal tides. The available potential energy is found to be maximum in north of the model domain. The internal tides activities are found to be maximum in the northern Bay of Bengal. [ABSTRACT FROM AUTHOR]

This study was selected to assemble the current information in order to establish a massbalanced ecosystem model within the resettled maritime limit zone of the Bay of Bengal, Bangladesh through ECOPATH approach covering over 90000 km². A total of 19 functional groups were considered demonstrating all trophic levels in the food web where the estimated trophic interactions between the groups were varied from 1 (primary producers and detritus) to 3.45 (sharks). The ecotrophic efficiency (EE) of most of the consumers was >0.80; indicating a largely exploited ecosystem and high energy transfer from lower to higher trophic levels. Moreover, the gross efficiency (0.0018) and transfer efficiency (11.12%) of the whole system symbolize the 'developing systems' with somewhat maturity. Ecosystem's overhead (64.6) and ascendancy (35.4) also designate the ecosystem's stability. Thus, this study concludes that the resettled maritime area of BoB reserves significant backup strength to face stress situations having capacity to rapid restoration to the original states. [ABSTRACT FROM AUTHOR]

An investigation of the eddy and coastal Kelvin wave activities in the Bay of Bengal (BoB) is carried out during premonsoon season in two years of Indian summer monsoon deficit in June (2009 and 2012), occurred in the recent warming hiatus period. Using altimeter observations, our study reveals that over the northern BoB cyclonic eddy kinetic energy is reduced by 35% and 50% from the climatology during premonsoon seasons in 2009 and 2012, respectively, while the cyclonic eddy area is reduced by 18% and 24%, respectively. A concurrent reduction is observed in the first upwelling Kelvin wave (uKW) activities in the eastern equatorial Indian Ocean as well as in the coastal BoB for these years. The reduction in the generation of the first uKW in the eastern equatorial Indian Ocean is attributed to the westerly wind anomalies in January–March of these years. Additionally, meridional wind stress anomalies during March–April in these years are found to be southerly, causing anomalous coastal downwelling in the eastern rim of BoB. This coastal downwelling blocks the propagation of the first uKW. The decrease in the first uKW activities in the coastal waveguide of the BoB reduces the radiation of upwelling Rossby waves, thereby decreasing the cyclonic eddy activities in the northern BoB. The results from this letter could be helpful for further understanding of upper ocean mixing processes in the BoB during monsoon deficit years. [ABSTRACT FROM PUBLISHER]

This paper presents the first results on comparisons of Scatterometer Satellite-1 (SCATSat-1) derived wind datasets with the in situ, reanalysis as well as another operational scatterometer derived winds in the Bay of Bengal during the period November 2016–March 2017. The comparisons of daily gridded wind products of SCATSat-1 with buoys show good correlations (>0.83), higher skill scores (>0.92), and lower root mean square errors (RMSEs) of 0–2 m/s for wind speeds (WS) at the buoy locations. Similarly, the results corresponding to wind directions (WD) show higher correlations (>0.95), higher skill scores (>0.96), and relatively lower RMSEs (15–30°). Further, the intercomparisons of SCATSat-1 with Advanced Scatterometer and European Centre for Medium Range Weather Forecasts reanalysis winds show strong correlations for both WS (>0.85) and WD (>0.94). This paper also reports the capability of SCATSat-1 to capture three tropical cyclones Kyant, Vardah, and Mora during the period of study with the highest WS of 23.5 m/s. [ABSTRACT FROM PUBLISHER]

Recent changes in sea level have appeared as a major threat to the existence of coastal habitats like mangroves and to the biodiversity characterizing such habitats. In this study benthic foraminifer analysis along with carbon isotopes (δ 13 C‰) and ratio between organic Carbon and Nitrogen (C/N) were analyzed from five intertidal stations in Sundarbans, the world's largest mangrove ecosystem to test the efficiency of these signatures toward tracking relative rise in sea level. The stability of these signatures with respect to gap of twenty months across varying elevations of the targeted stations has been tested. Benthic foraminifer abundance ranged from 0 to 118 individuals per 10 g and the assemblage was found to be mostly dominated by agglutinated species. The δ 13 C‰ values (−26.6 to −23.8) reflected that the origin of carbon is majorly from vascular land plants in some inputs from estuarine phytoplankton that are known to characterize tidal water of Sundarbans. The values of C/N (0.48–1.43) represented a microbially degraded total organic carbon (TOC) pool and thus were not a suitable proxy. Out of three signatures, δ 13 C‰ showed a strong co-relation with elevation and thus could be used as a reliable proxy to track relative sea level rise in mangrove environments. [ABSTRACT FROM AUTHOR]

