Supporting data: Seasonal predictability of sea ice and bottom temperature across the eastern Bering Sea shelf

• Main Authors: Kearney, Kelly (10222715), Alexander, Michael (10742833), Aydin, Kerim (10742836), Cheng, Wei (10742839), Hermann, Albert (10742842), Hervieux, Gaelle (10742845), Ortiz, Ivonne (10742848)
• Format: Dataset
• Language: unknown
• Published: 2021
• Subjects: Neuroscience; Physiology; Ecology; Immunology; Inorganic Chemistry; Astronomical and Space Sciences not elsewhere classified; Biological Sciences not elsewhere classified; Bering Sea; retrospective forecast; seasonal forecast; Sea ice
• Online Access: https://doi.org/10.5281/zenodo.4735496

This dataset includes the simulation output that supports the article, "Seasonal predictability of sea ice and bottom temperature across the eastern Bering Sea shelf", submitted to the Journal of Geophysical Reasearch: Oceans. All model simulations were run using the Bering10K ROMS model, an implementation of the Regional Ocean Modeling System (ROMS) tailored to the Bering Sea region. See manuscript for further details (to be linked here upon final publication). The dataset includes: B10K-NMME_CFS_monthlycomposite.nc: Monthly mean temperature and ice coverage output from the downscaled Climate Forecast System (CFS) retrospective forecast simulations. B10K-NMME_CanCM4_monthlycomposite.nc: Monthly mean temperature and ice coverage output from the downscaled Canadian Coupled Climate Model (CanCM4) retrospective forecast simulations. B10K-K20nobio_CFS_monthlycomposite.mat: Monthly mean temperature and ice coverage output from the CFS reanalysis-driven hindcast simulations Metrics (including anomaly correlation coefficient and significance tests) used within the study to quantify the simulation forecast skill.