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735 results for “Sea level”
Dataset for "The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6"
<p>This data set provides processed model output of ISMIP6 Greenland projections as documented and analysed in the following publication:</p> <p>Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andy Shepherd, Erika Simon, Cecile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald Slater, Robin Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6 , The Cryosphere, 2020. doi:10.5194/tc-2019-319</p> <p>About the data:<br> - The results are based on model output regridded conservatively to a 5x5 km regular ISMIP6 grid unless this is already the native grid. <br> - The results are calculated over the ice-covered area of Greenland, map projection error corrected, ice sheet model specific densities taken into account.<br> - The contribution of peripheral glaciers and ice caps has been removed, by considering their area-coverage in each grid cell.<br> - The results for the projections 'exp*' are all calculated as differences to the control experiment ctrl_proj (suffix cr in filename for control removed).<br> - Results for ctrl_proj and historical are un-corrected (no suffix cr in filename).</p> <p><br> Directory structure:<br> versionid<br> groupname1<br> modelname1<br> expid<br> scalars_mm_cr_GIS_groupname1_modelname1_expid.nc<br> scalars_rm_cr_GIS_groupname1_modelname1_expid.nc<br> scalars_zm_cr_GIS_groupname1_modelname1_expid.nc<br> ...</p> <p>Variables per file:</p> <p>scalars_mm_cr_GIS ----------------- Greenland wide numbers </p> <p>oarea - assumed ocean area [m2]<br> rhof - model specific freshwater density [kg m-3]<br> rhoi - model specific ice density [kg m-3]<br> rhow - model specific ocean water density [kg m-3]</p> <p>time - time, typically in days since X<br> iarea - Fraction of grid cell covered by land ice [1]<br> iareagr - Fraction of grid cell covered by grounded ice sheet<br> iareafl - Fraction of grid cell covered by ice sheet flowing over seawater</p> <p>ivol - ice volume [m3]<br> ivolgr - grounded ice volume [m3]<br> ivolfl - floating ice volume [m3]<br> ivaf - ice volume above flotation [m3]</p> <p>lim - ice mass [kg]<br> limgr - grounded ice mass [kg]<br> limfl - floating ice mass [kg]<br> limaf - ice mass above flotation [kg]</p> <p>sle - sea-level equivalent mass [m] !! decreases with mass loss !! <br> smb - spatially integrated surface mass balance anomaly [kg s-1]</p> <p><br> scalars_rm_cr_GIS ----------------- IMBIE2-Rignot basins xx=[no,ne,se,sw,cw,nw]</p> <p>oarea - assumed ocean area [m2]<br> rhof - model specific freshwater density [kg m-3]<br> rhoi - model specific ice density [kg m-3]<br> rhow - model specific ocean water density [kg m-3]</p> <p>time - time, typically in days since X<br> ivaf_xx - ice volume above flotation [m3]<br> smb_xx - spatially integrated surface mass balance anomaly [kg s-1]<br> limaf_xx - ice mass above flotation [kg]<br> sle_xx - sea-level equivalent mass [m] !! decreases with mass loss !! </p> <p><br> scalars_zm_cr_GIS ----------------- IMBIE2-Zwally basins xx=[z11,z12,z13,z14,z21,z22,z31,z32,z33,z41,z42,z43,z50,z61,z62,z71,z72,z81,z82]</p> <p>oarea - assumed ocean area [m2]<br> rhof - model specific freshwater density [kg m-3]<br> rhoi - model specific ice density [kg m-3]<br> rhow - model specific ocean water density [kg m-3]</p> <p>time - time, typically in days since X<br> ivaf_xx - ice volume above flotation [m3]<br> smb_xx - spatially integrated surface mass balance anomaly [kg s-1]<br> limaf_xx - ice mass above flotation [kg]<br> sle_xx - sea-level equivalent mass [m] !! decreases with mass loss !! </p> <p> </p> <p>Data usage notice:<br> If you use any of these results, please acknowledge the work of the people involved in producing them. Acknowledgements should have language similar to the below.