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.
212
datasets available to search
ShareScore release 0.9.0
Dataset results
212 results for “Climate Simulation”
High-resolution climate simulations using the Model for Prediction Across Scales - Atmosphere (MPAS-A; version 5.1)
Open the record for dataset details and reuse information.
Data for: Simulating effects of agricultural intensification and climate change: Nitrogen fertilization and drought stress decrease insect herbivore performance
Open the record for dataset details and reuse information.
Files associated with: Migration-based simulations for Canadian trees show limited tracking of suitable climate under climate change
Open the record for dataset details and reuse information.
Data from: Long-term grazing intensity by reindeer alters the response of the soil micro-food web to simulated climate change in subarctic tundra
Open the record for dataset details and reuse information.
Building consensus for ambitious climate action through the World Climate Simulation
Open the record for dataset details and reuse information.
Data and code for analysis of effects of climate change on kangaskhan and summary of simulations from Warren et al. 2020
Open the record for dataset details and reuse information.
Data from: Simulating climate change in situ in a tropical rainforest understorey using active air warming and CO2 addition
Open the record for dataset details and reuse information.
Data from: The Relationship between the Southern Ocean and the Eastern tropical Pacific in unforced and forced climate model simulations
Open the record for dataset details and reuse information.
Alpine climate and soils heterogeneity data and simulation results
Open the record for dataset details and reuse information.
CESM 1.2 climate model simulation output for: The Essential Role of Westerly Wind Bursts in ENSO Dynamics and Extreme Events Quantified in Model 'Wind Stress Shaving' Experiments
Open the record for dataset details and reuse information.
Data supplement for: Agreement of analytical and simulation-based estimates of the required land depth in climate models
Open the record for dataset details and reuse information.
Supporting Data for "A partial coupling method to isolate the roles of ocean and atmosphere in coupled climate simulations"
<p>Supporting data for "A partial coupling method to isolate the roles of the atmosphere and ocean in coupled climate simulations", submitted to Journal of Advances in modelling Earth system</p> <p>Monthly averaged variables for the 100 and 150 year fully coupled (b.e11.B1850C5CN.f09_g16.abrupt4xCO2.full.POP.100101_110012.nc) and partially coupled (b.e11.B1850C5CN.f09_g16.abrupt4xCO2.partial.POP.100101_115012.nc) abrupt CO2 quadrupling simulations and 40 yr ocean-driven partially coupled simulation (b.e11.B1850C5CN.f09_g16.prescribed.partial.POP.100101_115012.nc)</p> <p>Control simulation data is available on the NCAR HPSS /CCSM/csm/b.e11.B1850C5CN.f09_g16.005</p>
Climate simulation over the European Alps for the period 1902-2010 produced with the model MAR
<p>This directory contains the netcdf files produced with the MAR model (http://mar.cnrs.fr/; https://gitlab.com/Mar-Group) applied over the European Alps, for the period 1902-2010, based on a spatial resolution of 7km. This data is a downscaling of the ERA20C reanalysis. The list of variables available is described in the file variables.txt, and further information can be found in the file readme.txt</p>
Supplementary Material to "Comparison of equilibrium climate sensitivity estimates from slab ocean, 150-year, and longer simulations"
<p>This is supplementary data for Dunne, J. P., et al. (2020). Comparison of equilibrium climate sensitivity estimates from slab ocean, 150-year, and longer simulations. Geophysical Research Letters. 2020GL088852R. Data in this repository can be unpacked and the files are in the form- NetCDF and matlab files, along with a README. </p> <p>Model data for global average values of net top of the atmosphere radiative balance (W m-2) and 2m air temperature (degrees celsius) for preindustrial control and 4x abrupt CO2 simulations for a variety of models used in LongRunMIP, CMIP5, and CMIP6, as well as scripts used to calculate equilibrium climate sensitivity from these simulations. </p> <p> </p>
CESM1.2 simulation output for: The role of westerly wind bursts during different seasons versus ocean heat recharge in the development of extreme El Niño in a climate model
