pyslfp: Standardized Geographic and Physical Datasets for Sea Level Fingerprinting

This repository contains the standardized physical and geographic datasets required for the pyslfp Python library—a tool for computing self-consistent sea-level fingerprints and solving the sea-level equation on an elastic, rotating Earth. Glacial Isostatic Adjustment (GIA) Ice History ModelsIncludes global ice thickness, topography, and sea-level time-slices for the ICE-5G, ICE-6G (VM5a), and ICE-7G (VM7) models.Source: W.R. Peltier's Group, University of Toronto (https://www.atmosp.physics.utoronto.ca/~peltier/data.php). Elastic Load Love NumbersElastic Load Love numbers and tidal Love numbers calculated for the Preliminary Reference Earth Model (PREM; Dziewonski & Anderson, 1981).Methodology: These values were calculated using a spectral method implementation based on the method within: Al-Attar, D., & Tromp, J. (2014). "Sensitivity kernels for viscoelastic loading based on adjoint methods." Geophysical Journal International, 196(1), 34–77. Regional Geographic DatasetsStandardized shapefiles used for spatial masking and regional projections: Antarctic Basins: IMBIE2 drainage basins (Rignot et al., 2011). Greenland Basins: Mouginot drainage basins (Mouginot et al., 2019). Hydrological Basins: HydroBASINS Level 3 combined global river basins (Lehner & Grill, 2013). Oceanic Regions: IHO World Seas v3 (Marine Regions). Gloss Network locations: PSMSL (Permanent Service for Mean Sea Level). Tide Gauge Data. Holgate, S. J., et al. (2013). Usage:These datasets are designed to be managed by the pyslfp.downloader module. The library automatically fetches these files and stores them in a local data directory (typically ~/.pyslfp_data).