Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
48
datasets available to search
ShareScore release 0.7.1
Dataset results
48 results for “Earth Science”
Model data for "The GERB Obs4MIPs Radiative Flux Dataset: A new tool for climate model evaluation", submitted to Earth System Science Data
<p>© Crown Copyright, Met Office</p><p>The E1hrClimMon files contain the monthly mean diurnal cycles of TOA radiative fluxes (all-sky and clear-sky) for amip experiment of two configurations of HadGEM3: GC3.1 and GC5.0. The monthly mean diurnal cycle is constructed by averaging each UTC hourly mean over the entire month. The HadGEM3 OLR diagnostics used in this study differ from those submitted to CFMIP3. The OLR diagnostics submitted to CFMIP3 contain a correction that accounts for the surface temperature adjustment by the boundary layer scheme in model time steps between radiation time steps. This OLR diagnostic adjustment is introduced to conserve energy, but it significantly distorts the diurnal cycle of OLR. For comparison with the GERB obs4MIPs products, the OLR without this correction is recommended.</p><p>The COSP file contains the average monthly climatologies for the variables cfadLidarsr532 and clisccp for the amip simulations of GC3.1 and GC5.0.</p>
Test data for MetIVA ( An XR-based Interactive Visualization Platform for Real-time Exploring Dynamic Earth Science Data)
<p>Here,we presented the minimum demanded dataset to test the basic fuction of the software of MetIVA, which an XR-base interactive visualization platform for real-time exploring dynamic earth science data. The dynamic realtime data of traffic information (such as traffic volume, traffic spped, jam conditions) is directy obtained from the third-party supplier, such as Mapbox in the test version of MetIVA, the users can change it to other sources. The users have their own accounts on the cloud computing platform to run the numerical models (such as WRF), the outputed results (in NetCDF format) can be sent to cloud storage and the link address need to be provided in the MetIVA.</p>
Trained Surface Layer Models and Metrics for "Evidential Deep Learning: Enhancing Predictive Uncertainty Estimation for Earth System Science Applications"
Open the record for dataset details and reuse information.
Processing steps to generate a Digital Surface Model based on SPOT-7 tri-stereo images published in the study "An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar inundation areas at volcan Copahue (Argentina & Chile)" in the Journal of South American Earth Sciences https://doi.org/10.1016/j.jsames.2022.104138
<p>The Digital Surface Model (DSM) was created from SPOT-7 tri-stereo images for the Copahue volcano between the border of Argentina and Chile. Two versions of the DSM are provided: an unfiltered product and a final, filtered product. The final product has a spatial resolution of 5-m and was used for lahar inundation modeling for the Copahue volcano (Viotto, Toyos, and Bookhagen 2022, <a href="https://doi.org/10.1016/j.jsames.2022.104138">https://doi.org/10.1016/j.jsames.2022.104138</a> : An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at Volcán Copahue (Argentina & Chile). <em>Journal of South American Earth Sciences</em> ). The dataset provided should be cited together with the article. </p> <p><strong>DSM processing </strong></p> <p>The source images were given by a SPOT-7 snow- and cloud-free triplet (Nadir, Backward and Forward) of 1.5 m spatial resolution from 19 April 2018 (SPOT Image, Airbus Defence and Space GmbH, distributed by CONAE; Dataset ID: <em>SEN_SPOT7_20180419_142955500_000</em>, delivered by CONAE as <em>DS_SPOT7_20180419</em>).</p> <p>The data were processed with the suite of digital photogrammetry tools AMES Stereo Pipeline ASP (Beyer et al., 2018). The procedure for the generation of the DSM is summarized by following steps: </p> <ol> <li> <p>The orbital parameters (RCP models) were adjusted using the bundle adjustment tool with no ground control points, since they were unavailable.</p> </li> <li> <p>The scenes were map-projected onto the NASADEM (spatial resolution of 30 m) elevation dataset, assisted by the results of the orbital adjustment in Step 1.