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194 results for “21st century”

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edi56/100

Data for: Simulated postfire tree regeneration suggests reorganization of Greater Yellowstone forests during the 21st century

Tree regeneration underpins forest resilience, but how postfire tree regeneration will change with future climate and fire regimes is difficult to anticipate. Areas of sparse and failed postfire tree regeneration have been documented in western US forests, but how future recovery pathways will unfold is uncertain. We conducted a simulation study in the Greater Yellowstone Ecosystem (GYE; United States) using a process-based model, iLand, to ask how rates, composition, and spatial patterns of postfire tree regeneration vary with 21st-century climate. Subalpine forest and fire dynamics were simulated through 2100 under four climate scenarios, 2 × 2 factorial of aridity (wet and dry) and temperature (warm and hot), in five GYE landscapes. We tallied postfire tree seedling density by species in simulated fires (> 400 ha) at five years postfire. This data set contains three data sets to reproduce analyses for changes rates of regeneration, proportion of burned cells with regeneration failure, and postfire reorganization pathways. We include the data and R scripts used for these three analyses in the publication associated with these data.

openCC (other)Aug 2025View details →

zenodo44/100

Dataset for "Changes in Global Terrestrial Live Biomass over the 21st Century"

Live woody vegetation is the largest reservoir of biomass carbon with its restoration considered one of the most effective natural climate solutions. However, carbon fluxes associated with terrestrial ecosystems still remain the largest source of uncertainty of the global carbon balance. Here, we develop spatially explicit estimates of global carbon stock changes of live woody biomass from 2000 to 2019 using measurements from ground, air, and space. We show live biomass has removed 4.9-5.5 PgC yr-1 from the atmosphere in this century, offsetting 4.6±0.1 PgC yr-1 of gross emissions from land-use and environmental disturbances and adding substantially (0.23-0.88 PgC yr-1) to the global carbon stocks. Gross emissions and removals in the tropics were four times larger than temperate and boreal ecosystems combined. Although live biomass is responsible for more than 80% of gross terrestrial fluxes, soil, dead organic matter, and lateral transport may play important roles in terrestrial carbon sink.

opencc-by-4.0Dec 2020View details →

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FESOM-REcoM model data: Severe 21st-century ocean acidification in Antarctic Marine Protected Areas

This repository contains all post-processed model output used in the paper "Severe 21st-century ocean acidification in Antarctic Marine Protected Areas". It contains the data underlying the figures in the paper, such as regional averages, as well as masks for the marine protected areas and the grid information file of the original model output.The data were created using python scripts provided at <a href="https://doi.org/10.5281/zenodo.10295920">https://doi.org/10.5281/zenodo.10295920</a>. Original model output, including full fields of computed pH and saturation states with respect to aragonite and calcite, is available at the World Data Center for Climate (WDCC) under the following DOIs:<ul><li>simA, historical: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_hist_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_hist_vA_vC</a></li><li>simA, ssp126: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s126_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s126_vA_vC</a></li><li>simA, ssp245: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s245_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s245_vA_vC</a></li><li>simA, ssp370: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s370_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s370_vA_vC</a></li><li>simA, ssp585: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s585_vA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_A_s585_vA_vC</a></li><li>simB: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_B_1921_cA_cC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_B_1921_cA_cC</a></li><li>simC, historical: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_C_hist_vA_cC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_C_hist_vA_cC</a></li><li>simC, ssp245: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_C_s245_vA_cC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_C_s245_vA_cC</a></li><li>simC, ssp585: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_C_s585_vA_cC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_C_s585_vA_cC</a></li><li>simC, historical: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_D_hist_cA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_D_hist_cA_vC</a></li><li>simC, ssp585: <a href="https://doi.org/10.26050/WDCC/FESOM14-REcoM2_D_s585_cA_vC">https://doi.org/10.26050/WDCC/FESOM14-REcoM2_D_s585_cA_vC</a></li></ul>

opencc-by-4.0Dec 2023View details →

zenodo44/100

Dataset for "Mass loss of the Greenland ice sheet until the year 3000 under a sustained late-21st-century climate"

