Dataset Open Access

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

Daniel M. Gilford; Scott Kulp; Klaus Bittermann; Maya K. Buchanan; Robert Kopp; Chris Massey; Hans de Moel; Philip Orton; Benjamin H. Strauss; Sergey Vinogradov

Code supporting Strauss et al. (2021) published in Nature Communications. If you use any original data from this archive, please cite the study as:

Strauss, B.H., Orton, P.M., Bittermann, K. et al. Economic damages from Hurricane Sandy attributable to sea level rise caused by anthropogenic climate change. Nat Commun 12, 2720 (2021). https://doi.org/10.1038/s41467-021-22838-1

If you have any questions or comments, please contact Daniel Gilford at dgilford@climatecentral.org

Included are Input, Output, and Source files (compressed) used in the publication; data files are primarily in txt, csvxlsx, and mat formats. In the absence of a MATLAB license, mat files may be read with open access software such as SciPy. Code supporting this publication may be found at https://github.com/climatecentral/cc_sandy_matlab.

Archived Data Short Descriptions:

  • INPUT -- Input semi-empirical model, hydrodynamic, and observational data files used to create distributions/analyses in this study.
    • 8518750_meantrend.csv: 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.
    • cmip5.zip: CMIP5 semi-empirical model analyses for each individual model and scenarios (historical and counterfactual), and index files for reference.
    • hadcrut.zip: HadCRUT4 semi-empirical model analyses for each individual HadCRUT4 scenario (historical and counterfactuals)
    • Dangendorf2019_GMSL.txt: Monthly mean global mean sea level rise from Dangendorf et al. (2019).
    • Also included are datum information, block damages (/damage/ directory), hydrodynamic simulations (/simulations_july_2016/ directory),  and additional auxiliary files required to run the accompanying repository analyses.
  • OUTPUT -- Code outputs supporting this publication
    • fig1_data.mat: Quick access source data file which may be used to recreate Fig. 1 in the manuscript
    • SEanalysis.mat: The full output semi-empirical model analyses in this study
    • summary_samps.mat: Summary/ensemble analyses in this study
  • SOURCE -- 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.
    • Included is a readme.txt with full descriptions of source data files.

We acknowledge funding from NSF grant ICER-1663807, NASA grant 80NSSC17K0698, 

v1.2.1 corrects Table S6 units/description in readme file (in SOURCE)
Files (6.0 GB)
Name Size
INPUT_v1.2.zip
md5:05e2fc2cadaac4029174662eb75ee67c
3.1 GB Download
OUTPUT.zip
md5:0b79259b46314457ef896a1dbc2183d7
2.4 GB Download
SOURCE.zip
md5:0fcab2a54685e8e25b480bfde3db8457
514.7 MB Download
  • Dangendorf, S., Hay, C., Calafat, F.M. et al. Persistent acceleration in global sea-level rise since the 1960s. Nat. Clim. Chang. 9, 705–710 (2019). https://doi.org/10.1038/s41558-019-0531-8

  • Kopp, Robert. (2013). Does the mid-Atlantic United States sea level acceleration hot spot reflect ocean dynamic variability?. Geophysical Research Letters. 40. 10.1002/grl.50781

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