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Pirates killed U.S. couples after warning: court papers.

With Chapala's destructive landfall in Yemen just a couple of days in the past, a second tropical cyclone, Megh, has just formed in the Arabian Sea. This one is not forecast to become anywhere near as intense as Chapala did-though we know intensity forecasts can be wrong, as they were at early stages for both Chapala and Patricia.

Decadal climate variability in the southern Indian Ocean could be predicted up to 10 years ahead, according to a study led by Dr. MORIOKA at Application Laboratory, the Japan Agency for Marine-Earth Science and Technology (JAMSTEC: ASAHIKO Taira, President) and his colleagues. To investigate the predictability, the scientists have used sea surface temperature (SST) observation data during 1982 to 2015 to initialize a state-of-the-art coupled general circulation model, the Scale Interaction Experiment Frontier Research Center 2 for Global Change (SINTEX-F2*) with a simple SST-nudging scheme. Their decadal reforecast experiments demonstrated moderately high prediction skills of yearly mean SST in the southwest Indian Ocean at 10-year lead time.

The continental margin harbors a variety of habitats that support incredible biodiversity and the function of their oceans' ecosystems. The meiofauna is considered a significant component of the benthic faunal community from the polar to the tropical regions. The meiofaunal community in the deep Indian Ocean, especially along the depth gradient, is poorly investigated. The present study aims to explore the benthic meiofaunal community structure along the depth gradients and its associated environment in the western Indian continental margin (WICM) and abyssal plain in the eastern Arabian Sea. Sediment samples were collected from seven different depths (111-3,918 m) along the WICM including the oxygen minimum zone (OMZ) and abyssal plain. A total of 22 taxa (groups) were encountered along the WICM. The nematodes (85%) were the most dominant taxa in all the depths, followed by copepods (11%), nauplii (5%), and polychaetes (1.36%). Our results suggest that (a) the organic matter has accumulated in OMZ sites; (b) a high amount of total organic carbon did not influence the meiofaunal density or biomass; (c) oxygen and depth gradients were significant drivers of the meiofaunal community, low levels of oxygen contributed to lower taxa diversity and density at 485 and 724 m depths; (d) a significant relationship of meiofaunal density and biomass with chloroplastic pigment equivalent (CPE) values indicates pelagic-benthic coupling. Copepods, nauplii, tanaidaceans, isopods, kinorhynchs, and cumaceans were affected by the low-oxygen conditions at the OMZ sites. Enhanced meiofaunal diversity, density, and biomass at deeper sites (non-OMZ-D) was attributed to increased abundance of copepods, nauplii, tanaidaceans, isopods, kinorhynchs, and cumaceans and were mostly concentrated on the surface sediment (0-4 cm) triggered by enhanced bottom-water oxygen and freshness of available food outside the OMZ except 3,918 m. Therefore, the present study showed the meiofaunal community

The silver-lipped pearl oyster, Pinctada maxima, is the primary species used for the culture of pearls in the Indo-Pacific region. The Western Australian fishery relies on wild-caught animals, and as such, knowledge of the status and distribution of P. maxima underpins sustainable management of the fishery. Eighty Mile Beach, in tropical Western Australia, is the key harvest area for P. maxima, with oysters collected by divers to depths of ∼35 m, although there are anecdotal accounts of oysters beyond diving depths. Image-based, and acoustic methods were used to elucidate distribution patterns of P. maxima off Eighty Mile Beach, including data from 862 km2 of multibeam survey and 119 towed video transects spanning an area from the 20 to 100 m contour lines. We quantified habitat characters including depth, substrate, and benthic community composition associated with pearl oyster distribution. Multibeam sonar data was also coupled with towed video data to produce predictive statistical models of P. maxima habitat. We found P. maxima to depths of 76 m, although more than 90% of individuals occurred shallower than 40 m and less than 2% were found deeper than 50 m. Oysters occupied flat, sandy habitats with neighbouring benthic communities of filter feeders (>98% of observations). These results show P. maxima predominantly occurs in depths <40 m, with no evidence that extensive populations extend into deep water in the region.