Dataset for the paper "Mass loss of the Greenland ice sheet until the year 3000 under a sustained late-21st-century climate" (Journal of Glaciology, <a href="https://doi.org/10.1017/jog.2022.9">https://doi.org/10.1017/jog.2022.9</a>). Please see the README for details. V1.2: Now providing compressed netCDF files with reduced size. V1.1: Scalar flux variable 'dlimdt' (total ice mass change) added. README updated. V1: Initial upload. * * * * * * * Users should cite the original publication when using all or parts of these data.

opencc-by-4.0Feb 2022View details →

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Dataset for "Mass loss of the Antarctic ice sheet until the year 3000 under a sustained late-21st-century climate"

Dataset for the paper "Mass loss of the Antarctic ice sheet until the year 3000 under a sustained late-21st-century climate" (Journal of Glaciology, <a href="https://doi.org/10.1017/jog.2021.124">https://doi.org/10.1017/jog.2021.124</a>). Please see the README for details. V2: New version with ISMIP6-type variables and compressed netCDF files. V1: Initial upload. * * * * * * * The following script may be used to download the entire content of the archive on a Unix/Linux system: #!/bin/bash # --- download_all.sh --- wget https://zenodo.org/record/6215117/files/_README.pdf wget https://zenodo.org/record/6215117/files/run_specs_headers.zip for aexp in hist ctrl_proj_long \     exp05_long exp06_long exp07_long exp08_long exp09_long exp10_long \     exp12_long exp13_long \     expA5_long expA6_long expA7_long expA8_long \     expB6_long expB7_long expB8_long expB9_long expB10_long; do     wget https://zenodo.org/record/6215117/files/${aexp}.zip done for aexp in abuc_long abuciso_long \             abuk_long abukiso_long \             abum_long abumiso_long; do     wget https://zenodo.org/record/6215117/files/${aexp}.zip done * * * * * * * Users should cite the original publication when using all or parts of these data.

opencc-by-4.0Nov 2021View details →

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GFDL hurricane model track data associated with "Dynamical downscaling projections of late 21st century U.S. landfalling hurricane activity"

These data include North Atlantic tropical cyclone track and intensity for control and projected late 21st century simulation from the GFDL hurricane model used in a Climatic Change manuscript:  Knutson, T., J. Sirutis, M. Bender, R. Tuleya, and B. Schenkel, 2022: Dynamical downscaling projections of late 21st century U.S. landfalling hurricane activity. Clim. Change, 171, 1–23. A readme file included below describes the variables and format of the tropical cyclone track data.  Questions about the dataset may be directed to Ben Schenkel (<a href="mailto:benschenkel@gmail.com">benschenkel@gmail.com</a>) and Tom Knutson (<a href="mailto:tom.knutson@noaa.gov">tom.knutson@noaa.gov</a>).

opencc-by-4.0Jul 2022View details →

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GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (anonymized version - third part)

<a title="GENEActiv" href="https://activinsights.com/technology/geneactiv/" target="_blank" rel="noopener">GENEActiv</a> accelerometer .csv files converted with a 1 second epoch from raw GENEActiv .bin files recorded during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"]. Devices are 60-Hz triaxial accelerometers. This dataset also contains participantCharacteristics.csv that povides basic information about participants and read_a_binFile_share.R that is a short R code aiming at converting and saving accelerometer data from .bin files in 1 second epoch .csv files (consider the Methods section). Participant characteristics: 10 to 16 years old students and some parents. Number of participants: 231 (206 adolescents + 25 adults). Year of the study: 2018 - 2019. Place of the study: New Caledonia. The accelerometer .csv files with a 1 second epoch and extracted from raw .bin files are available in open datasets: <ul> <li><a title="Open dataset - first part" href="https://doi.org/10.5281/zenodo.12615468" target="_blank" rel="noopener">anonymized version - first part</a></li> <li><a title="Open dataset - second part" href="https://doi.org/10.5281/zenodo.12638746" target="_blank" rel="noopener">anonymized version - second part</a></li> <li><a title="Open dataset - third part" href="https://doi.org/10.5281/zenodo.12682660" target="_blank" rel="noopener">anonymized version - third part</a></li> </ul> The accelerometer raw .bin files are available in restricted datasets: <ul> <li><a title="Restricted dataset - first part" href="https://doi.org/10.5281/zenodo.11594645" target="_blank" rel="noopener">non-anonymized version - first part</a></li> <li><a title="Restricted dataset - second part" href="https://doi.org/10.5281/zenodo.12638965" target="_blank" rel="noopener">non-anonymized version - second part</a></li> <li><a title="Restricted dataset - third part" href="https://doi.org/10.5281/zenodo.12661429" target="_blank" rel="noopener">non-anonymized version - third part</a></li> </ul> Other participant characteristics (age, place of living, cultural community and socio-economic status) are available in a <a title="Information associated with GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [en: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (non-anonymized information version)" href="https://doi.org/10.5281/zenodo.12195186" target="_blank" rel="noopener">restricted non-anonymized dataset</a>. When using this dataset, please cite the following reference: <a title="Wattelez et al. 2025" href="https://doi.org/10.1016/j.dib.2024.111228" target="_blank" rel="noopener">G. Wattelez, S. Frayon, O. Galy, Assessing physical activity/behavior of adolescents living in the Pacific with accelerometer data: 231 GENEActiv records in New Caledonia, Data in Brief 58 (2025) 111228, doi: 10.1016/j.dib.2024.111228</a>

