scholarly journals Quantification and Trend Analysis of Multidecadal Global Dissolved Oxygen Changes

2021 ◽  
Author(s):  
Ayush Agrawal ◽  
James Swift
Keyword(s):  
Dissolved Oxygen ◽  
Water Column ◽  
Large Scale ◽  
Average Rate ◽  
Biogeochemical Cycles ◽  
Global Ocean ◽  
Climate Fluctuations ◽  
Ocean Productivity ◽  
Using Data ◽  
Thick Layers

Abstract Previous studies have found there to be measurable deoxygenation in regions of the world’s oceans, with changes linked to biogeochemical cycles, changes in ocean productivity, and climate fluctuations. Here, we investigated multidecadal large-scale dissolved oxygen trends in the principal basins of the Atlantic, Pacific, and Indian Oceans using data from WOCE, CLIVAR, and GO-SHIP cruises, representing some of the highest quality available water column data. We differenced spatially coincident older and more recent data, averaged differences in geographic subregions, and integrated results on 500-dbar thick layers from 500 dbar to 3500 dbar, with bottom levels extending to 6000 dbar. Overall, we found a deoxygenation below 500 dbar across all major basins at a global average rate of -0.06 µmol kg−1 year−1, with important variations between regions and layers. Our research demonstrates a deoxygenation trend coincident with the global ocean warming and increased stratification trends documented in other studies.

The Norwegian node for the European Multidisciplinary Seafloor and water column Observatory

2020 ◽  
Author(s):  
Thibaut Barreyre ◽  
Ilker Fer ◽  
Bénédicte Ferré
Keyword(s):  
Water Column ◽  
Ocean Circulation ◽  
Large Scale ◽  
Water Mass ◽  
Critical Role ◽  
Meridional Overturning Circulation ◽  
The Arctic ◽  
Global Ocean ◽  
Fram Strait ◽  
Nordic Seas

<p>NorEMSO is a coordinated, large-scale deep-ocean observation facility to establish the Norwegian node for the European Multidisciplinary Seafloor and water column Observatory (EMSO). The project aims to explore the under-sampled Nordic Seas to gain a better understanding of the critical role that they play in our climate system and global ocean circulation. An overarching scientific objective is to better understand the drivers for the temporal and spatial changes of water mass transformations, ocean circulation, acidification and thermo-chemical exchanges at the seafloor in the Nordic Seas, and to contribute to improvement of models and forecasting by producing and making available high quality, near real time data. NorEMSO will achieve this by combining expansion of existing and establishment of new observatory network infrastructure, as well as its coordination and integration into EMSO.</p><p>NorEMSO comprises of three main components: moored observatories, gliders, and seafloor and water column observatory at the Mohn Ridge (EMSO-Mohn).</p><p>Moored observation systems include an array of four moored observatories located at key positions in the Nordic Seas (Svinøy, Station M, South Cape, and central Fram Strait).</p><p>Gliders will be operated along five transects across both the Norwegian and the Greenland Seas to monitor circulation and water mass properties at those key locations. Transects in the Norwegian and Lofoten basins will focus on monitoring the Norwegian Atlantic Current, and a transect in Fram Strait will monitor properties and variability in the return Atlantic Water along the Polar Front in the northern Nordic Seas. In addition, transects in the Greenland and Iceland Seas will address the water mass transformation processes through wintertime open ocean convection, and the southbound transport of surface water from the Arctic Ocean and dense water that feeds the lower limb of the Atlantic Meridional Overturning Circulation in the East Greenland Current.</p><p>EMSO-Mohn will establish, at the newly discovered hydrothermal site on the Mohn Ridge, a fixed-point seabed-water-column-coupled and wireless observatory with a multidisciplinary approach – from geophysics and physical oceanography to ecology and microbiology. It is primarily directed at understanding hydrothermal fluxes and associated hydrothermal plume dynamics in the water column and how it disperses in an oceanographic front over the Mohn Ridge.</p><p>Following EMSO philosophy, NorEMSO will provide data and platforms to a large and diverse group of users, from scientists and industries to institutions and policy makers. The observations will serve climate research, ocean circulation understanding, numerical operational models, design of environmental policies, and education.</p>

scholarly journals Nitrogen isotopic constraints on nutrient transport to the upper ocean

2021 ◽  
Author(s):  
François Fripiat ◽  
Alfredo Martínez-García ◽  
Dario Marconi ◽  
Sarah E. Fawcett ◽  
Sebastian H. Kopf ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Ocean Circulation ◽  
Large Scale ◽  
Nutrient Transport ◽  
Deep Ocean ◽  
Global Ocean ◽  
Upper Ocean ◽  
Advective Flow ◽  
The North ◽  
Ocean Productivity

