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81 results for “Ice and climate”
Scripts for "Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model"
<p>The scripts used to generate the main figures and results of the work entitled ''Evaluation and Attribution of a Warm Winter Bias Over Arctic Sea Ice in a Climate Model'' by Michalezyk et al., submitted for publication in JAMES - AGU in 2024.</p> <p>If you have any questions, please contact Nicolas MICHALEZYK : nicolas.michalezyk@locean.ipsl.fr</p>
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 for "Estimating Contribution of Sea Ice and Land Snow to Climate Sensitivity"
<p>The reproducible dataset for "Estimating Contribution of Sea Ice and Land Snow to Climate Sensitivity".</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>
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>
Data for the publication "Evaluation of climatic impacts of ice nucleating particles through precipitation process with a GCM"
<p>These data are a set of annual-mean values for 5yr simulations using the MIROC6-SPRINTARS global aerosol-climate model with different treatments of precipitation (i.e., diagnostic and prognostic). The outputs include diagnostics from the satellite simulator COSP2.<br>The data are used in the manuscript entitled "Evaluation of climatic impacts of ice nucleating particles through precipitation process with a GCM". All data used in this study are available from the corresponding author upon request.</p>
Dataset for "Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice sheet -- climate coupled model"
<p>This archive contains the source data of the figures presented in the manuscript "Climate and ice sheet evolutions from the last glacial maximum to the pre-industrial period with an ice sheet -- climate coupled model".</p> <p>Contact: aurelien.quiquet@lsce.ipsl.fr</p>
Deglacial climate changes as forced by different ice sheet reconstructions - model ouputs
<p>This dataset contains the model output corresponding to the paper entitled "Deglacial climate changes as forced by different ice sheet reconstructions" submitted to Climate of the Past. For the description of the model and simulations we refer to this article.</p> <p> </p> <p><strong>Simulations:</strong><br> degla_P_bathy_500yr_is_SH_nobathy = with ICE_6G_C, fixed bathymetry<br> degla_P_bathy_500yr_is_SH = with ICE_6G_C, evolving bathymetry<br> degla_P_bathy_500yr_is_SH_bis = with ICE_6G_C, evolving bathymetry, mask modified<br> degla_T_bathyT_100yr_is_SH_nobathy = with GLAC-1D, fixed bathymetry<br> degla_T_bathyT_100yr_is_SH = with GLAC-1D, evolving bathymetry<br> degla_T_bathyT_100yr_is_SH_FWF = with GLAC-1D, evolving bathymetry, fresh water flux<br> degla_T_bathyT_100yr_is_SH_FWFtest3 = with GLAC-1D, evolving bathymetry, fresh water flux with intensity divided by 3<br> degla_T_bathyT_100yr_is_SH_FWFtest4 = with GLAC-1D, evolving bathymetry, fresh water flux with intensity divided by 4</p> <p> </p> <p><strong>Variables and corresponding files:</strong><br> <em>Evolution of ocean volume (m3):</em><br> volume_ocean_degla_P_bathy_500yr_is_SH.txt<br> volume_ocean_degla_T_bathyT_100yr_is_SH.txt</p> <p><em>Evolution of ocean surface area (1e6 km2):</em><br> surface_area_degla_P_bathy_500yr_is_SH.txt<br> surface_area_degla_T_bathyT_100yr_is_SH.txt</p> <p><em>Sea land masks for time slices:</em><br> tmask_bathy_P_0yr_SH_CC_PI.nc<br> tmask_degla_P_bathy_500yr_is_SH_21ka.nc<br> tmask_degla_T_bathyT_100yr_is_SH_21ka.nc<br> tmask_degla_P_bathy_500yr_is_SH_12ka.nc<br> tmask_degla_T_bathyT_100yr_is_SH_12ka.nc<br> tmask_degla_P_bathy_500yr_is_SH_9ka.nc<br> tmask_degla_T_bathyT_100yr_is_SH_9ka.nc</p> <p><em>Evolution