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9 results for “vertical land motion”
Data supplement to 'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900-2150'
<p>This is a data supplement to <strong>'Vertical land motion reconstruction unveils non-linear effects on relative sea level changes from 1900-2150</strong>'. It presents a global-scale Vertical Land Motion (VLM) reconstruction that resolves height changes in the period 1995-2020. It is based on the joint probabilistic analysis of an extensive network of more than 11,000 GNSS stations, tide gauges, and satellite altimetry. The approach used to derive this reconstruction is described in the paper. The dataset variables are explained in the .pdf file.</p>
Variable vertical land motion for sea level rise projections
<h1><strong>Data for Govorcin et al., 2024: Variable vertical land motion for sea level rise projections [submitted for publication].</strong></h1> <p><strong>Disclaimer:</strong> Data is subject to change due to the review process.</p> <p><strong>Repository Contains:</strong></p> <ul> <li> <p><strong>Vertical Land Motion over California</strong></p> <ul> <li><strong>Reference:</strong> International Terrestrial Reference System, solution 2014 (ITRF2014)</li> <li><strong>Period:</strong> 2015-2023</li> <li><strong>Data Type:</strong> GeoTIFF</li> <li><strong>Unit:</strong> mm/yr</li> </ul> </li> <li> <p><strong>Vertical Land Motion (Propagated) Formal Uncertainties (Rates Std.) over California</strong></p> <ul> <li><strong>Reference:</strong> International Terrestrial Reference System, solution 2014 (ITRF2014)</li> <li><strong>Period:</strong> 2015-2023</li> <li><strong>Data Type:</strong> GeoTIFF</li> <li><strong>Unit:</strong> mm/yr</li> </ul> </li> <li> <p><strong>Vertical Land Motion Temporal Variability over California</strong></p> <ul> <li><strong>Period:</strong> 2015-2023</li> <li><strong>Data Type:</strong> GeoTIFF</li> <li><strong>Unit:</strong> mm/yr</li> </ul> </li> <li> <p><strong>Archive: Output HDF5 (Mintpy format) and GNSS Files</strong></p> <ul> <li>Includes <code>velocity.h5</code>, <code>geometry.h5</code>, <code>gnss_model</code>, <code>calibrated_velocity.h5</code>, <code>CA_3D_rates.h5</code>, and <code>temporal variability</code> per track and merged, projected to vertical. See <strong>README</strong> for more information.</li> </ul> </li> </ul> <h2>Citation:</h2> <p>If you use this data in your work, research or publication, please cite the following article:</p> <p>Govorcin, M. Bekaert, D., Hamlington, B., Sangha, S., Sweet, W. (2024). Variable Vertical Land Motion for Sea Level Rise Projections, 01 August 2024, PREPRINT (Version 1) available at Research Square [https://doi.org/10.21203/rs.3.rs-4676043/v1]</p> <h2>Acknowledgment</h2> <p>The research was conducted at the Jet Propulsion Laboratory, California Institute of Technology. This research was supported by the Observational Products for End-Users from Remote Sensing Analysis (OPERA) project (<a href="https://www.jpl.nasa.gov/go/opera" target="_blank" rel="noopener">https://www.jpl.nasa.gov/go/opera</a>), managed by the Jet Propulsion Laboratory and funded by the Satellite Needs Working Group, that is creating remote sensing products to address Earth observation needs across U.S. civilian federal agencies.</p>
Vertical land motion due to present-day ice loss from Greenland's and Canada's peripheral glaciers
<p>Greenland's bedrock responds to the ongoing loss of ice mass with an elastic vertical land motion (VLM) that is measured by Greenland's GNSS Network (GNET). The measured VLM also contains other contributions, including the long-term viscoelastic response of the Earth to previous deglaciation.</p> <p>Greenland's ice sheet (GrIS) is producing the most significant contribution to the total VLM. The contribution of peripheral glaciers (PGs) from both Greenland (GrPGs) and Arctic Canada (CanPGs) has not been carefully accounted for in the GNSS time series analysis. This is a significant concern, since GNET stations are often closer to PGs than to the ice sheet. </p> <p>We find that PGs produce significant elastic rebound, especially in North and East Greenland. Across these regions, the PGs result in up to 37% of the elastic rebound. For a few stations in the North, the VLM from PGs is larger than the GrIS one.</p>
European CFP EGMS Vertical Land Motion
<p>This dataset contains the estimates of EGMS-derived vertical land motion in European Coastal Flood Plain.</p>
Vertical land motion due to present-day ice loss from Greenland’s and Canada’s peripheral glaciers
Open the record for dataset details and reuse information.
