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1,477 results for “earth”
Supplementary material for "Rare earth elements and yttrium in Polish rivers and the input of anthropogenic gadolinium into the Baltic Sea"
<p>This dataset is presented and discussed in the research article “Rare earth elements and yttrium in Polish rivers and the input of anthropogenic gadolinium into the Baltic Sea” by Alemu et al. This manuscript will be submitted to Environmental Pollution and was prepared by the following authors: Addis Kokeb Alemu (1,2), Keran Zhang (1), David Ernst (1), and Michael Bau (1). </p> <p>1Critical Metals for Enabling Technologies – CritMET, School of Science, Constructor University, Campus Ring 1, 28759 Bremen, Germany</p> <p>2Department of Chemistry, College of Natural and Computational Sciences, University of Gondar, P.O. Box 196, Gondar, Ethiopia</p> <p> </p> <p> </p> <p>Table A1 includes the general information and data for all sampling stations and reference materials used. </p> <p>Figs. A1 and A2 show the concentrations of total Gd and anthropogenic Gd in samples from the Oder River (OD) and its major tributary, the Warta River (Wa), as well as the Vistula River (VS) and its major tributaries: San (Sn), Bug (BG), Brda (BR), and Narew (NR).</p>
Marinoan Snowball Earth: The Impact of Deglaciation Duration on the Sea-Level History of Continental Margins
<p>Paleogeographies, ice histories, and predicted relative sea level output are available here as Matlab (.mat) files. Complementary text (.txt) files are included for latitude, longitude, and time. For different file formats or any questions to their use, please contact the corresponding author, Freya K Morris at: morrisfreya15@outlook.com</p>
Global and Sequential Imaging Observation of the Earth's Plasmasphere by PHOENIX Onboard EQUULEUS
<p>A dataset used in "<span>Global and Sequential Imaging Observation of the Earth’s Plasmasphere by PHOENIX Onboard EQUULEUS</span>"</p>
Supporting Data: The Effect of Ocean Salinity on Climate and its Implications for Earth's Habitability
<p>Data supporting "The Effect of Ocean Salinity on Climate and its Implications for Earth's Habitability" by SL Olson, MF Jansen, DS Abbot, I Halevy, and C Goldblatt, submitted to GRL on April 18, 2022. The ROCKE-3D rundecks and input files required to reproduce these results are also included. </p>
Data and scripts for Journal of Geophysical Research – Earth Surface publication: Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina
<p>This data source contains scripts and data associated with the JGR Earth Surface publication <strong>“Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina”</strong> by A. Mueting, B. Bookhagen, and M. R. Strecker. The Digital Elevation Model (DEM) of the lower part of the Quebrada del Toro and Río Capilla catchment in the NW Argentinian Andes was generated from SPOT-7 tri-stereo images using Ames Stereo Pipeline. The final dataset has a spatial resolution of 3 m. A full description of the DEM generation process and accuracy assessment can be found in the associated paper. The scripts are also available at https://github.com/UP-RS-ESP/DEM_ConnectedComponents.</p>
Combined data file for Jilbert et al. "Anthropogenic Inputs of Terrestrial Organic Matter Influence Carbon Loading and Methanogenesis in Coastal Baltic Sea Sediments", Frontiers in Earth Science 9, 2021
<p>The datafile contains all the new raw data presented in the figures in the publication.</p>
Data for Klaes et al. High-resolution stalagmite stratigraphy supports the Late Holocene tephrochronology of southernmost Patagonia. Comms. Earth Environ. (2022)..
