Regional Sea-level Budget from 1993-2016
DOI10.5281/zenodo.7385561Zenodo7385561MaRDI QIDQ6692434
Dataset published at Zenodo repository.
Author name not available (Why is that?)
Publication date: 1 December 2022
Copyright license: No records found.
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/. 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. This has no impact on the results of the manuscript, as the axis error occurred only when organising the files to be published. Please cite the appropriatepapers when using this data Please cite Regionalizing Sea-level Budget with Machine Learning Techniques when using this data set. However, most of the data heavily relies on previous work and data sets by many authors, so please acknowledge that work by citing the original sources of the data (which can be found in the main text of Regionalizing Sea-level Budget with Machine Learning Techniques). please check this carefully! 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) The code to generate this data and the manuscript figures can be found at https://github.com/carocamargo/SLB Corresponding author: carolina.camargo@nioz.nl
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