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.
364
datasets available to search
ShareScore release 0.9.0
Dataset results
364 results for “Convection”
The corona of a fully convective star with a near-polar flare
<p>Raw XMM-Newton EPIC data, data reduction scripts for XMM-SAS, and reduced images and spectra extracted with XSPEC. The observations include the X-ray emission of TIC 277539431, a rapidly rotating M7 dwarf star that produced a polar flare in 2021, observed by the Transiting Exoplanet Survey Satellite (see <a href="https://ui.adsabs.harvard.edu/abs/2021MNRAS.507.1723I">Ilin et al. 2021</a>).<br> <br> Publications based on this data set will be linked as they appear.</p>
Gridcell response to widespread afforestation using a Convection Permitting Model
<p>This folder contains gridcell absolute differences due to afforestation in:</p> <p>1. Evaporation<br> 2. Rainfall<br> 3. Runoff<br> 4. Overall Soil Moisture</p> <p>These are calculated for the overall period and for each season by calculating the difference between the afforestation and control land cover scenarios.</p> <p>There are also two maps which show the change in the topsoil moisture and the second layer below for summer.</p>
Datasets for 2D Vertical Convection: Base States and Leading Linear Modes using Snek5000-cbox
<p>This repository contains two types of datasets related to 2D vertical convection analysis, generated using the snek5000-cbox simulation framework. The first dataset includes base states computed with the Selective Frequency Damping (SFD) method, considering various aspect ratios and Prandtl numbers. The second dataset provides the decomposed amplitude, phase, frequency, and omega of the leading linear mode, accompanied by the corresponding base states for different aspect ratios and Prandtl numbers. All datasets are stored in the .h5 file format for easy access and analysis. The scripts used to produce the datasets are provided in the repository https://github.com/snek5000/snek5000-cbox/tree/main/doc/scripts/2022sidewall_conv_instabilities.</p>
Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia: companion dataset
<p>This folder includes the intermediate data for the following manuscript:</p><p>Ding et al., Impact of Convection-permitting and Model Resolution on the Simulation of Mesoscale Convective System Properties over East Asia</p><p>The simulations were done using ICON-NWP (ICON Numerical Weather Prediction) model, version 2.6.1, over Asian monsoon region (62E–150E, 5.5N–54.5N) for 2020 summer. At the moment, we upload the intermediate data for MCS tracking. For more data, please contact the authors.</p>
Sub-Lithospheric Small-Scale Convection Tomographically Imaged Beneath the Pacific Plate
Open the record for dataset details and reuse information.
Processed GPM-DPR Convective Profiles (April 2014 - November 2023)
Open the record for dataset details and reuse information.
Turbulent Mechanisms for the Deep Convective Boundary Layer in the Taklimakan Desert
Open the record for dataset details and reuse information.
High-CAPE summer convection in large-domain large-eddy simulations with ICON - model and observational data sets
<p>Data sets including all observational and ICON model data for publication in Atmosperic Chemistry and Physics Journal (ACP) - "High-CAPE summer convection in large-domain large-eddy simulations with ICON"</p>
Dataset for 'Rotational dependence of turbulent transport coefficients in global convective dynamo simulations of solar-like stars'
