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54 results for “Sea-level Rise”
Salt marsh litter quality and decomposition under sea-level rise scenarios: from leaves to fine absorptive roots
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Wave setup and wave-induced flooding dataset for "Coastal flooding and sea-level rise allowances in atoll island"
<p>This dataset contains the wave setup and wave-induced flooding from the simulations in a profile of a coral reef island. The complete description of the simulations can be found in "Coastal flooding and sea-level rise allowances in atoll island". The wave setup and flooding values correspond to the median values of the 3 simulations performed for each parameter combination. A measure of the dispersion of the three simulation is also given as the standard deviation of the three simulations.</p>
Sea-Level Rise in Southwest Greenland as a Contributor to Viking Abandonment
<p>Data and code to accompany the journal publication "Sea-Level Rise in Southwest Greenland as a Contributor to Viking Abandonment" in the Proceedings of the National Academy of Sciences of the United States of America (PNAS). This dataset includes data sets, computer codes and associated scripts, necessary to reproduce results in the article: (1) the surface computational grid; (2) model Greenland Ice Sheet history in time steps of 20 years from 1000 CE to present-day; (3) code to compute the relative sea-level change at any user specified set of sites across the same time steps; (4) code to map (2) and (3) on to conventional grids (e.g., latitude-longitude; Gauss-Legendre, etc.) based on a non-linear interpolation of data on a triangular grid via a second-order scheme; (5) code to convert sea level changes into time series of past topography from which flooding geometry (i.e., shoreline migration) can be tracked; and (6) code to integrate the flood geometries in (5) to compute time series of total flood area. More details in Readme.pdf.</p>
Supplementary Data Tables for 'The Global Drivers of Chronic Coastal Flood Hazards under Sea-Level Rise'
<p>Please refer to and cite the manuscript Hague et al. (2023), 'The Global Drivers of Chronic Coastal Flood Hazards under Sea-Level Rise', Earth's Future. https://doi.org/10.1029/2023EF003784 </p> <p> </p>
Warming stimulates mangrove carbon sequestration in rising sea-level at their northern limit: an in situ simulation
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Data from: Can restoring tidal wetlands reduce nuisance flooding of coasts under future sea-level rise?
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Impacts of bed topography resolution on sea-level rise projections from coupled subglacial hydrology and ice dynamics for Thwaites Glacier, Antarctica
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Datatset from "Coastal flooding in the Maldives induced by mean sea-level rise and wind-waves: from global to local coastal modelling"
<p>Resulting downscaled wave fields from the WaveWatch III simulations for the four main wave directions identified and six return periods (10, 20, 50, 100, 500, and 1000 years).</p>
Salt Water Exposure Exacerbates the Negative Response of Phragmites australis Haplotypes to Sea-Level Rise
<p>Dataset associated with the 2024 publication in the <em>Plants</em> journal dealing with <em>Phragmites australis </em>response to abiotic factors associated with rising sea levels. </p>
Elevation projections for the Mekong delta (Vietnam) under sedimentation strategies, subsidence, compaction, and sea-level rise
<p>Modelled elevation projections for the Mekong delta (Vietnam) to 2050 under scenarios of fluvial sedimentation, organic accumulation, anthropogenic-accelerated subsidence, natural compaction, and global sea-level rise. Data is in meters above sea level and georeferenced (WGS84 UTM zone 48N).<br> For methodology and detailed description of the data, please see Dunn and Minderhoud (2021) DOI to follow, in which part of the dataset is presented in Figure 6.</p>
The impact of Natural Variability on Regional Sea-Level Rise During the Satellite-Altimetry Era
<p>We share the datasets for each figure. Anyone can use the datasets under proper citation.</p>
Predicting changes in molluscan spatial distributions in mangrove forests in response to sea-level rise
<p class="MsoNormal"><span>Molluscs are an important component of the mangrove ecosystem, and the vertical distributions of molluscan species in this ecosystem are primarily dictated by tidal inundation. Thus, sea-level rise (SLR) may have profound effects on mangrove mollusc communities. Here, we used dynamic empirical models, based on measurements of surface elevation change, sediment accretion, and molluscan zonation patterns, to predict changes in molluscan spatial distributions in response to different sea-level rise rates in the mangrove forests of Zhenzhu Bay (Guangxi, China). The change in surface elevation was 4.76–9.61 mm yr</span><sup><span>−</span></sup><sup><span>1</span></sup><span> during the study period (2016–2020), and the magnitude of surface-elevation change decreased exponentially as original surface elevation increased. Based on our model results, we predicted that mangrove molluscs might successfully adapt to a low rate of SLR (2.00–4.57 mm yr</span><sup><span>−</span></sup><sup><span>1</span></sup><span>) by 2100, with molluscs moving seaward and those in the lower intertidal zones expanding into newly available zones. However, as SLR rate increased (4.57–8.14 mm yr</span><sup><span>−</span></sup><sup><span>1</span></sup><span>), our models predicted that surface elevations would decrease beginning in the high intertidal zones and gradually spread to the low intertidal zones. Finally, at high rates of SLR (8.14–16.00 mm yr</span><sup><span>−</span></sup><sup><span>1</span></sup><span>), surface elevations were predicted to decrease across the elevation gradient, with molluscs moving landward and species in higher intertidal zones blocked by landward barriers. Tidal inundation and the consequent increases in interspecific competition and predation pressure were predicted to threaten the survival of many molluscan groups in higher intertidal zones, especially arboreal and infaunal molluscs at the landward edge of the mangroves, resulting in a substantial reduction in the abundance of original species on the landward edge. Thus, future efforts to conserve mangrove floral and faunal diversity should prioritize species restricted to landward mangrove areas and protect potential species habitats.</span></p>
Dataset for Supplementary Figures of "The macroeconomic effects of adapting to high-end sea-level rise via protection and migration"
<p>This dataset served as input data for the analysis as presented in the article "The macroeconomic effects of adapting to high-end sea-level rise via protection and migration" and allows to reproduce Supplementary Figures 3-26.</p>
Increasing methane emissions from natural land ecosystems due to sea-level rise
<p>The file contains the datasets (data, scripts and GIS data) presented in "Increasing methane emissions from natural land ecosystems due to sea-level rise"</p>
Data from: Sea-level rise causes feeding habitat loss for migratory shorebirds in remote coastal wetlands of Brazilian Amazon.
