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122 results for “Sea Level Rise”
Data from: Evaluating the costs and benefits of marsh-management strategies while accounting for uncertain sea-level rise and ecosystem response
Prioritization of marsh-management strategies is a difficult task as it requires a manager to evaluate the relative benefits of each strategy given uncertainty in future sea-level rise and in dynamic marsh response. A modeling framework to evaluate the costs and benefits of management strategies while accounting for both of these uncertainties has been developed. The base data for the tool are high-resolution uncertainty-analysis results from SLAMM (the Sea-Level Affecting Marshes Model) under different adaptive-management strategies. These results are combined with an ecosystem-valuation assessment from stakeholders. Model results and stakeholder values are linked together using "utility functions" that characterize the relationship between stakeholder values and geometric metrics such as "marsh area," marsh edge," or "marsh width." The expected-value of each site's ecosystem benefits can then be calculated and compared using estimated costs for each strategy. Estimates of optimal marsh-management strategies may then be produced, maximizing the "ecosystem benefits per estimated costs" ratio.
Distribution of economic damages due to climate-driven sea-level rise across European regions and sectors
<p>The datasets generated during and/or analysed during the study</p>
Data for: Development of a learning community focused on sea-level rise and coastal habitat change
<p>Rapid habitat changes are occuring in salt marshes located in the Northeastern United States, including expansion of ponded areas on the marsh platform, die off of coastal forests, and subsequent colonization of 'ghost forests' by marsh vegetation. This work focuses on two main areas: (1) environmental conditions along the marsh forest border undergoing rapid transitions; and (2) environmental conditions and plant stress in marsh platforms with extensive ponding, with three study sites: in Long Island and Southern New England, where there are often significant slope breaks along the upland (slope ~0.01), and in southern New Jersey on the Atlantic Coastal plan (slope ~0.003).</p> <p>To better understand drivers of environmental change in marsh-forest borders undergoing rapid transitions, we measured shallow groundwater levels, soil salinity, and forest health and structure along the salt marsh-upland border at three sites with varying slopes using installation of shallow groundwater wells, drone imagery and associated image processing, and geophysical methods. To better understand drivers of environmental change on the marsh platform, we measured used piezometers to understand vertical gradients in marsh groundwater levels, and measured photosynthesis and plant biomass and used drone imagery to map plant stress indices, as indicators of plant stress. While we anticipate that this data will be published in journal articles of the next 2 years, we archive collected data to facilitated data sharing, as required by NSF.</p>
Research carried out on the Brazilian coast that deals with modeling sea level rise, and the methodologies applied in development.
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Light limitation and coral mortality in urbanised reef communities due to sea-level rise
<p>Dataset with coral mortality projections under sea-level rise</p>
Global impact of sea level rise on coastal fresh groundwater resources
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Sea level science – how can we predict sea level rise in the future?
<p>Sea level has been going up and down in the last millennia and while moving a camp wasn’t a big deal for our ancestors, moving today Venice or New-York is a different story. Sea level is currently rising at an accelerated rate due to the melt of land-based ice: glaciers, the Greenland and the Antarctic ice sheet. How high is the sea level going to be in 10 years, 50 years, 80 years, 500 years? How do we calculate how much the seas are going to rise?</p>
Supporting data and files for PNAS paper entitled Ice sheet contributions to future sea level rise from structured expert judgement.