</p> <p>“We thank the Climate and Cryosphere (CliC) effort, which provided support for ISMIP6 through sponsoring of workshops, hosting the ISMIP6 website and wiki, and promoted ISMIP6. We acknowledge the World Climate Research Programme, which, through it's Working Group on Coupled Modelling, coordinated and promoted CMIP5 and CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the CMIP data and providing access, the University at Buffalo for ISMIP6 data distribution and upload, and the multiple funding agencies who support CMIP5 and CMIP6 and ESGF. We thank the ISMIP6 steering committee, the ISMIP6 model selection group and ISMIP6 dataset preparation group for their continuous engagement in defining ISMIP6."</p> <p>You should also refer to and cite the following papers:</p> <p>Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andy Shepherd, Erika Simon, Cecile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald Slater, Robin Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6 , The Cryosphere, 2020. doi:10.5194/tc-2019-319</p> <p>Sophie Nowicki, Antony Payne, Heiko Goelzer, Helene Seroussi, William Lipscomb, Ayako Abe-Ouchi, Cecile Agosta, Patrick Alexander, Xylar Asay-Davis, Alice Barthel, Thomas Bracegirdle, Richard Cullather, Denis Felikson, Xavier Fettweis, Jonathan Gregory, Tore Hatterman, Nicolas Jourdain, Peter Kuipers Munneke, Eric Larour, Christopher Little, Mathieu Morlinghem, Isabel Nias, Andrew Shepherd, Erika Simon, Donald Slater, Robin Smith, Fiammetta Straneo, Luke Trusel, Michiel van den Broeke, and Roderik van de Wal: Experimental protocol for sea level projections from ISMIP6 standalone ice sheet models, The Cryosphere, doi:10.5194/tc-2019-322, 2020.</p>
Last interglacial (MIS 5e) sea-level proxies in Cyprus, Eastern Mediterranean
<p>This file is a record of relative sea level proxies of the last Interglacial sea-level (MIS 5e) along the Cyprus coastline. It has been exported from the World Atlas of Last Interglacial Shorelines - WALIS</p>
Engaging the Business and Tourism Industry in Visualizing Sea Level Rise Impacts to Transportation Infrastructure in Waikiki, Hawaii
<p>Transportation planners in coastal communities plan for future hazards and risks of sea-level rise (SLR), and often, they communicate risk in public meetings via PowerPoint presentations with charts as well as two-dimensional (2D) maps that visualize information using Geographic Information Systems (GIS) technologies. The project investigates the use of immersive technology to communicate SLR risk, including the development of an immersive three-dimensional (3D) model of the Waikiki neighborhood of Honolulu, Hawaii. According to the project’s original methodology, participants would have experienced the model using virtual reality (VR). However, due to the COVID-19 pandemic, the team pivoted to creating and implementing an internet-based survey instrument with embedded 2D charts and video of the animated 3D model. The flooding projections were derived from National Oceanic and Atmospheric Administration (NOAA) data. NOAA supplies the SLR Viewer, a screening-level tool that uses the best-available national projections to map areas vulnerable to current and future flood risks.</p>
Estimates of US coastal damages by local sea level
<p>Estimates of coastal property damage and business interruption from storms and estimates of property below sea level by region and exposure category. Regions are groups of US counties designated by state and <em>coastalflag</em>, which indicates whether a region includes counties sharing a US coastline (coastalflag=1) or only inland counties (coastalflag=0). Estimates are produced using the RMS Model.</p> <p>These values are used as inputs by <em>Probabilistic state-level estimates of US coastal storm property damages from climate change</em> (doi: https://dx.doi.org/10.5281/zenodo.820086) using the code at https://github.com/ClimateImpactLab/acp-impacts</p> <p>Hurricane damage estimates include estimates using historical hurricane activity as well as estimates including projected changes in hurricane frequency and intensity under RCP 4.5 and 8.5.</p>
Holocene relative sea-level data from the Atlantic coasts of South America
<p>This spreadsheet is a complete record of the Holocene sea-level proxies in the southwestern Atlantic, from Brazil to Argentina following the HOLSEA template. </p>
Paleo Sea Level Proxies and Indicators for Greenland