<p>Data supporting the results in "Sea-level rise causes feeding habitat loss for migratory shorebirds in remote coastal wetlands of Brazilian Amazon."</p> <p> </p>
Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks: Dataset 2
<p>Coastal communities rely on levees and seawalls as critical protection against sea-level rise; in the U.S. alone, $300 billion in shoreline armoring costs are forecast by 2100. But despite the local flood risk reduction benefits, these structures can exacerbate flooding and associated damages along other parts of the shoreline—particularly in coastal bays and estuaries, where nearly 500 million people globally are at risk from sea-level rise. The magnitude and spatial distribution of the economic impact of this dynamic, however, are poorly understood. Here we combine hydrodynamic and economic models to assess the extent of both local and regional flooding and damages expected from a range of shoreline protection and sea-level rise scenarios in San Francisco Bay, California. We find that protection of individual shoreline segments (5-75 km) can increase flooding in other areas by as much as 36 million cubic meters and damages by $723 million for a single flood event, and in some cases can even cause regional flood damages that exceed the local damages prevented from protection. We also demonstrate that strategic flooding of certain shoreline segments, such as those with gradually sloping baylands and space for water storage, can help alleviate flooding and damages along other stretches of the coastline. By matching the scale of the economic assessment to the scale of the threat, we reveal the previously uncounted costs associated with uncoordinated adaptation actions and demonstrate that a regional planning perspective is essential for reducing shared risk and wisely spending adaptation resources in coastal bays.</p> <p>This dataset is associated with a github repository https://github.com/rmgriffin/OLU-flood-externalities</p> <p>This dataset is part of a two record data repository associated with the paper "Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks." This is part two.</p>
Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks: Dataset 1
<p>Coastal communities rely on levees and seawalls as critical protection against sea-level rise; in the U.S. alone, $300 billion in shoreline armoring costs are forecast by 2100. But despite the local flood risk reduction benefits, these structures can exacerbate flooding and associated damages along other parts of the shoreline—particularly in coastal bays and estuaries, where nearly 500 million people globally are at risk from sea-level rise. The magnitude and spatial distribution of the economic impact of this dynamic, however, are poorly understood. Here we combine hydrodynamic and economic models to assess the extent of both local and regional flooding and damages expected from a range of shoreline protection and sea-level rise scenarios in San Francisco Bay, California. We find that protection of individual shoreline segments (5-75 km) can increase flooding in other areas by as much as 36 million cubic meters and damages by $723 million for a single flood event, and in some cases can even cause regional flood damages that exceed the local damages prevented from protection. We also demonstrate that strategic flooding of certain shoreline segments, such as those with gradually sloping baylands and space for water storage, can help alleviate flooding and damages along other stretches of the coastline. By matching the scale of the economic assessment to the scale of the threat, we reveal the previously uncounted costs associated with uncoordinated adaptation actions and demonstrate that a regional planning perspective is essential for reducing shared risk and wisely spending adaptation resources in coastal bays.</p> <p>This dataset is associated with a github repository https://github.com/rmgriffin/OLU-flood-externalities</p> <p>This dataset is part of a two record data repository associated with the paper "Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks." This is part one.</p>
Baltic Sea flood maps under the influence of sea-level rise, dike height increases and managed realignment
<p>The provided data was produced as part of the Ecas-Baltic project (2020 - 2023). The project is funded by the Federal Ministry of Education and Research in Germany (BMBF, funding code 03F0860H).</p><p>The dataset contains information supporting the conclusions presented in the following publication (the final, revised version of the article will be accessible via the journal webpage):</p><p>Kiesel, J., Honsel, L.E., Lorenz, M., Gräwe, U., and Vafeidis, A. T.: Raising dikes and managed realignment may be insufficient for maintaining current flood risk along the German Baltic Sea coast, <a href="https://www.nature.com/commsenv/">Communications Earth & Environment</a>, accepted for publication, 2023.</p><p> </p><p>The dataset contains:</p><p>- the flood maps containing both the maximum flood extent and maximum inundation depth at every grid cell of the coastal inundation model. The flood maps cover two sea-level rise (1 m and 1.5 m) and three adaptation scenarios (state dikes plus 1.5 m, all dikes plus 1.5 m and potential managed realignment sites including state dikes plus 1.5 m)</p><p>- the potential for physically plausible managed realignment sites along the German Baltic Sea coast</p><p>- a readme file containing further information on the datasets and related data and publications</p><p> </p><p>For methodological details we refer the reader to the publication cited above and the publication presenting the modelling setup (Kiesel et al., 2023: https://doi.org/10.5194/nhess-23-2961-2023). The previously mentioned article provides inundation maps representing the current state of adaptation in terms of dike lines and associated elevations (https://doi.org/10.5281/zenodo.7886455). The code to detect the potential physically plausible managed realignment sites is publically available from https://gitlab.com/larsenno/sumare.</p>
Economic evaluation of sea-level rise adaptation strongly influenced by hydrodynamic feedbacks: Dataset 1
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Data from: Testing sea-level rise impacts in tidal wetlands: a novel in situ approach
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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.