<p>This repository contains supporting documentation with background information about the structured expert judgement described in the paper entitled: Ice sheet contributions to future sea level rise from structured expert judgement.. It also includes the files containing the anonymous expert judgements for the target questions elicited.</p>
Sea level rise adaptation pushes an insular endemic rodent closer to extinction
<p>This Rproject contains the data and code relevant to the article with the same title published in Biodiversity and Conservation in 2023. Some of the data have been lightly processed, and thus may differ slightly from the sources cited in the article. In general, the script requires data from the data folders, and outputs figures/table to the "figures" folder. </p> <p><strong>NOTE: Use of these data for subsequent analyses is encourages, but please get in touch to disclose how the data are being used and to discuss how to cite/acknowledge the authors.</strong></p>
Data from: Evaluating the costs and benefits of marsh-management strategies while accounting for uncertain sea-level rise and ecosystem response
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Data for: Development of a learning community focused on sea-level rise and coastal habitat change
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Resilience of Coastal Wetlands to Sea Level Rise, CONUS, 1996-2100
This dataset provides information about the resilience of tidal wetlands to sea-level rise under three scenarios of global change. With rising seas, regularly inundated tidal wetlands may persist by vertical accretion of sediments (vertical resilience) and/or by migrating inland (lateral resilience), but local and regional conditions constrain these options. This dataset provides a vertical resilience index (VR) for coastal wetlands at 30 m resolution across the continental US predicted for 2100. The VR index was computed for current sea levels, local tidal dynamics, and coastal topography. It was also calculated for future sea levels predicted for 2100 by three IPCC Realized Concentration Pathway (RCP) scenarios: 2.5, 4.5, and 8.5. Moreover, the VR index incorporates estimated rates of sediment accretion. Relevant to lateral resiliency, the data include current and future tidal areas identified by mapping mean higher high water spring tide locations under the RCP scenarios. A shapefile outlining watershed units with tidal wetlands is included along with land cover classes for these areas for 1996 and 2011.
Pearl River Delta FVCOM model sea level rise scenarios
<p>Model data presented in: De Dominicis, M., Wolf, J., Jevrejeva, S., Zheng, P., Hu. Z. "Future interactions between sea level rise, tides and storm surges in the world's largest urban area", Geophysical Research Letters (2020).</p> <p>An FVCOM (Finite Volume Community Ocean Model) implementation for the South China Sea and the Pearl River Delta is used to understand how future sea level rise, tides and typhoon storm surges can interact and affect coastal inundation. Four future sea level rise scenarios have been analyzed: 0.3 m, 0.5 m, 0.9 m and 2.1 m. Two typhoons that impacted the PRD have been modelled: Hato (2017) and Mangkhut (2018).</p> <p>The dataset consists of water elevation data for 40 model experiments:</p> <ul> <li>EXP01-10 allow to study tide and sea level rise interactions. The Pearl River Delta model has been run for 1 month forced only by tides and sea level rise at the model boundary.</li> <li>EXP11-15 (for Hato) and EXP26-30 (for Mangkhut) allow the study of tide, surge and sea level rise interactions; in these experiments the model has been fully forced by atmospheric forcing, tides and sea level rise.</li> <li>EXP16-20 (for Hato) and EXP31-35 (for Mangkhut) allow the study of tide and sea level rise interactions and are needed for the calculation of the surge, the model has been forced by tides and sea level rise only at the model boundary. The surge can be calculated as the difference between the fully forced run (EXP11-15 and EXP26-30) and the corresponding tide-only forced run (EXP16-20 and EXP31-35) for a given sea level rise.</li> <li>EXP21-25 (for Hato) and EXP35-40 (for Mangkhut) allow the study of the surge and sea level rise interactions only (no tides); for these experiments the model has been forced by atmospheric forcing and sea level rise at the model boundary.</li> </ul>
On the role of anthropogenic activity and sea level rise in tidal distortion on the open coast of the Yellow Sea Shelf
<p>This dataset is created for manuscript entitle of On the role of anthropogenic activity and sea level rise in tidal distortion on the open coast of the Yellow Sea Shelf submitted to JGR-OS. All rights reserved andreviewers cannot use the data here until the manuscript is officially published. Otherwise, they will bear legal responsibility.</p>
Response of tidal duration asymmetry to interplay of coastline reconstruction and sea-level-rise: take South Yellow Sea shelf as an example
<p>The data is used in this article, which is "Response of tidal duration asymmetry to interplay of coastline reconstruction and sea-level-rise: take South Yellow Sea shelf as an example"</p>
Sea Level Rise Impacts on Wastewater Treatment Systems along the U.S. Coasts
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Sea Level Rise Impacts on Ramsar Wetlands of International Importance
The Sea Level Rise Impacts on Ramsar Wetlands of International Importance data set represents the results of an analysis using the boundaries for Ramsar sites designated under the Ramsar Convention on Wetlands and intersecting them with different elevation zones in the coastal zone to assess area and percent area that would become inundated under 1 and 2 meter sea level rise scenarios. This data set provides results for 613 sites with defined boundaries that were found to intersect with the 0-5m above mean sea level coastal zone, defined by NASA Shuttle Radar Topography Mission (SRTM) elevation data. In addition to assessing the degree of risk of inundation, the data set provides population density and percent of land that is urban within the site and within 1km and 5km buffers surrounding the site. The data set also reports on infant mortality rates within 1km and 5km buffers around the site, as a measure of poverty levels that may affect adaptive capacity.
