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.
7
datasets available to search
ShareScore release 0.9.0
Dataset results
7 results for “Shallow cumulus”
A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus clouds based on three-dimensional Path-Tracing
<p>Dataset to produce the results of the publication: "A Stereo Camera Simulator for Large-Eddy Simulations of Continental Shallow Cumulus clouds based on three-dimensional Path-Tracing"</p><p>The dataset contains:</p><ul><li>Large-Eddy Simulation (LES) model configuration files</li><li>Selected output data of the LES experiments</li><li>Data and analysis scripts for the figures</li><li>The rendered camera images</li><li>The cloud field, cloud hulls, and reconstructed hulls</li><li>A frozen version of the open-source Blender code (version 2.90) as used in this study</li></ul><p>For the latest version of Blender, please visit:</p><p><a href="https://chat.openai.com/c/www.blender.org">www.blender.org</a></p><p>It is important to note that the method was specifically tested only on version 2.90.</p><p> </p><p>This research is supported by the German Research Foundation (DFG) under project number 430226822 (https://gepris.dfg.de/gepris/projekt/430226822). This research was supported by the U.S. Department of Energy's Atmospheric System Research, an Office of Science Biological and Environmental Research program, under grant DE-SC0022126. This work used resources of the Deutsches Klimarechenzentrum (DKRZ) granted by its Scientific Steering Committee (WLA) under project ID bb1086. The Gauss Centre for Supercomputing e.V. (https://www.gauss-centre.eu/) is acknowledged for providing computing time on the Gauss Centre for Supercomputing (GCS) supercomputer JUWELS at the Jülich Supercomputing Centre (JSC) under projects VIRTUALLAB and RCONGM.</p>
Dataset for paper "Process Modeling of Aerosol-cloud Interaction in Summertime Precipitating Shallow Cumulus over the Western North Atlantic"
<p>This dataset contains LES model input and post-processed model output used in paper "Process Modeling of Aerosol-cloud Interaction in Summertime Precipitating Shallow Cumulus over the Western North Atlantic".</p>
Supplemental materials to "A Laboratory Analogy for Mixing by Shallow Cumulus Convection"
<p>These are the supplemental materials to the paper "A Laboratory Analogy for Mixing by Shallow Cumulus Convection" published in Journal of Fluid Mechanics. DOI: <span>10.1017/jfm.2025.173</span> </p> <ul> <li>code_raw_data_video_temperature.zip - The MATLAB postprocessing code, raw video, and raw temperature profile data.</li> <li>reference_exp_S3_evolution_show.mp4 - An introductory movie of the reference experiment (S3) with an illustration. </li> <li>change_heating_voltage_F1(speed_x_5.76)_F5.mp4 - A movie about experiments that change the heating power. Experiment F1 (left panel) is accelerated with a factor of 5.76.</li> <li>change_initial_thickness_T2_T4_T5_(all_speed_x_16).mp4 - A movie about experiments that change the initial thickness of the syrup layer. All experiments are accelerated with a factor of 16.</li> <li>change_syrup_concentration_S1_S3_S7_(all_speed_x_16).mp4 - A movie about experiments that change the initial syrup concentration. All experiments are accelerated with a factor of 16. </li> <li>derivation_note.pdf - A math derivation note for some equations in the manuscript.</li> </ul> <p>If you have any questions, please contact Dr. Hao Fu: haofu736@gmail.com; haofu@uchicago.edu </p>
The Role of Cloud-Cloud Interactions in the Lifecycle of Shallow Cumulus Clouds
<ul> <li>Supporting datasets for the paper "The Role of Cloud-Cloud Interactions in the Lifecycle of Shallow Cumulus<br> Clouds", which was submitted to the Journal of Atmospheric Sciences. </li> <li>Those are a subset of post-processed datasets from WRF-LES simulation and Lagrangian tracker (Feng et al., 2018). See manuscript for more details.</li> </ul> <p>Reference: </p> <p>Feng, Z., L. R. Leung, R. A. Houze, S. Hagos, J. Hardin, Q. Yang, B. Han, and J. Fan, 2018:634<br> Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics635<br> in Convection-Permitting Simulations Over the United States. Journal of Advances in Modeling636<br> Earth Systems, 10 (7), 1470–1494, https://doi.org/10.1029/2018MS001305.637<br> 30</p> <p> </p>