<p>This repository contains the spreadsheets containing the paleo sea level data in ODS spreadsheet and tab delimited text formats. I also included the bibtex file that has all of the references used in the spreadsheet. For updates, please<br>go to the main GAPSLIP database on Github:</p><p>https://github.com/evangowan/paleo_sea_level</p><p>Version 1.0.1 corrects some of the place names.</p>
Repository for adjoint convolution analysis of sea level variations near Charleston and Nantucket
<p>This repository contains adjoint sensitivity, forcing, and example adjoint-convolution script to reconstruct sea level variations near Charleston and Nantucket. </p>
SLIIDERS: Sea Level Impacts Input Dataset by Elevation, Region, and Scenario
<p>This record includes the Sea Level Impacts Input Dataset by Elevation, Region, and Scenario (SLIIDERS) dataset. It also includes source code to generate this product as well as necessary inputs that are not available for download elsewhere. Both the dataset and the source code are consistent with version 1.2. <strong>Note</strong>: The version associated with <a href="https://gmd.copernicus.org/articles/16/4331/2023/">Depsky et al., 2023</a> is v1.1.</p> <p>The zipped SLIIDERS Zarr store can be downloaded and accessed locally or can be directly accessed via code similar to the following:</p> <pre><code>from fsspec.implementations.zip import ZipFileSystem import xarray as xr xr.open_zarr(ZipFileSystem(url_of_file_in_record}}).get_mapper())</code></pre> <p><strong>File Inventory</strong></p> <p><em>Products</em></p> <ul> <li><strong>sliiders-v1.2.zarr.zip</strong>: SLIIDERS. A global dataset containing 18 socioeconomic variables, reflecting present day socioeconomic and geophysical characteristics of 11,980 coastal regions and projecting capital stock, GDP, and population growth trajectories through 2100 for five SSPs and two economic growth models. These variables are used as inputs to the pyCIAM modeling platform detailed in Depsky et al. 2023.</li> <li><strong>sliiders-v1.2.nc</strong>: Same as the original SLIIDERS dataset, but in netcdf format.</li> </ul> <p><em>Inputs</em></p> <p>All provided inputs are manually created or adjusted points used to create the coastline segments of SLIIDERS:</p> <ul> <li><strong>ciam_segment_pts_manual_adds.parquet</strong>: A list of segment points manually added to those that come from the extreme sea level model CoDEC (<a href="https://doi.org/10.5281/zenodo.3660926">Muis et al. 2020</a>)</li> <li><strong>gtsm_stations_ciam_ne_coastline_snapped.parquet:</strong> Stations from CoDEC snapped to coastlines from <a href="https://www.naturalearthdata.com/downloads/10m-physical-vectors/">Natural Earth</a></li> <li><strong>gtsm_stations_eur_tothin.parquet</strong>: A list of European points in CoDEC to thin. CoDEC provides ~10km resolution in Europe and ~50km elsewhere. For consistency, SLIIDERS uses ~50km spacing for its coastal segments globally.</li> </ul> <p><em>Source Code</em></p> <ul> <li><strong>sliiders-1.2.zip</strong>: The source code used to generate SLIIDERS v1.1. See READMEs within this code for more details. This is consistent with release v1.2 of the code maintained on github at <a href="https://github.com/ClimateImpactLab/SLIIDERS">https://github.com/ClimateImpactLab/SLIIDERS</a></li> </ul>
GTSM-ERA5-E dataset - Data underlying the paper "Global dataset of storm surges and extreme sea levels for 1950-2024 based on the ERA5 climate reanalysis"
<p>Extreme sea levels, generated by storm surges and high tides, have the potential to cause coastal flooding and erosion. Global datasets are instrumental for mapping of extreme sea levels and associated societal risks. Harnessing the backward extension of the ERA5 reanalysis, we present a dataset containing the statistics of water levels based on a global hydrodynamic model (GTSMv3.0) covering the period 1950-2024. This is an extension of a previously published dataset for 1979-2018 <a href="https://www.frontiersin.org/articles/10.3389/fmars.2020.00263/full" target="_blank" rel="noopener">(Muis et al. 2020)</a>. The timeseries (10-min, hourly mean and daily maxima) are