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234 results for “Global Ocean”
Seamless Projections of Global Storm Surge and Ocean Waves under a Warming Climate
<p>This is dataset of global ocean waves and storm surges used in the paper "Seamless Projections of Global Storm Surge and Ocean Waves under a Warming Climate" by Shimura et al. (2022, Geophysical Research Letters).</p> <p>AnnualMaxSSH_SeamlessExperiment.nc contains the global annual maximum storm surge in the seamless experiment.</p> <p>AnnualMaxHs_SeamlessExperiment.nc contains the global annual maximum significant wave heights in the seamless experiment.</p> <p>AnnualMaxHs_TimesliceExperiment_Historical.nc contains the global annual maximum significant wave heights in the time-slice experiment (the historical climate simulations).</p> <p>AnnualMaxHs_TimesliceExperiment_ProjectedFuture.nc contains the global annual maximum significant wave heights in the time-slice experiment (the projected future climate simulations).</p>
Constraints on the cycling of iron isotopes from a global ocean model
<p>Annual netcdf output files of NEMO/PISCES Fe isotope model experiments on the ORCA2 grid, as described and discussed in König, et al., <em>Constraints on the cycling of iron isotopes from a global ocean model</em>, Global Biogeochemical Cycles, 2021.</p>
CESM experiments for "Oceanic repeaters boost the global climatic impact of the Tibetan Plateau"
<p>This dataset is the outputs and codes of CESM experiments performed by the authors for their study titled, "Oceanic repeaters boost the global climatic impact of the Tibetan Plateau", which was submitted to Science Bulletin. There were six CESM experiments, namely amip-hist, amip-TIP-nosh, amip-TIP-alb0.5, amip-TIP-sh0.5, cmip-hist, and cmip-TIP-sh0.5. The CESM model (version 2.1.3) was provided by NCAR/UCAR. In all the experiments, hist (historical) experiments were control runs, whereas the TIP (Tibetan–Iranian Plateau coupling system) -labeled experiments were sensitivity runs.</p>
Sensitivity of the global ocean carbon sink to the ocean skin in a climate model : IPSL-CM6 dataset
<p>Daily outputs of 2000-2014 historical run with IPSL-CM6 (Boucher et al. 2020) with Bellenger et al. (2017) parameterization of the ocean skin (Bellenger et al. 2023)</p> <p>CM62-OSCO2-hist-2000-2014-1D.nc contains air-sea CO2 fluxes:</p> <p>F_CTL : Prognostic classical bulk flux from the control (CTL) run</p> <p>F_MBL_CTL : Diagnostic flux using the interactive ocean skin and the equilibrium model (Woolf et al. 2016) from the CTL run</p> <p>F_TBL_CTL : Diagnostic flux using the interactive ocean skin and the rapid model (Woolf et al. 2016) from the CTL run</p> <p>F_Wat_CTL : Diagnostic flux using a uniform ocean skin (Watson et al. 2020) from the CTL run</p> <p>F_MBL_CPL: Prognostic flux using the interactive ocean skin and the equilibrium model from the coupled (CPL) run</p> <p>CM62-OSCO2-hist-2000-2014-1D_oceanskin.nc contains ocean skin related outputs:</p> <p>tos / sos : Temperature / salinity of the ocean model's first level</p> <p>t_int / s_int : Temperature /salinity at the interface</p> <p>t_mbl / s_mbl : Temperature /salinity at the base of the Mass Boundary Layer (MBL)</p> <p>t_tbl : Temperature at the base of the Thermal Boundary Layer (TBL)</p> <p><em>Bellenger H., K. Drushka, W. E. Asher, G. Reverdin, M. Katsumata, and M. Watanabe: Extension of the prognostic model of sea surface temperature to rain-induced cool and fresh lenses, J. Geophys. Res. Oceans, 122, 484–507</em></p> <p>Bellenger, H., Bopp, L., Ethé, C., Ho, D., Duvel, J. P., Flavoni, S., Guez L., T. Kataoka, X. Perrot, L. Parc, and M. Watanabe (2023). Sensitivity of the global ocean carbon sink to the ocean skin in a climate model. Journal of Geophysical Research : Oceans, 128, e2022JC019479. <a href="https://doi.org/10.1029/2022JC019479">https://doi.org/10.1029/2022JC019479</a></p> <p><em>Boucher, O., and coauthors, 2020: Presentation and evaluation of the IPSL-CM6A-LR climate model, Journal of Advances in Modeling Earth System, 12, e2019MS002010, doi:</em><a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2019MS002010"><em>10.1029/2019MS002010</em></a></p> <p><em>Watson A. J., U. Schuster, J. D. Shutler, T. Holding, I. G. C. Ashton, P. Landschützer, D. K. Woolf, and L. Goddijn-Murphy, 2020: Revised estimates of ocean-atmosphere CO<sub>2</sub> flux are consistent with carbon inventory, Nature Comm., 11:4422, https://doi.org/10.1038/s41467-020-18203-3</em></p> <p><em>Woolf, D. K., P. E. Land, J. D. Shutler, L. M. Goddijn-Murphy, and C. J. Donlon, 2016: On the calculation of air-sea fluxes of CO2 in the presence of temperature and salinity gradients, J. Geophys. Res. Oceans, 121, 1229-1248.</em></p> <p> </p> <p> </p>
Dataset associated with "Effect of sampling bias on global estimates of ocean carbon export"
<p>Dataset and Matlab code for plotting the figures in the manuscript "Effect of sampling bias on global estimates of ocean carbon export", submitted to Geophysical Research Letters.</p>
Datasets: RECCAP2 A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