embargoedcc-by-4.0Jun 2024View details →

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GENEActiv accelerometer files collected during the project entitled "Cultures et comportements alimentaires de la jeunesse dans les pays francophones du Pacifique au XXIème siècle: exemple de la Nouvelle-Calédonie" [Eng: "Eating cultures and behaviors of young people in French-speaking Pacific countries in the 21st century: the example of New Caledonia"] (anonymized version - second part)

embargoedcc-by-4.0Jun 2024View details →

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Beneath the SURFace: An MRI-like View into the Life of a 21st Century Datacenter

This is a trace archive of metrics collected from the Lisa cluster at SURFsara associated with the article that will be published in USENIX;login: in July 2020. Github repository which contains documentation as well as scripts required to replicate the work from the login paper: <a href="https://github.com/sara-nl/SURFace">https://github.com/sara-nl/SURFace</a> Real-world data can be instrumental in answering detailed questions: How do we know which assumptions regarding large-scale systems are realistic? How do we know that the systems we build are practical? How do we know which metrics are important to assess when analyzing performance? To answer such questions, we need to collect and share operational traces containing real-world, detailed data. Not only is the presence of low-level metrics significant, but they also help avoid biases through their variety. To address variety, there exist several types of archives, such as the Parallel Workloads Archive, the Grid Workloads Archive, and the Google or Microsoft logs (the Appendix gives a multi-decade overview). However, such traces mostly focus on higher-level scheduling decisions and high-level, job-based resource utilization (e.g., consumed CPU and memory). Thus, they do not provide vital information to system administrators or researchers analyzing the full-stack or the OS-level operation of datacenters.  The traces we are sharing have the finest granularity of all other open-source traces published so far. In addition to scheduler-level logs, they contain over 100 low-level, server-based metrics, going to the granularity of page-faults or bytes transferred through a NIC.   The SURF archive Datacenters already exhibit unprecedented scale and are becoming increasingly more complex. Moreover, such computer systems have begun having a significant impact on the environment, for example, training some machine learning models has sizable carbon footprints. As our recent work on modern datacenter networks shows, low-level data is key to understanding full-stack operation, including high-level application behavior. We advocate it is time to start using such data more systematically, unlocking its potential in helping us understand how to make (datacenter) systems more efficient. We advocate that our data can contribute to a more holistic approach, looking at how the multitude of these systems work together in a large-scale datacenter.    This archive contains data from the Dutch National Infrastructure, Lisa.   <a href="https://userinfo.surfsara.nl/systems/lisa/description">Description of the Lisa system</a>   <a href="https://userinfo.surfsara.nl/systems/cartesius/description">Description of the Cartesius system</a>   We gather metrics, at 15-second intervals, from several data sources: <ul> <li> Slurm: all job, task, and scheduler related data, such as running time, queueing time, failures, servers involved in the execution, organization in partitions, and scheduling policies. </li> <li> NVIDIA Management Library (NVML): per GPU, data such as power metrics, temperature, fan speed, or used memory. </li> <li> IPMI: per server, data such as power metrics and temperature. </li> <li> OS-level: from either procfs, sockstat, or netstat data: low-level OS metrics, regarding the state of each server, including CPU, disk, memory, network utilization, context switches, and interrupts.  </li> </ul>   We also release other kinds of novel information, related to datacenter topology and organization.   The audience we envision using these metrics is composed of systems researchers, infrastructure developers and designers, system administrators, and software developers for large-scale infrastructure. The frequency of collecting data is uniquely high for open-source data, which could allow these experts unprecedented views into the operation of a real datacenter. * Note: For the GPU metrics a number of nodes were introduced to the system in late Feb/start of March and as such these specific nodes have no data available in January and February which may cause irregularities. The github will contain code snippets that will show how to filter this data such that this is not a problem and how to graph the parquet data (this is pending update in the next few days.

