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The Southern Indian Ocean is a major reservoir for rapid carbon exchange with the atmosphere, plays a key role in the world's carbon cycle. To understand the importance of anthropogenic CO2 uptake in the Southern Indian Ocean, a variety of methods have been used to quantify the magnitude of the CO2 flux between air and sea. The basic approach is based on the bulk formula-the air-sea CO2 flux is commonly calculated by the difference in the CO2 partial pressure between the ocean and the atmosphere, the gas transfer velocity, the surface wind speed, and the CO2 solubility in seawater. However, relying solely on wind speed to measure the gas transfer velocity at the sea surface increases the uncertainty of CO2 flux estimation. Recent studies have shown that the generation and breaking of ocean waves also significantly affect the gas transfer process at the air-sea interface. In this study, we highlight the impact of windseas on the process of air-sea CO2 exchange and address its important role in CO2 uptake in the Southern Indian Ocean. We run the WAVEWATCH III model to simulate surface waves in this region over the period from January 1st 2002 to December 31st 2021. Then, we use the spectral partitioning method to isolate windseas and swells from total wave fields. Finally, we calculate the CO2 flux based on the new semiempirical equation for gas transfer velocity considering only windseas. We found that after considering windseas' impact, the seasonal mean zonal flux (mmol/m2·d) increased approximately 10%-20% compared with that calculated solely on wind speed in all seasons. Evolution of air-sea net carbon flux (PgC) increased around 5.87%-32.12% in the latest 5 years with the most significant seasonal improvement appeared in summer. Long-term trend analysis also indicated that the CO2 absorption capacity of the whole Southern Indian Ocean gradually increased during the past 20 years. These findings extend the understanding of the roles of the Southern Indian Ocea

The role played by oceans - not only the Atlantic and Pacific, but also the Indian Ocean - in South American climate variability is one of the topics researched by Marcelo BARREIRO, Head of Atmospheric Sciences at Uruguay's University of the Republic (UDELAR).

Scientists use underwater robots to study India's monsoon.

Dead zones are a global water pollution challenge - but with sustained effort they can come back to life.

Why India needs its fishers to save the vanishing dugongs and their habitat.

Why seagrass is so important to our environment.

New study confirms the oceans are warming rapidly.

Microbes are dispersed widely over the oceans with islands acting as stepping-stones to help transport of land-based organisms.

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

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.

Global climate is regulated by the ocean, which stores, releases, and transports large amounts of mass, heat, carbon, and oxygen. Understanding, monitoring, and predicting the exchanges of these quantities across the ocean's surface, their interactions with the atmosphere, and their horizontal and vertical pathways through the global oceans, are key for advancing fundamental knowledge and improving forecasts and longer-term projections of climate, weather, and ocean ecosystems. The existing global observing system provides immense value for science and society in this regard by supplying the data essential for these advancements. The tropical ocean observing system in particular has been developed over decades, motivated in large part by the far-reaching and complex global impacts of tropical climate variability and change. However, changes in observing needs and priorities, new challenges associated with climate change, and advances in observing technologies demand periodic evaluations to ensure that stakeholders' needs are met. Previous reviews and assessments of the tropical observing system have focused separately on individual basins and their associated observing needs. Here we provide a broader perspective covering the tropical observing system as a whole. Common gaps, needs, and recommendations are identified, and interbasin differences driven by socioeconomic disparities are discussed, building on the concept of an integrated pantropical observing system. Finally, recommendations for improved observations of tropical basin interactions, through oceanic and atmospheric pathways, are presented, emphasizing the benefits that can be achieved through closer interbasin coordination and international partnerships.

Accurate estimation of air-sea fluxes is essential for advancing ocean modeling, observational studies, and understanding air-sea interactions. To address this need, the Indian National Centre for Ocean Information Services (INCOIS) developed and deployed a Flux Reference System (INCOIS-FRS) onboard ORV Sagar Nidhi. This article provides an overview of the system, its components, data acquisition methods, flux computation techniques, and preliminary results. The INCOIS-FRS integrates an Eddy Covariance Flux System (ECFS) and an Automated Weather Station (AWS). The ECFS collects high-frequency (20 Hz) data to directly estimate the latent heat flux (LHF), sensible heat flux (SHF), and momentum flux (τ) using the Eddy Covariance (EC) method. The AWS records meteorological and oceanic variables at 1 Hz, enabling flux estimates using the COARE 3.5 algorithm. A spectrally flat Class-A pyranometer and a pyrgeometer provide climate-grade measurements of downward shortwave and longwave radiation, which, combined with EC-derived SHF and LHF, yield the net heat flux. This article presents preliminary results inferred from data collected by INCOIS-FRS during a cruise in the Arabian Sea from 1-16 July 2023. Data from this system are useful for validating model outputs and satellite observations, refining flux parameterizations, marine boundary layer studies, and improving air-sea interaction models. INCOIS-FRS represents a first step toward equipping more oceanographic platforms, both crewed and uncrewed, with flux reference units. Future plans include expanding such deployments to enhance observational coverage and support research on air-sea fluxes across the Indian Ocean and other regions.