Work

FDTransformer: A firn density prediction framework combining a self-attention transformer network with firn densification physics

Year: 2025

Type: article

Abstract: measurements from three Greenland sites (Dye-2, KAN_U, and Summit) with varying firn evolution patterns, the FDTransformer reduces mean absolute error by 30%, 42%, and 24%, respectively, compared to the physics-based FDMs. This study demonstrates that combining deep learning techniques with firn densification physics can improve firn density assessment.

Source: iScience

DOI: 10.1016/j.isci.2025.113869

Authors: Xueyu Zhang, Lin Liu, Houjun Jiang, Zhicai Luo

Institutions: Huazhong University of Science and Technology, Anhui Jianzhu University

Language: English

Topic: Cryospheric studies and observations

Subfield: Atmospheric Science

Field: Earth and Planetary Sciences

Domain: Physical Sciences

SDG: Climate action

Open Access status: gold

Estimated APC paid: $3,240