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Dataset results
708 results for “Global dataset”
Global Datasets of Hourly Carbon and Water Fluxes Simulated Using a Satellite-based Process Model with Dynamic Parameterizations
<p>This new global hourly dataset serves as a 'handshake' among process-based models, remote sensing, and the eddy covariance flux network, providing a reliable long-term estimate of global gross primary productivity (GPP) and evapotranspiration (ET) with diurnal patterns and facilitating studies related to ecosystem functional properties, global carbon, and water cycles.</p> <p>The dataset include the GPP and ET of sunlit and shaded leaf components at an hourly timescale and a spatial resolution of 0.25-degree from 2001 to 2020.</p>
Dataset and Python Scripts used in the manuscript "Global-MHD Simulations using MagPIE : Impact of Flux Transfer Events on the Ionosphere"
<p>Dataset and Python Scripts used in the manuscript "Global-MHD Simulations using MagPIE : Impact of Flux Transfer Events on the Ionosphere".</p> <p>Authors: Arghyadeep Paul, Antoine Strugarek and Bhargav Vaidya<br> Date: 21 May, 2023</p> <p> </p> <ul> <li>Figure 1 has been plotted from two data files named Bx_By_Bz_prs_t_4783_C0.vtk and Bx_By_Bz_prs_t_4783_C1.vtk using the visualisation toolkit VisIt. Visit can be freely downloaded from https://wci.llnl.gov/simulation/computer-codes/visit</li> <li>Figure 2 has been plotted using the ipython notebook named "figure_2.ipynb" and the associated data files have been uploaded alongwith.</li> <li>Figure 3 has been plotted using the data file named "visit_prs_Bx_By_Bz_t_4964s.vtk" and the visualisation toolkit VisIt.</li> <li>Figure 4 has been plotted using the associated data files and the visualisation toolkit VisIt.</li> <li>Figures 5 and 6 has been plotted using the ipython notebook named "new_fig_5_and_6.ipynb" and the associated data files have been uploaded alongwith.</li> <li>Figure 7 has been plotted using the ipython notebook named "figure_7.ipynb" and the associated data files have been uploaded alongwith.</li> <li>Figure 8 has been plotted using the ipython notebook named "figure_8.ipynb" and the associated data files have been uploaded alongwith.</li> <li>Figure 9 has been plotted using the ipython notebook named "figure_9.ipynb" and the associated data files have been uploaded alongwith. An example swarm CSV data file is added for the python script. The original SWARM data can be downloaded from <a href="https://swarm-diss.eo.esa.int/">https://swarm-diss.eo.esa.int/</a> and the FAC data from two spacecrafts, Swarm A and C, named SW_OPER_FAC_TMS_2F has been used. This data was first published in Dong et.al. 2023 [https://doi.org/10.1029/2022GL102460].</li> </ul>
Dataset associated with "Effect of sampling bias on global estimates of ocean carbon export"
<p>Dataset and Matlab code for plotting the figures in the manuscript "Effect of sampling bias on global estimates of ocean carbon export", submitted to Geophysical Research Letters.</p>
Datasets: RECCAP2 A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes
<p>Processed data and scripts to produce figures for the contribution to RECCAP2: "A Synthesis of Global Coastal Ocean Greenhouse Gas Fluxes", published 2023.</p>
Datasets for "The direct and indirect effects of the environmental factors on global terrestrial gross primary productivity over the past four decades"
<p>The environmental changes can affect gross primary productivity (GPP) by altering not only the biogeochemical characteristics of the photosynthesis system (direct effects) but also the structure of the vegetation canopy (indirect effects). However, comprehensively quantifying the multi-pathway effects of environmental change on GPP is currently challenging. We proposed a framework to analyse the changes in global GPP by combining a nested machine-learning model and a theoretical photosynthesis model. We quantified direct and indirect effects of changes in key environmental factors (atmospheric CO2 concentration, temperature, solar radiation, vapor pressure deficit (VPD), and soil moisture) on global GPP from 1982 to 2020. The three datasets(RF_LAI, RF_GPP, and RF_GPPlai) are derived from LAI random forest model, GPP random forest model and hierarchical nested model respectively.</p>
AVONICHE: A global dataset of dietary and foraging niches for birds
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Dataset used for analyzing the critical area thresholds for undergoing rapid increases of established non-native terrestrial vertebrates in global islands
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Kernel weight contribution to yield genetic gain of maize: A global dataset of maize yield, kernel number, and kernel weight over the last century
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Dataset: Global market drivers for sustainable cephalopod food systems
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Dataset: A global synthesis of human impacts on the multifunctionality of streams and rivers
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A common resequencing‐based genetic marker dataset for global maize diversity
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A global 0.05° dataset for gross primary production of sunlit and shaded vegetation canopies (1992–2020)
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Data from: Gridded global datasets for Gross Domestic Product and Human Development Index over 1990-2015
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Dataset of global plant-soil feedback
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Global soil moisture–atmosphere feedback and N2O emission dataset
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Dataset for: Indirect nitrous oxide emission factors of fluvial networks can be predicted by dissolved organic carbon and nitrate from local to global scales
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Girasol, a sky imaging and global solar irradiance dataset
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AVOTREX: A global dataset of extinct birds and their traits (v. 1.0)
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Dataset S2: Global Synechococcus pigment type distribution from metagenomes with co-located mixed layer depths and sea surface properties
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Global Dataset of Ecohydrological Parameters Inferred from Satellite Observations
<p>This dataset contains global maps of</p> <p>(1) ecohydrological parameters for a theoretical model of the probability distribution of soil saturation;<br> (2) convergence, uncertainty and goodness-of-fit diagnostics; and<br> (3) soil water stress and uptake indexes,</p> <p>associated with analysis in: Bassiouni, M., S.P. Good, C.J. Still, and C.W. Higgins (2020), Plant water uptake thresholds inferred from satellite soil moisture. Geophysical Research Letters. <a href="https://doi.org/10.1029/2020GL087077">https://doi.org/10.1029/2020GL087077 </a></p> <p>All variable descriptions and units are included in the .nc metadata.</p> <p>Code associated with this dataset are publicly available:<br> Probabilistic Inference of Ecohydrological Parameters (PIEP): <a href="http://doi.org/10.5281/zenodo.1257718">http://doi.org/10.5281/zenodo.1257718</a>.<br> Data Management for Global PIEP: <a href="http://doi.org/10.5281/zenodo.3235820">http://doi.org/10.5281/zenodo.3235820</a></p> <p><strong>Abstract</strong><br> Empirical functions are widely used in hydrological, agricultural, and earth system models to parameterize plant water uptake. We infer soil water potentials at which uptake is downregulated from its maximum rate and at which uptake is zero, in biomes with < 60% woody vegetation at 36-km grid resolution. We estimate thresholds through Bayesian inference using a stochastic water balance framework to construct theoretical soil moisture probability distributions consistent with satellite surface soil moisture. The global median Nash–Sutcliffe efficiency between empirical soil moisture distributions derived from satellite soil moisture observations and best-fit theoretical distributions using inferred parameters is 0.8. Spatially variable thresholds capture location-specific vegetation and climate characteristics and can be connected to biome-level water uptake strategies.</p>
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.