Bing-Rui Li

Multi-Source Deep-Learning Reconstruction of Monthly Arctic Sea Ice Thickness Constrained by Satellite and In Situ Observations

Monthly Arctic sea ice thickness (SIT) fields are needed for sea ice volume estimation and climate diagnostics, but continuous reconstruction remains challenging because in situ observations are sparse and satellite retrievals are uncertain. We present ArcticSIT-ReconNet, a multi-source deep-learning framework that com...