<p>For moderate and slow rotation, magnetic activity of solar-like stars is observed to strongly depend on rotation, while for rapid rotation, only a very weak or no dependency is detected. These observations do not yet have a solid explanation in terms of dynamo theory. To work towards such an explanation, we numerically investigated the rotational dependency of dynamo drivers in solar-like stars, that is, stars that have a convective envelope of similar thickness as in the Sun. We ran semi-global convection simulations of stars with rotation rates from 0 to 30 times the solar value, corresponding to Coriolis numbers, Co, of 0 to 110. We measured the turbulent transport coefficients describing the magnetic field evolution with the help of the test-field method, and compared with the dynamo effect arising from the differential rotation, self-consistently generated in the models. The trace of the <strong><span class="math-tex">\(\alpha\)</span></strong> tensor increases for moderate rotation rates with Co<sup>0.5</sup> and levels off for rapid rotation. This behavior is in agreement with the kinetic <span class="math-tex">\(\alpha\)</span> based on the kinetic helicity, if one takes into account the decrease of the convective scale with increasing rotation. The <strong><span class="math-tex">\(\alpha\)</span></strong> tensor becomes highly anisotropic for Co > 1, <span class="math-tex">\(\alpha_{rr}\)</span> dominates for moderate rotation (1<Co<10), and <span class="math-tex">\(\alpha_{\phi\phi}\)</span> for rapid rotation (Co > 10). The effective meridional flow, taking into account the turbulent pumping effects, is markedly different from the actual meridional circulation profile. Hence, the turbulent pumping effect is dominating the meridional transport of the magnetic field. Taking all dynamo effects into account, we find three distinct regimes. For slow rotation, the <span class="math-tex">\(\alpha\)</span> and Rädler effects are dominating in presence of anti-solar differential rotation. For moderate rotation, <span class="math-tex">\(\alpha\)</span> and <span class="math-tex">\(\Omega\)</span> effects are dominant, indicative of <span class="math-tex">\(\alpha\Omega\)</span> or <span class="math-tex">\(\alpha^2\Omega\)</span> dynamos in operation, producing equatorward-migrating dynamo waves with the qualitatively solar-like rotation profile. For rapid rotation, an <span class="math-tex">\(\alpha^2\)</span> mechanism, with an influence from the Rädler effect, appears to be the most probable driver of the dynamo. Our study reveals the presence of a large variety of dynamo effects beyond the classical <span class="math-tex">\(\alpha\Omega\)</span> mechanism, which need to be investigated further to fully understand the dynamos of solar-like stars. The highly anisotropic <strong><span class="math-tex">\(\alpha\)</span></strong> tensor might be the primary reason for the change of axisymmetric to non-axisymmetric dynamo solutions in the moderate rotation regime.</p> <p>For the full article see <a href="https://arxiv.org/abs/1910.06776">https://arxiv.org/abs/1910.06776</a></p>
Supplement to the article "Predicting the morphology of ice particles in deep convection using the super-droplet method" (Shima et al., 2020, GMD)
<p>This is a supplement to the article "Predicting the morphology of ice particles in deep convection using the super-droplet method" authored by Shin-ichiro Shima, Yousuke Sato, Akihiro Hashimoto, and Ryohei Misumi, published in Geosci. Model Dev., 2020.</p> <p>Typical realization of CTRL, simulated by SCALE-SDM 0.2.5-2.2.0</p> <ul> <li>Movie01.QHYD_TYP-CTRL_2.2.0.gif: Spatial structure of the cumulonimbus</li> <li>Movie02.M-D_TYP-CTRL_2.2.0.gif: Mass-dimension relationship of the ice particles</li> <li>Movie03.phi-D_TYP-CTRL_2.2.0.gif : Aspect ratio–dimension relationship of the ice particles</li> <li>Movie04.rho-D_TYP-CTRL_2.2.0.gif : Apparent density–dimension relationship of the ice particles</li> <li>Movie05.V-D_TYP-CTRL_2.2.0.gif : Velocity-dimension relationship of the ice particles</li> </ul> <p>One realization of DX/2, simulated by SCALE-SDM 0.2.5-2.2.0</p> <ul> <li>Movie06.QHYD_DXx0.5_2.2.0.gif: Spatial structure of the cumulonimbus</li> </ul> <p>The same setup as Moves 1-5 (typical realization of CTRL) is used, but simulated by SCALE-SDM 0.2.5-2.2.1</p> <ul> <li>Movie07.QHYD_TYP-CTRL.2.2.1.gif: Spatial structure of the cumulonimbus</li> <li>Movie08.M-D_TYP-CTRL_2.2.1.gif: Mass-dimension