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 “LES modeling”
Challenges of constructing and selecting the "perfect" initial and boundary conditions for the LES model PALM
<p><strong>README</strong></p> <p>All the supplementary data needed for the reproduction of the experiment described in the manuscript are provided on this ZENODO repository. The supplementary data includes the following:<br>1. IBC-pre-post-process-revised.zip which contains:<br> - Radio sounding data used for vertical profile statistical and visual comparison. They are stored as "CHMU-soundings.dat" in the CHMU_soundings directory<br> - code for making the figures for vertical profile comparison between the WRF and PALM model<br> - code for performing the statistical analysis for the vertical profiles of PALM and the WRF model<br> - code for making the scatter plots of PALM and WRF vertical profiles<br> - code for making the heatmaps of the PALM model data</p> <p>2. PALM_code.zip contains the source code for the current version of the PALM model used for this experiment</p> <p>3. palm_inputs.zip contains:<br> - static driver file<br> - dynamic driver file<br> - configuration files for the first PALM run (p3d), and the configuration files for the restart runs (p3dr)<br>for each of the performed simulations</p> <p>4. postproc.zip contains:<br> - the code for performing statistical analysis for minimum (min), average (Avg), and maximum (max) three-day averaged differences for the WRF and PALM model outputs<br> - the code for making figures of the differences between selected pairs of WRF and PALM model outputs</p> <p>5. wrf_namelist.zip contains:<br> - list of files in which the setups/configuration for the WRF ensemble used in this experiment</p> <p><strong>PALM MODEL INSTALLATION AND USAGE GUIDE</strong></p> <p>A. Installation:</p> <p>1. First, make sure to satisfy the Software Requirements. On Debian-based Linux Distributions, this can be achieved by the following command:</p> <p><code>sudo apt-get install gfortran g++ make cmake coreutils libopenmpi-dev openmpi-bin libnetcdff-dev netcdf-bin libfftw3-dev python3-pip python3-pyqt5 flex bison ncl-ncarg</code></p> <p>2. Also, some additional python dependencies are needed, which can be installed using pip. In case you want to use a virtual environment for these dependencies, please make sure to create one first. Afterwards, you can install the python dependencies by executing the following command:</p> <p><code>python3 -m pip install -r requirements.txt</code></p> <p>3. Now the PALM model system can be installed with the following commands (please replace with the desired installation directory):</p> <p><code>export install_prefix=""</code><br><code>bash install -p ${install_prefix}</code><br><code>export PATH=${install_prefix}/bin:${PATH}</code></p> <p>4. The following optional command permanently adds this installation to your bash environment:</p> <p><code>echo "export PATH=${install_prefix}/bin:\${PATH}" >> ~/.bashrc</code></p> <p>5. Type <code>bash install -h</code> to get all available options of the install script. During installation, the script calls the respective install script of all packages in this repository and installs them to the chosen directory. Therefore, it is not necessary to manually install any of the packages.</p> <p>You can test your installation with the following commands:</p> <p><code>palmtest --cases urban_environment_restart --cores 4</code></p> <p>B. Usage:</p> <p>After a successful installation, the executables for all packages have been linked into the directory /bin and a default PALM configuration file can be found at /.palm.config.default. In case you have installed the python dependencies inside a virtual environment, that environment needs to be active whenever you wand to use PALM. For usage of each of the packages, please refer to their individual documentation. Next, you need to create your first PALM setup in order to start a simulation. To get a simple preconfigured setup and start your first PALM simulation, please execute the following sequence of commands:</p> <p><code>mkdir -p "${install_prefix}/JOBS/example_cbl/INPUT"</code><br><code>cp "packages/palm/model/tests/cases/example_cbl/INPUT/example_cbl_p3d" "${install_prefix}/JOBS/example_cbl/INPUT/"</code><br><code>cd ${install_prefix}</code><br><code>palmrun -r example_cbl -c default -a "d3#" -X 4 -v -z</code></p>
Analysis of a complex role of trees in street canyon using LES model (experiment: Terronska)
<h1>README</h1> <p>This is a companion dataset to the paper <em>Analysis of a complex role of trees in street canyon using LES</em> model by <em>Řezníček et al.</em>, to be submitted to <em><span>Quarterly</span> <span>Journal</span> of the Royal Meteorological Society</em>. All the supplementary data needed for the reproduction of the experiment described in the manuscript are provided on this ZENODO repository. The supplementary data includes the following:</p> <p>1. <em>01_palm_source_code.zip</em> contains the source code for the current version of the PALM model used for this experiment</p> <p>2. <em>02_inputs-configs.zip</em> which contains:</p> <ul> <li>static driver files (for cases 01 = full-trees, 02 = half-trees, 03 = no-strees)</li> <li>dynamic driver files (for different winds directions W = west, SW = southwest, S = south and stratifications C = convective, N = neutral + stable)</li> <li>configuration files for the first PALM run (p3d), and the configuration files for the restart runs (p3dr) for each of the performed simulations</li> <li>the files with N02 are apllied for child domain</li> </ul> <p>3. 