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33 results for “surface stress”
Historical Sea Surface Temperature (SST) data and thermal stress indices of the Tara Pacific Expedition's coral reef sampling sites, from May 1st 2002 to August 31st 2018.
<p>The Tara Pacific expedition (2016-2018) sampled coral ecosystems at 111 sampling sites around 32 islands in the Pacific Ocean, and sampled the surface of oceanic waters at 249 locations, resulting in the collection of nearly 58,000 samples (Gorsky et al. 2019, Planes et al. 2019, Flores et al. 2020). The expedition was designed to systematically study corals, fish, plankton, and seawater, and included the collection of samples for advanced biogeochemical, molecular, and imaging analysis.</p> <p>Here we provide a high-resolution historical dataset that spans from 2002 to each sites’ sampling date and gives an overview of past climate variability and heatwaves experienced by corals sampled at each site. Ocean skin temperature (11 and 12 µm spectral bands longwave algorithm) was extracted from 1km resolution level-2 MODIS-Aqua and MODIS-Terra from 2002 to the sampling date and from level-2 VIIRS-SNPP from 2012 to the sampling date. Day and night overpasses were used to maximize data recovery. Following recommendations from NASA Ocean Color (OB.DAAC), only SST products of quality 0 and 1 were used. The 9 closest pixels to the sampling sites of each scene were extracted. All the extracted pixels from the 3 satellites were then averaged daily to obtain daily SST averages and standard deviations time series for each sampling site, from 2002 to the sampling date.</p> <p>Each time series was first averaged on a Julian day basis to provide a seasonal average. This yearly seasonal average was triplicated and concatenated into a 3-year seasonal cycle to apply a digital low pass filter on the middle year without generating artifacts. A digital low pass filter (filter order 3, pass band ripple 0.1; “filfilt” function in matlab) with 36 Julian days windows was applied to the concatenated time series to remove high frequency noise. The middle year was then extracted from the concatenated time series to recover the seasonal cycle. The sea surface temperature anomaly was calculated as the SST minus the seasonal cycle over the full time series. Considering the short periods of missing data (mean of the 95th percentile of the duration of consecutive days with missing data: 9.8 ± 4.1 days), the missing values in the SST and SST anomaly time series were linearly interpolated in order to calculate thermal stress indices. The SST anomaly frequency was calculated as the number of days over the past 52 weeks when the SST anomaly is greater than or equal to 1 °C. Thermal stress indices relevant to coral reef health were then calculated using methodology developed for the Coral Reef Temperature Anomaly Database (CoRTAD) data base (Saha et al. 2019). Events of cold temperature accumulation were also reported to cause bleaching and mortality (Lirman et al. 2011; González-Espinosa & Donner 2020), therefore, the same set of indices were calculated for cold stress adapting the CoRTAD method, but using the minimum weekly climatologies.</p> <p>A condensed table containing single values associated with each sampling site was created ('TaraPacific_SST_timeseries_mean_products') extracting the minimum, maximum, sum, averages, standard deviations, and value recorded at the sampling day of each of these indices (detailed in the readme file provided with the dataset 'README_TaraPacific_historical_SST.md'). Additional metrics of the last heating and cooling events as well as the time of recovery is also provided to represent the state of thermal stress at the day of sampling.</p>
Arctic/Antarctic Ocean-Surface Stress Analysis, 2011-2021/2013-2021
