Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
21
datasets available to search
ShareScore release 0.9.0
Dataset results
21 results for “neutral winds”
Poker Flat Incoherent Scatter Radar (PFISR) Observations of E-region Neutral Winds
<p>Updated: 12-15-2021</p> <p><strong>RULES OF THE ROAD:</strong></p> <p>You are welcome to use the data 'as is', however, please inform me via email if you plan to use the dataset. There are a number of small issues with the dataset that are best discussed. We are interested in publications that use the data and derived values that are presented within the dataset. <strong>If you plan to publish these results, please circulate a draft by me (SRK) and we would appreciate an offer of co-authorship or at minimum an acknowledgement. You should include the NSF funding numbers NSF AGS - 1853408</strong></p> <p> </p> <p>As a general warning, the data from PFISR are quite noisy and you may need to perform significant averaging to produce usable results. Again, please contact me and we can discuss this in more detail.</p> <p>Version v0.6.4.2021.07.12 - This was the final processed version at the time that the final report was submitted to the NSF.</p> <p> </p> <p><strong>--------------- Previous from before ------------------</strong></p> <p>This file contains Poker Flat Incoherent Scatter Radar (PFISR) E-region Neutral Winds Data. These data correspond to monthly data files that include the E-region neutral winds and other parameters for the from March 2013-June 2019.</p> <p><strong>Publications of the Joule Heating Results:</strong></p> <p>https://doi.org/10.1029/2021JA029371</p> <p>https://doi.org/10.1029/2021JA029719</p> <p> </p> <p><strong>Publication of Neutral Wind Results:</strong></p> <p>Hopefully we will have something in 2021. </p> <p> </p> <p><strong>RAW ISR Data:</strong> These data were processed from the following files found in: https://data.amisr.com/database/tmp/Kaeppler/winds/ and https://data.amisr.com/database/tmp/Kaeppler/missing_IPY.tar.gz Please note that the error on the line of sight velocities may have been overestimated in these data and we scaled them by a eVLOS/sqrt(10). Interested persons should contact Ashton Reimer or Roger Varney at SRI International for more information about these data, please see amisr.com</p> <p>Truthfully, the ISR data should eventually be reprocessed and then the winds algorithm run over it again. This is a step for future work.</p> <p> </p> <p><strong>Processing Code is available upon request via email.</strong></p> <p> </p> <p><strong>File Documentation:</strong></p> <p> </p> <p><strong>Please see the change log:</strong></p> <p>Purpose: This is the overarching program and functions which process the<br> E region neutral winds from the fitted AC and LP data from PFISR.<br> This is a conversion fo process_eregwinds_srk.py which was originally written by<br> Nicolls into a more formal python class structure.</p> <p>2017-10-05 - v0.2</p> <p>The ProcessEregionNeutralWinds.py file has been validated against process_eregwinds_srk.py<br> using 20161121.001_ac_3min-fitcal.h5, 20170301.013_ac_3min-fitcal.h5, 20170302.001_ac_3min-fitcal.h5.<br> The program to run these is ComparePrograms.py. At this point these program match.<br> I am going to start diverging the code base, first subtly in the Joule Heating<br> since I found that Mike just looped over Nbeams, which isn't quite right, you need to loop<br> over the beams that were selected.</p> <p>Changes from this point forward will produce different results.</p> <p>2017-10-10 - v0.3.2017.10.10</p> <p>Version v0.3, I made some IO changes but I may start processing some data with this version.</p> <p>Version v0.4 - lots of small edits made to the IO and the plotting software. It all seems to work<br> I have also included the SNR and Ne into the monthly plots and other information.<br> Made processing smoother.</p> <p>03 13 2018 - added solar local time converion</p> <p>v0.4.1 - 09 08 2018 added some ability to extract out the raw electron and SNR densities for each altitude bin<br> v0.4.2 - 10 15 2018 added in obtaining the F-region flows - want to check against the electric field.