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The dissolved nitrate is one of the major essential nutrients for primary production in the tropical ocean and it is brought to the surface though mixing. The depth of nitracline determines how much of nitrate enters to the upper ocean through mixing. The depth of nitracline is traditionally estimated using nitrate concentrations measured at standard depths that introduces significant error due to interpolation of data. Based nitrate profiles measured at 5 m interval using nitrate sensors onboard Argo, the exact depth of nitracline was derived in the Bay of Bengal that displayed a significant linear relationship with depth of 26°C isotherm (D26). Based on climatological D26, the temporal and spatial variations in the depth of nitracline was estimated for the entire Bay of Bengal. The depth of nitracline varied between 5 and 80 m with large spatial and temporal variability in the Bay of Bengal and it is 5–20 m deeper than simulations of numerical models. The relationship between the depth of nitracline and photic zone integrated primary production indicates that 7.5 ± 3 mgC m−2 d−1 of primary production increases due to shallowing of 1 m of depth of nitracline. Therefore, models seem to be over estimating the photic zone integrated primary production by 5%–25% in the Bay of Bengal. The numerical models may improve the simulation of primary production and carbon cycling by accounting the accurate estimation of depth of nitracline in the model initialization. Plain Language Summary: In the tropical ocean, nitrate mainly controls the primary production and identifying the depth of nitracline, where nitrate concentration was 1 μM from that of surface, is important in simulating primary production by numerical models. All the numerical models are using nutrietns profiles collected at the standard depth and estimated depth of nitracline. Since the data collected at standard depth, and interpolation between depth may result in large error in the computation of nitracline depth. We used high depth resolution nitrate data collected by sensors and estimated nitracline depth and the same compared with modeled data. It was observed that models are estimating shallow nitracline than actual as a result higher biological response is simulated than reality. This exercise would be useful in improving model simulation in future. Key Points: The depth of nitracline is strongly controlled by depth of 20°C isothermDeeper nitracline depth was noticed during spring and shallowers during summerModels estimate shallower nitracline depth by 5–20 m than measured [ABSTRACT FROM AUTHOR]

In this paper we introduce about the marine data archived at Indian National Centre for Ocean Information Services (INCOIS), Ministry of Earth Sciences, India. Heterogeneous data from in situ, remote sensing and ocean models are archived. In-situ ocean observations includes data from Lagrangian as well Eulerian platforms like Argo floats, moored buoys etc, while remote sensing include data from NOAA satellite series, OceanScat etc. The data generated is translated into ocean information services through analysis and modelling. Data is disseminated to users using variety of means like web with GIS features, ERDDAP, Live Access server with facilities to search, visualize and download. [ABSTRACT FROM AUTHOR]

A GIS for ocean data applications named "Ocean Data and Information Systems (ODIS)" was designed and developed. The system is based on the University of Minnesota MapServer, an open source platform for publishing spatial data and interactive mapping applications to the web with MySQL as the backend database server. This paper discusses some of the details of the storage and organization of oceanographic data, methods employed for visualization of parameter plots, and mapping of the data. ODIS is conceived to be an end-to-end system comprising acquisition of data from a variety of heterogeneous ocean platforms, processing, integration, quality control, and web-based dissemination to users for operational and research activities. ODIS provides efficient data management and potential mapping and visualization functions for oceanographic data. [ABSTRACT FROM AUTHOR]

Intense blooms of the heterotrophic dinoflagellate, green Noctiluca scintillans, have been reported annually in the Northern Arabian Sea since the early 2000s. Although not known to produce organic toxins, these blooms are still categorized as a harmful due to their association with massive fish mortalities. Recent work has attributed these blooms to the vertical expansion of the oxygen minimum zone, driven by cultural eutrophication from major coastal cities in western India. As diatoms are preferred prey of green Noctiluca scintillans, more frequent blooms of this mixotroph will likely impact the productivity of important fisheries in the region. The present study uses a satellite algorithm to determine the distribution of both diatom and green Noctiluca blooms in the Northeastern Arabian Sea from 2009 to 2016. The results from shipboard microscopy of phytoplankton community composition were used to validate the satellite estimates. The satellite algorithm showed 76% accuracy for detection of green Noctiluca and 92% for diatoms. Shipboard measurements and data from biogeochemical-Argo floats were used to assess the relationship between oxygen concentrations and green Noctiluca blooms in the Northeastern Arabian Sea. Regardless of the presence of a Noctiluca bloom, the dissolved oxygen in the photic zone was always >70% saturated, with an average oxygen saturation >90%. The variability in the relative abundance of diatoms and green Noctiluca is not correlated with changes in oxygen concentration. These findings provide no evidence that cultural eutrophication has contributed to the decadal scale shifts in plankton composition in the Northeastern Arabian Sea oceanic waters. Conversely, the climatic warming of surface waters would have intensified stratification, thereby reducing net nutrient flux to the photic zone and decreasing silicate to nitrate ratios (Si:N); both factors that could increase the competitive advantage of the mixotroph, green Noctiluca, over diatoms. If so, the decadal-scale trajectory of phytoplankton community composition in the Northeastern Arabian Sea may be a harbinger of future climate-driven change in other productive oceanic systems., (Copyright © 2018 Elsevier B.V. All rights reserved.)

A new method of identifying anomalous oceanic temperature and salinity (T/S) data from Argo profiling floats is proposed. The proposed method uses World Ocean Database 2013 climatology to classify good against anomalous data by using convex hulls. An n-sided polygon (convex hull) with least area encompassing all the climatological points is constructed using Jarvis March algorithm. Subsequently Points In Polygon (PIP) principle implemented using ray casting algorithm is used to classify the T/S data as within or without acceptable bounds. It is observed that various types of anomalies associated with the oceanographic data viz., spikes, bias, sensor drifts etc can be identified using this method. Though demonstrated for Argo data it can be applied to any oceanographic data. •The patterns of variation of the parameter (temperature or salinity) corresponding to a particular depth, along the longitude or latitude can be used to build convex hulls.•This method can be effectively used for quality control by building Convex hulls for various observed depths corresponding to biogeochemical data which are sparsely observed.•This method has the advantage of treating the bulk of oceanographic in situ data in a single iteration which filters out anomalous data.