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955 results for “Ocean data”
Data from: Going with the flow: the role of ocean circulation in global marine ecosystems under a changing climate
Ocean warming, acidification, deoxygenation and reduced productivity are widely considered to be the major stressors to ocean ecosystems induced by emissions of CO2. However, an overlooked stressor is the change in ocean circulation in response to climate change. Strong changes in the intensity and position of the western boundary currents have already been observed, and the consequences of such changes for ecosystems are beginning to emerge. In this study, we address climatically induced changes in ocean circulation on a global scale but relevant to propagule dispersal for species inhabiting global shelf ecosystems, using a high resolution global ocean model run under the IPCC RCP 8.5 scenario. The ¼ degree model resolution allows improved regional realism of the ocean circulation beyond that of available CMIP5-class models. We use a Lagrangian approach forced by modelled ocean circulation to simulate the circulation pathways that disperse planktonic life stages. Based on trajectory backtracking, we identify present-day coastal retention, dominant flow and dispersal range for coastal regions at the global scale. Projecting into the future, we identify areas of the strongest projected circulation change and present regional examples with the most significant modifications in their dominant pathways. Climatically-induced changes in ocean circulation should be considered as an additional stressor of marine ecosystems in a similar way to ocean warming or acidification.
Code and data for "Sensitivity of Northern Hemisphere climate to ice-ocean interface heat flux parameterizations"
<p>This repository provides the source code and modeled data for three different ice-ocean heat flux<br> parameterizations of a 1-D idealized model, as well as 3-D climate models including CICE,<br> MPIOM and COSMOS, which are used in a GMD manuscript called "Sensitivity of Northern Hemisphere climate to ice-ocean interface heat flux parameterizations". The NCL-based scripts for plotting the figures are also provided.</p> <p><br> The file all.tar.gz consists of 4 folders as the following:</p> <p>1. 1-D<br> In the 1-D folder one can find the matlab source code for the 1-D idealized model with main.m being the main script and the others sub-scripts for calculating seasonal changes of different forcings, involving the surface albedo (albedo.m), shortwave fluxes (shortwave.m) and all other kinds of fluxes (otherfluxes.m).</p> <p>2. code<br> The code folder provides the source code of the three models used in our study: CICE, MPIOM and COSMOS.</p> <p>The most important code in terms of the ice-ocean heat flux in CICE can be found at code/cice/source/ice_therm_vertical.F90. The switch of the options of the three parameterizations can be achieved by changing the parameter "oceanic_heat" (1 for icebath, 2 for 2eq and 3 for 3eq) in the namelist when running the model.</p> <p>The mpiom folder contains the three different set of MPIOM source code for the three ice-ocean heat flux parameterizations respectively.</p> <p>In cosmos, one could find 4 sub-folders, with the folder echam5 containing the source code for the atmosphere module ECHAM5, and the other 3 folders containing the MPIOM source code incorporating with the three different ice-ocean heat flux parameterizations, similar as the mpiom folder.</p> <p>3. data<br> This folder provides the simulated output from the three models: CICE, MPIOM and COSMOS. Each model folder contains three sub-folders called 2eq, 3eq and icebath, representing the modelled data for the 2eq, 3eq and icebath parameterizations respectively. For CICE, we upload the modeled results of the last 10 years. For MPIOM and COSMOS, as the original data set are too large, here we upload the climatology of the data from the last 100 simulation years. Note that in cosmos, there are some additional variables which are listed seperately, namely the AMOC (amoc.nc), the sea surface pressure (slp.nc) as well as the surface temperature (tsurf.nc). reg.nc contains ocean temperature and salinity which have been interpolated onto a 1x1 regular grid.</p> <p>4. plot_figures<br> This folder gives the scripts based on NCL to plot the figures in the manuscript, with the *.ncl files being the plotting scripts and the *.eps being the figures. <br> All the code, data, scripts can be used by anyone who has interest.</p> <p> </p>
Model data for: Drawdown of atmospheric pCO2 via dynamic particle export stoichiometry in the ocean twilight zone
<p>Understanding the global carbon cycle is key to understanding the climate system. One of the large unknowns is the processes happening in the twilight zone of the ocean. Here, we focus on how elemental stoichiometry of particulate organic matter in the twilight zone affects the strength of the biological pump and atmospheric CO2. We show through modeling that atmospheric CO2 is very sensitive to the change in C:P ratio in the twilight zone. Numerous model studies study the link between the carbon cycle and flexible elemental stoichiometry of organic matter in the surface ocean. However, our model study is unique. It investigates the effects of stoichiometric changes both at the surface and in the subsurface ocean that also involve stoichiometric interaction between phytoplankton and zooplankton.<br> <br> We use a 3D numerical model to illustrate how C:P variability in the twilight zone can significantly modulate the strength of carbon sequestration and atmospheric CO2. We used the biogeochemical model MOPS (Kriest and Oschlies, Geosci. Model Dev., 8, 2929–2957, 2015) coupled to ECCO Transport Matrices.</p> <p>This repository contains model input and output files for each sensitivity run outlined in the paper. The run ID corresponds to different sensitivity run. See README for more details. </p>