<p>Processed data and scripts to produce figures for the contribution to RECCAP2: "A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes", published 2023.</p>
Environmental drivers and distribution of cold-water corals in the global ocean - Habitat Suitability Models
<p><strong>Publication Abstract</strong></p> <p>Species distribution models (SDMs) are useful tools for identifying the distribution of marine species in data limited environments. Outputs from SDMs have been used to identify areas for spatial management, analyzing trawl closures, quantitatively measuring the risk of bottom trawling, and evaluating protected areas for improving conservation management. Cold-water corals are globally distributed habitat forming organisms that are vulnerable to anthropogenic impacts and climate change, but data deficiency remains an ongoing issue for the effective spatial management of these important ecosystem engineers. In this study, we constructed 11 environmental seabed variables at 500m resolution based on the latest multi-depth global datasets and high-resolution bathymetry. Ensemble modeling methods were used to predict the global habitat suitability for ten widespread cold-water coral species, including six reef Scleractinian framework-forming species and four large gorgonian species. Temperature, depth, salinity, terrain ruggedness index, carbonate saturation state and chlorophyll were the most important factors in determining the global distributions of these species. The Scleractinian species <em>Madrepora oculata</em> showed the widest niche breadth, whilst most other species demonstrated somewhat limited niche breadth. The shallowest study species, <em>Oculina varicosa</em>, had the most distinctive niche of the group. The model outputs from this study represent the highest resolution global predictions for these species to date and are valuable in aiding the management, conservation and continued research into cold-water coral species.</p> <p><strong>Data description</strong></p> <p>These datasets (compressed Zip archives) contain the habitat suitability model outputs generated for the publication Tong et al., (2023) doi: 10.3389/fmars.2023.1217851, please refer to the manuscript for methodological details. These files are provided in an ArcGIS compatible TIFF format that is readable by various GIS packages and can be imported to R. </p> <p>AA.zip = <em>Acanella arbuscula</em><br> DP.zip = <em>Desmophyllum pertusum</em> (former and now unaccepted synonym <em>Lophelia pertusa</em>)<br> ER.zip = <em>Enallopsammia rostrata</em><br> GD.zip = <em>Goniocorella dumosa</em><br> MO.zip = <em>Madrepora oculata</em><br> OV.zip = <em>Oculina varicosa</em><br> PA.zip = <em>Paragorgia arborea</em><br> PP.zip = <em>Paramuricea placomus</em><br> PR.zip = <em>Primnoa resedaeformis</em><br> SV.zip = <em>Solenosmilia variabilis</em></p>
Environmental drivers and distribution of cold-water corals in the global ocean - Environmental Data Layers
<p><strong>Publication Abstract</strong></p> <p>Species distribution models (SDMs) are useful tools for identifying the distribution of marine species in data limited environments. Outputs from SDMs have been used to identify areas for spatial management, analyzing trawl closures, quantitatively measuring the risk of bottom trawling, and evaluating protected areas for improving conservation management. Cold-water corals are globally distributed habitat forming organisms that are vulnerable to anthropogenic impacts and climate change, but data deficiency remains an ongoing issue for the effective spatial management of these important ecosystem engineers. In this study, we constructed 11 environmental seabed variables at 500m resolution based on the latest multi-depth global datasets and high-resolution bathymetry. Ensemble modeling methods were used to predict the global habitat suitability for ten widespread cold-water coral species, including six reef Scleractinian framework-forming species and four large gorgonian species. Temperature, depth, salinity, terrain ruggedness index, carbonate saturation state and chlorophyll were the most important factors in determining the global distributions of these species. The Scleractinian species <em>Madrepora oculata</em> showed the widest niche breadth, whilst most other species demonstrated somewhat limited niche breadth. The shallowest study species, <em>Oculina varicosa</em>, had the most distinctive niche of the group. The model outputs from this study represent the highest resolution global predictions for these species to date and are valuable in aiding the management, conservation and continued research into cold-water coral species.</p> <p><strong>Data description</strong></p> <p>These datasets (compressed Zip archives) contain the ten global environmental layers that were generated for the publication Tong et al., (2023) doi: 10.3389/fmars.2023.1217851, using a trilinear interpolation approach based on the 500m GEBCO bathymetric data product. These layers are representations of seafloor conditions. Please refer to the manuscript for methodological details. These files are provided in an ArcGIS compatible TIFF format that is readable by various GIS packages and can be imported to R. </p> <p>aoxu.zip = Apparrent Oxygen Utilization<br> diso2.zip = Dissolved Oxygen<br> nit.zip = Nitrate<br> oa.zip = Omega Aragonite<br> oc.zip = Omega Calcite<br> ph.zip = pH<br> phos.zip = Phosphate<br> sal.zip = Salinity<br> sil.zip = Silicate<br> temp.zip = Temperature</p>