<p>This record contains data related to article "Constructing Satellite-based Ocean-surface Stress and Ekman Circulation in the Arctic and Antarctic Oceans". It offers a high-resolution, daily analysis of ocean-surface stress and Ekman circulation over the Arctic and Southern Ocean, derived from multiplatform satellite observations.</p> <p>All data are projected onto a 25 km EASE2 grid with daily resolution. The dataset (netcdf) contains the following variables:</p> <p>- zonal components of ocean-surface stress (TAUx, N/m2)</p> <p>- meridional components of ocean-surface stress (TAUy, N/m2)</p> <p>- magnitude of ocean-surface stress (TAU, N/m2)</p> <p>- uncertainty estimates for TAUx (N/m2)</p> <p>- uncertainty estimates for TAUy (N/m2)</p> <p>- Ekman Pumping Rate (m/s)</p> <p>- Land mask</p> <p>- Longitude</p> <p>- Latitude</p> <p>L.Yu acknowledges the support of the NASA Vector Wind Science Team program for this research.</p> <p> </p>
Evidence that stress-induced changes in surface temperature serve a thermoregulatory function
<p>Changes in body temperature following exposure to stressors have been documented for nearly two millennia, however, the functional value of this phenomenon is poorly understood. We tested two competing hypotheses to explain stress-induced changes in temperature, with respect to surface tissues. Under the first hypothesis, changes in surface temperature are a consequence of vasoconstriction that occurs to attenuate blood-loss in the event of injury and serves no functional purpose <em>per se</em>; defined as the Haemoprotective Hypothesis. Under the second hypothesis, changes in surface temperature reduce thermoregulatory burdens experienced during activation of a stress response, and thus hold a direct functional value; here, the Thermoprotective Hypothesis. To understand whether stress-induced changes in surface temperature have functional consequences, we tested predictions of the Haemoprotective and Thermoprotective hypotheses by exposing Black-capped Chickadees (n=20) to rotating stressors across an ecologically relevant ambient temperature gradient, while non-invasively monitoring surface temperature (eye region temperature) using infrared thermography. Our results show that individuals exposed to rotating stressors reduce surface temperature and dry heat loss at low ambient temperature and increase surface temperature and dry heat loss at high ambient temperature, when compared to controls. These results support the Thermoprotective Hypothesis and suggest that changes in surface temperature following stress exposure have functional consequences and are consistent with an adaptation. Such findings emphasize the importance of the thermal environment in shaping physiological responses to stressors in vertebrates, and in doing so, raise questions about their suitability within the context of a changing climate.</p>
The role of bottom friction in mediating the response of the Weddell Gyre circulation to changes in surface stress and buoyancy fluxes
<p>This repository contains code to reproduce the figures in the paper titled "The role of bottom friction in mediating the response of the Weddell Gyre circulation to changes in surface stress and buoyancy fluxes" published in the Journal of Physical Oceanography (DOI: <a href="https://doi.org/10.1175/JPO-D-23-0165.1">https://doi.org/10.1175/JPO-D-23-0165.1</a>), as well as the barotropic vorticity budget terms for each of simulation in the paper.</p>
Mediterranean Sea, NEMO4.2 / WW3 uncoupled and coupled surface: stress, currents and Stokes Drift
<pre>The NEMO version 4.2 has been updated to include new processes related to wave-current interactions. <br>A set of sensitivity experiments are performed using the hydrodynamic model, NEMO v4.2 standalone and coupled with <br>the spectral wave model WaveWatchIII (WW3) v6.07 through the OASIS library. <br><br>The configuration is based on the operational Copernicus Marine Service Mediterranean forecasting physical system (MedFS). <br>Both models are implemented at 1/24° resolution and are forced by ECMWF 1/10° horizontal resolution atmospheric fields.<br><br>Two-year (2019-2020) numerical experiments are carried out in both uncoupled and 1 way coupled mode.<br>This dataset contains the NEMO output of the daily surface fields for the surface stress, the surface currents <br>and the Stokes drift for the uncoupled and coupled experiments. <br>This dataset was created in the context of the IMMERSE H2020 project.</pre>
Analytical method for reconstructing the stress on a spherical particle from its surface deformation