<p>This data set comprises the LA-ICP-MS, ICP-MS, EPMA and NanoSIMS measurements as well as SEM imagery presented in the research paper 'High-resolution stalagmite stratigraphy supports the Late Holocene tephrochronology of southernmost Patagonia' by Klaes et al. The Th-U data of the revised chronology of stalagmite MA1 with the calculated correction values according to Budsky et al. (2016) are also included. In addition, stable isotope data from Schimpf et al. (2011) with the revised version of the age-depth model are given. For detailed information on the analyses (e.g., instruments used), the user is kindly referred to the methods section of the article. </p>
Dataset accompanying Buscombe et al.: Human-in-the-loop segmentation of earth surface imagery
<p>The datasets used in this study are provided in 7 folders:</p> <ol> <li> <p>"dataset A", containing data from Sandwich Town Neck Beach on Cape Cod, Massachusetts. These images are published as a USGS data series (Sherwood et al., 2021) are publicly available at <a href="https://doi.org/10.5066/P9BFD3YH">https://doi.org/10.5066/P9BFD3YH</a></p> </li> <li> <p>"dataset B", containing data from North and South Carolina collected immediately after Hurricane Florence in October 2018. National Geodetic Survey emergency response imagery courtesy of the National Oceanic and Atmospheric Administration, available at <a href="https://storms.ngs.noaa.gov/">https://storms.ngs.noaa.gov</a></p> </li> <li> <p>"dataset C", containing some examples of shoreline environments captured by a low-altitude aircraft. These images are published as a USGS data series (Kranenburg et al., 2020) are publicly available at <a href="https://doi.org/10.5066/P9CA3D8P">https://doi.org/10.5066/P9CA3D8P</a></p> </li> <li> <p>"dataset D", containing data collected from the Pearl River and its tributary the Bogue Chitto, and from the Chickasawhay, Buoy and Leaf tributaries of the Pascagoula River, in spring 2021. Used with permission from U.S. Fish and Wildlife Service</p> </li> <li> <p>"dataset E", containing Sentinel-2 satellite images of coastal lagoon environments in Salinas Rivermouth Natural Preserve and National Wildlife Refuge in Monterey, California. Sentinel-2 imagery courtesy of European Space Agency (ESA)</p> </li> <li> <p>"dataset F", containing Landsat-8 of Cape Hatteras, Cape Hatteras National Seashore, North Carolina. Landsat-8 imagery is courtesy of U.S. Geological Surve</p> </li> <li> <p>"code", containing a version of the code used to generate the results contained in this data repository. Full details about this code can be obtained from the github code repository (<a href="https://github.com/dbuscombe-usgs/dash_doodler">https://github.com/dbuscombe-usgs/dash_doodler</a>) and website (<a href="https://dbuscombe-usgs.github.io/dash_doodler/">https://dbuscombe-usgs.github.io/dash_doodler/</a>).</p> </li> </ol>
Global Socio-Economic and Environmental data for PyPSA-Earth: An Open Optimisation Model of the Earth Energy System.
<p><strong>PyPSA-Earth </strong>is an open model dataset of the global power system at different network levels that cover our Earth. The African model can be built using the code provided at <a href="https://github.com/pypsa-meets-africa/pypsa-africa">https://github.com/pypsa-meets-africa/pypsa-africa</a>. Other regions follow soon under the same code base.</p> <p>Since the GitHub codebase is not suited for handling large changing files, we provide here separate <strong>data bundles and cutouts</strong> to be downloaded and extracted as noted in the <a href="https://pypsa-meets-africa.readthedocs.io/en/latest/index.html">documentation</a></p> <p>The below-provided<strong> data files </strong>contain various open data for improving energy system modelling decisions. A thorough description with license restrictions will follow soon.</p>
SeisSol input files for the dynamic rupture scenarios based on the 2004 Sumatra-Andaman earthquake published in Madden et al. (2022) "The state of pore fluid pressure and 3D megathrust earthquake dynamics" JGR-Solid Earth
