Assimilating Summer Sea‐Ice Thickness Observations Improves Arctic Sea‐Ice Forecast

Abstract Accurate Arctic sea‐ice forecasting for the melt season is still a major challenge because of the lack of reliable pan‐Arctic summer sea‐ice thickness (SIT) data. A new summer CryoSat‐2 SIT observation data set based on an artificial intelligence algorithm may alleviate this situation. We a...

Full description

Saved in:
Bibliographic Details
Main Authors: Ruizhe Song, Longjiang Mu, Svetlana N. Loza, Frank Kauker, Xianyao Chen
Format: Article
Language:English
Published: Wiley 2024-07-01
Series:Geophysical Research Letters
Online Access:https://doi.org/10.1029/2024GL110405
Tags: Add Tag
No Tags, Be the first to tag this record!