of global mean temperature (degree C):</em><br> Temperature_evolution_degla_P_bathy_500yr_is_SH_nobathy.txt<br> Temperature_evolution_degla_T_bathyT_100yr_is_SH_nobathy.txt<br> Temperature_evolution_degla_P_bathy_500yr_is_SH.txt<br> Temperature_evolution_degla_P_bathy_500yr_is_SH_bis.txt<br> Temperature_evolution_degla_T_bathyT_100yr_is_SH_nobathy.txt<br> Temperature_evolution_degla_T_bathyT_500yr_is_SH.txt<br> Temperature_evolution_degla_T_bathyT_100yr_is_SH.txt<br> Temperature_evolution_degla_T_bathyT_100yr_is_SH_FWF.txt<br> Temperature_evolution_degla_T_bathyT_100yr_is_SH_FWFtest3.txt<br> Temperature_evolution_degla_T_bathyT_100yr_is_SH_FWFtest4.txt</p> <p><em>Temperature maps for time slices:</em><br> temp_degla_P_bathy_500yr_is_SH_nobathy_21ka.nc<br> temp_degla_T_bathyT_100yr_is_SH_nobathy_21ka.nc<br> temp_degla_P_bathy_500yr_is_SH_nobathy_10ka.nc<br> temp_degla_T_bathyT_100yr_is_SH_nobathy_10ka.nc</p> <p><em>Evolution of salinity:</em><br> iLOVECLIM_salinity_ICE-6G_C.nc<br> iLOVECLIM_salinity_GLAC-1D.nc</p> <p><em>Temperature evolution at NGRIP location:</em><br> iLOVECLIM_t2m_NGRIP_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_t2m_NGRIP_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_t2m_NGRIP_degla_P_bathy_500yr_is_SH_bis.nc<br> iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH.nc<br> iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_FWF.nc<br> iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_FWFtest3.nc<br> iLOVECLIM_t2m_NGRIP_degla_T_bathyT_100yr_is_SH_FWFtest4.nc</p> <p><em>Temperature evolution at EDC location:</em><br> iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH.nc<br> iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_t2m_EDC_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_t2m_EDC_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_t2m_EDC_degla_P_bathy_500yr_is_SH_bis.nc<br> iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_FWF.nc<br> iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_FWFtest3.nc<br> iLOVECLIM_t2m_EDC_degla_T_bathyT_100yr_is_SH_FWFtest4.nc</p> <p><em>Evolution of surface albedo (all globe):</em><br> iLOVECLIM_alb_all_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_alb_all_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_alb_all_degla_P_bathy_500yr_is_SH_bis.nc<br> iLOVECLIM_alb_all_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_alb_all_degla_T_bathyT_100yr_is_SH.nc</p> <p><em>Evolution of surface albedo (Northern Hemisphere):</em><br> iLOVECLIM_alb_NH_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_alb_NH_degla_T_bathyT_100yr_is_SH.nc<br> iLOVECLIM_alb_NH_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_alb_NH_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_alb_NH_degla_P_bathy_500yr_is_SH_bis.nc</p> <p><em>Evolution of surface albedo (Southern Hemisphere):</em><br> iLOVECLIM_alb_SH_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_alb_SH_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_alb_SH_degla_P_bathy_500yr_is_SH_bis.nc<br> iLOVECLIM_alb_SH_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_alb_SH_degla_T_bathyT_100yr_is_SH.nc</p> <p><em>Evolution of sea ice area in the Northern Hemisphere (1e12 km2):</em><br> iLOVECLIM_sea_ice_NH_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_sea_ice_NH_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_sea_ice_NH_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_sea_ice_NH_degla_T_bathyT_100yr_is_SH.nc</p> <p><em>Evolution of sea ice area in the Southern Hemisphere (1e12 