available via the Climate Data Store of ECMWF at DOI: 10.24381/cds.a6d42d60. Using this extended ERA5 dataset, we calculate percentiles and estimate extreme water levels for various return periods globally. The percentiles dataset includes the 1, 5, 10, 25, 50, 75, 90, 95 and 99th percentiles. The extreme water levels include return values for 1, 2, 5, 10, 25, 50, 75 and 100 years, and they are estimated using POT-GPD method applied with a threshold of 99th percentile of the timeseries and using a 72-hour window for declustering peak events, and MLE method for fitting the GPD parameters. The parameters (shape, scale and location) are also supplied with this dataset.</p> <p>Validation of the underlying timeseries and the statistical values shows that there is a good agreement between observed and modelled sea levels, with the level of agreement being very similar to that of the previously published dataset. The extended 75-year dataset allows for a more robust estimation of extremes, often resulting in smaller uncertainties than its 40-year precursor. The present dataset can be used in global assessments of flood risk, climate variability and climate changes.</p> <p>Global modelling of water levels and extreme value analysis are associated with a number of uncertainties and limitations, that are particularly important to consider when conducting local assessments. Please refer to the Usage Notes in the corresponding manuscript (Aleksandrova et al. 2025, paper currently under review) for an overview of limitations.</p>
Global Mean Sea Level, Trajectory and Extrapolation
<p>Global Mean Sea Level, Trajectory and Extrapolation</p> <p>This file contains Global Mean Sea Level (GMSL) variations along, data for the quadratic fit (trajectory) to the GMSL variations, and an extrapolation of this trajectory to 2050.</p> <p>Column 1 provides the calendar year plus the decimal fraction of the current year. The GMSL variations(column 2) are computed at the NASA Goddard Space Flight Center under the auspices of the NASA Sea Level Change program. All units for sea level are in centimeters The GMSL was generated using the NASA-SSH Simple Gridded Sea Surface Height from Standardized Reference Missions Version 1: https://podaac.jpl.nasa.gov/dataset/NASA_SSH_REF_SIMPLE_GRID_V1. It combines Sea Surface Heights from the TOPEX/Poseidon, Jason-1, OSTM/Jason-2, HDR Jason-3, and Sentinel-6 Michael Freilich missions.</p> <p>In addition, the rate and acceleration are estimated from full record of GMSL relative to the midpoint of the record and then used to generate a quadratic fit to the data. This quadratic fit is provided in column 3. The rate associated with this quadratic fit at any time in the record is also provided (column 4). </p> <p>The parameters estimated from the quadratic fit are also used to generated an extrapolated time series out to 2050 (column 5). These are provided at yearly intervals. This is not a projection and is only considered an extrapolation of the current trajectory of GMSL variations. This also differs from Nerem et al. (2022) and Sweet et al. (2022) as additional signals are not removed from GMSL prior to estimating the rate and acceleration parameters. The yearly rate associated with this extrapolation is also provided (column 6).<br><br>If you use these data please cite:<br>Willis, J.K., Hamlington, B.D., and Fournier, S., Global Mean Sea Level Time Series, Trajectory and Extrapolation. Dataset access [YYYY-MM-DD] at 10.5281/zenodo.7702314.</p> <p>References:</p> <p>Nerem, R. S., Frederikse, T., & Hamlington, B. D. (2022). Extrapolating Empirical Models of Satellite‐Observed Global Mean Sea Level to Estimate Future Sea Level Change. <em>Earth's Future</em>, <em>10</em>(4), e2021EF002290.</p> <p>Sweet, W. V., Hamlington, B. D., Kopp, R. E., Weaver, C. P., Barnard, P. L., Bekaert, D., ... & Zuzak, C. (2022). <em>Global and regional sea level rise scenarios for the United States: updated mean projections and extreme water level probabilities along US coastlines</em>. Interagency Technical Report.</p>
Replication package for "Why do people persist in sea-level rise threatened coastal regions? Empirical evidence on risk aversion and place attachment"