relationship of the ice particles</li> <li>Movie09.phi-D_TYP-CTRL_2.2.1.gif: Aspect ratio–dimension relationship of the ice particles</li> <li>Movie10.rho-D_TYP-CTRL_2.2.1.gif: Apparent density–dimension relationship of the ice particles</li> <li>Movie11.V-D_TYP-CTRL_2.2.1.gif: Velocity-dimension relationship of the ice particles</li> </ul> <p>The same setup as Moves 1-5 (typical realization of CTRL) is used, but simulated by SCALE-SDM 0.2.5-2.2.2</p> <ul> <li>Movie12.QHYD_TYP-CTRL.2.2.2.gif: Spatial structure of the cumulonimbus</li> <li>Movie13.M-D_TYP-CTRL_2.2.2.gif: Mass-dimension relationship of the ice particles</li> <li>Movie14.phi-D_TYP-CTRL_2.2.2.gif: Aspect ratio–dimension relationship of the ice particles</li> <li>Movie15.rho-D_TYP-CTRL_2.2.2.gif: Apparent density–dimension relationship of the ice particles</li> <li>Movie16.V-D_TYP-CTRL_2.2.2.gif: Velocity-dimension relationship of the ice particles</li> </ul>
The MATLAB code for "A kinematic model for understanding rain formation efficiency of a convective cell"
<p>Please check the code for the 1D model and the plotting commands. Please start from main.m </p>
CFD analysis of natural convection cooling of the in-vessel components during a shutdown of the EU DEMO fusion reactor (dataset)
<p>Simulation file for the publication "CFD analysis of natural convection cooling of the in-vessel components during a shutdown of the EU DEMO fusion reactor" submitted to <em>Fusion Engineering and Design</em>.</p> <p>Work carried out within the framework of the EUROfusion Consortium.</p> <p>Needs Simcenter STAR-CCM+ v2019.3 to be viewed.</p>
Data for "A Generalized Mixing Length Closure for Eddy-Diffusivity Mass-Flux Schemes of Turbulence and Convection"
<p>This folder contains the data used in the publication: </p> <p>Lopez-Gomez, I., Cohen, Y., He, J., Jaruga, A., Schneider, T., 2020: A Generalized Mixing Length Closure for Eddy-Diffusivity Mass-Flux Schemes of Turbulence and Convection, Journal of Advances in Modeling Earth Systems.</p> <p>If you make use of this data in your work, please cite our paper when doing so.</p>
Data for "Aerosol invigoration of atmospheric convection through increases in humidity"
<p>Codes, simulation input files, and simulation output data supporting “Aerosol invigoration of atmospheric convection through increases in humidity”. Enclosed README files provide detailed descriptions of the archive contents.</p>
Impact of Different Nesting Methods on the Simulation of a Severe Convective Event Over South Korea Using the Weather Research and Forecasting Model
<p>The data from various platforms (NCEP FNL, TRMM, ERA5, AWS) and WRF Model output utilised to generate the figures in the current study (https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2020JD033084) are available at this Zenodo data repository.</p>
Dataset for "Galileo observation of electron spectra dawn-dusk asymmetry in the middle Jovian magnetosphere: Evidence for convection electric field"
<p>This dataset contains the numerical values used to generate the figures in the main article and supporting information.</p>
Flash propagation and inferred charge structure relative to radar-observed ice alignment signatures in a small Florida Mesoscale Convective System
<p>Data for paper of above title, submitted to <em>Geophysical Research Letters</em>, June 2017. Manuscript number: 2017GL072767</p>
Data for 'Strengthening of the f mode due to subsurface magnetic fields in simulations of convection'
<p>Simulation output and postprocessing scripts for 'Strengthening of the f mode due to subsurface magnetic fields in simulations of convection' (<a href="https://arxiv.org/abs/2409.14840">https://arxiv.org/abs/2409.14840</a>). </p>
Final Version of the Data associated to the publication "A Benchmark for Finite Prandtl Number Convection: Comparison of Boltzmann and Navier-Stokes Solutions"