<br> v0.4.3 - 10 29 2018 added in some more altitude into the Joule Heating so I can make better figures<br> v0.4.4 - 11 20 2018 made some pretty major changes to IO to include consistent calculation of<br> Pedersen conductivity from FastConductivity.py. Made some changes to the Joule heating calculation and checked<br> formulas. It is worth checking again.</p> <p>v0.4.5 - 11 20 2018: added in Hall and Pedersen conductivities from fitted electron density data.<br> v0.4.6 - 12 03 2018: Tried to fix some of the double counting and time problems in testMakeMonthlyh5</p> <p>05 22 2019: added some statements to bypass the geophysical parameters. Also need in config file now.<br> Additionally wrote in IOEregionwinds a try except statement</p> <p>07 29 2019: Running the code for the 06 data reprocessed by Ashton</p> <p>v0.5.0 - 10-15-2019: put in some filtering on the LOS velocity discharging bad Chi square and bad error codes on the fit.</p> <p>v0.5.1 - 10-23-2019: changed chi square to 0.01 for lower boundary</p> <p>v0.5.3 - 12-02-2019: Added in that now passing in the Chi2 and Fitcode filtering by Config file<br> Bigger change that I am scaling the AC dVlos by some sort of factor while Ashton figures this out.<br> We decided that a conversative scaling would be to reduce the dVLOS by 1/sqrt(10).<br> The chi square produced in the data Ashton sent me typically was around 0.01, so the uncertaintiies on the LOS velocities<br> may be over estimated. So we are just changing this as a temporary fix while Ashton fixes the uncertainty estimation.</p> <p>v0.5.5 02 01 2020 - Added in calculation of Coriolis, Centrifugal, and Lorentz forcing<br> v0.5.5 02 10 2020 - Added a correction to qvert so that way I can calculate the lorentz term.<br> Found an error where qvert = 0 in the if statement goes to false.</p> <p>v0.5.5 02 15 2020 - Put in nuInscaler into the main program, scaling ALL kappas by the scaler number</p> <p>v0.5.6 02 28 2020 -- Added some more vlos diagostics and the calculation of the scale height. Added Altitude offset</p> <p>v0.5.6.2020.03.12_nuin_fracoff - testing putting in the Brekke formula for ion neutral collision frequency and took out frac</p> <p>v0.5.7.2020.04.10 - Put in Ashton's revised ion neutral collision frequency formulas into IO.<br> Also wrote a testscript and at least for the file I used was only different by 2.5%.<br> Revised where the mag data is being pulled from since the URL is deprecated<br> Added in Kappa which is now being interpolate - plan to see where kappa =1 is located for the paper.<br> commented out nuin scaler just so I am not chasing my tail</p> <p> test v0.5.7.2020.04.13_org commented back in original ion neutral collision frequency method<br> possible mistake that not summing up properly.</p> <p> test v0.5.7.2020.04.13_newnuin_orgsum_noTr800 - new formula for nuin except took off Tr>800.<br> I expect this should be almost the same as before since the formulas are basically the same.<br> did the original sum using frac[0] and frac[1] want to see if I am underestimating</p> <p> v0.5.7.2020.04.13_newnuin_orgsum_yesTr800 - same as above except now including Tr>800.</p> <p> 'v0.5.7.2020.04.13_newnuin_newsum_noTr800' - using the new sum now and new col freq</p> <p> v0.5.7.2020.04.13_updatedorg - updated original uses original method but including the NO term</p> <p>v0.6.0.2020.04.15 -- Now think I have the new ion neutral collision frequency working and validated.<br> Found a mistake in how I was calculating the ion neutral collision frequency that<br> the fraction weight I was using only included the O+ and O2+ terms and not NO+<br> Turns out I was basically weighting by about 0.5, so I was effectively reducing the<br> ion neutral collision frequency by about a factor of 0.5 or less...<br> From this point forward need to start using any results from > v0.6<br> This revision has changed previous results signi</p> <p>v0.6.0.2020.04.21 -- updated to now include the temperature correction for the O2+</p> <p>v0.6.1.2020.04.23 -- made a number of changes to the geomagnetic files and reprocessed from CDAweb.