AbstractOcean circulation supplies the surface ocean with the nutrients that fuel global ocean productivity. However, the mechanisms and rates of water and nutrient transport from the deep ocean to the upper ocean are poorly known. Here, we use the nitrogen isotopic composition of nitrate to place observational constraints on nutrient transport from the Southern Ocean surface into the global pycnocline (roughly the upper 1.2 km), as opposed to directly from the deep ocean. We estimate that 62 ± 5% of the pycnocline nitrate and phosphate originate from the Southern Ocean. Mixing, as opposed to advection, accounts for most of the gross nutrient input to the pycnocline. However, in net, mixing carries nutrients away from the pycnocline. Despite the quantitative dominance of mixing in the gross nutrient transport, the nutrient richness of the pycnocline relies on the large-scale advective flow, through which nutrient-rich water is converted to nutrient-poor surface water that eventually flows to the North Atlantic.

scholarly journals Temperature and dissolved oxygen stratification in the lake Rudrasagar: Preliminary investigations

2014 ◽  
Vol 2 (1) ◽  
Author(s):  
Mihir Pal Pal ◽  
Nihar R. Samal ◽  
Pankaj k. Roy Roy ◽  
Malabika B. Roy
Keyword(s):  
Dissolved Oxygen ◽  
Water Temperature ◽  
Water Column ◽  
Large Scale ◽  
Coupled Model ◽  
Aquatic Organisms ◽  
Life Forms ◽  
Health Condition ◽  
Natural Lake ◽  
The Impact

Temperature drives the major physico-chemical and biological actions in inland water bodies. The higher the water temperature, the greater the biogeochemical activity influenced by the environmental intrinsic and extrinsic parameters. Temperature also controls the dynamics of sustainability of various aquatic organisms that live in lakes and reservoirs, though higher life forms, such as fish, insects, zooplankton, phytoplankton, and other aquatic species all have a recommended temperature variety. The increase in water temperature due to the increase in atmospheric air temperature results in lake water column stratification and the dissolved oxygen level variation in aquatic systems are greatly affected. The vertical distributions of dissolved oxygen in the water column are highly dependent due to change in vertical temperature gradient. In the present paper, an effort has been made to investigate the impact of temperature stratification on dissolved oxygen variability in the Rudrasagar, a natural lake in western Tripura. The changes in dissolved oxygen distribution in this natural lake will give us an idea of regional lake health condition and will also establish the need of further large scale research concerning the development of a biophysical-coupled model.   Keywords: Thermal stratification, Dissolved Oxygen, Thermocline, Rudrasagar Lake, Hypolimnion

Student Perceptions of Community: A Different Perspective

NASPA Journal ◽  
1998 ◽  
Vol 35 (4) ◽  
Author(s):  
Jackie Clark ◽  
Joan Hirt
Keyword(s):  
Student Perceptions ◽  
Large Scale ◽  
Research University ◽  
Small Scale ◽  
Social Environments ◽  
Common Assumption ◽  
Small Communities ◽  
Public Research University ◽  
The Common ◽  
Using Data

The creation of small communities has been proposed as a way of enhancing the educational experience of students at large institutions. Using data from a survey of students living in large and small residences at a public research university, this study does not support the common assumption that small-scale social environments are more conducive to positive community life than large-scale social environments.

DESIGN AND IMPLEMENTATION OF THE OCEANOGRAPHIC MODELING AND OBSERVATION NETWORK (REMO) FOR PHYSICAL OCEANOGRAPHY STUDIES AND OCEAN FORECASTING

2014 ◽  
Vol 31 (2) ◽  
Author(s):  
Jose Antonio Moreira Lima
Keyword(s):  
Atlantic Ocean ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Integrated Approach ◽  
Sea Surface ◽  
Global Ocean ◽  
Height Anomaly ◽  
The North ◽  
Observation Network ◽  
Ocean Forecasting

This paper is concerned with the planning, implementation and some results of the Oceanographic Modeling and Observation Network, named REMO, for Brazilian regional waters. Ocean forecasting has been an important scientific issue over the last decade due to studies related to climate change as well as applications related to short-range oceanic forecasts. The South Atlantic Ocean has a deficit of oceanographic measurements when compared to other ocean basins such as the North Atlantic Ocean and the North Pacific Ocean. It is a challenge to design an ocean forecasting system for a region with poor observational coverage of in-situ data. Fortunately, most ocean forecasting systems heavily rely on the assimilation of surface fields such as sea surface height anomaly (SSHA) or sea surface temperature (SST), acquired by environmental satellites, that can accurately provide information that constrain major surface current systems and their mesoscale activity. An integrated approach is proposed here in which the large scale circulation in the Atlantic Ocean is modeled in a first step, and gradually nested into higher resolution regional models that are able to resolve important processes such as the Brazil Current and associated mesoscale variability, continental shelf waves, local and remote wind forcing, and others. This article presents the overall strategy to develop the models using a network of Brazilian institutions and their related expertise along with international collaboration. This work has some similarity with goals of the international project Global Ocean Data Assimilation Experiment OceanView (GODAE OceanView).

scholarly journals Modeling Fused Filament Fabrication using Artificial Neural Networks