opencc-by-4.0Jun 2020View details →

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Data, Sensitivity of 21st-century projected ocean new production changes to idealized biogeochemical model structure

Data for reproducing figures in journal article submitted to Biogeosciences in December 2020. Data generated from global 1-degree simulations of the CESM in an ocean-ice configuration. NP model by Brett. See 10.5281/zenodo.4361705 for code for NP model and to use this dataset to recreate paper figures.

opencc-by-4.0Dec 2020View details →

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Data set: "A 21st Century Warming Threshold for Sustained Greenland Ice Sheet Mass Loss"

This data set includes the materials required to reproduce the figures and tables presented in the study: "A 21st Century Warming Threshold for Sustained Greenland Ice Sheet Mass Loss". The data consist of: <ul> <li>Maps of annual historical and projected surface mass balance (SMB) of the Greenland ice sheet (GrIS) from RACMO2.3p2 at 1 km spatial resolution in NetCDF format.</li> </ul> <ol> <li>smb_rec.1950-2014.BN_RACMO2.3p2-CESM2-Historical.1km.YY.nc: annual cumulative GrIS SMB (kg m-2 or mm w.e. per year) from RACMO2.3p2 forced by CESM2 for the historical period 1950-2014, further statistically downscaled to 1 km spatial resolution.</li> <li>smb_rec.2015-2099.BN_RACMO2.3p2-CESM2-SSP5-85.1km.YY.nc: annual cumulative GrIS SMB (kg m-2 or mm w.e. per year) from RACMO2.3p2 forced by CESM2 under a high-end warming scenario SSP5-8.5 for the period 2015-2099, further statistically downscaled to 1 km spatial resolution.</li> <li>Icemask_Topography_lon_lat_average_1km_GrIS.nc: mask file including an ice mask (Promicemask) separating Greenland's peripheral glaciers and ice caps (values 1 and 2) from the main ice sheet (value 3), surface topography derived from the GIMP DEM, and longitude/latitude coordinates on the 1 km grid. </li> </ol> NB: the NetCDF files above use a Polar Stereographic North (EPSG:3413) projection with a horizontal resolution of 1 km x 1 km. The reference point is located at 45ºW longitude and 70ºN latitude. <ul> <li>Time series of historical and projected annual GrIS-integrated SMB (Gigatons or Gt per year) and annual mean GrIS temperature (TGrIS; K) from RACMO2.3p2 at 1 km spatial resolution in ASCII format.</li> </ul> <ol> <li>SMB_TGrIS_RACMO2.3p2-CESM2_Historical_1950-2014.dat: time series of annual GrIS-integrated SMB (Gt yr-1) and mean TGrIS (K) from the CESM2-forced RACMO2.3p2 simulation for the historical period 1950-2014.</li> <li>SMB_TGrIS_RACMO2.3p2-CESM2_SSP5-8.5_2015-2099.dat: time series of annual GrIS-integrated SMB (Gt yr-1) and mean TGrIS (K) from the CESM2-forced RACMO2.3p2 projection under a high-end warming scenario SSP5-8.5 (2015-2099).</li> </ol> <ul> <li>Time series of historical and projected reconstruction of annual GrIS-integrated SMB (Gt yr-1) and mean TGrIS (K) from 12 CESM2 historical members and 10 CESM2 projections under various warming scenarios, namely SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5.</li> </ul> <ol> <li>Reconstructed_SMB_CESM2_Historical_1950-2014.dat: time series of reconstructed annual GrIS-integrated SMB (Gt yr-1) from the parent historical CESM2 simulation (HIST-parent) used to force RACMO2.3p2 and 11 additional historical CESM2 members (HIST-X) for 1950-2014.  </li> <li>Reconstructed_SMB_CESM2_Projections_2015-2099.dat:  time series of reconstructed annual GrIS-integrated SMB (Gt yr-1) from the parent CESM2 projection (SSP5-8.5-parent) used to force RACMO2.3p2 and 9 additional CESM2 projection members (SSP1-2.6-X to SSP5-8.5-X ) for 2015-2099. </li> <li>TGrIS_CESM2_Historical_1950-2014.dat: time series of annual mean TGrIS (K) from the parent historical CESM2 simulation (HIST-parent) used to force RACMO2.3p2 and 11 additional historical CESM2 members (HIST-X) for 1950-2014.