km2):</em><br> iLOVECLIM_sea_ice_SH_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_sea_ice_SH_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_sea_ice_SH_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_sea_ice_SH_degla_T_bathyT_100yr_is_SH.nc</p> <p><em>Winter sea ice fraction and mixed layer depth (m) at time slices:</em><br> iLOVECLIM_sea_ice_mld_bathy_P_21000yr_SH_21ka.nc<br> iLOVECLIM_sea_ice_mld_bathy_T_21000yr_SH_21ka.nc<br> iLOVECLIM_sea_ice_mld_degla_P_bathy_500yr_is_SH_nobathy_10ka.nc<br> iLOVECLIM_sea_ice_mld_degla_T_bathyT_100yr_is_SH_nobathy_10ka.nc<br> iLOVECLIM_sea_ice_mld_degla_P_bathy_500yr_is_SH_10ka.nc<br> iLOVECLIM_sea_ice_mld_degla_T_bathyT_100yr_is_SH_10ka.nc</p> <p><em>Evolution of the maximum strength of AMOC:</em><br> iLOVECLIM_AMOC_degla_P_bathy_500yr_is_SH_nobathy.nc<br> iLOVECLIM_AMOC_degla_P_bathy_500yr_is_SH.nc<br> iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_nobathy.nc<br> iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH.nc<br> iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_FWF.nc<br> iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_FWFtest3.nc<br> iLOVECLIM_AMOC_degla_T_bathyT_100yr_is_SH_FWFtest4.nc</p> <p><em>Meridional overtunring circulation at time slices:</em><br> MOC_degla_P_bathy_500yr_is_SH_21ka.nc<br> MOC_degla_P_bathy_500yr_is_SH_10ka.nc<br> MOC_degla_P_bathy_500yr_is_SH_nobathy_10ka.nc<br> MOC_degla_T_bathyT_100yr_is_SH_21ka.nc<br> MOC_degla_T_bathyT_100yr_is_SH_10ka.nc</p>
Radiative transfer model and datasets for Li et al. (2023), 'Wintertime low-level clouds over sea ice cool the Arctic climate system'
<p>Source code for the radiative transfer model (RAPRAD) and cloud radiative flux data used in the study Li et al. (2022).</p>
NEEM seasonal dO18 data for "Climate information preserved in seasonal water isotope at NEEM: relationships with temperature, circulation and sea ice"
<p>NEEM seasonal dO18 data over the period 1855-2004.</p> <p><strong>Please cite the following reference when using the data:</strong></p> <p>Zheng, M., Sjolte, J., Adolphi, F., Vinther, B. M., Steen-Larsen, H. C., Popp, T. J., and Muscheler, R.: Climate information preserved in seasonal water isotope at NEEM: relationships with temperature, circulation and sea ice, Climate of the Past, 14, 1067-1078, <a href="https://doi.org/10.5194/cp-14-1067-2018">https://doi.org/10.5194/cp-14-1067-2018</a>, 2018.</p> <p> </p>
Use of sea ice by arctic terns Sterna paradisaea in Antarctica and impacts of climate change
Open the record for dataset details and reuse information.
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 model codes, data, and plot scripts 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>7_experiments.zip contains modified model code and output data of each experiment in this study.</li> <li>off-line test.zip contains off-line test code and output data.</li> <li>plot_scripts.zip are the NCL scripts used for figures in the paper.</li> </ul>
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 model codes, data, and plot scripts 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>Figs&Table are the NCL scripts used for figures and table in the paper.</li> <li>Model_Results contains output data of each experiment in this study.</li> <li>Mods_Scripts contains modified model code.</li> <li>Offline_Code contains off-line test code.</li> </ul>
Model data - Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions
<p>Model data for JGR paper : Impact of Ural blocking on early-winter climate variability under different Barents-Kara sea ice conditions</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>
Data supporting 'Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea-Ice Loss using an Idealized Aquaplanet GCM' by Neil T Lewis et al.
