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1,028 results for “simulation model”
Dataset and results for "Comparing machine learning and deep learning models for probabilistic post-processing of satellite precipitation-driven streamflow simulation"
<p>Dataset and results for "Comparing machine learning and deep learning models for probabilistic post-processing of satellite precipitation-driven streamflow simulation"</p> <p>Yuhang Zhang1, Aizhong Ye1*, Phu Nguyen2, Bita Analui2, Soroosh Sorooshian2, Kuolin Hsu2</p> <p>1 State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.</p> <p>2 Center for Hydrometeorology and Remote Sensing, Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, California, CA 92697, USA.</p> <p>## Dataset </p> <p>Streamflow simulations from one observed precipitation (CMA) and three satellite precipitation products (PDIR, IMERG-F, and GSMaP) for 522 sub-basins.</p> <p>- Q-CMA (streamflow reference)<br> - Q-PDIR (uncorrected)<br> - Q-IMERGF (uncorrected)<br> - Q-GSMAP (uncorrected)</p> <p>### Data structure</p> <p>- Head section (row1-row5)<br> - SubNO: 522 <br> - BeginT: 2003-01-01 00:00 <br> - EndT: 2019-12-31 00:00 <br> - Interval: 1440s (daily)<br> - Revise: 10 (scaling factor to keep int datatype)<br> - Point1 Point2 ... (Subbasin No.)<br> - Data section<br> - 6209 rows, 522 cols</p> <p>## Results</p> <p>Two post-processing model results for test period (2015-1-1 to 2018-12-31).</p> <p>### Data structure</p> <p>- 1462 rows, every row denotes each day from 2015-1-1 to 2018-12-31</p> <p>- 100 columns, every column denotes each quantile from 0.005 to 0.995, total 100 quantiles.</p> <p>### qrf-output</p> <p>- pdir (single input)<br> - imergf (single input)<br> - gsmap (single input)<br> - all (multiple inputs)</p> <p>### lstm-output</p> <p>- pdir (single input)<br> - imergf (single input)<br> - gsmap (single input)<br> - all (multiple inputs)</p> <p> </p>
Model code, data, and plot scripts for the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".
<p>The code, scripts, and data used in the paper "Impacts of Ice-Particle Size Distribution Shape Parameter on Climate Simulations with the Community Atmosphere Model Version 6 (CAM6)".</p> <ul> <li>All Figures&Table and their corresponding NCL scripts are under the directory of Figs&Table. </li> <li>The modified model code, corresponding original model code, and model run scripts are under the directory of Mods_Scripts.</li> <li>The postprocessing NCL scripts, which select useful variables from simulation results, are under the directory of PostProcessing.</li> <li>The zonal mean data from model results used for making figures and corresponding data processing scripts are under the directory of Model_Results.</li> <li>The FORTRAN code used for offline tests is under the directory of Offline_Code.</li> <li>The code, data, and NCL scripts used for the figures and table in the Appendix are under the directory of Appendix.</li> </ul>
Model simulation data used in "An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing" (Thor et al., GMD, 2022)
<p>This archive contains files that were used to produce the results published in the article "An inconsistency in aviation emissions between CMIP5 and CMIP6 and the implications for short-lived species and their radiative forcing" by Thor et al.</p> <p>The directory nml contains namelist setups (configuration files) used for each of the simulations that were performed for this study.<br> The used MESSy version is d2.54.0.3-pre2.55-02-2077-g6eca90858-dirty_6eca90858ecb4ee8fb8900681a94a79ac3d612af_2021-01-26T11:10:08+01:00_2021-02-18T09:14:01+0100 for the QCTM simulations and d2.54.0.3-pre2.55-02-1466-g1fb086944_1fb0869442bf4f1bb10a7dd5f36e4bde5c0cf6d7_2020-10-27T18:17:50+01:00_2020-10-27T18:24:16+0100 for the aerosol simulations (http://www.messy-interface.org).</p> <p>The directory figures contains ipython scripts that were used to produce the figures in the paper.</p>
POPC bilayer with 50% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs
<p>POPC bilayer with 50% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs. Last 180ns of 200ns long simulation.</p> <p>See also http://nmrlipids.blogspot.cz/2017/07/quantifying-effect-of-bound-charge-on.html and https://github.com/NMRLipids/MATCH/tree/master/Data/Lipid_Bilayers/POPC%2B50%25DHMDMAB/T313K/MODEL_LIPID14</p>