2021 ◽  
Author(s):  
Paul Oehlmann ◽  
Paul Osswald ◽  
Juan Camilo Blanco ◽  
Martin Friedrich ◽  
Dominik Rietzel ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Cost Effective ◽  
Print Quality ◽  
Ann Model ◽  
Production Environment ◽  
Fused Filament Fabrication ◽  
Artificial Neural ◽  
Using Data ◽  
Artificial Neural Network Ann

AbstractWith industries pushing towards digitalized production, adaption to expectations and increasing requirements for modern applications, has brought additive manufacturing (AM) to the forefront of Industry 4.0. In fact, AM is a main accelerator for digital production with its possibilities in structural design, such as topology optimization, production flexibility, customization, product development, to name a few. Fused Filament Fabrication (FFF) is a widespread and practical tool for rapid prototyping that also demonstrates the importance of AM technologies through its accessibility to the general public by creating cost effective desktop solutions. An increasing integration of systems in an intelligent production environment also enables the generation of large-scale data to be used for process monitoring and process control. Deep learning as a form of artificial intelligence (AI) and more specifically, a method of machine learning (ML) is ideal for handling big data. This study uses a trained artificial neural network (ANN) model as a digital shadow to predict the force within the nozzle of an FFF printer using filament speed and nozzle temperatures as input data. After the ANN model was tested using data from a theoretical model it was implemented to predict the behavior using real-time printer data. For this purpose, an FFF printer was equipped with sensors that collect real time printer data during the printing process. The ANN model reflected the kinematics of melting and flow predicted by models currently available for various speeds of printing. The model allows for a deeper understanding of the influencing process parameters which ultimately results in the determination of the optimum combination of process speed and print quality.

scholarly journals Air-Sea Interactions over Eddies in the Brazil-Malvinas Confluence

2021 ◽  
Vol 13 (7) ◽  
pp. 1335
Author(s):  
Ronald Souza ◽  
Luciano Pezzi ◽  
Sebastiaan Swart ◽  
Fabrício Oliveira ◽  
Marcelo Santini
Keyword(s):  
Latent Heat ◽  
Large Scale ◽  
Surface Wind ◽  
Heat Fluxes ◽  
Lower Atmosphere ◽  
Meteorological Variables ◽  
Global Ocean ◽  
Study Region ◽  
Cold Core

The Brazil–Malvinas Confluence (BMC) is one of the most dynamical regions of the global ocean. Its variability is dominated by the mesoscale, mainly expressed by the presence of meanders and eddies, which are understood to be local regulators of air-sea interaction processes. The objective of this work is to study the local modulation of air-sea interaction variables by the presence of either a warm (ED1) and a cold core (ED2) eddy, present in the BMC, during September to November 2013. The translation and lifespans of both eddies were determined using satellite-derived sea level anomaly (SLA) data. Time series of satellite-derived surface wind data, as well as these and other meteorological variables, retrieved from ERA5 reanalysis at the eddies’ successive positions in time, allowed us to investigate the temporal modulation of the lower atmosphere by the eddies’ presence along their translation and lifespan. The reanalysis data indicate a mean increase of 78% in sensible and 55% in latent heat fluxes along the warm eddy trajectory in comparison to the surrounding ocean of the study region. Over the cold core eddy, on the other hand, we noticed a mean reduction of 49% and 25% in sensible and latent heat fluxes, respectively, compared to the adjacent ocean. Additionally, a field campaign observed both eddies and the lower atmosphere from ship-borne observations before, during and after crossing both eddies in the study region during October 2013. The presence of the eddies was imprinted on several surface meteorological variables depending on the sea surface temperature (SST) in the eddy cores. In situ oceanographic and meteorological data, together with high frequency micrometeorological data, were also used here to demonstrate that the local, rather than the large scale forcing of the eddies on the atmosphere above, is, as expected, the principal driver of air-sea interaction when transient atmospheric systems are stable (not actively varying) in the study region. We also make use of the in situ data to show the differences (biases) between bulk heat flux estimates (used on atmospheric reanalysis products) and eddy covariance measurements (taken as “sea truth”) of both sensible and latent heat fluxes. The findings demonstrate the importance of short-term changes (minutes to hours) in both the atmosphere and the ocean in contributing to these biases. We conclude by emphasizing the importance of the mesoscale oceanographic structures in the BMC on impacting local air-sea heat fluxes and the marine atmospheric boundary layer stability, especially under large scale, high-pressure atmospheric conditions.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

scholarly journals Assisting scalable diagnosis automatically via CT images in the combat against COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bohan Liu ◽  
Pan Liu ◽  
Lutao Dai ◽  
Yanlin Yang ◽  
Peng Xie ◽  
...  
Keyword(s):  
Large Scale ◽  
Area Under The Curve ◽  
Independent Set ◽  
Reference Method ◽  
Ct Images ◽  
Loss Of Life ◽  
Case Identification ◽  
Reverse Transcription Pcr ◽  
Using Data

AbstractThe pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

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