03_maps-GIS contains maps in gis or png format with one hour averages outputs: </p> <ul> <li>the cases are terC/N_W/SW/S_01/02/03 for the stratifications, wind direcrions and trees-scenario (see the legend above)</li> <li>abs for absolute values, diff for differences from no-tree scenario, 01h = 1 hour average</li> <li>variables are bio_UTCI - universal thermal climate index [deg C], kc_PM10 = PM10 concentration in 2m or 10m height [<span>μ</span>/m^3], theta_2m = temperature in 2m [deg C], wspeed_10m = wind-speed in 10m, tsurf = surface temperature [deg C], rad_sw_in = incoming shortwave radiation flux [W/m^2] and rad_lw_out = outgoing longwave radiation flux [W/m^2]</li> </ul> <p>4. 04_cuts contains svg and png plots with vertical and horizontal (xy) cuts </p> <ul> <li>the cases are terC/N_W_01/02/03 for the stratifications and trees-scenario (see the legend above) and west winds</li> <li>jugp-ciirc = the vertical cut for (JugP) street (near the ciirc-CTU building), terr-street = the vertical cut for (Terr) street</li> </ul> <h1>PALM MODEL INSTALLATION AND USAGE GUIDE</h1> <h2>A. Installation</h2> <p>1. First, make sure to satisfy the Software Requirements. On Debian-based Linux Distributions, this can be achieved by the following command:</p> <p><code>sudo apt-get install gfortran g++ make cmake coreutils libopenmpi-dev openmpi-bin libnetcdff-dev netcdf-bin libfftw3-dev python3-pip python3-pyqt5 flex bison ncl-ncarg</code></p> <p>2. Also, some additional python dependencies are needed, which can be installed using pip. In case you want to use a virtual environment for these dependencies, please make sure to create one first. Afterwards, you can install the python dependencies by executing the following command:</p> <p><code>python3 -m pip install -r requirements.txt</code></p> <p>3. Now the PALM model system can be installed with the following commands (please replace with the desired installation directory):</p> <p><code>export install_prefix=""</code><br><code>bash install -p ${install_prefix}</code><br><code>export PATH=${install_prefix}/bin:${PATH}</code></p> <p>4. The following optional command permanently adds this installation to your bash environment:</p> <p><code>echo "export PATH=${install_prefix}/bin:\${PATH}" >> ~/.bashrc</code></p> <p>5. Type <code>bash install -h</code> to get all available options of the install script. During installation, the script calls the respective install script of all packages in this repository and installs them to the chosen directory. Therefore, it is not necessary to manually install any of the packages.</p> <p>You can test your installation with the following commands:</p> <p><code>palmtest --cases urban_environment_restart --cores 4</code></p> <h2>B. Usage</h2> <p>After a successful installation, the executables for all packages have been linked into the directory <code>/bin</code> and a default PALM configuration file can be found at <code>/.palm.config.default</code>. In case you have installed the python dependencies inside a virtual environment, that environment needs to be active whenever you wand to use PALM. For usage of each of the packages, please refer to their individual documentation. Next, you need to create your first PALM setup in order to start a simulation. To get a simple preconfigured setup and start your first PALM simulation, please execute the following sequence of commands:</p> <p><code>mkdir -p "${install_prefix}/JOBS/example_cbl/INPUT"</code><br><code>cp "packages/palm/model/tests/cases/example_cbl/INPUT/example_cbl_p3d" "${install_prefix}/JOBS/example_cbl/INPUT/"</code><br><code>cd ${install_prefix}</code><br><code>palmrun -r example_cbl -c default -a "d3#" -X 4 -v -z</code></p> <h1>ACKNOWLEDGEMENT</h1> <p>This research was supported by the Johannes Amos Comenius Programme (OP JAC), project No. CZ.02.01.01/00/22_008/0004605, Natural and anthropogenic<br>georisks.</p> <p>The dataset is published under the Creative Commons Attribution 4.0 International License (CC-BY-4.0). This license allows others to distribute, remix, adapt, and build upon the dataset for any purpose, even commercially, as long as they give appropriate credit to the original creator(s).</p>
Codes and datasets associated with the paper "Dynamic LES modeling of a diurnal cycle"
<p>Here, you will find some of the codes, images, and datasets utilized in the article: </p> <p>Basu et al. (2008). "Dynamic LES modeling of a diurnal cycle", Journal of Applied Meteorology and Climatology, 47, 1156-1174. (<a href="https://journals.ametsoc.org/doi/pdf/10.1175/2007JAMC1677.1">https://journals.ametsoc.org/doi/pdf/10.1175/2007JAMC1677.1</a>)</p> <p>Matlab codes: MatlabCodes.tar.gz (Contains all the analyses and visualization codes used in the paper)</p> <p>Observational data: Wangara_Observations.tar.gz (These data were manually typed directly from the original Wangara document)</p> <p>LES data (binary): LES_160x160x160.tar.gz and LES_80x80x80.tar.gz</p>
CFD Modeling Results and Related Data and Codes for Plotting of "A Mesoscale-to-LES Modeling of Tornado-like Vortex and Associated Local Strong Winds in Urban Area"
<p>The CFD modeling outputs, derived maximum wind fields in the analysis area, the topography data, the Python codes used to produce the figures, as we as the namelist of WRF simulation are available. The CFD modeling outputs are in binary format. The ctl. files of corresponding binary data (or dataset if ordered chronologically) are available in each directory (named after each experiment in our study).</p>
Diablo model output for LES basal slope effects study
Open the record for dataset details and reuse information.
