BUSCADOR RECOLECTA

Please note that the time series of the GRD component is flipped in the latitude axis (ordered South-North, instead of North-South as the other datasets). So before using, it should be flipped. -- This repository contains the following files: budget_components_ENS.nc Regional (1x1 degree) trend, uncertainty and time series of the ensemble mean of each of the budget components: total sea-level change (from altimetry) and the drivers (steric, GRD and dynamic). Please note that the time series of the GRD component is flipped in the latitude axis (ordered South-North, instead of North-South as the other datasets). So before using, it should be flipped. In order to avoid creating a new DOI for this dataset, we have added just a warning, instead of updating the file. If required the individual data sets used for the ensemble, please contact the author. -- masks.nc netcdf containing land-ocean mask, as well as the domains maps (SOM and delta-MAPS). We refer to the manuscript for more information of how the regional domains were acquired. -- dmaps_trend.pkl (and .xlsx) Trend and uncertainties of each of the budget components for each delta-MAPS domains. Available as an excel table (.xlsx) and as pickle file (.pkl). -- som_trend.pkl (and .xlsx). Trend and uncertainties of each of the budget components for each SOM domains. Available as an excel table (.xlsx) and as pickle file (.pkl), This repository contains supporting data for Camargo et al.: 'Regionalizing Sea-level Budget with Machine Learning Techniques', Ocean Sciences (2022), https://egusphere.copernicus.org/preprints/2022/egusphere-2022-876/., budget_components_ENS.nc, dmaps_trends.pkl, dmaps_trends.xlsx, masks.nc, SOM_trends.pkl, SOM_trends.xlsx, Peer reviewed

This repository contains the following files: budget_components_ENS.nc. Regional (1x1 degree) trend, uncertainty and time series of the ensemble mean of each of the budget components: total sea-level change (from altimetry) and the drivers (steric, GRD and dynamic). If required the individual data sets used for the ensemble, please contact the author. -- masks.nc: netcdf containing land-ocean mask, as well as the domains maps (SOM and delta-MAPS). We refer to the manuscript for more information of how the regional domains were acquired. -- dmaps_trend.pkl (and .xlsx): Trend and uncertainties of each of the budget components for each delta-MAPS domains. Available as an excel table (.xlsx) and as pickle file (.pkl). -- som_trend.pkl (and .xlsx): Trend and uncertainties of each of the budget components for each SOM domains. Available as an excel table (.xlsx) and as pickle file (.pkl), This repository contains supporting data for Camargo et al.: 'Regionalizing Sea-level Budget with Machine Learning Techniques', Ocean Sciences (2022, submited)., budget_components_ENS.nc, dmaps_trends.pkl, dmaps_trends.xlsx, masks.nc, SOM_trends.pkl, SOM_trends.xlsx, Peer reviewed