Data and Software supporting "Human-caused sea level rise drives 21st-century worldwide water level extremes"

This data (doi: 10.5281/zenodo.15446540) and software (doi: 10.5281/zenodo.18010948) supports the publication of Human-caused sea level rise drives 21st-century worldwide water level extremes at Science Advances in 2026. Please cite the study if you use any of this data: Gilford, D. M., Lin, Y., Dahl, K., Pershing, A., Kopp, R. E., & Strauss, B. Human-caused sea level rise drives 21st-century worldwide water level extremes. Science Advances, under review (submitted 2025). The creation of each data file is detailed in the associated Jupyter Notebooks and Python modules. Briefly, included are: [AIS/glac/GMSL/GrIS/regionalocean/steric/thermosteric/total_rsl_mean]_rel1900.nc --- Gridded sea level contributors since 1900 through 2018 cmip_[counterfactual/forcing]_runs.nc --- CMIP6 forcing and counterfactual semi-empirical model runs ewl_exceedances_at_gesla.nc --- Attributable and baseline extreme water level exceedances at quality-controlled GESLA stations over 1950-2018 EWL_thresholds.pkl --- Extreme water level exceedance thresholds defined statistically at each tide gauge filtered_stns_meta.csv --- Tide gauge station metadata after (minor) filtering GESLA_BudgetClosure.pkl --- Indices identifying tide gauge budget closure stations GESLA_QCScores.pkl --- Tide gauge station quality control scores saved_IMFs_relative_1957.nc --- Instrinsic mode functions from ensemble empirical modal decomposition defining the regional ocean residual (relative to 1957) SE_attribution_scaled_at_gesla.nc --- Attributable sea level rise from semi-empirical models at quality-controlled GESLA stations over 1900-2018 SEmodel_distributions.nc --- Raw semi-empirical model distributions SEmodel_gmst_[counterfactual/forcing].nc --- CMIP6 and ERA5 forcing and counterfactual temperatures driving semi-empirical model runs timevarying_ASLR_gridded.nc --- Gridded attributable sea level contributors since 1900 through 2018 Please direct any questions about this data to Daniel Gilford.