</p> </li> <li>The stereo correlation of the map-projected scenes including the results of the adjusted orbital parameters, was performed three times, using as first scene (i.e., primary image) the nadir (N), backward (B), and forward (F) images . In each run, the order of images to perform the stereo correlation was: N-F-B, F-N-B, and B-N-F. Thus, three point clouds were generated. Specific ASP correlator settings (other than defaults parameters; for details see the provided stereo-default file) were set in the following way: <em>Correlation Kernel</em>: 15 x 15 pixels; <em>Sub-pixel Refinement Kernel</em>: 21 x 21 pixels; <em>Subpixel Refinement Mode</em>: 2 (Weighted Affine Adaptive Window Correlator EM)</li> <li> <p>The three point clouds were merged into one point cloud with a regular grid of 5 m (unfiltered product, known as <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em>).</p> </li> </ol> <p>The quality of the final point cloud was assessed by comparing the unfiltered DSM with a spatial resolution of 12-m against the WorldDEM<sup>TM</sup> elevation dataset (Collins et al., 2015). The WorldDEM was provided by Airbus Defence and Space GmbH under license for the scope of the Viotto et al., 2022 study. The comparison of the pixel-to-pixel heights above the ellipsoid (WGS84) between the two datasets resulted in a mean difference of 0.67 m and a standard deviation of +/- 4.82 m. </p> <p>Comprehensive details on the methodologies evaluated to create the dataset with ASP, can be found in the corresponding master's thesis “Topografía digital y modelado de lahares en el Volcán Copahue, Argentina-Chile” from S. Viotto (link: https://rdu.unc.edu.ar/handle/11086/15384). Recommended literature about processing DEMs from SPOT imagery is given by Mueting et al., 2021 (<a href="https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330">https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2021JF006330</a>). </p> <p><strong>Creation of the Final, Filtered DSM product</strong></p> <p>The corrections and improvements applied to the unfiltered product to create the final, filtered DSM (named DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif) are summarized by following steps. </p> <p> </p> <ol> <li> <p><em>Water Bodies Delineation</em></p> </li> </ol> <p>The delineation of the water bodies was based on a mask created from the free access water bodies datasets provided by the Instituto Geográfico Nacional of Argentina (<a href="https://www.ign.gob.ar/NuestrasActividades/InformacionGeoespacial/CapasSIG">https://www.ign.gob.ar/ NuestrasActividades/InformacionGeoespacia l/CapasSIG</a>) and by the Ministerio de Bienes Nacionales in Chile ( <a href="https://www.ide.cl/index.php/aguas-continentales/item/1508-catastro-de-lagos">https://www.ide.cl/index.php /aguas-continentales/item/1508-catastro-de-lagos</a>). A total of 45 lakes within the area of interest were considered. Lakes with areas below or equal to 25 m2 were smoothed with a median filter in the last step. Lakes with areas above this threshold were filled in with a constant value and their borders were smoothed with a median filter to provide smooth shorelines.</p> <p><em>2 . Void Filling</em></p> <p>Voids (other than water bodies) were filled with the tool “Close Gaps” from Saga GIS software. </p> <p><em>3. Smoothing</em></p> <p>Finally, the elevation dataset was smoothed with a median filter using a 3 x 3 pixel window, excluding water bodies filled in the step 1. </p> <p><strong>Final Remarks and Suggestion</strong></p> <p>The quality assessment of the final version by visual inspection of the hillshades suggested an improvement of the signal to noise ratio. However, the void filling process may be improved.</p> <p><br> </p> <p><strong>Dataset Description</strong></p> <table align="center"> <caption> </caption> <tbody> <tr> <td>Digital Surface Models</td> <td> <p>No Data Value = -9999</p> <p>Format = float 32 bit</p> <p>File Format = GeoTiff</p> <p>Vertical Datum: WGS84</p> <p>Projection information: EPSG 32719 (UTM19S)</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>) </p> <p>Versions: </p> <ul> <li> <p>Unfiltered product: without corrections <em>DSM_Copahue_UTM19S_WGS84_5m_raw.tif</em></p> </li> <li> <p>Final, filtered product: smoothed and void filled <em>DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</em></p> </li> </ul> </td> </tr> <tr> <td>Water Bodies Mask</td> <td> <p>No Lake Value = 0</p> <p>Lakes Values = 1 to 45</p> <p>File Format= GeoTiff</p> <p>Spatial Resolution: 5m (subfix: <em>_5m</em>)</p> <p>Projection information : EPSG 32719 (UTM19S)</p> <p><em>WB_mask_5m_UTM19S.tif</em></p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p><strong>Repository structure</strong></p> <p>|__ 01_Scripts</p> <p> |+ run21_CopahueDSM_AMES_sviotto.sh</p> <p> |+ stereo.default</p> <p>|__ 02_DSMs</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_raw.tif</p> <p> |+ DSM_Copahue_UTM19S_WGS84_5m_VoidFilled.tif</p> <p> |+ WB_mask_5m_UTM19S.tif</p> <p><strong>References</strong></p> <p>Beyer, R. A., Alexandrov, O., & McMichael, S. (2018). The Ames Stereo Pipeline: NASA's open source software for deriving and processing terrain data. <em>Earth and Space Science</em>, 5, 537– 548. <a href="https://doi.org/10.1029/2018EA000409">https://doi.org/10.1029/2018EA000409</a></p> <p>Collins, J., Riegler, G., Schrader, H., Tinz, M., 2015. Applying terrain and hydrological editing to TanDEM-X data to create a consumer-ready worlddem product. Int. Arch. Photogram. Rem. Sens. Spatial Inf. Sci. 40 (7), 1149. https://doi.org/10.5194/isprsarchives-XL-7-W3-1149-2015.</p> <p>Mueting, A., Bookhagen, B., & Strecker, M. R. (2021). Identification of debris-flow channels using high-resolution topographic data: A case study in the Quebrada del Toro, NW Argentina. <em>Journal of Geophysical Research: Earth Surface</em>, 126, e2021JF006330. <a href="https://doi.org/10.1029/2021JF006330">https://doi.org/10.1029/2021JF006330</a></p> <p>Viotto, S., Toyos, G., & Bookhagen, B. (2022). An assessment of the effects of DEM quality and spatial resolution on a model for mapping lahar hazard inundation at volcán copahue (Argentina & Chile). Journal of South American Earth Sciences, 104138. https://doi.org/10.1016/j.jsames.2022.104138</p> <p> </p> <p> </p>
Arraylake: A Cloud-Native Data Lake Platform for Earth System Science
<p>The vast amount of earth system data available today is an incredible resource for understanding our planet and confronting the challenge of climate change. Traditionally, a few large organizations have provided most of the data, and users have downloaded data to local computers. This way of working is becoming increasingly infeasible as data volumes grow and as AI-based methods demand direct access to full-scale data archives. With essentially infinite compute and storage capacity, cloud computing has the potential to revolutionize our interaction with weather and climate data, allowing everyone to bring their own compute workloads to bear against a single shared copy of the data. Over the past years, via our work in the Pangeo project, we have prototyped a cloud-native approach to weather and climate data in the cloud, combining scalable computing technologies such as Xarray and Dask with analysis-ready, cloud-optimized data in formats like Zarr. While these tools show great potential, they remain difficult to deploy and use in an operational context for many scientists and institutions.</p> <p>Motivated by this challenge, we founded Earthmover, a company aimed at democratizing access to state-of-the-art cloud-native data analytics, and built Arraylake, a data platform which enables teams of any size to manage and analyze weather and climate data in the cloud. Arraylake users can access high-quality public datasets alongside their own private data, all via the high-performance Zarr data standard. This talk describes Arraylake’s architecture, novel version control system for data, and approach to supporting all common climate data formats (NetCDF, HDF5, Grib, Tiff, Zarr) via a single, user-friendly interface. Via a short demo, we illustrate how Arraylake helps overcome common data management challenges that have henceforth limited widespread adoption of cloud computing in earth system science.</p>
Datasets for Age, Gender, and International Author Networks in the Earth and Space Sciences: Implications for Addressing Implicit Bias
<p>These files provide supplemental information and tabular data for figures in Hanson, Wooden, Lerback: Age, Gender, and International Author Networks in the Earth and Space Sciences: Implications for Addressing Implicit Bias, Submitted to Earth and Space Science.</p>
VIC-Res Upper Mekong -- 2005-2020 -- Vu et al., 2023, Hydrology and Earth System Sciences