<p>Supplemental data for the following manuscript: Lea Johanna Krüger, Michael te Vrugt, Stephan Bröker, Bernhard Wallmeyer, Timo Betz, Raphael Wittkowski, "Analytical method for reconstructing the stress on a spherical particle from its surface deformation".</p><p>Bead1_ExperimentalData.tif and Bead2_ExperimentalData.tif contain the measured bead shapes as TIF files. Bead1_ExperimentalData.txt and Bead2_ExperimentalData.txt contain the measured bead shapes as point clouds. Bead1_SphericalHarmonicsExpansionCoefficients.txt and Bead2_SphericalHarmonicsExpansionCoefficients.txt contain expansions of the bead shapes into spherical harmonics.</p>
Isoprene concentrations data used in the paper "Assessment of isoprene and near surface ozone sensitivities to water stress over the Euro-Mediterranean region"
<p>Isoprene concentrations collected by E. Bourtsoukidis and J. Williams during a field-campaign that took place in Cyprus (site field: Ineia; Latitude: 34.96° N, Longitude: 32.39° E) during the summer 2014 (from July 7 to August 3; data collected every 45 minutes) using the technique of gas chromatography - mass spectrometry (GC-MS) (Derstroff et al., 2017). These data have been used to validate isoprene concentrations simulated by the regional climate model RegCM applied in the study "<em>Assessment of isoprene and near surface ozone sensitivities to water stress over the Euro-Mediterranean region</em>" (https://doi.org/10.5194/egusphere-2022-1522).</p>
Evidence that stress-induced changes in surface temperature serve a thermoregulatory function
Open the record for dataset details and reuse information.
Evaluation of the Effect of a Postural Reflex Rehabilitation Program on a Foam Surface on Stress Urinary Incontinence in Women
ClinicalTrials.gov study NCT04390204. IPD Sharing: Not stated. Countries: 1. Publications: 1.
ECCO Ocean and Sea-Ice Surface Stress - Daily Mean 0.5 Degree (Version 4 Release 4)
This dataset contains daily-averaged ocean and sea-ice surface stress interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Ocean and Sea-Ice Surface Stress - Monthly Mean llc90 Grid (Version 4 Release 4)
This dataset provides monthly-averaged ocean and sea-ice surface stress on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Ocean and Sea-Ice Surface Stress - Monthly Mean 0.5 Degree (Version 4 Release 4)
This dataset contains monthly-averaged ocean and sea-ice surface stress interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Ocean and Sea-Ice Surface Stress - Daily Mean llc90 Grid (Version 4 Release 4)
This dataset provides daily-averaged ocean and sea-ice surface stress on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
Greenland Surface Strain Rates & Stresses
<div> <p><a href="https://theghub.org/resources/4723/about">These datasets available via Ghub are 2D principal strain rates and principal stresses across the surface of the Greenland Ice Sheet.</a></p> <p>We started with representative surface velocities over a 20-year period (Joughin et al., 2016). We smoothed the velocities with a 1 km × 1 km boxcar filter, which carries through many high-strain-rate features. We propagated errors in the velocity observations through this filter and then calculated the two horizontal principal strain rates by taking centered spatial derivatives of the smoothed velocities. We calculated the errors in these strain rates following basic error propagation principles.</p> <p>The equations for principal strain rates and their errors can be found as Equations 1-4 in Poinar & Andrews (2021), "Challenges in predicting Greenland supraglacial lake drainages at the regional scale", <em>The Cryosphere</em>, 15, 1455–1483, <a href="http://doi.org/10.5194/tc-15-1455-2021" target="_blank" rel="nofollow noreferrer noopener noreferrer noopener noreferrer noopener noreferrer">doi:10.5194/tc-15-1455-2021</a>.</p> <p>Finally, we also convert surface strain rates into surface stresses using Glen's flow law. See attachment pdf "Stresses from Strain Rates" for formulas.</p> <h2>Update: Finer-res version, 26 November 2023</h2> <p>A 250 m resolution version is now available, although the strain rates should NOT be interpreted finer than a scale of ~1 ice thickness (~1 km).