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Dataset results
81 results for “ocean simulation”
Brightness Temperature Spectra 400-1200 cm**-1 from satellite METEOR-29 instrument SI-1 in February 1979 along with radiative transfer simulations from 4 different reanalyses, clear scenes only over ocean
<p>This dataset is published in support of a tentative journal publication in a peer-reviewed journal. The full data record is scheduled for release under DOI:10.15770/EUM_SEC_CLM_0086</p>
Simulated Warming Hole in Paleo-Pacific Oceans
<p>Data generated in this study are archived here.</p>
Evaluation of multi-season convection permitting atmosphere - mixed layer ocean simulations of the Maritime Continent.
<p>Supporting data for figures in GMD draft paper: Evaluation of multi-season convection permitting atmosphere - mixed layer ocean simulations of the Maritime Continent.</p>
Contrasting carbon dioxide removal potential and nutrient feedbacks of simulated ocean alkalinity enhancement and macroalgae afforestation
<p>PISCES model outputs supporting the associated publication.</p> <p>Files are for the following simulations: historical control (CTL), OAE without nutrient addition (OAE), OAE with nutrient addition (OAE_Fe_Si), macroalgae afforestation without nutrient feedbacks (MACRO) and macroalgae afforestation with nutrient feedbacks (MACRO_N_P). The following outputs are provided at monthly resolution: air-sea carbon flux (Cflx), export flux at 100m (EPC100) and depth integrated net primary production of phytoplankton (INTPP). In addition masks of the regions of OAE (mask_OAE) and macroalgae afforestation (mask_MACRO) are provided. All files have been regridded from the original eORCA025 grid to a regular 360x180 degree grid.</p>
NICOCO simulation data for the article "Diagnostic method for atmosphere–ocean coupling over tropical oceans at the sub-seasonal timescale"
<p>This data set includes data from an 8-year integration on the atmosphere-ocean coupled model NICOCO from 1 January 2010 to 31 December 2017. All outputs are daily averages on 1 x 1 degrees resolution. Output variables are sea surface temperature (K) and column water vapor (kg m-2). </p>
Data from: Wind-driven emission of marine ice nucleating particles in the Scripps Ocean-Atmosphere Research Simulator (SOARS)
Open the record for dataset details and reuse information.
Data from: The Relationship between the Southern Ocean and the Eastern tropical Pacific in unforced and forced climate model simulations
Open the record for dataset details and reuse information.
Numerical simulation of cool hydrothermal processes in the upper volcanic crust beneath a marine sediment pond: North Pond, North Atlantic Ocean
Open the record for dataset details and reuse information.
Supporting Data for "A partial coupling method to isolate the roles of ocean and atmosphere in coupled climate simulations"
<p>Supporting data for "A partial coupling method to isolate the roles of the atmosphere and ocean in coupled climate simulations", submitted to Journal of Advances in modelling Earth system</p> <p>Monthly averaged variables for the 100 and 150 year fully coupled (b.e11.B1850C5CN.f09_g16.abrupt4xCO2.full.POP.100101_110012.nc) and partially coupled (b.e11.B1850C5CN.f09_g16.abrupt4xCO2.partial.POP.100101_115012.nc) abrupt CO2 quadrupling simulations and 40 yr ocean-driven partially coupled simulation (b.e11.B1850C5CN.f09_g16.prescribed.partial.POP.100101_115012.nc)</p> <p>Control simulation data is available on the NCAR HPSS /CCSM/csm/b.e11.B1850C5CN.f09_g16.005</p>
Model code and output of CSIBv4 pan-Arctic sea ice-ocean DMS simulation
<p>here i deposit the model source code and output of the manuscript "Spatio-temporal variability in modelled bottom-ice and sea-surface dimethylsulfide concentrations and fluxes in the Arctic during 1979-2015" by Hayashida et al. (2020).</p> <p><strong>See "readme.txt" for information.</strong></p> <p>For question, contact Hakase Hayashida.</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>
Supplementary Material to "Comparison of equilibrium climate sensitivity estimates from slab ocean, 150-year, and longer simulations"
<p>This is supplementary data for Dunne, J. P., et al. (2020). Comparison of equilibrium climate sensitivity estimates from slab ocean, 150-year, and longer simulations. Geophysical Research Letters. 2020GL088852R. Data in this repository can be unpacked and the files are in the form- NetCDF and matlab files, along with a README. </p> <p>Model data for global average values of net top of the atmosphere radiative balance (W m-2) and 2m air temperature (degrees celsius) for preindustrial control and 4x abrupt CO2 simulations for a variety of models used in LongRunMIP, CMIP5, and CMIP6, as well as scripts used to calculate equilibrium climate sensitivity from these simulations. </p> <p> </p>
CESM1.2 simulation output for: The role of westerly wind bursts during different seasons versus ocean heat recharge in the development of extreme El Niño in a climate model
<p>This is the subset of CESM1.2 model simulation output that was used for analysis and visualization of Yu and Fedorov [2020] (DOI:10.1029/2020GL088381). Please refer to README for details.</p>
Data from: Energy expenditure of adult green turtles (Chelonia mydas) at their foraging grounds and during simulated oceanic migration