<p>This data repository holds VIC-Res model input / output data for the paper "Vu, D.T., Dang, T. D., Pianosi, F., & Galelli, S. Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins. Hydrol. Earth Syst. Sci., 27, 3485–3504, 2023"</p><p>The model can be used to simulate hydrological processes and streamflow routing in the Upper Mekong River basin for the period 2005-2020. The streamflow routing scheme can be run with and without water reservoirs.</p>
Sedgwick Museum of Earth Sciences door
52.203066, 0.122016 Source: Objaverse 1.0 / Sketchfab
SolSysELTs2022 Part II: Puzzling origin of water on Earth: frontiers in cometary science with METIS/EELT
<p>Contributed talk: presentation and video recording</p>
Cross-track Infrared Sounder (CrIS) Level 2 Earth System Science Profiling Algorithm Ammonia Retrieval Algorithm (ESSPA-NH3) V1 (SNDRSNIL2ESPNH3)
The objective of this limited edition data collection is to examine the ammonia products generated by the ESSPA (Earth System Science Profiling Algorithm) algorithm from the Cross-track Infrared Sounder (CrIS) instruments. The CrIS instrument used for this product is deployed on board the Suomi National Polar-orbiting Partnership (SNPP) platform and uses the Normal Spectral Resolution (NSR) data. The CrIS instrument is a Fourier transform spectrometer with a total of 1305 NSR infrared sounding channels covering the longwave (655-1095 cm-1), midwave (1210-1750 cm-1), and shortwave (2155-2550 cm-1) spectral regions.The NH3 L2 ammonia algorithm is based on an AER (Atmospheric and Environmental Research, Inc.) program initially developed to process TES (Tropospheric Emissions Spectrometer) trace gas products. This version runs within the ESSPA software framework: it uses the AER OSS forward model and an optimal estimation approach with a Levenberg-Marquardt algorithm. Temperature and water profiles are obtained from the CLIMCAPS Field of Regard (FOR) products, as are initial guesses for surface temperature and emissivity. The algorithm consists of a two-step sequential retrieval the first step retrieves surface temperature and emissivity and the second step an ammonia profile. The algorithm produces ammonia retrievals on every field of view (FOV) in each FOR.A level 2 granule has been set as 6 minutes of data, 30 footprints crosstrack by 45 lines along track. There are 240 granules per day, with an orbit repeat cycle of approximately 16 day.
Generated datasets for Yue et al. (2020, Earth and Space Science): "Combining In-situ and Satellite Observations to Understand the Vertical Structure of Tropical Anvil Cloud Microphysical Properties During the TC4 Experiment"
<p>This archive contains the data sets generated from the research conducted by Yue et al. (2020) titled "Combining In-situ and Satellite Observations to Understand the Vertical Structure of Tropical Anvil Cloud Microphysical Properties During the TC4 Experiment" published in Earth and Space Science. The method to generated the following data sets is described in Yue et al. (2020) and stored as Matlab .mat files.</p> <p>CombiningTC4_Satellite_eof_cov_mat.mat contains the correlation matrix shown in Figure 1a.</p> <p>TC4_processed.mat contains the correlation matrix shown in Figure 1b.</p> <p>RO_processed.mat contains the correlation matrix shown in Figure 2a.</p> <p>RVOD_processed.mat contains the correlation matrix shown in Figure 2b.</p> <p>ICE_processed.mat contains the correlation matrix shown in Figure 2c.</p> <p> </p> <p> </p>
All data for: Megaherbivore impacts on ecosystem and Earth system functioning: The current state of the science
<p>Megaherbivores (adult body mass >1000 kg) are suggested to disproportionately shape ecosystem and Earth system functioning. We systematically reviewed the empirical basis for this general thesis and for the more specific hypotheses that (i) megaherbivores have disproportionately larger effects on Earth system functioning than their smaller counterparts, (ii) this is true for all extant megaherbivore species and (iii) their effects vary along environmental gradients. We furthermore explored possible biases in our understanding of megaherbivore impacts. We found that there are too few studies to quantitatively evaluate the general thesis or any of the hypotheses for all but the African savanna elephant. Following this finding, we performed a qualitative vote counting analysis. Our synthesis of this analysis suggests that megaherbivores can elicit strong impacts on e.g. vegetation