</p> <p>This version uses the Savitzky-Golay filter for smoothing and differentiation, as described in the the attached .m file, following work by Brent Minchew, doi:10.1017/jog.2018.47. Processes controlling the downstream evolution of ice rheology in glacier shear margins: case study on Rutford Ice Stream, West Antarctica. Minchew, Meyer, Robel, Gudmundsson, and Simons, 2018.</p> <h2>Update: Stresses with uncertainties, 27 March 2024</h2> <p>The principal stresses (as well as the principal strain rates) now come with uncertainties propagated through.</p> <h2>References</h2> <p>Joughin, I., Smith, B. E., Howat, I., and Scambos, T. (2016). "MEaSUREs Multi-year Greenland Ice Sheet Velocity Mosaic, Version 1", NASA National Snow and Ice Data Center Distributed Active Archive Center, <a href="http://doi.org/10.5067/QUA5Q9SVMSJG" target="_blank" rel="nofollow noreferrer noopener noreferrer noopener noreferrer noopener noreferrer">doi:10.5067/QUA5Q9SVMSJG</a>. NSIDC-0670.</p> <p>Poinar &amp; Andrews (2021), "Challenges in predicting Greenland supraglacial lake drainages at the regional scale", <em>The Cryosphere</em>, 15, 1455–1483, <a href="http://doi.org/10.5194/tc-15-1455-2021" target="_blank" rel="nofollow noreferrer noopener noreferrer noopener noreferrer noopener noreferrer">doi:10.5194/tc-15-1455-2021</a>.</p> </div>
Experimental investigation on effects of loading rate, surface roughness and normal stress on repeating stick-slip behaviors
<p>TEST DATA</p>
MetOp-B ASCAT Scatterometer Inter-Calibrated ESDR Level 2 Ocean Surface Equivalent Neutral Wind Vectors and Wind Stress Vectors Version 1.1
This dataset contains ocean surface wind vectors (equivalent neutral and true 10m) and wind stress vectors derived from satellite-based scatterometer observations (the MetOp-B ASCAT scatterometer), representing the first science quality release of these data (post-provisional after v1.0) funded under the MEaAUREs program. This product from MetOp-B ASCAT has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-A, ScatSat-1, and QuikScat satellites (all of which can be found on the MEaSUREs OSVW Project Page), and if used together create an unbroken record of winds from 1999 to 2022. The wind vector and stress retrievals are provided on a non-uniform grid within the swath (Level 2 (L2) products) at 12.5 km pixel resolution. Each L2 file corresponds to a specific orbital revolution number, which begins at the southernmost point of the ascending orbit. The thumbnail shows data for two orbits - using all orbits for a single day will provide global coverage.<br><br>The dataset represents the first science quality release funded under the MEaSUREs (Making Earth System Data Records for Use in Research Environments) program. Version 1.1 provides a set of updates and improvements from version 1.0, including: 1) increased data coverage, 2) improved quality control, and 3) new global metadata attributes featuring revolution number, equator crossing longitude, and equator crossing time (UTC). The primary purpose of this release is for science evaluation by the NASA International Ocean Vector Winds Science Team (IOVWST).
MetOp-B ASCAT Scatterometer Inter-Calibrated ESDR Level 3 Ocean Surface Equivalent Neutral Wind Vectors and Wind Stress Version 1.0
This dataset contains gridded ocean surface wind vectors (equivalent neutral and true 10m) and wind stress vectors derived from satellite-based scatterometer observations (the MetOp-B ASCAT scatterometer), representing the first science quality release of these data funded under the MEaSUREs program. This product from MetOp-B ASCAT has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-A, ScatSat-1, and QuikScat satellites, all of which can be found on the MEaSUREs OSVW Project Page. The wind vector and stress retrievals are provided on a global grid (one per file) at 12.5 km pixel resolution, but data exist only over areas of the globe that fell within one of the satellite swaths/orbits for that day (see thumbnail). <br><br>The dataset represents the first science quality release funded under the MEaSUREs (Making Earth System Data Records for Use in Research Environments) program. Note that this is the first version of the Level 3 data (V1.0) but they were derived from V1.1 of the Level 2 product. The primary purpose of this release is for science evaluation by the NASA International Ocean Vector Winds Science Team (IOVWST).