<br> Wrote new code to be able to process the files from CDAweb in the new format.<br> Also changed the geomagnetic data files</p> <p>v0.6.1.2020.06.07 -- changed the generation of Monthly files to hopefully be in order now<br> Added in missingIPY files given to me by ashton, maybe improve data covarege<br> Some work going to need to be done to make sure that all of the 10, 15, and 20 minute data are there.</p> <p>v0.6.1.2020.06.15_Weijia -- Updated the data for Weijia's study in particular since we are missing a lot of IPY data for 02-04 2013 and 2014.</p> <p>'v0.6.2.2020.07.01' -- Updated the data with new IPY27 mode for 2013 and 2014 Ashton processed. Also now put in mechanical Joule heating term.<br> Put in the conductance and conductivity now too.</p> <p>v0.6.2.2020.07.30 -- Made some changes to IO since Weijia noticed the mechanical heating terms were missing from the monthly files.</p> <p>v0.6.3.2020.10.19 -- Tried to elimated all extra instance of nuinscaler, and also output that variable. Added in variables<br> To get the Ti, Tn, ion neutral collision frequency along the vertical beam for diagnostic purposes<br> included dVest for F-region plasma drifts for Rafael</p> <p>v0.6.4.2020.11.20 -- Extracted some more parameters including F107 and the Hall and Pedersen Drags</p> <p>v0.6.4.2021.07.21 -- Final Run of data for NSF project</p> <p> </p>
Gradient winds and neutral flow dawn-dusk asymmetry in the auroral oval during geomagnetically disturbed conditions (data files)
<p>Data files with wind profiles used to generate figures in the paper entitled "Gradient winds and neutral flow dawn-dusk asymmetry in the auroral oval during geomagnetically disturbed conditions"</p>
Simulation data used for publication "Seeding of equatorial plasma bubbles by vertical neutral wind" by Yokoyama et al.
<p>The dataset includes two-dimensional simulation output used in the paper.</p> <p>"altitude.dat" and "zonal.dat" contains grid information.</p> <p>"read_n_phi_2D.pro" is an IDL file to read the dataset, with detailed description of each data.</p> <p>The original three-dimensional simulation output is too large to publish at the repository. Author (TY) is willing to share the original data.</p>
Experimental and numerical data of an article on the prediction of wind load on pylons for a neutral atmospheric boundary layer ow over two successive hills
<p>his deposit contains experimental and numerical data related to the article entitled "Towards prediction of wind load on pylons for a neutral atmospheric boundary layer flow over two successive hills" that will be publised in Journal of Wind Engineering & Industrial Aerodynamics. It consists in post-processed experimental data (turbulence statistics) for flows around 2D hills, measured by PIV, and numerical date of k-epsilon simulations of the same configirations. All data are provided in matlab metadata format. Matlab functions are given to plot all the figures of the article.</p>
Ionospheric Electron Densities, Neutral Temperature, Winds and Post-processed Output from TIEGCM Simulations in Support of Publication "Physical Processes Driving the Response of the F2-region Ionosphere to the 21 August 2017 Solar Eclipse at Millstone Hill"
This dataset is associated with the publication "Physical Processes Driving the Response of the F2-region Ionosphere to the 21 August 2017 Solar Eclipse at Millstone Hill". In particular, the NCAR- Community model: high-resolution thermosphere-ionosphere-electrodynamics general circulation model (TIEGCM) has been used to investigate the response of ionospheric F2-region electron density (Ne) at Millstone Hill (42.610N, 71.480W, maximum obscuration: 63%) to the Great American Solar Eclipse on 21 August 2017. Two sets of model runs were done, one with the eclipse and the other without. Model outputs of winds, temperatures and electron densities, as well as diagnostic variables of key chemical and physical processes that determined the ionosphere responses to the eclipse, were analyzed and used in producing a paper: Physical Processes Driving the Response of the F2-region Ionosphere to the 21 August 2017 Solar Eclipse at Millstone Hill.
