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Dataset results
617 results for “Climate models”
Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model
<p>This archive provides the GRISLI ice sheet model and iLOVECLIM model outputs as part of the manuscript "Northern Hemisphere ice sheets and ocean interactions during the last glacial period in a coupled ice sheet-climate model".<br><br></p> <p>Contact: louise.abot@locean.ipsl.fr</p>
Dataset to reproduce the paper "A new framework to evaluate urban design using urban microclimatic modelling in future climatic conditions"
<p>This dataset has been generated with the paper " A new framework to evaluate urban design using urban microclimatic<br> modelling in future climatic conditions" (https://doi.org/10.3390/su10041134). A Python notebook is also included to conduct the analysis.</p> <ol> <li>Data analysis - Sustainability paper.ipynb : Python notebook</li> <li>Geneva_Eur11_TDY_2010_2039 : Climate file for the year 2039 obtained from RCA4</li> <li>Geneva_Eur11_TDY_2010_2039_cim : Climate file for the year 2039 obtained from RCA4-CIM</li> <li>Geneva_Eur11_TDY_2010_2039 : Climate file for the year 2069 obtained from RCA4</li> <li>Geneva_Eur11_TDY_2010_2069_cim : Climate file for the year 2069 obtained from RCA4-CIM</li> <li>Geneva_Eur11_TDY_2010_2099 : Climate file for the year 2099 obtained from RCA4</li> <li>Geneva_Eur11_TDY_2010_2099_cim : Climate file for the year 2099 obtained from RCA4-CIM</li> <li>heating_2039 : Heating demand from CitySim for the year 2039</li> <li>heating_2039_cim : Heating demand from CitySim-CIM for the year 2039</li> <li>heating_2069 : Heating demand from CitySim for the year 2069</li> <li>heating_2069_cim : Heating demand from CitySim-CIM for the year 2069</li> <li>heating_2099 : Heating demand from CitySim for the year 2099</li> <li>heating_2099_cim : Heating demand from CitySim-CIM for the year 2099</li> <li>heating_2099_minP : Heating demand from CitySim for the year 2099 with Minergie-P scenario</li> <li>heating_2099__minP_cim : Heating demand from CitySim-CIM for the year 2099 with Minergie-P scenario</li> <li>cooling_2039 : Cooling demand from CitySim for the year 2039</li> <li>cooling_2039_cim : Cooling demand from CitySim-CIM for the year 2039</li> <li>cooling_2069 : Cooling demand from CitySim for the year 2069</li> <li>cooling_2069_cim : Cooling demand from CitySim-CIM for the year 2069</li> <li>cooling_2099 : Cooling demand from CitySim for the year 2099</li> <li>cooling_2099_cim : Cooling demand from CitySim-CIM for the year 2099</li> <li>cooling_2099_minP : Cooling demand from CitySim for the year 2099 with Minergie-P scenario</li> <li>cooling_2099__minP_cim : Cooling demand from CitySim-CIM for the year 2099 with Minergie-P scenario</li> <li>temp_cim : simulated temperature from CIM using Meteonorm</li> <li>temp_meteonorm : temperature from Meteonorm</li> <li>u_cim : simulated wind speedfrom CIM using Meteonorm</li> <li>u_meteonorm : wind speed from Meteonorm</li> </ol> <p> </p>
Some atmospheric model fields shown in paper titled "E3SMv0-HiLAT: A Modified Climate System Model Targeted for the Study of High Latitude Processes
<p>These files contain 2-D fields of atmospheric T and P maps, as climatologies averaged over years 234-253 of the E3SMv0-HiLAT model preindustrial simulation, and from the CESM Large Ensemble control simulation (LENS), the basis for two of the plots in our manuscript that is, as of January 2019, in review at JAMES. All of these data files are binary, written sequentially, 288 x 192. Also included are some PowerPoint-generated pdf images of the two fields.</p>
Supporting model output for 'Empirical stream thermal sensitivities may underestimate stream temperature response to climate warming'.
