Bias corrected era5 skin temperature over the Arctic sea ice – 1981 to 2018 monthly means and climatology

• Main Author: Zampieri, Lorenzo
• Format: Dataset
• Language: English
• Published: 2023
• Subjects: Sea ice; Arctic; Reanalysis; Numerical weather predictions; Era5; bias correction; Machine Learning; Mogensen
• Online Access: https://zenodo.org/record/8338265; https://doi.org/10.5281/zenodo.8338265

This dataset is generated in the context of the peer-reviewed study of Zampieri et al., 2023. The users can find a detailed description of the bias correction strategy and information on the scientific value of the dataset in the paper. Please, do not hesitate to contact me to obtain further information and suggestions on how to employ this dataset for your specific purpose. References: Zampieri, L., Arduini, G., Holland, M., Keeley, S., Mogensen, K., Shupe, M., Tietsche, S. (2023) A machine learning correction model of the winter clear-sky temperature bias over the Arctic sea ice in atmospheric reanalyses. Monthly Weather Review. DOI:10.1175/MWR-D-22-0130.1 Acknowledgments: As part of the Virtual Earth System Research Institute (VESRI), funding for the Multiscale Machine Learning In coupled Earth System Modeling (M2LInES) project was provided to Lorenzo Zampieri by the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program.