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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.

It sounds like a bad sci-fi plot: a fleet of 'bio robots' are let loose in the world's third largest ocean to study its physical and biological makeup.

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.