Database of nitrification and nitrifiers in the global ocean
<p>This is a dataset compiling the observations of nitrification rates and nitrifiers' abundance in the global ocean. A template for scientists who want to add their data to the database is also provided. </p> <p>Tang, W., Ward, B. B., Beman, M., Bristow, L., Clark, D., Fawcett, S., Frey, C., Fripiat, F., Herndl, G. J., Mdutyana, M., Paulot, F., Peng, X., Santoro, A. E., Shiozaki, T., Sintes, E., Stock, C., Sun, X., Wan, X. S., Xu, M. N., and Zhang, Y.: Database of nitrification and nitrifiers in the global ocean, Earth Syst. Sci. Data, 15, 5039–5077, https://doi.org/10.5194/essd-15-5039-2023, 2023.</p>
Mind the Gap: Comparing Exploration Effort with Global Biodiversity Patterns and Climate Projections to Determine Ocean Areas with Greatest Exploration Needs- Dive metadata
<p>Meta data for deep submergence dive locations associated with "Mind the Gap: Comparing Exploration Effort with Global Biodiversity Patterns and Climate Projections to Determine Ocean Areas with Greatest Exploration Needs" published in Frontier of Marine Science 2023. </p>
Protecting the global ocean for biodiversity, food and climate
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Global Ocean particulate organic phosphorus, carbon, oxygen for respiration, and nitrogen (GO-POPCORN) data from Bio-GO-SHIP cruises
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Integrating climate adaptation and biodiversity conservation in the global ocean
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Data from: The Tara Oceans voyage reveals global diversity and distribution patterns of marine planktonic ciliates
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Data from: Explaining the ocean’s richest biodiversity hotspot and global patterns of fish diversity
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Data from: Combining mesocosms with models to unravel the effects of global warming and ocean acidification on a temperate marine ecosystem
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The vulnerability of shellfish aquaculture to climate change and ocean acidification– a global assessment
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A hierarchy of global ocean models coupled to CESM1
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CNR global observation-based OMEGA3D quasi-geostrophic vertical and horizontal ocean currents (1993-2018): validation subset.
<p>A subset of the Global Ocean Multi Observations OMEGA3D product is provided here for comparison with independent in situ observations and model data. OMEGA3D product has been developed by the Consiglio Nazionale delle Ricerche in the framework of the Copernicus Monitoring Environment Marine Service (https://doi.org/10.25423/cmcc/multiobs_glo_phy_w_rep_015_007). It consists of 26 year of 3D quasi-geostrophic vertical and horizontal ocean currents (January 1993-December 2018) provided over a regular grid at 1/4° horizontal resolution, with 75 non-uniformly spaced vertical levels between the surface and 1500 m depth. The subset provided here includes horizontal velocities at 15 m and 1000 m depths (that can be used for validation with independent velocity estimates from SVP drifters and Argo floats displacements, respectively) and vertical velocities at 100 m depth (for comparison with model re-analyses). OMEGA3D product is delivered with a weekly sampling (representative of each Wednesday). The velocities are obtained by solving a Q-vector formulation of the Omega equation that explicitly considers the effect of both geostrophic advection and upper layer turbulent mixing as described by KPP parameterization. Omega forcings are estimated from the CMEMS observation-based ARMOR3D temperature and salinity multi-year data and ERA-Interim surface fluxes. </p>
Impact of horizontal resolution on global ocean-sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)
<p>Datasets for the Geoscientific Model Development publication: "Impact of horizontal resolution on global ocean-sea-ice model simulations based on the experimental protocols of the Ocean Model Intercomparison Project phase 2 (OMIP-2)"</p> <p>Abstract: This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea-ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958-2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (~1º) to eddy-resolving (~0.1º) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the 20 extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and Antarctic Circumpolar Current – are 25 significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve’’ most of these features, the improvements in temperature or salinity are inconsistent among the different model families and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.</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.