Global Mean Sea-Level Rise Projections to 2150 and 2300 (PROTECT)
<p>Full-track projections of global mean sea-level rise from PROTECT. Please check the deliverable text for details regarding these data.</p>
data supplement of "The causes of sea-level rise since 1900"
<p><strong>Data supplement for 'The causes of sea-level rise since 1900'</strong><br> (c) 2020 All Rights Reserved</p> <p>This is the data supplement for Thomas Frederikse, Felix Landerer, Lambert Caron, Surendra Adhikari, David Parkes, Vincent W. Humphrey, Soenke Dangendorf, Peter Hogarth, Laure Zanna, Lijing Cheng, Yun-Hao Wu: 'The causes of sea-level rise since 1900', Nature, 2020 (<a href="https://doi.org/10.1038/s41586-020-2591-3">https://doi.org/10.1038/s41586-020-2591-3</a>).</p> <p>A NetCDF-formatted file with the global sea-level curve and the components can also be obtained from NASA PO.DAAC: <a href="https://doi.org/10.5067/GMSLT-FJPL1">https://doi.org/10.5067/GMSLT-FJPL1</a>.</p> <p><strong>PLEASE CITE THE APPROPRIATE PAPERS WHEN USING THIS DATA</strong><br> Please cite 'The causes of sea-level rise since 1900' when using this data set. However, most of the data heavily relies on previous work by many authors, and please acknowledge that work by citing the original sources of the data. The main text and materials and methods section of 'The causes of sea-level rise since 1900' contains the full list of sources of all the data.<br> <strong>PLEASE CHECK THIS CAREFULLY!</strong></p> <p>This supplement contains the following files:</p> <ul> <li><em>global_basin_timeseries.xlsx </em><br> Global-mean and basin-mean time series of sea level and the individual contributing processes</li> <li><em>region_info.xlsx </em><br> List of all tide-gauge stations and VLM estimates used for each region</li> <li><em>GMSL_ensembles.nc </em><br> All 5000 ensemble members of GMSL and the contributing processes. The variable 'likelihood' provides the normalized likelihood of each ensemble member.</li> <li>Spatial patterns in relative sea level and solid-Earth deformation and the standard deviation due to each barystatic process are provided for each process individually: <ul> <li><em>AIS.nc </em><br> Antarctic Ice Sheet</li> <li><em>GrIS.nc </em><br> Greenland Ice Sheet</li> <li><em>glac.nc </em><br> Glaciers (excluding Greenland periphery)</li> <li><em>tws.nc </em><br> Terrestrial Water Storage</li> <li><em>total.nc </em><br> All <em>barystatic</em> processes combined</li> <li><em>steric.nc </em><br> Mean and standard deviation (1957-2018) of the steric anomalies (thermo- and halosteric)</li> </ul> </li> </ul> <p>The code to generate this data can be found at <a href="https://github.com/thomasfrederikse/sealevelbudget_20c">https://github.com/thomasfrederikse/sealevelbudget_20c</a></p> <p> </p>
Repository for "Impacts of Sea-Level Rise and Wave Inundation in the Tongariki Complex, Rapa Nui"
<p>This repository contains the necessary information to interpret, replicate and build upon the findings presented in the manuscript titled "Impacts of Sea-Level Rise and Wave Inundation in the Tongariki Complex, Rapa Nui". Any additional data not included here should be accessed from the original sources, which are referenced in the manuscript and its associated supplementary material. </p>
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International Brain Laboratory public data
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OpenNeuro
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