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Description
With the aim of using machine learning as a tool to predict and understand sea-ice motion in the Arctic on one-day timescales, these data include processed satellite and reanalysis measurements of sea-ice velocity, sea-ice concentration, and wind velocity. Also included are outputs from statistical model predictions. Finally, we include all files required to download and process raw data, run statistical models, and plot analyses of outputs. Outputs from machine learning models were funded by Office of Naval Research grant N00014-20-1-2772. Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp) Hoffman, Lauren; Mazloff, Matthew R.; Gille, Sarah T.; Giglio, Donata; Bitz, Cecilia M.; Heimbach, Patrick; Matsuyoshi, Kayli. (2023). Data From: Machine learning for daily forecasts of Arctic sea-ice motion: an attribution assessment of model predictive skill. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0X06774
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