Data for Understanding the moisture variance in precipitating shallow cumulus convection
<p>Data accompanying the paper titled: Understanding the moisture variance in precipitating shallow cumulus convection .</p> <p> </p> <p>This repository contains configuration files and output statistics for three idealized simulations run with LES model MicroHH (van Heerwaarden et al., 2017). </p> <p><br> The experimental setup of all cases is based on the Rain in Cumulus over the Ocean (RICO) field experiment as used in the GEWEX Cloud System Study (GCSS) RICO model inter comparison study (Rauber et al., 2007; vanZanten et al, 2011). The experiment, defined as the standard case (referenced as STD), uses the GCSS configuration, while the second experiment, termed as the moist case (referenced as MST), is initialized with an increased moisture content in the cloud layer and above of about 2 g/kg. Both of these experiments cover a domain size of 50 x 50 x 6 km with an isotropic grid spacing of 25 m. The control simulation (referenced as CTRL) is a non-precipitating reference simulation. The setup for the control case is identical to the setup of the standard case, except for a smaller domain size of 8 x 8 x 6 km.</p> <p> </p> <p> </p> <p>The files are organized in the following way: </p> <p>Each case has its own folder (CTRL, MST, and STD). </p> <p>Each such folder contains a 'setup' sub-folder with the configuration files for the microHH simulation: an '.ini' file and a '.py' file that generates initial conditions and forcings. </p> <p>Output statistics are located in the 'statistics_output' sub-folders. They contain '.nc' files with statistics from 30 h to 35 h of the simulation. Conditional spatial averaging was performed in order to understand the significance of the convective regions. Files valid for cloud active regions are marked with '_CA'. Files valid for non active regions are marked with '_NA' (Bastak Duran, Geleyn, Vana, Schmidli, & Brozkova, 2018). Files without '_CA' or '_NA' are valid for the whole domain.</p>
Data for submitted manuscript "Connections between Sub-cloud Coherent Structures and the Life Cycle of Shallow Cumulus Clouds: Evidence from Large Eddy Simulation"
<p>This is the dataset for a submitted manuscript "Connections between Sub-cloud Coherent Structures and the Life Cycle of Shallow Cumulus Clouds: Evidence from Large Eddy Simulation" for peer review.</p> <p>The NetCDF file includes masked objects for sub-cloud coherent structures and cloud for tracking.</p>
"Halo Region around Shallow Cumulus Clouds in Large Eddy Simulations"
<p>This dataset is used to examine the halo regions around shallow cumulus clouds. We performed large eddy simulations of shallow cumulus clouds based on the Barbados Oceanographic and Meteorological Experiment (BOMEX) using Met Office-NERC (National Environment Research Concil) Cloud model (MONC). A set of simulations with different model resolutions is performed. The available horizontal grid spacings are 10 m, 25 m, 50 m and 100 m and the corresponding vertical resolutions are 10 m, 25 m, 25 m, and 40 m, respectively. All simulations have the same model top, that is, 3 km. To save the computational cost, we use the same horizontal grid boxes (600 X 600). To test the robustness, we perform sensitivity simulations with modified mixing length scales in the sub-grid scale turbulence scheme. We also perform large eddy simulations using another numerical model, Cloud Model 1 (CM1) to check if the results are sensitive to the numerical details (advection schemes) and domain size. The simulations with CM1 have the same model resolution configurations as in MONC, but they have the same domain size (7.2 X 7.2 X 3)km^3. For more details of the simulation set up, please refer to our submitted paper. As the whole simulation has a huge dataset, we only choose part of the results that can reproduce the figures in our submitted paper for repository. </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.