</li> <li>TGrIS_CESM2_Projections_2015-2099.dat: time series of annual mean TGrIS (K) from the parent CESM2 projection (SSP5-8.5-parent) used to force RACMO2.3p2 and 9 additional CESM2 projection members (SSP1-2.6-X to SSP5-8.5-X ) for 2015-2099. </li> </ol> NB: the file Crossref_sim_names.txt cross-references the simulation abbreviations in the above .dat files to official simulation names from the National Center for Atmospheric Research (NCAR). The daily downscaled SMB data set from the CESM2-forced RACMO2.3p2 historical simulation and SSP5-8.5 projection are freely available from the authors upon request and without conditions (contact: b.p.y.noel@uu.nl). Besides SMB, the data set includes daily total precipitation (snow and rain), snowfall, total melt (snow and ice), meltwater runoff, retention and refreezing, total sublimation (surface and drifting snow), snow drift erosion, as well as 2 m air temperature at 1 km horizontal resolution.  Abstract: "Under anticipated future warming, the Greenland ice sheet (GrIS) will pass a threshold when meltwater runoff exceeds the accumulation of snow, resulting in a negative surface mass balance (SMB < 0) and sustained mass loss. In spite of several recent warm summers with high melt rates, SMB < 0 has not been reached since at least the year 1958. Here we dynamically and statistically downscale the outputs of an Earth system model to 1 km resolution to infer that a Greenland near-surface atmospheric warming of 4.5 ± 0.3 °C—relative to pre-industrial—is required for GrIS SMB to become persistently negative. Climate models from CMIP5 and CMIP6 translate this regional temperature change to a global warming threshold of 2.7 ± 0.2 °C. Under a high-end warming scenario, this threshold may be reached around 2055, while for a strong mitigation scenario it will likely not be passed."

opencc-by-4.0Jan 2021View details →

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Deep learning reveals hotspots of global oceanic oxygen changes in the 21st century

This is a global ocean-scale dissolved oxygen dataset derived from a deep learning method using hydrometeorological and biogeocheical driver factors. The dataset provides yearly estimates of dissolved oxygen concentration during 2003 to 2020 throughout the whole water column, with a spatial resolution of  0.25° × 0.25°. The unprecedented high-resolution dataset provides information on dissolved oxygen spatial distribution and temporal trend, making it a significant contribution to understanding global warming and anthropogenic stressors.

opencc-by-4.0Mar 2024View details →

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Supplementary Data for "Sequencing the Pandemic: Rapid and High-Throughput Processing and Analysis of COVID-19 Clinical Samples for 21st Century Public Health"

Supplementary material for F1000 methods manuscript. Includes raw sequencing metrics for two COVID sequencing methodologies, as well as a complete cost breakdown for each methodology.

opencc-by-4.0Jan 2022View details →

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Data for manuscript: Ecological lags govern the pace and outcome of plant community responses to 21st century climate change

These data were used in the analyses reported in Block et al. "Ecological lags govern the pace and outcome of plant community responses to 21st century climate change".

opencc-by-4.0Mar 2022View details →

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Will forest dynamics continue to accelerate throughout the 21st century in the Northern Alps?