Rates of Vertical Land Motion (VLM) on Tutuila Island, American Samoa (December 3, 2015 to August 16, 2022)
<p>[Version 4] Latest version, updated to fix errors that were found in the vlm.mat data file.</p><p>VLM rates across Tutuila Island from December 5, 2015 to August 16, 2022, derived using a redundant multi-primary variant of the PS-InSAR technique. Dataset associated with the published version of the publication "Mapping Vertical Land Motion in Challenging Terrain: Six-Year Trends on Tutuila Island, American Samoa, With PS-InSAR, GPS, Tide Gauge, and Satellite Altimetry Data" by S. A. Huang, J. M. Sauber, and R. Ray. Available at <a href="https://doi.org/10.1029/2022GL101363">https://doi.org/10.1029/2022GL101363</a>.</p><p>ampl.mat: Amplitude backscatter averaged from all scenes, multilooked for speckle reduction and resampled to the dataset size. Normalized to 1.</p><p>latvals.mat: Latitude vector associated with the dataset.</p><p>lonvals.mat: Longitude vector associated with the dataset.</p><p>plot_ps_data.m: Matlab script to visualize the data included in all the *.mat files. Requires Computer Vision Toolbox.</p><p>vlm.mat: Computed VLM rates across Tutuila Island [mm/yr]. All non-PS have an "NaN" value.</p><p>vlm_se.mat: Standard error of VLM across Tutuila Island [mm/yr]. All non-PS have an "NaN" value.</p>
Rates of Vertical Land Motion (VLM) on Tutuila (American Samoa) and Upolu (Samoa) (from 3 December 2015 to 16 April 2020 and from 28 April 2020 to 27 November 2023)
<p>Dataset associated with the resubmitted manuscript under revision "Spatiotemporal Patterns of Subsidence and Sea Level Rise in the Samoan Islands Nearly 15 Years after the 2009 Samoa-Tonga Earthquake" by S. A. Huang, J. M. Sauber, S.-C. Han, R. Ray, and E. J. Fielding.</p> <p>Average VLM rates are provided for Tutuila (American Samoa) and Upolu (Samoa) over two subsets:</p> <ol> <li>3 December 2015 to 16 April 2020</li> <li>28 April 2020 to 27 November 2023</li> </ol> <p>VLM rates were derived using the PS-InSAR technique described in the publication at https://doi.org/10.1109/LGRS.2024.3358737. </p> <p>The following files are included here:</p> <ul> <li>plot_ps_data_tutuila_upolu.m: Matlab script to visualize the data included in all the *.mat files (Figures 4 and 5 and the histograms in 8c and 9c without annotations). Requires Computer Vision Toolbox.</li> </ul> <p>Upolu:</p> <ul> <li>upolu_ampl.mat: Amplitude backscatter from Upolu averaged from all scenes, multilooked for speckle reduction and resampled to the dataset size. Normalized to 1.</li> <li>latvals.mat: Latitude vector associated with both Upolu datasets.</li> <li>lonvals.mat: Longitude vector associated with both Upolu datasets.</li> <li>upolu_15-20_vlm.mat: Computed VLM rates across Upolu for the 2015-2020 time period [mm/yr]. All non-PS have an "NaN" value.</li> <li>upolu_15-20_vlm_uncert.mat: Uncertainty of VLM across Upolu for the 2015-2020 time period [mm/yr]. All non-PS have an "NaN" value.</li> <li>upolu_20-23_vlm.mat: Computed VLM rates across Upolu for the 2020-2023 time period [mm/yr]. All non-PS have an "NaN" value.</li> <li>upolu_20-23_vlm_uncert.mat: Uncertainty of VLM across Upolu for the 2020-2023 time period [mm/yr]. All non-PS have an "NaN" value.</li> </ul> <p>Tutuila: </p> <ul> <li>tutuila_ampl.mat: Amplitude backscatter from Tutuila averaged from all scenes, multilooked for speckle reduction and resampled to the dataset size. Normalized to 1.</li> <li>tutuila_latvals.mat: Latitude vector associated with both Tutuila datasets.</li> <li>tutuila_lonvals.mat: Longitude vector associated with both Tutuila datasets.</li> <li>tutuila_15-20_vlm.mat: Computed VLM rates across Tutuila Island for the 2015-2020 time period [mm/yr]. All non-PS have an "NaN" value.</li> <li>tutuila_15-20_vlm_uncert.mat: Uncertainty of VLM across Tutuila Island for the 2015-2020 time period[mm/yr]. All non-PS have an "NaN" value.</li> <li>tutuila_20-23_vlm.mat: Computed VLM rates across Tutuila Island for the 2020-2023 time period [mm/yr]. All non-PS have an "NaN" value.</li> <li>tutuila_20-23_vlm_uncert.mat: Uncertainty of VLM across Tutuila Island for the 2020-2023 time period[mm/yr]. All non-PS have an "NaN" value.</li> </ul>
Chesapeake Bay Vertical Land Motions 2019
<p>Global Positioning System (GPS) data from 2019 campaign in the Chesapeake Bay region </p>
Chesapeake Bay Vertical Land Motions 2020
<p>Global Positioning System (GPS) data from the 2020 campaign in the Chesapeake Bay region</p>
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