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.
14
datasets available to search
ShareScore release 0.9.0
Dataset results
14 results for “air turbulence”
Data for "Schlieren and BOS velocimetry of a round turbulent helium jet in air"
<p>This is a subset of data used in our publication <a href="https://arxiv.org/abs/2202.04122">Schlieren and BOS velocimetry of a round turbulent helium jet in air</a> </p> <p> </p> <p>In the four helium-jet schlieren-image datasets given below, the nozzle diameter is 1.4 mm, the camera frame rate is 6000 fps and the individual image exposure is 0.0001667 s. 3000 images are provided for each dataset, or 1/2 s in real-time, which we determined to provide statistically-adequate data. Please see the <a href="https://arxiv.org/abs/2202.04122">paper</a> for more detail.</p> <p><strong>20210125-Run1</strong>: traditional mirror-schlieren, $Re_d = 5,890$, $U_j = 436$ m/s, and the scale is 0.29 mm/pixel.</p> <p><strong>20210206-Run1</strong>: traditional mirror-schlieren, $Re_d = 11,300$, $U_j = 682$ m/s, and the scale is 0.29 mm/pixel.</p> <p><strong>20210419-Run1</strong>: background-oriented schlieren (BOS), $Re_d = 5,890$, $U_j = 436$ m/s, and the scale is 0.26 mm/pixel. These are raw BOS images that must be processed with a reference image in order to yield pseudo-schlieren results. The reference (flow-off, tare) image is the first image in the sequence and is so named.</p> <p><strong>20210420-Run1</strong>: background-oriented schlieren (BOS), $Re_d = 11,300$, $U_j = 682$ m/s, and the scale is 0.26 mm/pixel. These are raw BOS images that must be processed with a reference image in order to yield pseudo-schlieren results. The reference (flow-off, tare) image is the first image in the sequence and is so named.</p>
Database: Influence of large-scale freestream turbulence on bypass transition in air and organic vapour flows
<p>This is an open-access database of numerical simulations of freestream-turbulence induced transitions of zero-pressure-gradient flat plates boundary layers. The data have been collected at Arts et Metiers Institute of Technology, at DynFluid laboratory, in the period 2021-2024 within the REGAL-ORC project- REal GAs effects on Loss mechanisms of ORC turbine flows, a project in collaboration with FH Münster in Germany.</p> <p>Work related to the database is published in Journal of Fluid Mechanics, under the title: "Influence of large-scale freestream turbulence on bypass transition in air and organic vapour flows". The aims of this work was to investigate freestream-turbulence induced transitions, in particular under relatively large integral length scale, of air and organic vapors boundary layers.</p> <p>This version contains evolutions of averaged quantities in the streamwise direction, along with profiles and spectra in the boundary layer for all the different simulations performed. This database is supplemented with python codes to read the data and descriptions of the data in the headers and README files.</p>
The Sensitivity of Southern Ocean Air-Sea Carbon Fluxes to Background Turbulent Diapycnal Mixing Variability
<p> </p> <p>The mixing map for background diapycnal diffusivity used in the paper 'The Sensitivity of Southern Ocean Air-Sea Carbon Fluxes to Background Turbulent Diapycnal Mixing Variability' in the spatially variable mixing case ExVar.</p> <p>The ExVar map is constructed as the sum of contributions from tides and topographically-generated lee waves and features horizontal and vertical variations in a background mixing rate.</p>
Data from: Turbulence organization and mean profile shapes in the stably stratified boundary layer: Zones of uniform momentum and air temperature
Open the record for dataset details and reuse information.
Data to support "Reduced winter-time Clear Air Turbulence in the trans-Atlantic region under Stratospheric Aerosol Injection by Katie L Barnes, Anthony C Jones, Paul D Williams and James M Haywood, Submitted to Geophysical Research Letters, November 2024"
<p>This dataset contains all the UKESM1 climate model output needed to reproduce Figures 1-4 in the paper "Reduced winter-time Clear Air Turbulence in the trans-Atlantic region under Stratospheric Aerosol Injection by Katie L Barnes, Anthony C Jones, Paul D Williams and James M Haywood, Submitted to Geophysical Research Letters, November 2024". UKESM1 is the Met Office Earth System Model (N96 resolution) with simulations using a fully-coupled ocean-atmosphere following CMIP6 protocol.</p> <p>All files are CF-1.7 compliant and in NetCDF format with appropriate metadata. Each file contains 6 hourly data for the 30 simulated years used in the paper (50 for the pre-industrial control period).</p> <p>The following simulations are included, following ScenarioMIP and GeoMIP specifications:</p> <p>Folder | Simulation name | Time period<br>-------------------------------------------------------------<br>piControl | PiControl | 2250-2299<br>historical | Historical | 1985-2014<br>ssp245 | SSP2-4.5 | 2070-2099<br>ssp585 | SSP5-8.5 | 2070-2099<br>g6sulfur | G6sulfur | 2070-2099</p> <p>The files use CMIP-like naming conventions.</p> <p>VARIABLE_LEVEL_TIMEPERIOD_MODEL_EXPERIMENT_STARTDATE-ENDDATE_SEASON.nc</p> <p>The variables comprise:</p> <p>Short name | Description (units, if any)<br>-------------------------------------------------------------<br>ua | zonal wind (m.s-1)<br>va | meridional wind (kg.m-3)<br>ta | air temperature (K)</p> <p>All figures in the paper were produced using Python (3.11) and Iris scientific analysis software.</p> <p>All data is Crown Copyright, Met Office, and is made available under the terms of the Non-Commercial Government Licence: http://www.nationalarchives.gov.uk/doc/non-commercial-government-licence/version/2/</p> <p>Description of the UKESM1 model is provided in Sellar, A. A., et al.: UKESM1: Description and evaluation of the U.K. Earth System Model. Journal of Advances in Modeling Earth Systems, 11, 4513–4558. https://doi.org/10.1029/2019MS001739, 2019.</p> <p>Description of the ScenarioMIP specifications are provided here: O'Neill, B. C., et al.: The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461–3482, https://doi.org/10.5194/gmd-9-3461-2016, 2016.</p> <p>Description of G6sulfur is provided here: Kravitz, B., et al. : The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results, Geosci. Model Dev., 8, 3379–3392, https://doi.org/10.5194/gmd-8-3379-2015, 2015. </p>
Data from: Dust settling from turbulent layers in the free troposphere: Implications for the Saharan Air Layer
Open the record for dataset details and reuse information.
