There is a newer version of this record available.

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. (2020) submitted to Nature Communications. If you use any original data from this archive, please cite the study as:

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)

If you have any questions or comments, please contact Daniel Gilford at

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

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 on 29 July 2020.
    • CMIP5 semi-empirical model analyses for each individual model and scenarios (historical and counterfactual), and index files for reference.
    • 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 is a cleaned up version of v1.1.
Files (6.0 GB)
Name Size
3.1 GB Download
2.4 GB Download
514.9 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).

  • 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

All versions This version
Views 83133
Downloads 190
Data volume 40.2 GB0 Bytes
Unique views 37628
Unique downloads 160


Cite as