POPC bilayer with 42% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs
<p>POPC bilayer with 42% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs. Last 180ns of 200ns long simulation.</p> <p>See also http://nmrlipids.blogspot.cz/2017/07/quantifying-effect-of-bound-charge-on.html and https://github.com/NMRLipids/MATCH/tree/master/Data/Lipid_Bilayers/POPC%2B42%25DHMDMAB/T313K/MODEL_LIPID14</p>
POPC bilayer with 30% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs
<p>POPC bilayer with 30% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs. Last 80ns of 100ns long simulation.</p> <p>See also http://nmrlipids.blogspot.cz/2017/07/quantifying-effect-of-bound-charge-on.html and https://github.com/NMRLipids/MATCH/tree/master/Data/Lipid_Bilayers/POPC%2B30%25DHMDMAB/T313K/MODEL_LIPID14</p>
POPC bilayer with 10% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs
<p>POPC bilayer with 10% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs. Last 80ns of 100ns long simulation.</p> <p>See also http://nmrlipids.blogspot.cz/2017/07/quantifying-effect-of-bound-charge-on.html and https://github.com/NMRLipids/MATCH/tree/master/Data/Lipid_Bilayers/POPC%2B10%25DHMDMAB/T313K/MODEL_LIPID14</p>
POPC bilayer with 20% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs
<p>POPC bilayer with 20% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs. Last 80ns of 100ns long simulation.</p> <p>See also http://nmrlipids.blogspot.cz/2017/07/quantifying-effect-of-bound-charge-on.html and https://github.com/NMRLipids/MATCH/tree/master/Data/Lipid_Bilayers/POPC%2B20%25DHMDMAB/T313K/MODEL_LIPID14</p>
POPG lipid bilayer simulation at T298K ran with MODEL_CHARMM_GUI force field and Gromacs
<p>POPG lipid bilayer simulation at T298K ran 100ns with the force field given by CHARMM gui using Gromacs.</p> <p>118 POPG, 4110 TIP3P and 118 potassium molecules.</p> <p> </p>
POPC bilayer simulated at T313K with the Lipid14 model using Gromacs
<p>POPC bilayer with 50% of dihexadecyldimethylammonium simulated at T313K with the Lipid14 model using Gromacs. 70ns long simulation.</p> <p>See also http://nmrlipids.blogspot.cz/2017/07/quantifying-effect-of-bound-charge-on.html and https://github.com/NMRLipids/MATCH/tree/master/Data/Lipid_Bilayers/POPC/T313K/MODEL_LIPID14</p>
Simulations of POPC lipid bilayer in water solution at various NaCl and CaCl2 concentrations using ECC-POPC force field and various water models
<p>Classical molecular dynamics simulations of a POPC lipid bilayer in water solution at various NaCl and CaCl2 concentrations using ECC-POPC force field parameters, various water models and ECC-ions.</p> <p>Simulations with SPC/E water model are in a separate Zenodo deposit<br> https://doi.org/10.5281/zenodo.1118266</p> <p>file names report molar fraction of cations (i.e. not bulk concentrations)</p> <p>simulations performed with Gromacs 5.1.4 (*.xtc files) and openMM 7 (*.dcd files)</p> <p>simulation length 300 ns</p> <p>temperature 313 K (otherwise noted)</p>
A Hydrodynamic-Based Physical Unified Modeling for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behavior
<p>Simulation results for manuscript "A Hydrodynamic-Based Physical Unified Modelling Framework for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behaviour", submitted to Water Resources Research.</p>
A Hydrodynamic-Based Physical Unified Modeling for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behavior
<p>Simulation results for manuscript "A Hydrodynamic-Based Physical Unified Modelling Framework for Simulating Shallow Landslide Local Failures, Mass Release and Debris Flow Run-out Extent Behaviour", submitted to Water Resources Research.</p>
Data publication: Simulation of macroscopic boundary value problems using phenomenological material model for steel fiber reinforced high performance concrete (HPC)
<p>This data set contains all necessary inputs for the Simulation of macroscopic boundary value problems using phenomenological material model, including boundary conditions, material parameters and numerical results. The discretization is realized in terms of the finite element method. </p>
Dataset belonging to SNF project: Use of physiologically based pharmacokinetic modelling to simulate dosing requirements of long-acting intramuscular antiretroviral drugs in special populations and to manage drug-drug interactions
Open the record for dataset details and reuse information.