Observational evidence suggests that forests in the Northern Alps are changing at an increasing rate as a consequence of climate change. Yet, it remains unclear whether the acceleration of forest change will continue in the future, or whether downregulating feedbacks will eventually decouple forest dynamics from climate change. Here we studied future forest dynamics at Berchtesgaden National Park, Germany by means of a process-based forest landscape model, simulating an ensemble of 22 climate projections until the end of the 21st century. Our objectives were (i) to assess whether the observed acceleration of forest dynamics will continue in the future, (ii) to analyze how uncertainty in future climate translates to variation in future forest disturbance, structure, and composition, and (iii) to determine the main drivers of future forest dynamics. We found that forest dynamics continue to accelerate in the coming decades, with a trend towards denser, structurally more complex and more species rich forests. However, changes in forest structure leveled off in the second half of the 21st century regardless of climate scenario. In contrast, climate scenarios caused trajectories of tree species change to diverge in the second half of the 21st century, with stabilization under RCP 2.6 and RCP 4.5 scenarios and accelerated loss of conifers under RCP 8.5. Disturbance projections were 3 to 20 times more variable than future climate, whereas projected future forest structure and composition varied considerably less than climate. Indirect effects of climate change via alterations of the disturbance regime had a stronger impact on future forest dynamics than direct effects. Our findings suggest that dampening feedbacks within forest dynamics will decelerate forest change in the second half of the 21st century. However, warming beyond the levels projected under RCP 4.5 might profoundly alter future forest disturbance and composition, challenging conservation efforts and ecosystem service supply. --

opencc-zeroMar 2022View details →

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A 21st century high-resolution glacier and ice sheet fractional area dataset: Code and Data

This resource contains code and input data to develop a high-resolution (0.1°) gridded global glacier and ice sheet fractional area dataset, which is also available in this resource. The dataset is developed from Randolph Glacier Inventory v6.0 shapefiles and supplementary shapefiles for the Antarctic and Greenland ice sheets. The approach is adapted from Li et al., (2021; <a href="https://doi.org/10.1017/jog.2021.28">https://doi.org/10.1017/jog.2021.28</a>). The dataset provides estimates of the fraction (0 to 1) of land cover that is glaciated in each 0.1° x 0.1° grid cell. The dataset was designed for use in the SPEAR model (<a href="https://www.gfdl.noaa.gov/spear/">https://www.gfdl.noaa.gov/spear/</a>) from the NOAA Geophysical Fluid Dynamics Laboratory (GFDL), but may be useful for other applications as well. This work is documented in a NOAA Technical Memorandum (citation information to follow).

opencc-by-4.0Apr 2022View details →

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Extreme sea level rise along the Indian Ocean coastline: Observations and 21st century projections

This file include all the data sets used to make the figures in the paper " Extreme sea level rise along the Indian Ocean coastline: Observations and 21st century projections "

opencc-by-4.0May 2022View details →

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Dataset for: Fire and forest loss in the Dominican Republic during the 21st Century

This dataset is required to reproduce the code for the manuscript entitled 'Fire and forest loss in the Dominican Republic during the 21st Century' Preprint: https://doi.org/10.1101/2021.06.15.448604 Code: https://github.com/geofis/forest-loss-fire-reproducible

opencc-by-4.0Nov 2021View details →

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Fig. 3 in A review of reptile research in Malaysia in the 21st century

Fig. 3. Bar plots grouped by category. Numbers above bars represent the total number of papers published in each category (A); number of papers published in the systematics category, grouped by data type (B).

opencc-by-4.0Sep 2021View details →

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Fig. 2 in A review of reptile research in Malaysia in the 21st century

Fig. 2. Percentage of papers published by category (A); number of papers published in each category according to taxonomic group (B).

opencc-by-4.0Sep 2021View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas

neuroscienceopenDocumentation, web resources, and API references are available online.

Last verified 2026-04-30Open record

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.

abode-home-cage

behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.

Last verified 2026-04-30Open record

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.

dandi-nwb

electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.

Last verified 2026-04-30Open record

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.

ibl

behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.

Last verified 2026-04-29Open record

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.

openneuro

neuroscienceopenPublished datasets are available on demand over the internet.

Last verified 2026-04-29Open record