structure, and biodiversity and all the elephant species promote seed dispersal. We were however unable to evaluate whether these effects are disproportionate to smaller large herbivores. Although environmental conditions can mediate megaherbivore impact, few studies quantified the effect of rainfall or soil fertility on megaherbivore impacts, precluding prediction of megaherbivore effects on the Earth system, particularly under future climates. Moreover, our review highlights major taxonomic, thematic and geographic biases in our understanding of megaherbivore effects. Most of the studies focused on African savanna elephant impacts on vegetation structure and biodiversity, with other megaherbivores and Earth system functions comparatively neglected. Studies were also biased towards semi-arid and relatively fertile systems, with the arid, high-rainfall and/or nutrient-poor parts of the megaherbivores' distribution ranges largely unrepresented. Our findings highlight that the empirical basis of our understanding of the ecological effects of extant megaherbivores is still limited for all species, except African savanna elephant, and that our current understanding is biased towards certain environmental and geographic areas. We further outline a detailed, urgently needed avenue for future research.</p>
New data from Dai et al., Prolonged deep-ocean carbonate chemistry recovery after the Paleocene-Eocene Thermal Maximum, Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2023.118353
<p>New trace element and carbon isotope data from Dai et al., Prolonged deep-ocean carbonate chemistry recovery after the Paleocene-Eocene Thermal Maximum, Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2023.118353</p>
New trace element and carbon isotope data from Dai et al., Prolonged deep-ocean carbonate chemistry recovery after the Paleocene-Eocene Thermal Maximum, Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2023.118353
<p>New trace element and carbon isotope data from Dai et al., Prolonged deep-ocean carbonate chemistry recovery after the Paleocene-Eocene Thermal Maximum, Earth and Planetary Science Letters, https://doi.org/10.1016/j.epsl.2023.118353</p>
All data for: Megaherbivore impacts on ecosystem and Earth system functioning: The current state of the science
Open the record for dataset details and reuse information.
Interdisciplinary Research in Earth Science, Long Island Sound
Integration of new remote sensing tools for characterization of tidal marsh area extent, vegetation communities and inundation regimes, and advanced retrievals of estuarine biological and biogeochemical processes with multi-disciplinary ecological, paleoecological, and socioeconomic datasets, spatial econometric models of population growth, and a novel coupled hydrodynamic-photo-biogeochemical model specifically designed for the marsh-estuarine continuum in the heavily urbanized Long Island Sound.
Automated Event Service: Efficient and Flexible Searching for Earth Science Phenomena Project
<p> Develop an Automated Event Service system that:<br /> Methodically mines custom-defined events in the reanalysis data sets of global atmospheric models.<br /> Enables researchers to specify their custom, numeric event criteria using a user-friendly web interface to search the reanalysis data sets.<br /> Supports Event Specification Language (ESL) for more flexibility and versatility.<br /> Contains a social component that enables the dynamic formation of collaboration groups for researchers to cooperate on event definitions of common interest.<br /> Provides rapid results via high performance computing and advanced search technologies.<br /> &nbsp;</p>
Earth Science Mission Control Center Systems Study Project
Earth Science Mission Control Center Systems Study Project
Earth Resources Observation and Science (EROS) Center's Earth as Art Image Gallery
The Earth Resources Observation and Science (EROS) Center manages this collection of Landsat 7 scenes created for aesthetic purposes rather than scientific interpretation.
Earth Resources Observation and Science (EROS) Center's Earth as Art Image Gallery 3
The Earth Resources Observation and Science (EROS) Center manages the Earth as Art Three exhibit, which provides fresh and inspiring glimpses of different parts of our planet's complex surface.
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.