Metop-B ASCAT Inter-Calibrated ESDR Level 2 Observed and Modeled Spatial Derivatives of Surface Wind and Wind Stress Version 1.0
This dataset contains the curl and divergence of ocean surface equivalent neutral wind and wind stress, derived from satellite-based scatterometer observations (the MetOp-B ASCAT scatterometer), representing the first science quality release of these data (post-provisional after v1.0) funded under the MEaSUREs program. This product from MetOp-B ASCAT has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-A, ScatSat-1, and QuikScat satellites, all of which can be found on the MEaSUREs OSVW Project Page. These Level 2 data are provided on a non-uniform grid within the satellite swath at ~12.5 km pixel resolution. Each L2 file corresponds to a specific orbital revolution number, which begins at the southernmost point of the ascending orbit - the thumbnail preview shows data for all orbits over a day (typically 14 orbits). Estimates for the curls and divergences are computed over several spatial domains with varying radii from the point of interest, and included as separate variables.<br><br>The dataset represents the first science quality release funded under the MEaSUREs (Making Earth System Data Records for Use in Research Environments) program. The primary purpose of this release is for science evaluation by the NASA International Ocean Vector Winds Science Team (IOVWST). This V1.0 of the data was derived from V1.1 of the L2 wind and stress product.
SCATSAT-1 Inter-Calibrated ESDR Level 2 Observed and Modeled Spatial Derivatives of Surface Wind and Wind Stress Version 1.0
This dataset contains the curl and divergence of ocean surface equivalent neutral wind and wind stress, derived from satellite-based scatterometer observations aboard SCATSAT-1, representing the first science quality release of these data funded under the MEaSUREs program. This product from SCATSAT-1 has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-A, MetOp-B, and QuikScat satellites, all of which can be found on the MEaSUREs OSVW Project Page. These Level 2 data are provided on a non-uniform grid within the satellite swath at ~12.5 km pixel resolution. Each L2 file corresponds to a specific orbital revolution number, which begins at the southernmost point of the ascending orbit. There are typically 14 orbits per day, and the thumbnail preview shows coverage for the first ten orbits in an example day. Estimates for the curls and divergences are computed over several spatial domains with varying radii from the point of interest, and included as separate variables.<br><br>The dataset represents the first science quality release funded under the MEaSUREs (Making Earth System Data Records for Use in Research Environments) program. The primary purpose of this release is for science evaluation by the NASA International Ocean Vector Winds Science Team (IOVWST). This V1.0 of the data was derived from V1.1 of the L2 wind and stress product.
MetOp-A ASCAT Scatterometer Inter-Calibrated ESDR Level 3 Ocean Surface Equivalent Neutral Wind Vectors and Wind Stress Version 1.0
This dataset contains gridded ocean surface wind vectors (equivalent neutral and true 10m) and wind stress vectors derived from satellite-based scatterometer observations (the MetOp-A ASCAT scatterometer), representing the first science quality release of these data funded under the MEaSUREs program. This product from MetOp-A ASCAT has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-B, ScatSat-1, and QuikScat satellites, all of which can be found on the MEaSUREs OSVW Project Page. The wind vector and stress retrievals are provided on a global grid (one per file) at 12.5 km pixel resolution. Data exist only over areas of the globe that fell within one of the satellite swaths/orbits for that day (see thumbnail). <br><br>The dataset represents the first science quality release funded under the MEaSUREs (Making Earth System Data Records for Use in Research Environments) program. Note that this is the first version of the Level 3 data (V1.0) but they were derived from V1.1 of the Level 2 product. The primary purpose of this release is for science evaluation by the NASA International Ocean Vector Winds Science Team (IOVWST).
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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.