Simulation data used in "Modeling the Inception and Stepped Propagation of Positive Lightning Leaders"
<p>This dataset includes all simulation data used in "Modeling the Inception and Stepped Propagation of Positive Lightning Leaders." These datasets are output from an upward leader model, described in the paper, under a variety of different conditions and settings. Included also are several charts and animations for select datasets.</p>
Long Simulation of Global Sea Surface Temperature using Linear Inverse Model
<p>The content of this dataset includes (a) observed product, which is the averaged product of the Hadley Centre Sea Ice and Sea Surface Temperature (HadISST), the Extended Reconstructed Sea Surface Temperature version 5 (ERSSTv5), and the Centennial in situ Observation-Based Estimates (COBE). This is called "global_sst_1958to2017.mat", i.e., 60 yrs of monthly SST over 1958-2017; it also contains the trend, the seasonal climatology, the anomaly field after subtracting trend and seasonal climatology, longitude, latitude, time, and land-sea mask. (b) 20 realizations of long SST simulation generated by a Linear Inverse Model (LIM). Each realization contains 6000 months (or 500 yrs) of SST. The file is named "stochastic_simulation_lim_sst_mem*.mat". </p> <p>To cite dataset if plot or extracted used in any publication, use the reference below:</p> <p>Xu, T., et al. (2022). "An increase in marine heatwaves without significant changes in surface ocean temperature variability." <span>Nature Communications</span> <strong>13</strong>(1): 7396.</p>
NOAA Coastwatch Satellite Course (Set up an Application Model of Digital Satellite Data Simulation by Video Graphic Technology of Oceanic data Remotely Sensed of algerian coast)
<p>The goal of the course is to familiarize NOAA/university researchers, Sea Grant professionals and agency/org. partners with different types of ocean satellite data, different tools, and teach participants how to use satellite data in their own research/outreach using their choice of software (NOAA ,2023)</p>
Southern Hemisphere Circumpolar Wavenumber-4 Pattern Simulated in SINTEX-F2 Coupled Model
<p>These datasets are used to produce Figures in the paper by Senapati et al. (2024). </p> <p>Senapati, B., Morioka, Y., Behera, S. K., & Dash, M. K. (2024). Southern Hemisphere circumpolar wavenumber‐4 pattern simulated in SINTEX‐F2 coupled model. Journal of Geophysical Research: Oceans, 129, e2023JC020801. <a href="https://doi.org/10.1029/2023JC020801" rel="noopener">https://doi.org/10.1029/2023JC020801</a></p>
A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0
<p>This dataset accompanies the GMD article 'A conservative immersed boundary method for the multi-physics urban large-eddy simulation model uDALES v2.0' (https://doi.org/10.5194/egusphere-2024-96).</p> <ul> <li>The input files to run the presented cases using uDALES are contained in 'inputs'.</li> <li>The model outputs are contained in separate folders: 'XCC', 'indoor-outdoor', 'XCB', and 'SEB'. When downloaded, move into a folder called 'outputs' so that the paths defined in the scripts work as intended (see below).</li> <li>The Matlab scripts to plot the figures are contained in 'scripts'.</li> <li>The figures shown in the article are contained in 'figures'.</li> </ul>
ScienceDex guides
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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.