<p><strong>Steps to replicate the tables and figures in “Why do people persist in sea-level rise threatened coastal regions? Empirical evidence on risk aversion and place attachment”</strong></p> <p><em>by Ivo Steimanis, Matthias Mayer and Björn Vollan</em></p> <p><strong>General information:</strong></p> <ul> <li>Instructions for replication of the results using Stata. All do-files were created in Stata 16.</li> <li>There are 4 folders (DO-FILES, DTA-FILES, OUTPUT, XLS-FILES), in the replication package. Copy these folders to your computer in a common directory</li> </ul> <p> </p> <p><strong>Do-files:</strong></p> <ul> <li>In the DO-FILES folder run the <strong>“00_master.do”</strong> to replicate the results reported in the main manuscript and the supplementary materials. The results will be saved in the OUTPUT folder. All additional Stata packages will be automatically installed.</li> <li><strong>“01_merge_generate.do” </strong>merges the different datasets and creates additional variables using in the analysis</li> <li><strong>“02_analysis.do” </strong>provides the code to replicate all figures and tables reported in the main manuscript and supplementary materials</li> </ul> <p> </p> <p><strong>Data sets:</strong></p> <ul> <li>“bd_combine.dta”: cleaned survey data from Bangladesh</li> <li>“vn_combine.dta”: cleaned survey data from Vietnam</li> <li>“data_analysis.dta”: main data set with the survey data from Bangladesh and Vietnam merged</li> </ul>
Sea Level observations from Passage West, Cork, Ireland in 1842
<p>Data are described in Pugh, D. T., Bridge, E., Edwards, R., Hogarth, P., Westbrook, G., Woodworth, P. L., & McCarthy, G. D. (2021). Mean Sea Level and Tidal Change in Ireland since 1842: A case study of Cork. Ocean Science Discussions, 1-26. </p> <p>Location: Passage West, Co. Cork, Ireland <br> Latitude: 51.871 <br> Longitude: -8.334 <br> Height is given in ft ODD and m ODM <br> ODM is Ordnance Datum Malin and is current national datum used in Ireland. ODD is Ordnance Datum Dublin and is a historical datum. See paper for details on tranfer between datums <br> Time is stored as hh:mm:ss <br> Missing Values = -9999 <br> Data were gather from tide pole readings. Missing data indicate times when observations were not taken. </p>
The observation of the dynamic sea level (DSL) is available from the AVISO
<p>The observation of the DSL used for the publication about formulation of a new explicit tidal scheme in ocean general circulation model by Jin et al., currently under review for GMD journal. (See https://doi.org/10.5194/gmd-2021-441).</p>
IPCC AR6 Relative Sea Level Projection P-Boxes
<p><strong>Description</strong></p> <p>This data set contains detailed elements of the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections for all of the p-boxes described in AR6 WG1 9.6.3 (under ar6-regional-pboxes.zip), as well as a variant excluding the AR6 estimates of background sea level change (under ar6-regional_novlm-pboxes.zip).</p> <p>Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool.</p> <p><strong>Required Acknowledgements and Citation </strong></p> <p>In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used:</p> <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> <p><em>Please also include in the acknowledgements of works citing these projections:</em></p> <blockquote> <p>We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool.</p> </blockquote> <p><strong>IPCC AR6 Licensing</strong></p> <p>The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</p> <p> </p>
IPCC AR6 Relative Sea Level Projection Distributions
<p><strong>Description</strong></p> <p>This data set contains detailed elements the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projection distributions for all the workflows described in AR6 WG1 9.6.3.2, as well as distributions for the components contributing to relative sea level change.</p> <p>Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool.</p> <p><strong>Required Acknowledgements and Citation </strong></p> <p>In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used:</p> <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> <p><em>Please also include in the acknowledgements of works citing these projections:</em></p> <blockquote> <p>We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool.</p> </blockquote> <p><strong>IPCC AR6 Licensing</strong></p> <p>The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</p> <p> </p>