<p>Model output used to generate figures in the manuscript 'Empirical stream thermal sensitivities may underestimate stream temperature response to climate warming'.</p>
Atmospheric and sea ice model fields from the perturbed parameter ensemble E3SMv0-HILAT used to examine emergent relationships among climate variables in the Arctic
<p>These files contain time series of several sea ice ad atmospheric fields produced in an ensemble of perturbed parameter simulations using the E3SMv0-HiLAT model. The time series are used to produced seasonal means, which are used to examine emerging relationships in the ensemble discussed in our manuscript, as of September 2019, in review at JGR</p>
Laboratory modeling of gap-leaping and intruding western boundary currents under different climate change scenarios
<p>Western boundary currents (WBCs), such as, the Kuroshio and the Gulf Stream, are very intense currents flowing along the western boundaries of the oceans.<br>WBCs -and their respective extensions- have an important effect on climate because of their huge heat transports, the corresponding air–sea interactions and the role they play in sustaining the global conveyor belt. It is therefore very relevant to analyze WBC dynamics not only through observations and numerical modelling, but also by means of laboratory experiments; to this respect several rotating tank experiments have been performed in recent years.<br>The new laboratory experiments proposed here for the Hydralab+ 19GAPWEBS project are aimed at analyzing the interactions of a WBC with gaps located along the western coast. Examples of such processes include the Gulf Stream leaping from the Yucatan to Florida and the Kuroshio leaping, and partly penetrating, through the South and East China Seas and through the wider gap separating Taiwan to Japan. In the experiments the WBC is produced by a horizontally unsheared current flowing over a topographic beta slope; along the western lateral boundary a sequence of gaps of different widths simulate the openings present in the above mentioned locations.</p>
Code and data to reproduce the results of the paper: "Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece"
<p>Code and data to reproduce the results of Knitter et al. (2019): Land Use Patterns and Climate Change---A Modeled Scenario of the Late Bronze Age in Southern Greece. ERL.</p>
Figure 2 in Ensemble distribution modeling of the Mesopotamian spiny-tailed lizard, Saara loricata (Blanford, 1874), in Iran: an insight into the impact of climate change
Figure 2. The habitat suitability map of the Mesopotamian spiny-tailed lizard in southwestern Iran.
Illustrations for 'Disturbances in the evergreen boreal forest and their impact on 21st century vegetation and climate dynamics - A stochastic modeling approach' (Doctoral thesis)
<p>This repository contains all the original illustrations I created for my doctoral thesis at the Technical University of Munich. This work is published under a Creative Commons CC-BY-SA license, which means that you are free to use and adapt this work under the same license for commercial and non-commercial applications as long as you credit the original work. To credit, please cite this repository as well as my doctoral thesis.</p> <p> </p> <p> </p>
Data used in "Revealing dominant patterns of aerosols regimes in the lower troposphere and their evolution from preindustrial times to the future in global climate model simulations" (Li et al., Atmos. Chem. Phys. 2024)
<p>This dataset contains the processed EMAC simulation used as input to the clustering algorithm and the resulting regimes discussed in Li et al. (<em>Atmos. Chem. Phys.</em>, 2024).</p>
Impact of a Bimodal Dust Distribution on the 2018 Martian Global Dust Storm with the NASA/Ames Mars Global Climate Model
<p>This dataset is simulation data from the NASA Ames Mars GCM, produced for the research article titled "Impact of a Bimodal Dust Distribution on the 2018 Martian Global Dust Storm with the NASA/Ames Mars Global Climate Model." It is presented in NetCDF format.</p>
Ocean basin mask for coordinated climate model experiments to explore tropical basin interaction
<p>This is a netcdf dataset containing a basin mask for distinguishing major ocean basins (Atlantic, Pacific, etc.). It has been simplified to for use with the TBI experiments coordinated by the CLIVAR Research Focus on Tropical Basin Interaction (https://www.clivar.org/research-foci/basin-interaction). The original data can be found at https://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NODC/.WOA09/.Masks/.basin/index.html?Set-Language=en</p>
Data analysis & code: Quantifying the impact of climate change and forest management on Swedish forest ecosystems using the dynamic vegetation model LPJ-GUESS
<p><span>This file contains code to optimize the allometric parameters, to plot the figures, and details of the underlying data analysis in "Quantifying the impact of climate change and forest management on Swedish forest ecosystems using the dynamic vegetation model LPJ-GUESS" (Bergkvist et al.). <br></span></p>
Model results and data associated with "Antecedent effect models as an exploratory tool to link climate drivers to herbaceous perennial population dynamics data"
<p>Model results and data (including Bayesian posteriors) associated with "Antecedent effect models as an exploratory tool to link climate drivers to 3 herbaceous perennial population dynamics data".</p> <p>This is a repository created to store the posteriors of the models fit within this project. Because these occupy so much space, it makes sense to store them in a separate repository.</p> <p>There are two directories:</p> <ul> <li><em>model_results/</em> contains all of the posteriors (files with character pattern <em>main_posterior_#.csv</em>). The three types of files contained in this directory are described in <em>metadata_model_results.xlsx</em>. The number # corresponds to column "index" in file <em>raw_data/design_insample.csv</em>.</li> <li><em>raw_data/</em> is mostly not essential: it contains the raw data to fit models, and it replicates folder <em>data/</em> in repository https://dx.doi.org/10.5281/zenodo.13909628.</li> </ul>
Supplementary files: Machine Learning Insights into Türkiye's Climate Variability: Predictive Modelling and Spatial Analysis
<p>This dataset and python code were used in the study titled "Machine Learning Insights into Türkiye's Climate Variability: Predictive Modelling and Spatial Analysis".</p>
Definition of the terms verification, validation, evaluation and benchmarking for use in the climate model context
<p>Schematic definition of the terms Verification, Validation, Evaluation and Benchmarking for use in the climate model context. Note that although through benchmarking some kind of ranking can be performed based on the chosen metric and selected observations, this is by far not a generally applicable ranking valid for all metrics, all realms and all possible observational references.</p>
Different schemes that are most commonly used for the evaluation and benchmarking of climate models.
