Data for: Mapping the global distribution of lead and its isotopes in seawater with explainable machine learning

This repository contains the data for the article 'Mapping the global distribution of lead and its isotopes in seawater with explainable machine learning' by Olivelli et al., submitted to Earth System Science Data (https://doi.org/10.5194/essd-2025-17). The files included are as follows: Pb_climatology.nc and Pb_climatology.csv include the climatologies of Pb concentration, 206Pb/207Pb and 208Pb/207Pb in netcdf and csv format. The climatologies are obtained from the models developed and carefully described in the article and are gridded according to the World Ocean Database (WOD) 2018 grid. WOD_Pb_dataset-cleanedSOPbconc.csv is the dataset used for the development of the Pb concentration, 206Pb/207Pb and 208Pb/207Pb models. Ensemble_Pb-conc.csv, Ensemble_67Pb.csv and Ensemble_87Pb.csv contain all the predictions of the 100 model ensemble members for the Pb concentration, 206Pb/207Pb and 208Pb/207Pb models, respectively. They also include the coefficient of variations of each cell in the WOD grid calculated from the 100 individual ensemble predictions. Global-prediction_masked-df_no-coords.csv is the prediction dataset and is used to predict all values of Pb concentration, 206Pb/207Pb and 208Pb/207Pb. The associated code repository can be found at: https://github.com/OlivelliAri/Pb-ML_GEOTRACES. --- Version v4 includes smoothed fields of Pb concentration, 206Pb/207Pb, and 208Pb/207Pb in the Pb_climatology.nc file. Smoothing is applied using a 3 × 3 window (lat × lon). Version v3 includes the 'Global-prediction_masked-df_no-coords.csv' file. Version v2 includes changes in the structure of the 'Pb_climatology.nc' file to facilitate data visualization and processing.