Measuring the energy requirements of animals under natural conditions and determining how acquired energy is allocated to specific activities is a central theme in ecophysiology. Turtle reproductive output is fundamentally linked with their energy balance so a detailed understanding of marine turtle energy requirements during the different phases of their life cycle at sea is essential for their conservation. We used the non-invasive accelerometry technique to investigate the activity patterns and energy expenditure (EE) of adult green turtles (Chelonia mydas) foraging year-round at a seagrass meadow in Mayotte (n = 13) and during simulated oceanic migration (displacement from the nesting beach) off Mohéli (n = 1), in the south-western Indian Ocean. At the foraging site, turtles divided their days between foraging benthically on the shallow seagrass meadow during daylight hours and resting at greater depth on the inner side of the reef slope at night. Estimated oxygen consumption rates (sinline image) and daily energy expenditures (DEE) at the foraging site were low (sinline image during the day was 1·6 and 1·9 times the respective resting rate at night during the austral summer and winter, respectively), which is consistent with the requirement to build up substantial energy reserves at the foraging site, to sustain the energy-demanding breeding migration and reproduction. Dive duration (but not dive depth) at the foraging site shifted significantly with season (dive duration increased with declining water temperatures, Tw), while overall activity levels remained unchanged. In parallel with a significant seasonal decline in Tw (from 28·9 ± 0·1 °C to 25·3 ± 0·4 °C), there was a moderate (˜19%) but significant decline in DEE of turtles during the austral winter (901 ± 111 kJ day−1), when compared with the austral summer (1117 ± 66 kJ day−1). By contrast, the turtle moved continuously during simulated oceanic migration, conducting short/shallow dives in the day, which (predominately at night) were interspersed with longer and deeper 'pelagic' dives. Estimated oxygen consumption rates during a simulated migration (1·25 ± 0·16 mL O2 min−1 kg−0·83) were found to be significantly increased over the foraging condition, equal to ˜3 times the resting rate at night (0·42 ± 0·02 mL O2 min−1 kg−0·83), and daily energy expenditure amounted to 2327 ± 292 kJ day−1, underlining the tremendous energetic effort associated with breeding migration. Our study indicates that the accelerometry technique provides a new and promising opportunity to study marine turtle energy relations in great detail and under natural conditions.
Surface Kinetic energy from MITgcm-GEOS5 Coupled Ocean-Atmosphere Simulation
<p>Annual mean of surface kinetic energy computed from MITgcm-GEOS5 coupled ocean-atmosphere simulation, with a spacing grid of 4 km.</p> <p>The temporal coverage for the annual mean spans from March 01, 2020, to March 01, 2021.</p>
Simulation of Southern Ocean cloud processes using the high-resolution regional UK Met Office Unified Model with interactive aerosols
<p>Code and model data used to create the figures for Price et al., 2024, JGR (in prep.).</p>
MPAS-Ocean Barotropic Tidal Simulation Run Directories
<p>This file contains the initial files needed to run the barotropic tidal simulations in MPAS-Ocean.</p> <p>Download the resolution you want (icos7-10 or vr45to5). Inside the resolution directory is "inline", "scalar", and "shared". "Inline" is the run directory for inline SAL. "Scalar" is the run directory for scalar SAL. "Shared" contains data needed to run either case.</p> <p> The steps are:</p> <ol> <li>download</li> <li>unzip: tar xvfz filename.tar.gz</li> <li>navigate to run directory (resolution/inline OR resolution/scalar)</li> <li>add a link to shared files (e.g., ln -s ../shared/* )</li> <li>add a link to your compiled executable of MPAS-Ocean</li> <li>run, e.g. mpirun -n $N ocean_model</li> </ol> <p>If the simulation was successful, you will see:</p> <pre><code>tail -n 1 log.ocean.0000.out Logging complete. Closing file at ...</code></pre> <p>See Github page: https://github.com/E3SM-Project/E3SM for Quick Start Guide and more.</p>
NOAA Coastwatch Satellite Course (Set up an Application Model of Digital Satellite Data Simulation by Video Graphic Technology of Oceanic data Remotely Sensed of algerian coast)
<p>The goal of the course is to familiarize NOAA/university researchers, Sea Grant professionals and agency/org. partners with different types of ocean satellite data, different tools, and teach participants how to use satellite data in their own research/outreach using their choice of software (NOAA ,2023)</p>
Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations
<p>This dataset contains the NPOCE (http://npoce.org.cn) data used in the following submission for Journal of Geophysical Research: Oceans:</p> <p>Hu, S., J. Sprintall, C. Guan, B. Sun, F. Wang, G. Yang, F. Jia, J. Wang, D. Hu, and F. Chai (2018), Spatio-temporal Features of Intra-seasonal Oceanic Variability in the Philippine Sea from Mooring Observations and Numerical Simulations, Journal of Geophysical Research: Oceans.</p> <p>Variables in this dataset are eddy kinetic energy (EKE) observed by the NPOCE moorings, longitudes, latitudes, depths and dates.</p> <p> </p> <p> </p>
Simulations in Support of "The Impact of Cloud Microphysics and Ice Nucleation on Southern Ocean Clouds"
<p>Single column model simulations in support of manuscript: The Impact of Cloud Microphysics and Ice Nucleation on Southern Ocean Clouds</p><p>Each simulation is a zip file with prognostic and diagnostic variable outputs as NetCDF files in each zip file. Includes sensitivity tests, timestep tests and baseline simulations used in the paper. </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.