IPCC AR6 Relative Sea Level Projections without Background Component
<p><strong>Description</strong></p> <p>This data set contains detailed elements the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. In particular, it contains relative sea level projections that exclude the background term (representing primarily land subsidence or uplift). It includes probability distributions for all the workflows described in AR6 WG1 9.6.3.2, as well as p-boxes derived from these distributions.</p> <p>Most users will not want this dataset, but rather the dataset at https://doi.org/10.5281/zenodo.5914709. These data may be of use for users who want to substitute their own estimates of the background term. Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool.</p> <p><strong>Required Acknowledgements and Citation </strong></p> <p>In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used:</p> <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> <p><em>Please also include in the acknowledgements of works citing these projections:</em></p> <blockquote> <p>We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea-Level Change Team for developing and hosting the IPCC AR6 Sea-Level Projection Tool.</p> </blockquote> <p><strong>IPCC AR6 Licensing</strong></p> <p>The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</p>
Dublin's Corrected Mean Sea Level (1938-2016)
<p>These datasets have been created and published to accompany the paper "A newly reconciled data set for identifying sea level rise and variability in Dublin Bay" by Shoari Nejad et al 2021.</p> <p> Filename format: <dataset_name>_dublin_<variable_names>_<startyear>_to_<endyear>.csv.</p> <p>Time and date variables are described using standard names: Year, Month, Day, Hour, Minute, Date (dd/mm/yyyy). All times are UTC. Sea level variables are described in the format <variable_name>_<unit>_<datum>. Ordnance Datum Malin (ODM) is used with geoid model OSGM15. LAT is 2.599 m below ODM for Dublin Port. None of the datasets is adjusted for atmospheric effects. </p>
IPCC AR6 Sea Level Projections
<p><strong>Description</strong></p> <p>This data set contains the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. It contains the full set of samples for the global projections (under ar6.zip), as well as summary relative sea level projections (under ar6-regional-confidence.zip and, without the AR6 estimate of background sea level process rates, ar6-regional_novlm-confidence.zip). Most users will want to focus on the confidence_output_files, which correspond most directly to the figures and tables in the report. For the global projections, samples from the individual probability distributions described in AR6 WG1 9.6.3 are in the full_sample* directories.</p> <p>Regional projections can also be accessed through the NASA/IPCC Sea Level Projections Tool at <a href="https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool">https://sealevel.nasa.gov/ipcc-ar6-sea-level-projection-tool</a>.</p> <p>See <a href="../communities/ipcc-ar6-sea-level-projections">https://zenodo.org/communities/ipcc-ar6-sea-level-projections</a> for additional related data sets.</p> <p>See <a href="https://github.com/Rutgers-ESSP/IPCC-AR6-Sea-Level-Projections">https://github.com/Rutgers-ESSP/IPCC-AR6-Sea-Level-Projections</a> for a guide to available resources.</p> <p><strong>Required Acknowledgements and Citation </strong></p> <p>In order to document the impact of these sea-level rise projections, users of the projections are obligated to cite chapter 9 of Working Group 1 contribution to the the IPCC Sixth Assessment Report, the Framework for Assessment of Changes To Sea-level (FACTS) model description paper, and the version of the data set used:</p> <ul> <li>Fox-Kemper, B., H.T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S.S. Drijfhout, T.L. Edwards, N.R. Golledge, M. Hemer, R.E. Kopp, G. Krinner, A. Mix, D. Notz, S. Nowicki, I.S. Nurhati, L. Ruiz, J.