Data from: Genomics detects population structure within and between ocean basins in a circumpolar seabird: the white-chinned petrel
<p>The Southern Ocean represents a continuous stretch of circumpolar marine habitat, but the potential physical and ecological drivers of evolutionary genetic differentiation across this vast ecosystem remain unclear. We tested for genetic structure across the full circumpolar range of the white-chinned petrel (<i>Procellaria aequinoctialis</i>) to unravel the potential drivers of population differentiation and test alternative population differentiation hypotheses. Following range-wide comprehensive sampling, we applied genomic (genotyping-by-sequencing or GBS; 60,709 loci) and standard mitochondrial-marker approaches (cytochrome b and 1st domain of control region) to quantify genetic diversity within and among island populations, test for isolation by distance, and quantify the number of genetic clusters using neutral and outlier (non-neutral) loci. Our results supported the multi-region hypothesis, with a range of analyses showing clear three-region genetic population structure, split by ocean basin, within two evolutionary units. The most significant differentiation between these regions confirmed previous work distinguishing New Zealand and nominate subspecies. Although there was little evidence of structure within the island groups of the Indian or Atlantic oceans, a small set of highly-discriminatory outlier loci could assign petrels to ocean basin and potentially to island group, though the latter needs further verification. Genomic data hold the key to revealing substantial regional genetic structure within wide-ranging circumpolar species previously assumed to be panmictic.</p>
Data from: A daily global mesoscale ocean eddy dataset from satellite altimetry
Mesoscale ocean eddies are ubiquitous coherent rotating structures of water with radial scales on the order of 100 kilometers. Eddies play a key role in the transport and mixing of momentum and tracers across the World Ocean. We present a global daily mesoscale ocean eddy dataset that contains ~45 million mesoscale features and 3.3 million eddy trajectories that persist at least two days as identified in the AVISO dataset over a period of 1993–2014. This dataset, along with the open-source eddy identification software, extract eddies with any parameters (minimum size, lifetime, etc.), to study global eddy properties and dynamics, and to empirically estimate the impact eddies have on mass or heat transport. Furthermore, our open-source software may be used to identify mesoscale features in model simulations and compare them to observed features. Finally, this dataset can be used to study the interaction between mesoscale ocean eddies and other components of the Earth System.
Speciation data for "Genesis of a CO2-rich and H2O-depleted atmosphere from the Earth's early global magma ocean"
<p>Here we present the speciation statistics for volatile-bearing pyrolite melts. For computational details and nomenclature, please refer to the manuscript, "Genesis of a CO2-rich and H2O-depleted atmosphere from the Earth’s early global magma ocean" by N.V. Solomatova and R. Caracas.</p> <p>The data is organized by composition and temperature.</p> <p>File names contain the lattice parameter (e.g., a16.0) in Angstroms, indicating that the cell is 16x16x16 Angstroms in size, for example. The corresponding volumes and densities are tabulated in each folder (e.g., "4CO_4000K_densities.dat"). </p> <p>The first column of each *stat.dat file contains the species type. Long species (e.g., Na_1Ca_2Fe_4Mg_30Al_3Si_24O_93C_4) typically represent the silicate melt and short species (e.g., O_1C_1 and O_2C_1) represent the vapor phase. Underscores represent subscripts (e.g., O_2C_1 denotes a CO2 molecule). The second column is the lifetime of the species in femtoseconds. The third column is the percent of the total. The fourth column is the number of elements in each species (e.g., O_1C_1 has 2 elements and O_2C_1 has 3 elements). Note that the majority of the "H_1" species represent free protons within the melt phase.</p>
Data from: Novel and disappearing climates in the global surface ocean from 1800 to 2100
<p>Marine ecosystems are experiencing unprecedented warming and acidification caused by anthropogenic carbon dioxide. For the global sea surface, we quantified the degree that present climates are disappearing and novel climates (without recent analogs) are emerging, spanning from 1800 through different emission scenarios to 2100. We quantified the sea surface environment based on model estimates of carbonate chemistry and temperature. Between 1800 and 2000, no gridpoints on the ocean surface were estimated to have experienced an extreme degree of global disappearance or novelty. In other words, the majority of environmental shifts since 1800 were not novel, which is consistent with evidence that marine species have been able to track shifting environments via dispersal. However, between 2000 and 2100 under Representative Concentrations Pathway (RCP) 4.5 and 8.5 projections, 10–82% of the surface ocean is estimated to experience an extreme degree of global novelty. Additionally, 35–95% of the surface ocean is estimated to experience an extreme degree of global disappearance. These upward estimates of climate novelty and disappearance are larger than those predicted for terrestrial systems. Without mitigation, many species will face rapidly disappearing or novel climates that cannot be outpaced by dispersal and may require evolutionary adaptation to keep pace.</p>
Data from: Large scale patterns of marine diatom richness: drivers and trends in a changing ocean.
