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 [email protected] Included are Input, Output, and Source files (compressed) used in the publication; data files are primarily in txt, csv, xlsx, 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,

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 [email protected] Included are Input, Output, and Source files (compressed) used in the publication; data files are primarily in txt, csv, xlsx, 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, hydrodynamic simulations, 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.

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 [email protected] Included are Input, Output, and Source files (compressed) used in the publication; data files are primarily in txt, csv, xlsx, 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,

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 [email protected] Included are Input, Output, and Source files (compressed) used in the publication; data files are primarily in txt, csv, xlsx, 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,