-B. Sallée, A.B.A. Slangen, and Y. Yu, 2021: Ocean, Cryosphere and Sea Level Change. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1211–1362, <a href="https://doi.org/10.1017/9781009157896.011" rel="nofollow">doi:10.1017/9781009157896.011</a>.</li> <li>Kopp, R. E., Garner, G. G., Hermans, T. H. J., Jha, S., Kumar, P., Reedy, A., Slangen, A. B. A., Turilli, M., Edwards, T. L., Gregory, J. M., Koubbe, G., Levermann, A., Merzky, A., Nowicki, S., Palmer, M. D., & Smith, C. (2023). The Framework for Assessing Changes To Sea-Level (FACTS) v1.0: A platform for characterizing parametric and structural uncertainty in future global, relative, and extreme sea-level change. Geoscientific Model Development, 16, 7461–7489. <a href="https://doi.org/10.5194/gmd-16-7461-2023" rel="nofollow">https://doi.org/10.5194/gmd-16-7461-2023</a></li> <li>Garner, G. G., T. Hermans, R. E. Kopp, A. B. A. Slangen, T. L. Edwards, A. Levermann, S. Nowikci, M. D. Palmer, C. Smith, B. Fox-Kemper, H. T. Hewitt, C. Xiao, G. Aðalgeirsdóttir, S. S. Drijfhout, T. L. Edwards, N. R. Golledge, M. Hemer, G. Krinner, A. Mix, D. Notz, S. Nowicki, I. S. Nurhati, L. Ruiz, J-B. Sallée, Y. Yu, L. Hua, T. Palmer, B. Pearson, 2021. IPCC AR6 Sea Level Projections. Version 20210809. Dataset accessed [YYYY-MM-DD] at <a href="https://doi.org/10.5281/zenodo.5914709" rel="nofollow">https://doi.org/10.5281/zenodo.5914709</a>.</li> </ul> <p><em>Please also include in the acknowledgements of works citing these projections:</em></p> <blockquote> <p>We thank the projection authors for developing and making the sea-level rise projections available, multiple funding agencies for supporting the development of the projections, and the NASA Sea Level Change Team for developing and hosting the IPCC AR6 Sea Level Projection Tool.</p> </blockquote> <p><strong>IPCC AR6 Licensing</strong></p> <p>The IPCC AR6 Sea-Level Rise Projections are licensed by the authors under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/). The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</p>
Location List for IPCC AR6 Sea Level Projections
<p>This data set contains the location list file for the sea-level projections associated with the Intergovernmental Panel on Climate Change Sixth Assessment Report. It can be used to cross-reference location IDs with names of the locations.</p> <p>Column 1 – Location name (string with spaces having been replaced with underscores)<br> Column 2 – Location ID (integer value)<br> Column 3 – Latitude (-90 to 90 degrees)<br> Column 4 – Longitude (-180 to 180 degrees)</p> <p>See <a href="https://zenodo.org/communities/ipcc-ar6-sea-level-projections">https://zenodo.org/communities/ipcc-ar6-sea-level-projections</a> for additional related data sets.</p>
Biogeomorphic modeling to assess the resilience of tidal-marsh restoration to sea level rise and sediment supply - Supporting code and data
<p>Code and data to reproduce figures and analyses of the paper:</p> <p>Gourgue, O., van Belzen, J., Schwarz, C., Vandenbruwaene, W., Vanlede, J., Belliard, J.-P., Fagherazzi, S., Bouma, T.J., van de Koppel, J., and Temmerman, S.: Biogeomorphic modeling to assess resilience of tidal marsh restoration to sea level rise and sediment supply, Earth Surf. Dynam., submitted.</p> <p>Standard Python dependencies:</p> <ul> <li>GDAL</li> <li>Geopandas</li> <li>Matplotlib</li> <li>NumPy</li> <li>Rasterio</li> <li>SciPy</li> <li>Seaborn</li> <li>Shapely</li> <li>scikit-learn</li> </ul> <p>Third-party Python dependencies:</p> <ul> <li>Centerline (https://github.com/fitodic/centerline)</li> <li>pputils (https://github.com/pprodano/pputils)</li> <li>pysheds (https://github.com/mdbartos/pysheds)</li> </ul> <p>In-house Python dependencies:</p> <ul> <li>Demeter 1.0.5 (https://doi.org/10.5281/zenodo.5205258)</li> <li>OGTools 1.1 (https://doi.org/10.5281/zenodo.3994952)</li> <li>TidalGeoPro 0.1 (https://doi.org/10.5281/zenodo.5205285)</li> </ul>
ScienceDex guides
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