Resource for Hatch et al (2024), "What is the neutral wind in height-integrated electrodynamics?"
<p>Data and python scripts for creating figures in Hatch et al (2024), "What is the neutral wind in height-integrated ionospheric electrodynamics?"</p> <p>The 'data' folder contains PFISR measurements and neutral wind profiles needed for calculating the Hall- and Pedersen-weighted neutral winds. The 'scripts' folder contains python scripts.</p> <p>Figure 1: journal__20231228__plot_wind_profiles_grouped_by_day.py</p> <p>Figure 2: journal__20231209__look_at_swipe_for_rocket_times.py</p> <p>Figure 3: journal__20231220__is_it_any_better_to_use_neutralwind_at_160km_than_to_assume_uEq0QQ.py</p> <p>Figure 4: journal__20231209__look_at_swipe_for_rocket_times.py</p>
Thermospheric neutral wind and temperature over Cachoeira Paulista
<p>The data sets are observations of thermospheric neutral winds and temperatures which can be used to study the dynamics of low latitude ionosphere in Brazil. The data have been organized by Dr Jonas R. Souza (jonas.souza@inpe.br) from National Institute for Space Research - INPE.</p>
Inferring neutral winds in the ionospheric transition region from AGW-TID observations with the EISCAT VHF radar and the Nordic Meteor Radar Cluster
<p>[Dataset] Inferring neutral winds in the ionospheric transition region from AGW-TID observations with the EISCAT VHF radar and the Nordic Meteor Radar Cluster</p>
Ground Magnetic Disturbances due to Neutral-wind-driven Ionospheric Currents
<p>This dataset includes GITM outputs of an idealized event. This dataset is used to analyze the geomagnetic disturbances due to neutral-wind-driven ionospheric currents, and their relative importance compared to the geomagnetic disturbances driven by magnetospheric convection electric field.</p>
Studying solar storm impact on global neutral wind pattern using WACCM-X numerical simulations and Meteor radar observations
Open the record for dataset details and reuse information.
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-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).
QuikSCAT 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 aboard QuikScat, representing the first science quality release of these data funded under the MEaSUREs program. This product from QuikScat has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-A, MetOp-B, and ScatSat-1, 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).
SCATSAT-1 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 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. 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-A 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-A 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-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), 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 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).
SCATSAT-1 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 aboard ScatSat-1, representing the first science quality release of these data (post-provisional after v1.0) funded under the MEaAUREs 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), 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).
QuikSCAT 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 aboard QuikScat, representing the first science quality release of these data (post-provisional after v1.0) funded under the MEaAUREs program. This product from QuikScat has been intercalibrated with similar scatterometer measurements from instruments on the MetOp-A, MetOp-B, and ScatSat-1 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).
Thermospheric neutral wind and temperature over Cachoeira Paulista
<p>The datasets are observations of thermospheric neutral winds and temperatures recorded by a Fabry-Perot interferometer. These data can be used to study the dynamics of the low-latitude ionosphere in Brazil. The data were organized by Dr. Jonas R. Souza (jonas.souza@inpe.br) from the National Institute for Space Research - INPE.</p>
QuikSCAT Scatterometer Inter-Calibrated ESDR Level 2 Ocean Surface Equivalent Neutral Wind Vectors and Wind Stress Vectors Version 1.0
This dataset contains the first provisional release of the MEaSUREs-funded Earth Science Data Record (ESDR) of inter-calibrated ocean surface wind vectors (equivalent neutral and true 10m) and wind stress vectors derived from QuikSCAT scatterometer observations. The primary purpose of this release is for provisional evaluation by the NASA International Ocean Vector Winds Science Team (IOVWST). As such, this release is not intended for science-quality research, and is subject to future revision based on feedback provided by the IOVWST. 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 (rev) number, which begins at the southernmost point of the ascending orbit.
ScienceDex guides
Understand access before you commit
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.