In recent years, shoreline determination has become an issue of increasing importance and concern, especially at the local level, as sea level continues to rise. This study identifies the rates of absolute and net erosion, accretion, and shoreline stabilization along the coast of Kuakata, a vulnerable coastal region in south-central Bangladesh. Shoreline change was detected by applying remote sensing and geographic information system (RS-GIS)-based techniques by using Landsat Thematic Mapper (TM), Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) satellite images at 30-m resolution from 1989, 2003, 2010, and 2020. The band combination (BC) method was used to extract the shoreline (i.e., land-water boundary) due to its improved accuracy over other methods for matching with the existing shoreline position. This study also used participatory rural appraisal (PRA) tools which revealed the societal impacts caused by the shoreline changes. Coupling RS-GIS and PRA techniques provides an enhanced understanding of shoreline change and its impacts because PRA enriches the RS-GIS outcomes by contextualizing the findings. Results show that from 1989 to 2020, a total of 13.59 km2 of coastal land was eroded, and 3.27 km2 of land was accreted, suggesting that land is retreating at about 0.32 km2 yr-1. Results from the PRA tools support this finding and demonstrate that fisheries and tourism are affected by the shoreline change. These results are important in Kuakata, a major tourist spot in Bangladesh, because of the impacts on fisheries, recreation, resource extraction, land use planning, and coastal risk management.

In this study, we presented a high-resolution benthic foraminiferal assemblage record from the western Bay of Bengal (BoB) (off Krishna-Godavari Basin) showing millennial-scale variations during the last 45 ka. We studied temporal variations in benthic foraminiferal assemblages (relative abundances of ecologically sensitive groups/species, microhabitat categories, and morphogroups) to infer past changes in sea bottom environment and to understand how monsoon induced primary productivity-driven organic matter export flux and externally sourced deep-water masses impacted the deep-sea environment at the core site. Our records reveal a strong coupling between surface productivity and benthic environment on glacial/interglacial and millennial scale in concert with Northern Hemisphere climate events. Faunal data suggest a relatively oxic environment when the organic matter flux to the sea floor was low due to low primary production during intensified summer monsoon attributing surface water stratification and less nutrient availability in the mixed layer. Furthermore, records of oxygen-sensitive benthic taxa (low-oxygen vs. high-oxygen benthics) indicate that changes in deep-water circulation combined with the primary productivity-driven organic matter flux modulated the sea bottom oxygen condition over the last 45 ka. We suggest that the bottom water at the core site was well-ventilated during the Holocene (except for the period since 3 ka) compared with the late glacial period. At the millennial timescale, our faunal proxy records suggest relatively oxygen-poor condition at the sea floor during the intervals corresponding to the cold stadials and North Atlantic Heinrich events (H1, H2, H3, and H4) compared with the Dansgaard/Oeschger (D-O) warm interstadials. The study further reveals oxygen-poor bottom waters during the last glacial maximum (LGM, 19-22 ka) which is more pronounced during 21-22 ka. A major shift in sea bottom condition from an oxygenated bottom wa

The oxygen minimum zone has a significant effect on primary production, marine biodiversity, food web structure, and marine biogeochemical cycle. The Arabian Sea oxygen minimum zone (ASOMZ) is one of the largest and most extreme oxygen minimum zones in the world, with a positional decoupling from the region of phytoplankton blooms. The core of the ASOMZ is located to the east of the high primary production region in the western Arabian Sea. In this study, a coupled physical-biogeochemical numerical model was used to quantify the impact of ocean circulation and settling of particulate organic matters (POMs) on the decoupling of the ASOMZ. Model results demonstrate that the increased (decreased) dissolved oxygen replenishment in the western (central) Arabian Sea is responsible for decoupling. The oxygen-rich intermediate water (200-1,000 m) from the southern Arabian Sea enters the Arabian Sea along the west coast and hardly reaches the central Arabian Sea, resulting in a significant oxygen replenishment in the western Arabian Sea high-productivity region (Gulf of Aden) but only a minor contribution in the central Arabian Sea. Besides that, the POMs that are remineralized to consume central Arabian Sea dissolved oxygen comprises not only local productivity in winter bloom but also the transport from the western Arabian Sea high-productivity region (Oman coast) in summer bloom. More dissolved oxygen replenishment in the western Arabian Sea, and higher dissolved oxygen consumption and fewer dissolved oxygen replenishment in the central Arabian Sea could contribute to the decoupling of the ASOMZ and phytoplankton productive zone.

Rising sea levels, coupled with the natural variability of atoll islands and coral reefs, is creating new uncertainty in international law, with geopolitical implications.