Aim Plankton diversity is a pivotal element of marine ecosystem stability and functioning. A major obstacle in the assessment of diversity is the lack of consistency between patterns assessed by molecular and morphological data. This work aims to reconcile the two in a single richness measure, to investigate the environmental drivers affecting such measure, and finally to predict its spatio-temporal patterns. Location & Time period This is a global-scale study, based on data collected within the 2009-2013 interval during the Tara Oceans expedition. Major taxa studied The focus of this study is diatoms. They play an important role in several biogeochemical cycles and within marine food webs, while displaying a high taxonomic and functional richness. Methods We integrate measures of diatom richness across the global ocean using molecular and morphological approaches, giving particular attention to the rare biosphere. We then perform a machine-learning-based analysis of these reconciled patterns to extrapolate diatom richness at the global scale and to identify the main environmental processes governing it. Finally, we model the response of diatom richness to climate change. Results By filtering out 0.3% of the rarest operational taxonomic units, molecular-based richness patterns show the best possible match with the morphological approach. Temperature, phosphate, chlorophyll a and the Lyapunov exponent are the major explainers of these reconciled patterns. Global scale predictions provide a first approximation of the global geography of diatom richness and of the possible impacts of climate change. Main conclusion Our models suggest that diatom richness is controlled by different processes characteristic of distinct environmental scenarios: lateral mixing in highly dynamic regions, and both nutrient availability and temperature elsewhere. We present herein the implications of these processes on richness and how these same implications differ from other diversity indices because of the main component of richness: the rare biosphere.
Figure Data for Oka et al. (2021) "Glacial mode shift of the Atlantic meridional overturning circulation by warming over the Southern Ocean"
<p>Figure Data for Oka et al. (2021) "Glacial mode shift of the Atlantic meridional overturning circulation by warming over the Southern Ocean" </p>
Satellite-retrieved cloud top radiative cooling data in 2014 over global ocean
<p>Satellite-retrieved cloud-top radiative cooling data in 2014 over global ocean, used in a manuscript submitted to GRL (Zheng et al., 2021, GRL).</p>
GFDL-ESM2G Model data and scripts in support of "The deep ocean's role in climate and CO2 sensitivity"
<p>GFDL-ESM2G Model data and analysis scripts in support of the manuscript "The deep ocean's role in climate and CO2 sensitivity" by John Dunne and Lori Sentman submitted to Geophysical Research Letters including results from experiments with progressively shoaled maximum ocean depths of 4000 m to 1000 m in 500 m increments.</p>
Data from: Descriptive multi-agent epidemiology via molecular screening on Atlantic salmon farms in the northeast Pacific Ocean
<p>Rapid expansion of salmon aquaculture has resulted in high-density populations that host diverse infectious agents, for which surveillance and monitoring are critical to disease management. Screening can reveal infection diversity from which disease arises, differential patterns of infection in live and dead fish that are difficult to collect in wild populations, and potential risks associated with agent transmission between wild and farmed hosts. We report results from a multi-year infectious-agent screening program of farmed salmon in British Columbia, Canada, using quantitative PCR to assess presence and load of 58 infective agents (viruses, bacteria, and eukaryotes) in 2931 Atlantic salmon (Salmo salar). Our analysis reveals temporal trends, agent correlations within hosts, and agent-associated mortality signatures. Multiple agents, most notably Tenacibaculum maritimum, were elevated in dead and dying salmon. We also report detections of agents only recently shown to infect farmed salmon in BC (Atlantic salmon calicivirus, Cutthroat trout virus-2), detection in freshwater hatcheries of two marine agents (Kudoa thyrsites and Tenacibaculum maritimum), and detection in the ocean of a freshwater agent (Flavobacterium psychrophilum). Our results provide information for farm managers, regulators, and conservationists, and enable further work to explore patterns of multi-agent infection and farm/wild transmission risk.</p>
Data for contribution of marine phytoplankton and bacteria to ocean alkalinity