<p>Final Version of V_rms and Nu for the three codes, GAIA, StreamV, TLBM, used for a benchmark manuscript titled "A Benchmark for Finite Prandtl Number Convection: Comparison of Boltzmann and Navier-Stokes Solutions", Authors: Gabriele Morra, Peter Mora, Christian Huttig, Nicola Tosi, Henri Samuel, David A. Yuen</p> <p>The Zip file contains both npy and out versions of V_rms and Nu. In the out files, time is embedded in each file. In the "npy" version, time is a separate npy file. In this final version, pdf figures for each case are also embedded.</p>
Code and data for RCEMIP-II: Mock-Walker Simulations as Phase II of the Radiative-Convective Equilibrium Model Intercomparison Project
<p>Model configuration code and post-processed data for simulations with SAM6.11.2 (Khairoutdinov and Randall, 2003) and CAM6 (https://github.com/ESCOMP/CESM/releases/tag/release-cesm2.1.3) needed to reproduce figures in the protocol paper for RCEMIP-II (Wing et al., 2023):</p> <p>Wing, A. A., Silvers, L. G., and Reed, K. A.: RCEMIP-II: Mock-Walker Simulations as Phase II of the Radiative-Convective Equilibrium Model Intercomparison Project, Geosci. Model Dev. Discuss. [preprint], https://doi.org/10.5194/gmd-2023-235, in review, 2023.</p> <p>SAM6.11.2 data (SAM6.11.2-lambda6000.zip and SAM6.11.2-lambda6144.zip):</p> <ul> <li>lambda6000: simulations with wavelength 6000 km</li> <li>lambda6144: simulations with wavelength 6144 km</li> <li>Each simulation, for a given mean SST ($SST) and delta SST ($dT) has the following data files <ul> <li>crh_avg_$SST_$dT.mat: column relative humidity averaged over the short (y) dimension, as a function of x and time.</li> <li>mockwalker2048x128x74_3km_12s_$SST_$dT.nc: domain-averaged 0D (function of t) and 1D (function of z and t) data <ul> <li>The "long" simulations, which have a domain that is twice as long as normal, instead have files with names mockwalker4096x128x74_3km_12s_$SST_$dT.nc</li> <li>The "wide" simulations, which have a domain that is twice as wide as normal, instead have files with names mockwalker2048x256x74_3km_12s_$SST_$dT.nc</li> <li>The "longwide" simulations, which have a domain that is twice as long and twice as wide as normal, instead have files with names mockwalker4096x256x74_3km_12s_$SST_$dT.nc</li> </ul> </li> <li>SAM_CRM_MW_$SST_$dT_1D_cldfrac_avg.nc: domain cloud fraction profile (function of z and t) following cfv2 definition of Stauffer and Wing (2022)</li> </ul> </li> </ul> <p>SAM6.11.2 configuration files (SAM6.11.2-lambda6000-config.zip and SAM6.11.2-lambda6144.zip):</p> <ul> <li>lambda6000: simulations with wavelength 6000 km</li> <li>lambda6144: simulations with wavelength 6144 km</li> <li>Each simulation, for a given mean SST and delta SST has the following configuration files <ul> <li>snd: Initial sounding</li> <li>prm: Namelist parameters</li> <li>grd: Vertical grid</li> <li>domain.f90: Domain size and number of subdomains</li> <li>simpleocean.f90: SST specification</li> </ul> </li> </ul> <p>CAM6 data (CAM6.zip):</p> <ul> <li>Each simulation, for a given mean SST ($SST) and delta SST ($dT) has the following data files <ul> <li>MockWalk54_humidity_HCF_$dT_$SST.nc: column relative humidity averaged over 4 longitude points, as a function of latitude and time.</li> <li>CAM6_MockW_$dT_cos_$SST_3_yr_HCF_0D_rlut_avg.nc: domain-averaged longwave flux at the top of the atmosphere</li> <li>CAM6_MockW_$dT_cos_$SST_3_yr_HCF_0D_rsut_avg.nc: domain-averaged upwelling shortwave flux at the top of the atmosphere</li> <li>CAM6_MockW_$dT_cos_$SST_3_yr_HCF_0D_rsdt_avg.nc: domain-averaged downwelling shortwave flux at the top of the atmosphere</li> <li>CAM6_MockW_$dT_cos_$SST_3_yr_HCF_1D_cldfrac_avg.nc: domain-averaged cloud fraction profile (function of z and t)</li> </ul> </li> </ul> <p>CAM6 configuration files (CAM6-MW295dT1p25-config.tar, CAM6-MW300dT1p25-config.tar, CAM6-MW305dT1p25-config.tar): Contains model initialization and configuration files for simulations with delta SST = 1.25 K. Simulations with other delta SST values need only change the delta SST parameter. </p>
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.