Turbulence within the upper ocean mixed layer plays a key role in various physical, biological, and chemical processes. Between September and November 2011, a dataset of 570 vertical profiles of the turbulent kinetic energy (TKE) dissipation rate, as well as conventional hydrological and meteorological data, were collected in the upper layer of the tropical Indian Ocean. These data were used to statistically analyze the vertical distribution of the TKE dissipation rate in the mixed layer. The arithmetic-mean method made the statistical TKE dissipation rate profile more scattered than the median and geometric-mean methods. The statistical TKE dissipation rate were respectively scaled by the surface buoyancy flux and the TKE dissipation rate at the mixed-layer base. It was found that the TKE dissipation rate scaled by that at the mixed-layer base exhibited better similarity characteristics than that scaled by the surface buoyancy flux, whether the stability parameter D/|LMO| was greater or less than 10, indicating that the TKE dissipation rate at the mixed-layer base is a better characteristic scaling parameter for reflecting the intrinsic structure of the TKE dissipation rate in the mixed layer, where D and LMO are respectively the mixed-layer thickness and the Monin-Obukhov length scale. The parameterization of the TKE dissipation rate at the mixed-layer base on the shear-driven dissipation rate and the surface buoyancy flux was further explored. It was found that the TKE dissipation rate at the mixed-layer base could be well fitted by a linear combination of three terms: the wind-shear-driven dissipation rate, the surface buoyancy flux, and a simple nonlinear coupling term of these two .

The weak monsoon rainfall simulation in the CMIP6 models calls for further process understanding about the Indian summer monsoon (ISM), especially the intraseasonal variabilities. Here, the remote forcing from the Southern Hemisphere on the Indian summer monsoon is examined. Over the southeastern Indian Ocean (SEIO), intraseasonal warm SST anomalies can induce low-level southeasterly wind anomalies and accelerate the background southeasterly wind. According to the mechanism of Wind-Evaporation-SST (WES) feedback, the wind acceleration gives rise to the positive anomalies of surface latent heat flux (LHF). The intraseasonal wind anomalies propagate equatorward along with the background southeasterlies; the positive LHF increases the moist static energy over the equator. As a result, deep convections are reinforced over tropics, which strengthen the northward-propagating monsoon intraseasonal oscillations. During boreal summer, the northward intraseasonal oscillation prompts enhanced rainfall events over the monsoon region. Current results indicate the inter-hemispheric impacts as an inevitable contributor to the heavy precipitation during ISM in the Northern Hemisphere. In CMIP6, the models with better SST simulations over SEIO can have stronger equatorial rainfall and more realistic northward propagation. The unsatisfactory simulations of CMIP6 are associated with the defective ocean-atmosphere interaction over SEIO, and one clue is the feeble variances of intraseasonal oceanic signals over SEIO, which is far from the observation. This research offers a new perspective on the chronic dry monsoon bias in the Northern Hemisphere; the cross-equatorial process and the bias of intraseasonal oceanic variation over SEIO deserve further attention in the coupled models.

The Seychelles-Chagos Thermocline Ridge (SCTR, 5°S-10°S, 50°E-80°E) is a unique open-ocean upwelling region in the southwestern Indian Ocean. Due to the negative wind stress curl between the equatorial westerlies and southeasterly trade winds, SCTR is known as a strong upwelling region with high biological productivity, providing a primary fishing zone for the surrounding countries. Given its importance in shaping the variability of the Indian Ocean climate by understanding the sea-air interaction and its dynamics, the simulation of SCTR is evaluated using outputs from the Coupled Model Intercomparison Project Phase Sixth (CMIP6). Compared to observations, 23 out of 27 CMIP6 models tend to simulate considerably deeper SCTR thermocline depth (defined as the 20°C isotherm depth (D20))- a common bias in climate models. The deep bias is related to the easterly wind bias in the equatorial to southern Indian Ocean, which is prominent in boreal summer and fall. This easterly wind bias produces a weak annual mean Ekman pumping, especially in the boreal fall. Throughout the year, the observed Ekman pumping is positive and is driven by two components: the curl term, is associated with the wind stress curl, leads to upwelling during boreal summer to fall; the beta term, is linked to planetary beta and zonal wind stress, contributes to downwelling during boreal spring to fall. However, the easterly wind bias in the CMIP6 increases both the positive curl and negative beta terms. The beta term bias offsets the curl term bias and reduces the upwelling velocity. Furthermore, the easterly wind bias is likely caused by the reduced east-west sea surface temperature (SST) difference associated with a pronounced warm bias in the western equatorial Indian Ocean, accompanied by the east-west mean sea level pressure gradient over the Indian Ocean. Furthermore, this study finds local wind-induced Ekman pumping to be a more dominant factor in thermocline depth bias than Rossby waves,

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

A new study led by the University of Liverpool has found that wandering albatrosses with older partners spend less time on foraging trips than those with more sprightly partners so that their mate has a shorter wait without food.