Monthly Turbulent Flux Dataset for the Arctic Ocean using AIRS-AMSU version 6 data
Open the record for dataset details and reuse information.
The bulk parameterizations of turbulent air-sea fluxes in NEMO4: the origin of Sea Surface Temperature differences in a global model study
<p>This repository contains the code and the data used to produce the results of "The bulk parameterizations of turbulent air-sea fluxes in NEMO4: the origin of Sea Surface Temperature differences in a global model study" a discussion paper by G. Bonino, D. Iovino, L. Brodeau, S. Masina submitted to Geoscientific Model Development.</p> <p>- DATA.tar contains the 5 days model outputs to produce the figures in the manuscript.</p> <p>- CODE.tar contains the code and the namelists to run the experiments. The namelists and the modified code for run each experiments are available in the subfolder CODE/cfgs/. </p>
Data files for JGR paper "Not all Clear Air Turbulence is Kolmogorov" by Paola Rodriguez Imazio et al.
<p>The files</p> <p>adlr_20190911a-ST08-T2.nc<br> HALO-DB_dataset6560_release1_ST08_20190911a_BAHAMAS.ames</p> <p>contain the 100 Hz and 1 Hz BAHAMAS data from SOUTHTRAC research flight ST08.</p> <p>The grid-file</p> <p>wrfprs_d01.013</p> <p>contains the WRF outout produced to generate Figure 5 of the paper.</p> <p>Andreas Dörnbrack</p> <p>andreas.doernbrack@dlr.de</p> <p>July, 28 2022</p> <p> </p>
Data for clear-air turbulence calculated from high-resolution radiosonde measurements at cruising altitudes in China during the period from 2010 to 2022.
<p>The file is the turbulence dissipation rate(ε) data, calculated using high-resolution radiosonde measurements at cruising altitudes in China, during the period from 2010 to 2022. More description can be seen in the read_me.txt.</p>
Data for clear-air turbulence calculated from high-resolution radiosonde observations at cruising altitudes in China during the period from 2010 to 2022.
<p>The file is the turbulence dissipation rate(ε) data, calculated using high-resolution radiosonde measurements at cruising altitudes in China, during the period from 2010 to 2022. More description can be seen in the read me.txt.</p>
clear-air turbulence
<p>1. Clear-air turbulence:This file contains turbulence dissipation rate(ε) data, calculated using high-resolution radiosonde measurements at cruising altitudes in China, during the period from 2010 to 2022.</p> <p>2. Each year's data is placed in the same folder named "yyyy", representing the respective year.</p> <p>3. The subfile name is 'yyyymm', where yyyy represents the year, mm represents the month.</p> <p>4. The data matrix is day(28/29/30/31) x stations(119)</p> <p>day: Every day of each month</p> <p>stations: 119 radiosonde sites in China</p> <p>5. A 'nan' value in the data indicates a missing value</p>
Turbulent Air Motion Measurement System (TAMMS) IMPACTS
The Turbulent Air Motion Measurement System (TAMMS) IMPACTS dataset consists of wind speed, wind direction, and cross-wind speed measurements from the TAMMS instrument onboard the NASA P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S. Atlantic Coast (2020-2023). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to advance prediction capabilities significantly. The files are available from January 18, 2020, through February 28, 2023, in ASCII-ict format.
Turbulent Air Motion Measurement System (TAMMS) IMPACTS V1
The Turbulent Air Motion Measurement System (TAMMS) IMPACTS dataset consists of wind speed, wind direction, and cross wind speed measurements from the TAMMS instrument onboard the NASA P-3 aircraft during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. IMPACTS was a three-year sequence of winter season deployments conducted to study snowstorms over the U.S Atlantic Coast (2020-2022). The campaign aimed to (1) Provide observations critical to understanding the mechanisms of snowband formation, organization, and evolution; (2) Examine how the microphysical characteristics and likely growth mechanisms of snow particles vary across snowbands; and (3) Improve snowfall remote sensing interpretation and modeling to significantly advance prediction capabilities. The files are available from January 18, 2020 through February 26, 2020 in ASCII-ict format.
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.