<p>This dataset contains the input files of the dynamic rupture scenarios from Madden, E. H., T. Ulrich and A.-A. Gabriel (2022), The State of Pore Fluid Pressure and 3-D Megathrust Earthquake Dynamics, Journal of Geophysical Research-Solid Earth, <a href="https://doi.org/10.1029/2021JB023382">https://doi.org/10.1029/2021JB023382</a>. (Earlier preprint available at: <a href="https://doi.org/10.1002/essoar.10508297.1">https://doi.org/10.1002/essoar.10508297.2</a>)</p> <p><strong>easi/yaml parameter files for the 6 scenarios studied: </strong><br> PAR_Sumatra_scen1new_gen.par, PAR_Sumatra_scen2new_gen.par, PAR_Sumatra_scen3new_gen.par, PAR_Sumatra_scen4new_gen.par, PAR_Sumatra_scen5new_gen.par, PAR_Sumatra_scen6new_gen.par</p> <p><strong>easi/yaml files setting initial on-fault friction, stress and pore fluid pressure conditions for the 6 scenarios studied: </strong>iniStress_Sumatra_scen1new.yaml, iniStress_Sumatra_scen2new.yaml, iniStress_Sumatra_scen3new.yaml, iniStress_Sumatra_scen4new.yaml, iniStress_Sumatra_scen5new.yaml, iniStress_Sumatra_scen6new.yaml<br> <br> <strong>easi/yaml file describing the rock elastic properties in all 6 scenarios:</strong> <br> matprops_Sumatra_2019_LVZ.yaml<br> <br> <strong>mesh file:</strong> <br> topo4_splays_fix9-14.1e6-28m.dtc1-v2-suma</p> <p> </p>
A mechanism for the strange metal phase in rare-earth intermetallic compounds
<p>Codes and numerical data for each Figure created for the study in Jiangfan Wang, et al., <em>A mechanism for the strange metal phase in rare-earth inter-metallic compounds </em>and its supporting information.</p>
Data sets for 'Mechanical Compliance of Individual Fractures in a Heterogeneous Rock Mass from Production-type Full-waveform Sonic Data', submitted to JGR: Solid Earth
<p>Synthetic and field FWS data sets are supplied for validation of proposed methods for compliance estimation of individual fractures. Each zip contains ‘ReadMe.txt ‘, which illustrates the files and corresponding parameters. More details about the setup in the submitted paper ‘Mechanical Compliance of Individual Fractures in a Heterogeneous Rock Mass from Production-type Full-waveform Sonic Data’.</p>
Antarctic surface climate and surface mass balance in the Community Earth System Model version 2 (1850-2100) - AWS data
<p>This Antarctica AWS temperature and wind speed dataset was compiled by Alexandra Gossart and Niels Souverijns (<a href="https://doi.org/10.1175/JCLI-D-19-0030.1">https://doi.org/10.1175/JCLI-D-19-0030.1</a>).</p>
Supporting trees and alignments for the publication: Cryptic and abundant marine viruses at the evolutionary origins of Earth's RNA virome
<div class="page"> <div class="layoutArea"> <div class="column"> <p>Whereas DNA viruses are known to be abundant, diverse, and commonly key ecosystem players, RNA viruses are relatively understudied outside disease settings. Here, we analyzed ≈28 terabases of Global Ocean RNA sequences to expand Earth's RNA virus catalogues and their taxonomy, investigate their evolutionary origins, and assess their marine biogeography from pole to pole. Using new approaches to optimize discovery and classification, we identified RNA viruses that necessitate substantive revisions of taxonomy (doubling phyla and adding >50% new classes) and evolutionary understanding. "Species"-rank abundance determination revealed that viruses of new phyla<span> </span><em>"Taraviricota"</em><span>, </span>a missing link in early RNA virus evolution, and<span> </span><em>"Arctiviricota"</em><span> </span>are widespread and dominant in the oceans. These efforts provide foundational knowledge critical to integrating RNA viruses into ecological and epidemiological models.</p> </div> </div> </div>
ARISE-SAI-1.5: Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection, with cooling to 1.5C
<p>Assessing Responses and Impacts of Solar climate intervention on the Earth system with Stratospheric Aerosol Injection (ARISE-SAI) is a set of simulations carried out with the Community Earth System Model, version 2 with the Whole Atmosphere Community Climate Model, version 6 (CESM2(WACCM6)) that aims at simulating a plausible deployment of solar climate intervention of stratospheric aerosol injection to enable community assessment of responses of the Earth system. This first set of simulations introduce stratospheric aerosol injection at ~ 21 km in simulated year 2035, called ARISE-SAI-1.5, utilize the middle-of-the-road SSP2-4.5 emission scenario,, and keep global mean surface air temperature near 1.5°C above the pre-industrial value. Sulfur dioxide injections in the ARISE-SAI-1.5 simulations are placed at four injection locations (15°S, 15°N, 30°S, 30°N) into one grid box at 180° longitude, and midpoint altitude of 21.6 km. The injection amount at each latitude is specified annually by a “controller” algorithm. This strategy ensures that the global mean surface temperature (T0), north-south temperature gradient (T1), and equator-to-pole temperature gradient (T2) remain close to ~ 1.5°C above the pre-industrial value throughout the simulation.