<p>Different schemes that are most commonly used for the evaluation and benchmarking of climate models. Most of the schemes can be applied to different realms (e.g. atmosphere, ocean, land...), and each scheme can include more than one diagnostic or metric. Scheme 1 only includes the portrait plot as metric which is very versatile in its application across different domains, analysed variables and number of included observations or time periods. Scheme 2 represents all diagnostics that are based on analyses of biases and variabilities. Scheme 3 includes all diagnostics that focus on spatial analyses, e.g. spatial correlations or physical connections between neighboring regions/realms. Scheme 4 includes any budget assessments. These diagnostics are commonly applied globally, but can also be applied regionally if boundary conditions and fluxes across boundaries are clearly defined. Scheme 5 represents all other statistical approaches for model evaluation, e.g. the analyses of distributions. Scheme 6 finally includes all diagnostics that aim for describing Earth System and its interconnections and changes as a whole, e.g. emergent constraints or equilibrium climate sensitivity (ECS).</p>
A Factor Two Difference in 21st-Century Greenland Ice Sheet Surface Mass Balance Projections from Three Regional Climate Models for a Strong Warming Scenario (SSP5-8.5)
<p>1km regridded Greenland Ice Sheet SMB / Runoff / Melt projection until 2100. Projections from MAR, RACMO, HIRHAM forced by CESM2 (SSP5-8.5).</p>
Large ensemble climate modelling time series for the Rhine catchment, including drought2018 storylines
<p>Dataset associated with <strong>Van der Wiel, Lenderink, De Vries (2021): Physical storylines of future European drought events like 2018 based on ensemble climate modelling, <em>Weather and Climate Extremes, </em>DOI <a href="http://doi.org/10.1016/j.wace.2021.100350">10.1016/j.wace.2021.100350</a>.</strong></p> <p>Large ensemble climate modelling time series for the Rhine catchment. The dataset contains three ensembles (present-day, pre-industrial + 2C-warming, pre-industrial + 3C-warming) of 2000 years each, various variables related to drought are included. All data is derived from the EC-Earth global climate model (v2, Hazeleger et al. 2012, DOI <a href="https://doi.org/10.1007/s00382-011-1228-5">10.1007/s00382-011-1228-5</a>). Descriptions of large ensemble experimental setup can be found in Van der Wiel et al. (2019, DOI <a href="http://doi.org/10.1029/2019GL081967">10.1029/2019GL081967</a>). Files: *_d_ECEarth_??_Rhine.tar.gz</p> <p>Additionally, three sets of storylines of droughts similar to the western European drought of 2018 are included. These are the simulated events selected from the large ensembles, using metrics 1, 2 and 3 of Van der Wiel et al. (2021, DOI <a href="http://doi.org/10.1016/j.wace.2021.100350">10.1016/j.wace.2021.100350</a>). Files: drought18_m[123]_Rhine.tar.gz</p>
Data supplement for: Agreement of analytical and simulation-based estimates of the required land depth in climate models
<p>Many current-generation climate models have land components that are too shallow. Under climate change conditions, the long-term warming trend at the surface propagates deeper into the ground than the commonly used 3-10m. Shallow models alter the terrestrial heat storage and distribution of temperatures in the subsurface, influencing the simulated land-atmosphere interactions. Previous studies focusing on annual timescales suggest that deeper models are required to match subsurface-temperature observations and the classic analytical heat conduction solution. However, for a systematic investigation of land-model deepening in the frame of anthropogenic climate change, the classic analytical solution is inaccurate because it does not mimic the timescale and amplitude of the simulated warming trend. This study intends to bridge the gap between analytical and simulation-based estimates of the subsurface thermodynamic state by adapting the classic analytical framework to mimic long-term anthropogenic warming. The analysis shows that a land-model depth of at least 170m is recommended for a proper simulation of the post-1850 ground climate, which differs up to 30% from the estimate of the classic approach. Compared to previous studies, this provides an accurate estimate of the required land model depth for long-term climate-change simulations and indicates the relative bias in insufficiently deep land models.</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.