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Dataset Open Access

Data Supporting: "Economic Damages from Hurricane Sandy Attributable to Sea Level Rise Caused by Anthropogenic Climate Change"

Daniel M Gilford; Klaus Bittermann; Robert Kopp; Ben Strauss; Scott Kulp

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  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.4289245", 
  "container_title": "Nature Communications", 
  "title": "Data Supporting: \"Economic Damages from Hurricane Sandy Attributable to Sea Level Rise Caused by Anthropogenic Climate Change\"", 
  "issued": {
    "date-parts": [
  "abstract": "<p>Code supporting Strauss et al. (2020) submitted to Nature Communications. If you use any original data from this archive, please cite the&nbsp;study as:</p>\n\n<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:\u00a0Economic Damages from Hurricane Sandy Attributable to Sea Level Rise Caused by Anthropogenic Climate Change. Nature Communications. (under review, Dec. 2020)</code></pre>\n\n<p>If you have any questions or comments, please contact Daniel Gilford at</p>\n\n<p>Included are Input, Output, and Source&nbsp;files (compressed) used in the publication; data files are primarily in <strong>txt</strong>, <strong>csv</strong>,&nbsp;<strong>xlsx</strong>,&nbsp;and <strong>mat</strong>&nbsp;formats. In the absence of a MATLAB license,&nbsp;<strong>mat</strong>&nbsp;files may be read with open access software such as <a href=\"\">SciPy</a>.&nbsp;Code supporting this publication may be found at&nbsp;<a href=\"\"></a>.</p>\n\n<p><em>Archived Data Short&nbsp;Descriptions:</em></p>\n\n<ul>\n\t<li><strong>INPUT</strong> -- Input semi-empirical model and observational data files used to create distributions forming the backbone of the analyses in this study.\n\n\t<ul>\n\t\t<li><strong>8518750_meantrend.csv</strong>: The Battery, NY monthly mean sea levels and trends/uncertainty, accessed from&nbsp; on&nbsp;29 July 2020.</li>\n\t\t<li><strong></strong>: CMIP5 semi-empirical model analyses for each individual model and scenarios (historical and counterfactual), and index files for reference.</li>\n\t\t<li><strong></strong>: HadCRUT4&nbsp;semi-empirical model analyses for each individual HadCRUT4 scenario (historical and counterfactuals)</li>\n\t\t<li><strong>Dangendorf2019_GMSL.txt</strong>: Monthly mean global mean sea level rise from <a href=\"\">Dangendorf et al. (2019)</a>.</li>\n\t</ul>\n\t</li>\n\t<li><strong>OUTPUT</strong>&nbsp;-- Output analyses supporting this publication\n\t<ul>\n\t\t<li><strong>fig1_data.mat</strong>: Quick access source data file which may be used to recreate Fig. 1 in the manuscript</li>\n\t\t<li><strong>SEanalysis.mat</strong>: The full output semi-empirical model analyses in this study</li>\n\t\t<li><strong>summary_samps.mat</strong>: Summary/ensemble analyses in this study</li>\n\t</ul>\n\t</li>\n\t<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.\n\t<ul>\n\t\t<li>Included is a <strong>readme.txt</strong>&nbsp;with full file descriptions.</li>\n\t</ul>\n\t</li>\n</ul>", 
  "author": [
      "family": "Daniel M Gilford"
      "family": "Klaus Bittermann"
      "family": "Robert Kopp"
      "family": "Ben Strauss"
      "family": "Scott Kulp"
  "version": "1.0", 
  "type": "dataset", 
  "id": "4289245"
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