<p>Data supporting Lewis et al., 2024. Assessing the Spurious Impacts of Ice-Constraining Methods on the Climate Response to Sea-Ice Loss using an Idealised Aquaplanet GCM. Submitted to Journal of Climate. </p> <p>All data is in NetCDF format. </p> <p>Output from each experiment is contained in its own folder (e.g., 'ALB.1'). For a description of each experiment, see the accompanying paper. </p> <p>Data files contain the following outputs: </p> <p>dyn_vars_daily_clim.nc contains day of year- and zonally-averaged atmospheric fields (u, v, T, etc). </p> <p>eddy_products.nc constains day of year- and zonally-averaged products of atmospheric fields (e.g., u'v'). </p> <p>ice_temp_daily.nc contains daily-averaged surface temperature and sea-ice thickness. </p> <p>toa_fluxes_clim.nc contains day of year-averaged top of atmosphere radiative fluxes (e.g., OLR). </p> <p>For the experiments NDG1.05, NDG1.1, and NDG1.2, nudge_daily_clim.nc is also included, and contains the day of year-averaged nudging heat flux applied to melt the ice. </p>
Model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"
<p>This folder contains the model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"</p> <p>The code for plotting the figures is the notebook Plot_figures.ipynb</p> <p>Fig1/simulation_output/ : Model output necessary for plotting the first figure </p> <p>The last timestep of each simulation is provided. There is one file for 1D variables (ice volume, ice volume above flotation), and one file for 2D variables (ice sheet thickness for instance).</p> <ul> <li><span>melt_insoPI_output/ : melt branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>growth_insoPI_output/ : growth branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>melt_insoMAX_output/ : melt branch, maximum insolation. Results for different CO2 levels</span></li> <li><span>growth_insoMIN_output/ : growth branch, minimum insolation. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig1/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p>Fig2/simulation_output/ : Model output necessary for plotting the second figure </p> <p>The last timestep of each simulation is provided. </p> <ul> <li><span>melt_insoPI_enhancedmelt_albfb/ : melt branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_albfb/ : growth branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>melt_insoPI_enhancedmelt_fixedalb/ : melt branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_fixedalb/: growth branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig2/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p><span>Fig3/simulation_output/ : Model output necessary for plotting the third figure </span></p> <ul> <li><span>1xCO2_nocoupling/ : simulation with pre-industrial CO2 levels and insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_nocoupling/ : simulation with 8xpiCO2 (pre-industrial CO2) levels, pre-industrial insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_transient_albfb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model </span></li> <li><span>8xCO2_transient_fixedalb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model excluding the albedo-melt feedback</span></li> </ul> <p> </p>
Genetic datasets, climatic conditions at sampled localities, and occurrence data to: Ice age-driven range shifts of diploids and expanding autotetraploids within a conserved niche (Grünig, Patsiou & Parisod, 2024, New Phytologist)
<div> <h3><strong>This repository includes</strong></h3> - An overview of the raw sequencing reads deposited in the European Nucleotide Archive (ENA) for the 370 individuals sampled in 17 diploid and 19 tetraploid field populations <div>- Scripts used to genotype diploids and autotetraploids samples of <em>Biscutella laevigata</em> from ddRADseq data</div> <div>- Input data (as vcf format) used in population genetic analyses</div> <div>- Scripts used to run the different genetic analyses</div> <div>- Dataset of extracted climatic conditions at sampled localities</div> <div>- Occurrence dataset used for the climatic niche modelling</div> <br> <h3><strong>Description of the data and file structure</strong></h3> <strong>00.ENA_samples_correspondance.txt: </strong>provides ENA project ID, run ID (i.e. raw fastq files), sample ID, and alias for each sample included in the study.