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Bay of Bengal (BoB) has immense significance with respect to ecological diversity and natural resources. Studies on microbial profiling and their functional significance at sediment level of BoB remain poorly represented. Herein, we describe the microbial diversity and metabolic potentials of BOB deep-sea sediment samples by subjecting the metagenomes to Nanopore sequencing. Taxonomic diversity ascertained at various levels revealed that bacteria belonging to phylum Proteobacteria predominantly represented in sediment samples NIOT_S7 and NIOT_S9. A comparative study with 16S datasets from similar ecological sites revealed depth as a crucial factor in determining taxonomic diversity. KEGG annotation indicated that bacterial communities possess sequence reads corresponding to carbon dioxide fixation, sulfur, nitrogen metabolism, but at varying levels. Additionally, gene sequences related to bioremediation of dyes, plastics, hydrocarbon, antibiotic resistance, secondary metabolite synthesis and metal resistance from both the samples as studied indicate BoB to represent a highly diverse environmental niche for further exploration. • Deep-sea sediment metagenome of Bay of Bengal reveals distinct functional significance. • Colwellia is shown to be the dominant genus from metagenome. • Antibiotic Resistance and Metal Resistance were identified from the metagenome. • A full length type III polyketide synthase gene was annotated from NIOT_S9 metagenome. [ABSTRACT FROM AUTHOR]

The present study explores the capabilities of advanced machine learning algorithms in predicting the sea-surface p CO 2 (partial pressure of carbon dioxide) in the open oceans of the Bay of Bengal (BoB). We collect the available observations (outside EEZ (Exclusive Economic Zone)) from the cruise tracks and the mooring stations. Due to the paucity of data in the BoB, we attempt to predict p CO 2 based on the Sea Surface Temperature (SST) and the Sea Surface Salinity (SSS). Comparing the MLR, the ANN, and the XGBoost algorithm against a common dataset reveals that the XGBoost performs the best for predicting the sea-surface p CO 2 in the BoB. Using the satellite-derived SST and SSS, we predict the sea-surface p CO 2 using the XGBoost model and compare the same with the in-situ observations. The model performs satisfactorily, having a correlation of 0.75 and the RMSE of ± 12. 23 μ atm. Further using this model, we emulate the monthly variations in the sea-surface p CO 2 for the central BoB between 2010–2019. Using the satellite data, we show that the central BoB is warming at a rate of 0.0175 °C per year, whereas the SSS decreases at a rate of -0.0088 PSU per year. The modeled p CO 2 shows a declination at a rate of −0.4852 μ atm per year. We perform sensitivity experiments to find that the variations in SST and SSS contribute ≈ 41% and ≈ 37% to the declining trends of the p CO 2 for the last decade. Seasonal analysis shows that the pre-monsoon season has the highest rate of decrease of the sea-surface p CO 2. • Performance of MLR, ANN, and XGboost for emulating sea-surface p CO 2 is evaluated. • XGBoost outperforms MLR and ANN in reproducing sea-surface p CO 2. • The p CO 2 reproducibility using satellite-derived SST and SSS is best using XGBoost. • The central BoB has been warming at a rate of 0.0175°C per year during 2010–2019. • The sea-surface p CO 2 decreases at a rate of −0.4852 μ atm per year in the BoB. [ABSTRACT FROM AUTHOR]

Remote sensing-based analysis has been carried out to study the impact of “Phailin” cyclone on ocean phytoplankton distribution off Odisha coast and on the northern Bay of Bengal water. Oceansat-2 Ocean Colour Monitor (OCM) and MODIS-Terra sensors-derived chlorophyll images have been generated over the study area during October 2013. There has been observation of drastic change in the chlorophyll concentration of the north-western Bay of Bengal water with effect of the cyclone “Phailin,” which hit Gopalpur, Odisha coast on 12 October night at around 21:00 h IST. The postcyclone images of Oceansat-2 OCM data and retrieved chlorophyll concentration were observed to be very high, \bf3.0 - 4.0\;\bfmg/m^\bf3 in coastal water, which was around \bf0.5 - 1.0\;\bfmg/m^\bf3 during precyclone. Similarly, the postcyclone chlorophyll was around \bf0.80 - 1.50\;\bfmg/m^\bf3 in the offshore water, unusually high compared to precyclone concentration (< \bf0.60\;\bfmg/m^\bf3). The cyclone track of India Meteorological Department (IMD) has been superimposed on chlorophyll images and observed as proxy along the chlorophyll front with algal bloom features. There has been observation of cooling in the northern Bay of Bengal and off Odisha coast with impact of the induced upwelling, entrainment and mixing of the water column, as evident from the sea surface temperature (SST) data analysis. Interesting features such as cold core eddies and fronts have been visualized. This study is important to assess the impact of Phailin cyclone on ocean productivity on the local and basin scale and its deviation from seasonal trend as well. [ABSTRACT FROM PUBLISHER]