Output Data from the CLASS model, the CLASS-L model, and the LES.
<p>These data sets are for the work documented in Modifications to the CLASS Boundary Layer Model for Improved Interaction between the Mixed Layer and Clouds (https://doi.org/10.1029/2023MS004202).</p> <p>Please download these data first to run "Plotcode_Open.m" available at https://doi.org/10.5281/zenodo.11186607.</p>
Reference LES Simulations for Ocean Models Validation
<p>All Large-Eddy Simulations (LES) computations are conducted with the open-source PALM solver (<a href="https://palm.muk.uni-hannover.de/trac">https://palm.muk.uni-hannover.de/trac</a>) and version 5.0 of the Los Alamos National Laboratory (<a href="https://github.com/lanl/palm_lanl">https://github.com/lanl/palm_lanl</a>) branch. The simulations use a cubical domain with length L=128m, three grid resolutions (N=128<sup>3</sup>, 256<sup>3</sup>, or 512<sup>3</sup>), and mimic four single-column canonical oceanic regimes in which the surface flux and background stratification profiles are imposed. These simulations are named cooling (c), stratification (s), evaporation (e), and mixed (m):</p> <ul> <li><strong>cooling cases</strong> test different surface heat fluxes: Q<sub>h</sub>=-1.185x10<sup>-5</sup> (c<sub>01</sub>), -2.371x10<sup>-5</sup> (c<sub>02</sub>), -4.742x10<sup>-5</sup> (c<sub>04</sub>), and -18.966x10<sup>-5</sup> (c<sub>16</sub>) [K.m/s]. The background stratification is set through a vertical temperature gradient (T<sub>z</sub>) equal to 0.1 [K/m], and both the salinity surface flux (Q<sub>s</sub>) and the background stratification due to vertical salinity gradient (S<sub>z</sub>) are equal to zero.</li> <li><strong>stratification cases</strong> are similar to the cooling c<sub>02</sub> case, but Q<sub>h</sub>=-2.371x10<sup>-5</sup> [K.m/s], and T<sub>z</sub>=0.01 (s<sub>01</sub>), 0.1 (s<sub>10</sub>), or 0.2 (s<sub>20</sub>) [K/m].</li> <li><strong>evaporation cases</strong> define Q<sub>h</sub>=T<sub>z</sub>=0, S<sub>z</sub>=-0.025 [PSU/m], and Q<sub>s</sub>=3.115x10<sup>-6</sup> (e<sub>01</sub>) or 1.225x10<sup>-5</sup> (e<sub>04</sub>) [PSU/(m<sup>2</sup>.s)].</li> <li><strong>mixed cases</strong> combine heat and salinity surface fluxes, and the background stratification is imposed by both vertical temperature and salinity gradients. There are four mixed cases in which Q<sub>h</sub>=-1.185x10<sup>-6</sup> [K.m/s], T<sub>z</sub>=0.05 [K/m], S<sub>z</sub>=-0.025 [PSU/m], and Q<sub>s</sub> is either 0 (m<sub>01</sub>), 3.115x10<sup>-6</sup> (m<sub>02</sub>), 9.10x10<sup>-6</sup> (m<sub>03</sub>), or 4.55x10<sup>-5</sup> (m<sub>04</sub>) [PSU/(m<sup>2</sup>.s)].</li> </ul> <p>The simulations run 96h at a latitude of 43.29<sup>o</sup>, and utilize a linear equation of state where the reference temperature and salinity are 293.15 K and 35 PSU. The subgrid turbulent scales are modeled through the Moeng and Wyngaard SGS closure (see PALM documentation), and the flow is perturbed during the first 150 s of simulation with normally distributed fluctuations with a maximum amplitude of 10<sup>-4</sup>. The dataset provides 1D and 3D statistics. The 1D profiles are time-averaged during 3600 s and written every 3600 s. The 3D fields are not time-averaged and written every 3600 s, except those obtained with the grid having 512<sup>3</sup> points. In this case, the data are written every 21,600 s. The 3D fields are not in the tar file but can be requested by emailing the authors (fmsoarespereira@lanl.gov). The PALM input decks of the simulations are included in the shared files.<br> <br> <strong>Note:</strong> the PALM version used in this work requires the 1D salinity flux profiles to be normalized by the product of N<sub>x </sub>and<sub> </sub>N<sub>y </sub>(number of grid points in x and y)</p> <p> </p> <p><strong>LA-UR-22-32996</strong></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.