<br> <div> </div> <div><strong>1.scripts_reads_to_vcf.zip:</strong> consists of the following:</div> - <strong>1.reads_to_vcf.md: </strong>md file with scripts documenting the read quality check, demultiplexing, mapping, SNP calling using GATK4, and filtering steps<br> <div>- Additional scripts called within <strong>1.reads_to_vcf.md</strong>:</div> <div>-- 1.3. Mapping: <strong>02_run_mapping_XXX.py</strong> and <strong>BWA-mem_bisc1_sg.py</strong> scripts</div> <div>-- 1.4.a. HaplotypeCaller: <strong>03_V1_gvcf.py</strong></div> <div>-- 1.4.b. GDBI + genotypeGVCF: <strong>03_V3_gdbi_genotype_per100scaf.py</strong></div> <br> <div><strong>2.datasets_genetics.tar.gz</strong> consists of the following</div> <br> <div>- <strong>bisc_all370_diminDP15_tetraminDP30.vcf.gz</strong>: "Initial SNPs dataset" = biallelic SNPs fulfilling GATK quality hard filtering recommendations, present in at least 50% of samples. Genotypes with DP<15 for diploids and DP<30 for tetraploids are set to no-call. This vcf was used as basis for fastsimcoal dataset preparation, and as basis for subsequent selection of loci fulfilling requirements of each analysis. It includes 2246701 biallelic SNPs for 370 samples</div> <br> <div>- <strong>bisc_all370_diminDP15_tetraminDP30_MD05_pruned.vcf.gz:</strong> subset of the "Initial SNPs dataset" retaining SNPs called in at least 50% of samples, and pruned for Linkage disequilibrium. This vcf includes 107574 biallelic SNPs for 370 samples and was used in the analysis of the proportion of diploids diagnostic alleles shared by tetraploids.</div> <br> <div>- <strong>bisc_all370_diminDP15_tetraminDP30_MD01_pruned.vcf.gz: </strong>subset of the "Initial SNPs dataset", retaining SNPs called in at least 90% of samples, and pruned for Linkage disequilibrium. This vcf includes 4444 biallelic SNPs for 370 samples and was used in the analyses of Population diversity and differentiation (SpaGeDi, GenoDive, PCA), and f3-statistics.</div> <br> <div>- <strong>bisc_all370_diminDP15_tetraminDP30_MD0.1_pruned_MAC3rm.vcf.gz:</strong> subset of the "Initial SNPs dataset", retaining SNPs called in at least 90% of samples, pruned for Linkage disequilibrium, and with a minor allele count of 3. This vcf includes 2593 biallelic SNPs for 370 samples and was used in STRUCTURE analysis</div> <br><br> <div><strong>3.pres_2x.txt:</strong> list of the 128 diploid occurrences used in climatic niche modelling</div> <br> <div><strong>3.pres_4x_strat_reg.txt:</strong> list of the 924 tetraploid occurrences used in climatic niche modelling</div> <br> <div><strong>biscall_chelsa_ordered_noDEM.txt:</strong> climatic data extracted from the CHELSA dataset at sampled localities</div> <br> <div><strong>4.plot_GTfreqs.md:</strong> markdown file including scripts to plot allele and genotype frequencies</div> <br> <div> </div> <h3><strong>Sharing/Access information</strong></h3> Raw sequencing reads have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI under the accession number PRJEB48869:<a href="https://www.ebi.ac.uk/ena/browser/view/PRJEB48869"> https://www.ebi.ac.uk/ena/browser/view/PRJEB48869</a></div>
Scherrenberg et al. (2024) supplement (Climate of the past): Ice-sheet model code, and output of Northern Hemisphere ice-sheet evolution of the past 800 kyr
<p>Supplement to Scherrenberg et al. (2024), article in Climate of the Past.</p> <p>This data-set contains ice-sheet model (IMAU-ICE) code (see IMAU_ICE_Code.zip; see https://github.com/IMAU-paleo/IMAU-ICE/tree/main for the most recent version of the model), the model output and configuration files (see Data_output.zip), and scripts to create figures (see Scripts_and_Figures.zip).</p> <p>Please note that additional input fields are required to run IMAU-ICE and to produce the figures. See Scherrenberg et al., (2024) for more information or contact the corresponding author.</p> <p>Citation: M.D.W. Scherrenberg, C.J. Berends, R.S.W. van de Wal: Late Pleistocene glacial terminations accelerated by proglacial lakes, climate of the past, special issue "icy landscapes of the past", 2024</p>
Data for: Global coupled climate response to polar sea ice loss: evaluating the effectiveness of different ice-constraining approaches
<p>This is the data for the paper titled "Global coupled climate response to polar sea ice loss: Evaluating the effectiveness of different ice-constraining approaches".</p>
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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.