We apply a coupled physical and biogeochemical (ROMS+PISCES) to understand the influence of distinct drivers and mechanisms on the sea-surface p CO 2 and the air-sea CO 2 flux of the Bay of Bengal (BoB). The model evaluation suggests that the model simulated sea-surface p CO 2 is in accord with the observations. The north of BoB is found to be a sink for the atmospheric CO 2 , whereas the rest of the region acts as a source. The effect of dissolved inorganic carbon (DIC) and the total alkalinity (TALK) is found to be predominant but is contrasting in nature. Mixing-induced changes in DIC and TALK results in high p CO 2 (+570 μatm) and, consequently, the positive CO 2 flux. The biological activity does draw down the surface p CO 2 (−120 μatm) but is insufficient in completely opposing the effect of mixing. The uptake of CO 2 in the north is due to the CO 2 solubility, which is a function of salinity and temperature. The northern rivers, having a high discharge rate, reduce the salinity and temperatures in the north, which possibly aids in this region to be a sink. In the northeast monsoon season, the impact of temperature and DIC is high and opposing. The TALK reduces the p CO 2 in the northeast monsoon, but the magnitude is low. The p CO 2 in the southwest monsoon is influenced primarily by temperature, whereas in the postmonsoon monsoon, the freshwater dominates. The pre-monsoon season experiences the TALK, temperature, and freshwater increase the p CO 2 anomalies, and only the DIC reduces p CO 2 anomalies. • The northern Bay of Bengal (BoB) is a sink of CO2. • Circulation is the assertive mechanism driving sea-surface pCO2 variability. • Biology and solubility oppose but do not cancel the circulation effect. • The DIC and TALK cancel out each other's effect. • Freshwater flux dominates the region's source and sink characteristics. [ABSTRACT FROM AUTHOR]

• The Bay of Bengal (BoB) does not act as a sink of CO 2 as hitherto hypothesized. • The freshwater plume dynamics influences the spread of CO 2 sink region. • The region having thick barrier layer displays CO 2 sink characteristics. • The annual mean values of CO 2 fluxes reveal northern BoB to be a sink of CO 2. • The southern BoB emulates CO 2 source characteristics. The high influx of freshwater in the Bay of Bengal (BoB) region forms a freshwater plume at the surface. This plume's dispersal spreads a low-density layer of water on the surface, forming a barrier layer between the mixed layer depth and the isothermal layer. The low saline water reduces the sea surface partial pressure of carbon dioxide (p CO 2), and the barrier layer thickness (BLT) inhibits the interaction between the subsurface and surface layers of BoB. In this study, we run a high resolution coupled physical-biogeochemical model to understand the effect of variability of freshwater plume spread (FPS) and the BLT on the seasonality of sea-surface p CO 2. By comparing with observation data, we find that the model satisfactorily simulates the sea-surface p CO 2 and the FPS for the BoB region. As the FPS begins to develop in the southwest monsoon season, the CO 2 sink region also begins to form in the same manner. The region with sea surface salinity (SSS) less than 31 PSU was recognized as a freshwater plume. The region with SSS lower than 31 PSU showed under-saturated levels of p CO 2. The model analysis showed that the CO 2 sink spread exceeded the FPS in the winter monsoon season, covering almost 50% of the BoB region. This spread was attributed to the BLT, which is highest during the winter monsoon season. Based on the spatial CO 2 flux, we find the Northern BoB a sink of atmospheric CO 2 (−0.35 ± 0.75 mol C m-2 yr-1). The Southwestern BoB acts as a source of CO 2 (0.72 ± 0.61 mol C m-2 yr-1) throughout the year and has the highest magnitude of flux, whereas the Southeastern BoB also acts as a weak source of CO 2 (0.214 ± 0.52 mol C m-2 yr-1). [ABSTRACT FROM AUTHOR]

The Bay of Bengal is a semi-enclosed ocean basin situated in the eastern part of the North Indian Ocean. Though the physical dynamical features of the Bay of Bengal have been studied and measured in detail, the carbonate chemistry of this basin has been less explored, and very few reliable data-sets exist. This paucity of data has emerged as a major challenge in modeling and understanding the carbonate system parameters for this region. In this study, a coupled physical-biogeochemical (ROMS-PISCES) model has been configured and run to emulate the surface carbonate system parameters (DIC, TALK, pCO 2 , and pH) for the Bay of Bengal region. Model skill assessment analysis has been performed using available observational data-sets. Two different numerical experiments have been performed (WB indicating the use of default bulk formulae of ROMS to calculate wind stress and WoB indicating the calculated wind stresses of QuikSCAT climatology product using different bulk formula), to understand which one reproduces the carbonate parameters better. Both the numerical experiments are rigorously compared for physical as well as carbonate system parameters. The numerical experiments have been passed through exhaustive statistical analysis by comparing it with the observed data-sets. The temperature, the primary driver affecting pH and pCO 2 has been reproduced by both the experiments excellently, and the correlation value is more than 0.9 with RAMA buoy data (15 o N, 90 o E). The salinity, when compared with the NIOA climatology data, shows that the WoB experiment has better captured both the spatial and temporal variation of salinity. Both the numerical experiments have been compared individually with three sets of observed carbonate data. The WoB run has been found to emulate carbonate system parameters satisfactorily than the WB run. The pCO 2 and pH show a good positive correlation with RAMA data and the values are 0.87, and 0.93, respectively. • A coupled physical-biogeochemical model has been set up for the Bay of Bengal region to emulate its carbonate chemistry. • The model has been rigorously evaluated with the available data sets using 8 statistical indices to establish its skills. • The model is excellent in simulating the spatial heterogeneity and temporal variation of all the carbonate parameters. • The importance of modeling physical characteristics to reproduce the carbonate chemistry for Bay of Bengal is highlighted. [ABSTRACT FROM AUTHOR]