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.
5
datasets available to search
ShareScore release 0.9.0
Dataset results
5 results for “gravimetry”
Arctic glaciers mass balance from satellite gravimetry only
<p>This document describes the LEGOS-Magellium mass balance dataset for Arctic glacier regions based on satellite gravimetry only. A similar dataset using an a priori based on DEM differencing has been submitted to GLAMBIE (Pfeffer et al., 2024). previously. The dataset submitted here does not use an a priori, but uses only satellite gravimetry data. </p> <p>The total mass balance is evaluated for five regions of the 6th version of the Randolph Glacier Inventory , namely the Arctic Canada North, Arctic Canada South, Iceland, Svalbard, and, Russian Arctic. The total mass balance of Arctic glaciers is evaluated mainly based on satellite gravimetry measurements. An ensemble approach updated from Blazquez et al. (2018) is adopted to evaluate uncertainties associated with the processing and post-processing of GRACE (Gravity Recovery And Climate Experiment) and GRACE-FO (GRACE-Follow On) data. The effect of land hydrology is estimated for each region, but not corrected in the total mass balance dataset, because of the small water mass balance values and large errors inherent to hydrological models. Total mass changes expressed in Gt are estimated from April 2002 to September 2022 for five RGI regions. The uncertainty on total mass changes is provided with a confidence interval of 95%. The dataset is provided in the GlaMBIE CSV file format.</p> <p>The data product has been developed in collaboration between LEGOS and Magellium within the scope of the hybridation<br>challenge funded by the CNES (R&T Hybrid Spatial Gravimetry 2022/2023).</p> <p><strong>Reference</strong>:</p> <ul> <li>Blazquez, A., Meyssignac, B., Lemoine, J., Berthier, E., Ribes, A., & Cazenave, A. (2018). Exploring the uncertainty in GRACE estimates of the mass redistributions at the Earth surface : Implications for the global water and sea level budgets. Geophysical Journal International, 215(1), 415‑430. https://doi.org/10.1093/gji/ggy293</li> <li>Pfeffer, J., Coupry, B., Berthier, E., Blazquez, A., & Barnoud, A. (2024). Arctic Glaciers Mass Balance from satellite gravimetry and DEM differencing [Jeu de données]. Zenodo. https://doi.org/10.5281/ZENODO.13134559</li> </ul> <p> </p>
Treatment of temporal aliasing effects in the context of next generation satellite gravimetry missions
<p><strong>Simulated gravity field solutions</strong> published in:<br> Daras, I. and Pail, R. (2017), <em>Treatment of temporal aliasing effects in the context of next generation satellite gravimetry missions</em>, Journal of Geophysical Research: Solid Earth (in revision)</p> <p>Results relate to the solutions used for generating the Figures of the publication.</p> <p>All gravity field solutions are in <strong>icgem </strong>format. The solutions include the effect of static gravity field model GOCO03s.</p> <p><strong>Filename description </strong>for Figures 3, 4, 6, 8, 10 and 11 (fields appear only if applicable):<br> Retrieval content<br> - AOHIS : Atmosphere, Hydrology, Ocean, Ice and Solid Earth <br> - HIS : Hydrology, Ice and Solid Earth<br> - A : Atmosphere<br> - O : Ocean<br> - H : Hydrology<br> - OTerr : OT error retrieval</p> <p>Strategies for HIS retrieval<br> - str1 : strategy 1<br> - str2 : strategy 2</p> <p>Constellation<br> - asc : alternative constellation</p> <p>Retrieval period<br> - hd : half-daily<br> - 1d : daily<br> - 3d : 3-daily<br> - 11d : 11- daily</p> <p>Noise case<br> - fn : full noise case<br> - un : undersampling noise case<br> - ind : individual parameter noise case (see text)</p> <p>Parameterization method<br> - d120 : nominal 11-day solution up to d/o 120<br> - CoPa.1d10.d120 : CoPa 1/10-11/120<br> - CoPa.1d20.3d30.1d120 : CoPa 1/20-3/30-11/120 (sequential parameterization)</p> <p>Time indexing (for Co-estimated short-term solutions)<br> - 01 : Co-estimated solution refering to epoch 01</p> <p><strong>Filename description</strong> for Figure 7:<br> - icgem : format of gravity field solution<br> - yymmdd : starting epoch of the long-term solution for which the daily solutions were co-estimated <br> (e.g. 960112 : refers to the 11-day solution of the time period 1996/01/12 - 1996/01/22)<br> - dual : 2-pair Bender-type solution (standard for all simulations of the paper)<br> - 20.1.11 : 1-day solutions with d/o 20 spatial resolution resulting from a daily co-parameterization of an 11-day long-term solution<br> - wiese : dummy, refers to the paper of D. Wiese <br> - dd : day of the 11-day period</p>
Data Supporting Uplift Mechanism of the Highest Mountains at Eastern Himalayan Syntaxis Revealed by in Situ Dense Gravimetry
<p>The data of the gravity observation network at the Eastern Himalayan Syntaxis, which include Longitude, Latitude, Elevation, Free-Air gravity anomaly (FGA), Bouguer gravity anomaly (BGA), and Moho depth. These data are shown in Figure 1, Figure 2, and Figure 3.</p>
Arctic Glaciers Mass Balance from satellite gravimetry and DEM differencing
<p>This document describes the LEGOS-Magellium mass balance dataset for Arctic glacier regions based on satellite gravimetry and DEM (Digital Elevation Model) differencing. The total mass balance is evaluated for five regions of the 6th version of the Randolph Glacier Inventory namely the Arctic Canada North, Arctic Canada South, Iceland, Svalbard, and the Russian Arctic. The total mass balance of Arctic glaciers is evaluated mainly based on satellite gravimetry measurements. An ensemble approach updated by Blazquez et al. (2018) is adopted to assess uncertainties associated with the processing and post-processing of GRACE (Gravity Recovery And Climate Experiment) and GRACE-FO (GRACE-Follow On) data. A priori information from DEM differencing (Hugonnet et al., 2021) is used to reduce leakage errors associated with the mislocation of signal sources. Total mass changes expressed in Gt are estimated from April 2002 to September 2022 for five RGI regions. The uncertainty on total mass changes is provided with a confidence interval of 95%. The dataset is provided in the GlaMBIE CSV file format.</p> <p>References:</p> <ul> <li>Blazquez, A., Meyssignac, B., Lemoine, J., Berthier, E., Ribes, A., & Cazenave, A. (2018). Exploring the uncertainty in GRACE estimates of the mass redistributions at the Earth surface : Implications for the global water and sea level budgets. Geophysical Journal International, 215(1), 415‑430. https://doi.org/10.1093/gji/ggy293</li> <li>Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F., & Kääb, A. (2021). Accelerated global glacier mass loss in the early twenty-first century. Nature, 592(7856), Article 7856. https://doi.org/10.1038/s41586-021-03436-z</li> </ul> <p>The data product has been developed in collaboration between LEGOS and Magellium within the scope of the hybridization<br>challenge funded by the CNES (R&T Hybrid Spatial Gravimetry 2022/2023). </p>
Relating North Atlantic Deep Water transport to ocean bottom pressure variations as a target for satellite gravimetry missions
Open the record for dataset details and reuse information.
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.