<p>This is the subset of CESM1.2 model simulation output that was used for analysis and visualization of Yu and Fedorov [2020] (DOI:10.1029/2020GL088381). Please refer to README for details.</p>
Evaluation dataset for urban climate simulation
<p>The dataset was used in the following papers:</p> <p>(1) Li, Z., Zhou, Y., Wan, B., Chung, H., Huang, B., & Liu, B. (2019). Model evaluation of high-resolution urban climate simulations: using the WRF/Noah LSM/SLUCM model (Version 3.7. 1) as a case study. <em>Geoscientific Model Development</em>, <em>12</em>(11), 4571-4584.</p> <p>(2) Li, Z., Wan, B., Zhou, Y., & Wong, H. (2020). Incoming data quality control in high-resolution urban climate simulation: Hong Kong-Shenzhen area urban climate simulation as a case study using WRF/Noah LSM/SLUCM model (Version 3.7. 1). <em>Geoscientific Model Development Discussions</em>, 1-13.</p>
AWE-GEN-2d downscaled climate simulations for Omo-Turkana and Zambezi river basins
<p>AWE-GEN-2d downscaled climate simulations generated for the DAFNE project</p> <p>Refer to the README.txt for data access and description.</p>
Code to run the analyses of "Forest storm resilience depends on the interplay between functional composition and climate - insights from European-scale simulations" by Barrere et al. (2024).
<p>Repository containing the code to run the model and statistical analyses of the paper "Forest storm resilience depends on the interplay between functional composition and climate - insights from European-scale simulations" by Julien Barrere, Björn Reineking, Maxime Jeaunatre and Georges Kunstler, accepted by Functional Ecology in 2024.</p><p> </p><p>The code requires prior installation of the <a href="https://github.com/gowachin/matreex">matreex</a> R package, developped by Maxime Jeaunatre (INRAE), and of the ```targets``` package. The data folder, required to run the code, can be made available upon request to julienbarrere3@gmail.com</p><p> </p><p>Once the packages are installed and the data folder is placer in the main folder, just run ```targets::tar_make()``` from R and the script will download the other packages required and run the analyses.</p><p> </p><p>A version of this code is also available in the github <a href="https://github.com/jbarrere3/FunDiv_ipm">repository</a></p><p> </p><p> </p>
Ramping simulations from "Global Precipitation Correction Across a Range of Climates Using CycleGAN"
<p>Four-year ramping simulations from "Global Precipitation Correction Across a Range of Climates Using CycleGAN" depicting the real input C48 and C384 precipitation and the generated C384 (ML) and C48 (ML) precipitation based on these inputs for each 3-hourly sample.</p>
Future wave climate in the Mediterranean Sea and associated uncertainty from an ensemble of 31 GCM-RCM wave simulations
<p>The data provided is used in a study aimed at assessing future changes in the Mediterranean wave climate. A total of 31 GCM-RCM simulations were used to characterize the wave climate during the historical (1979-2005), mid-century (2034-2060), and end-century (2074-2100) periods. Changes in seasonal significant wave height (Hs) and peak period (Tp) wave parameters are evaluated for both the mean and intense (quantile 0.95) wave climate, along with the shift in wave direction (wave peak dominant direction, θp) for sea states characterized as intense. The robustness of the climate change signal is evaluated following the guidelines outlined in the Sixth Assessment Report (AR6) of the Intergovernmental Panel on Climate Change. Additionally, using a wave hindcast as a reference, the changes in future extreme events are assessed by fitting a GEV to a unique and coherent set of bias-corrected annual maxima from each model.</p> <p>We provide data used to obtain the results of our study, comprising: 1) wave climate statistics for Hs, Tp, and θp for each model and each period studied; 2) two sets of annual maxima distribution for each model, which were bias-corrected assuming that the set of extreme events follows either a Gumbel distribution or a GEV distribution. For more details on the methods to obtain these files describing wave climate statistical as used in the study, please refer to Toomey et al., 2024: "Future wave climate in the Mediterranean Sea and associated uncertainty from an ensemble of GCM-RCM wave simulations."</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.