<p>The contributions of phytoplankton and bacteria cells to alkalinity (A<sub>T</sub>) were measured in seawater samples obtained from 205 locations including the East Sea, the North Pacific Ocean, the Bering Sea, the Chukchi Sea, and the Arctic Ocean. We attributed the differences in A<sub>T</sub> values measured for unfiltered versus filtered samples to A<sub>T</sub> components contributed by phytoplankton (retained on a 0.7 µm filter) and by phytoplankton and bacteria combined (A<sub>T</sub><sub>-BIO</sub>; retained on a 0.45 µm filter). The A<sub>T</sub><sub>-BIO </sub>values reached 10-19 μmol kg<sup>-1</sup> in the East Sea and the North Pacific Ocean, and progressively decreased to a level of 1 μmol kg<sup>-1 </sup>with distance<sup> </sup>towards the Arctic Ocean. The study shows that the A<sub>T</sub><sub>-BIO </sub>values are non-negligible in coastal and open ocean environments and need to be considered when assessing the accuracy of carbon parameters calculated using the thermodynamic models that use measured A<sub>T</sub> as an input parameter.</p>
An ocean turbulence data reduction scheme for autonomous, vertically profiling floats: datasets
<p>See <a href="https://doi.org/10.5281/zenodo.5719505">https://doi.org/10.5281/zenodo.5719505</a> instead</p>
Implementing Riverine Biogeochemical Inputs in ECCO-Darwin: A Sensitivity Analysis of Terrestrial Fluxes in a Data-Assimilative Global Ocean Biogeochemistry Model
<p>Resolving riverine biogeochemical inputs in ocean biogeochemistry models is pivotal for capturing the spatiotemporal variability of nutrients and carbon in coastal regions and in the global ocean. ECCO-Darwin is a pioneering data-assimilative global-ocean biogeochemistry model, which, to date, has focused on the pelagic zone. In this work, we use an optimized version of ECCO-Darwin to perform a sensitivity analysis to quantify the response of the open ocean and coastal margins to lateral inputs of carbon and nutrients. We generate riverine inputs by combining point-source freshwater discharge from JRA55-do with the Global NEWS 2 watershed model, accounting for lateral inputs from 5171 watersheds worldwide. While adding carbon and nutrients along with freshwater improves biogeochemical skill in river plume regions and coastal waters, the open-ocean response may be overestimated due to an excess of carbon and nutrients advected offshore. This highlights the need for a more nuanced representation of land-to-ocean and nearshore processes for quantifying how global ocean primary production and carbon cycling respond to land-to-ocean inputs.</p>
The effect of past saturation changes on noble gas reconstructions of mean ocean temperature: Model Output Data
<p>This dataset contains model output for the simulations presented in "<em>The effect of past saturation changes on noble gas reconstructions of mean ocean temperature</em>".</p> <p>The NetCDF4 files contain the following variables:</p> <ul> <li>Potential Temperature</li> <li>Salinity</li> <li>Sea-ice area</li> <li>Ar, Kr, Xe, and N<sub>2</sub> concentrations</li> <li>AMOC strength and Northern-Sourced Water fraction (only transient runs)</li> </ul>
Structural data for "Structural and rheological evolution of brittle fault zones in mafic crust: Implications for the strength of oceanic transform faults"
<p>Structural data for "Structural and rheological evolution of brittle fault zones in mafic crust: Implications for the strength of oceanic transform faults"</p>
GPS data set used in the paper "Anelastic response of the Earth's crust underneath the Canary Islands revealed from ocean tide loading observations"
<p>Data set of continuous GPS observations at CVAN site in Gran Canaria (Canary Islands, Spain). The period of observation spans from July 3, 2013 to November 30, 2015. Data was acquired during the execution of the research project GCL2011-25494 of the Spanish Research Agency. </p> <p>This data set belongs to the Research Group ‘Geodesia’ of the University Complutense of Madrid, Spain, and has been used in the paper "Anelastic response of the Earth's crust underneath the Canary Islands revealed from ocean tide loading observations", by Jose Arnoso, Machiel S. Bos, Maite Benavent, Nigel T. Penna, Sergio Sainz-Maza, submitted to Geophysical Journal International, 2022.</p>
The supplementary (hourly output data & computational performance log) for OMARE of the Ocean Dynamics manuscript
<p>The supplementary (hourly output data & computational performance log) for OMARE of the Ocean Dynamics manuscript with the title: Computational performance and scalability Analysis for the flexible ocean Modeling framework of OMARE (Ocean Modeling with Adaptive REsolution).</p> <p>amr_wbc.tar.gz: The hourly output data of core prognostics (u, v, ssh, ts) of experiments X-AMR, X, S for OMARE in TianHe platform, including the picture results (png format).</p> <p>Computational_Performance.zip: The computational performance logs of the M, S, X, L-M-50, M-S-30, M-S-100, S-X-10, for OMARE in ThianHe and IntelCluster platform. The computational performance logs of X-AMR and I/O in TianHe platform.</p>
Multicomponent ocean-bottom seismic data decomposition using separate calibration filters
<p>All relevant pictures in the article</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.