4302772
doi
10.5281/zenodo.4302772
oai:zenodo.org:4302772
Scott Kulp
Climate Central
Klaus Bittermann
Tufts University, Potsdam Institute
Maya K. Buchanan
Climate Central
Robert Kopp
Rutgers University
Chris Massey
USACE
Hans de Moel
Vrije Universiteit
Philip Orton
Stevens Institute of Technology
Benjamin H. Strauss
Climate Central
Sergey Vinogradov
Binera, Inc.; Stevens Institute of Technology
Data Supporting: "Economic Damages from Hurricane Sandy Attributable to Sea Level Rise Caused by Anthropogenic Climate Change"
Daniel M. Gilford
Rutgers University, Climate Central
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Sea Level Rise
Climate Change
Hurricane Sandy
Attribution
Semi-empirical Modeling
Damages
Hydrodynamic modeling
Flooding
<p>Code supporting Strauss et al. (2020) submitted to Nature Communications. If you use any original data from this archive, please cite the study as:</p>
<pre><code>B. H. Strauss, P. Orton, K. Bittermann, M. K. Buchanan, D. M. Gilford, R. E. Kopp, S. Kulp, C. Massey, H. de Moel, S. Vinogradov, 2020: Economic Damages from Hurricane Sandy Attributable to Sea Level Rise Caused by Anthropogenic Climate Change. Nature Communications. (under review, Dec. 2020)</code></pre>
<p>If you have any questions or comments, please contact Daniel Gilford at dgilford@climatecentral.org</p>
<p>Included are Input, Output, and Source files (compressed) used in the publication; data files are primarily in <strong>txt</strong>, <strong>csv</strong>, <strong>xlsx</strong>, and <strong>mat</strong> formats. In the absence of a MATLAB license, <strong>mat</strong> files may be read with open access software such as <a href="https://docs.scipy.org/doc/scipy/reference/generated/scipy.io.loadmat.html">SciPy</a>. Code supporting this publication may be found at <a href="https://github.com/climatecentral/cc_sandy_matlab">https://github.com/climatecentral/cc_sandy_matlab</a>.</p>
<p><em>Archived Data Short Descriptions:</em></p>
<ul>
<li><strong>INPUT</strong> -- Input semi-empirical model, hydrodynamic, and observational data files used to create distributions/analyses in this study.
<ul>
<li><strong>8518750_meantrend.csv</strong>: The Battery, NY monthly mean sea levels and trends/uncertainty, accessed from https://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?id=8518750 on 29 July 2020.</li>
<li><strong>cmip5.zip</strong>: CMIP5 semi-empirical model analyses for each individual model and scenarios (historical and counterfactual), and index files for reference.</li>
<li><strong>hadcrut.zip</strong>: HadCRUT4 semi-empirical model analyses for each individual HadCRUT4 scenario (historical and counterfactuals)</li>
<li><strong>Dangendorf2019_GMSL.txt</strong>: Monthly mean global mean sea level rise from <a href="https://www.nature.com/articles/s41558-019-0531-8">Dangendorf et al. (2019)</a>.</li>
<li>Also included are datum information, block damages (<strong>/damage/</strong> directory), hydrodynamic simulations (<strong>/simulations_july_2016/ </strong>directory), and additional auxiliary files required to run the accompanying repository analyses.</li>
</ul>
</li>
<li><strong>OUTPUT</strong> -- Code outputs supporting this publication
<ul>
<li><strong>fig1_data.mat</strong>: Quick access source data file which may be used to recreate Fig. 1 in the manuscript</li>
<li><strong>SEanalysis.mat</strong>: The full output semi-empirical model analyses in this study</li>
<li><strong>summary_samps.mat</strong>: Summary/ensemble analyses in this study</li>
</ul>
</li>
<li><strong>SOURCE</strong> -- Individual source data files for each Figure (1, 2, 3a-b), Table (1-2), Supplementary Figure (S1-4), and Supplementary Table (S1-6) in this study.
<ul>
<li>Included is a <strong>readme.txt</strong> with full descriptions of source data files.</li>
</ul>
</li>
</ul>
<p>We acknowledge funding from NSF grant ICER-1663807, NASA grant 80NSSC17K0698, </p>
v1.2 is a cleaned up version of v1.1.
Zenodo
2020-12-02
info:eu-repo/semantics/other
4289244
1.2
1623699011.446469
2376811539
md5:0b79259b46314457ef896a1dbc2183d7
https://zenodo.org/records/4302772/files/OUTPUT.zip
3062758168
md5:05e2fc2cadaac4029174662eb75ee67c
https://zenodo.org/records/4302772/files/INPUT_v1.2.zip
514863099
md5:edd720e5b70c508c6d3f1dd4ef10fd7f
https://zenodo.org/records/4302772/files/SOURCE.zip
public
10.5281/zenodo.4289244
isVersionOf
doi
Nature Communications
2020-12-02