</p> <p> </p> <p>The files contained here contain output of surface temperature (TREFHT), total precipitation (PRECT), SO4, and controller log files with amounts of SO2 injection. </p>
Descarga de imágenes satélite con Earth Explorer
<p>Este video explica el proceso de descarga de imágenes satelitales a través de la aplicación Earth Explorer (https://earthexplorer.usgs.gov/). También se especifica una introducción a la teledetección.</p> <p> </p> <p>This video explains the process of downloading satellite images through the Earth Explorer app (https://earthexplorer.usgs.gov/). An introduction to remote sensing is also specified.</p>
The conductivity profile of Earth-ionosphere cavity used in the paper "Finite-difference time-domain analysis of ELF radio wave propagation in the spherical Earth-ionosphere waveguide and its validation based on analytical solutions" by Volodymyr Marchenko, Andrzej Kulak, Janusz Mlynarczyk
<p>The file "Marchenko_FDTD_Paper_Conductivity_Profile.dat" contains the conductivity profile of Earth-ionosphere cavity. The first column provides the altitude (in km) and the second column provides the conductivity (in S/m).</p>
Supplementary Datasets for 'Exploring rift geodynamics in Ethiopia through olivine-spinel Al-exchange thermometry and rare-earth element distributions'
<p>Supplementary Datasets for 'Exploring rift geodynamics in Ethiopia through olivine-spinel Al-exchange thermometry and rare-earth element distributions'.</p> <p>Dataset S1: Qualitative X-ray maps of Mg, Ca, Al, Ni, P in olivine-spinel pairs.<br> Dataset S2: Quantitative EPMA point analyses of olivine and spinel. Includes Sheet 1: Secondary standards; Sheet 2: Sample data.<br> Dataset S3: Full inversion outputs from MultiNest.</p>
Modification of the Loss Cone for Energetic Particles in the Earth's Inner Magnetosphere
<p>Journal of Geophysical Research</p> <p>Computer generated data to study the shift of the loss cone</p>
Data for NHESS manuscript by Biass et al. (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data
<p>This repository contains the data produced in the context of the following paper:</p> <blockquote> <p>Biass S, Jenkins SF, Aberhard WH, Delmelle P, Wilson T (2022): Insights into the vulnerability of vegetation to tephra fallouts from interpretable machine learning and big Earth observation data, Accepted in NHESS</p> </blockquote> <p>Naming convention is: `run_date`_`landcover`_`impact_metrics`_`VI`_`anomaly`_test.pkl, where:</p> <ul> <li>Landcover is either crops, shrubs, herbaceous vegetation (grass), forests (trees) or all together</li> <li>Impact metrics is either minV (impact magnitude) or minT (impact duration)</li> <li>VI is the vegetation index (here, EVI)</li> <li>Anomaly is the impact indicator (here, cumulative difference index)</li> </ul> <p>Refer to the associated paper for more information on the methodology.</p> <p>Files are saved as .pkl and were generated by the <a href="https://explainerdashboard.readthedocs.io/en/latest/">explainerdashboard</a> library. They are the result of <a href="https://xgboost.readthedocs.io/en/stable/">XGBoost</a> runs that were optimised with <a href="https://optuna.org">Optuna</a> and analysed with the <a href="https://shap.readthedocs.io/en/latest/">SHAP</a> library. They contain:</p> <ol> <li>The explanatory variables and observed and computed target variables for all features</li> <li>The SHAP values</li> </ol> <p>To load the files, use <a href="https://explainerdashboard.readthedocs.io/en/latest/cli.html?highlight=load#explainerdashboard.explainers.BaseExplainer.from_file">this method</a>.</p> <p> </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.