Impact of Sea-Ice Thickness and Permittivity on Polarimetric GNSS-Reflectometry Data Acquired During the MOSAiC Expedition
Global Navigation Satellite System Reflectometry (GNSS-R) has long been explored for retrieving sea ice properties, but in-situ validation in the central Arctic during the freezing season is rare, limiting its application. The primary objective of this study is to advance the current understanding of multi-polarization GNSS-R remote sensing for sea ice application. This paper presents observations from the full-polarization GNSS-R(FpolGNSSR) prototype during the MOSAiC expedition. The FpolGNSSR, with four polarization channels and high antenna gain (11.3 dB), aims to assess the impact of sea-ice thickness and permittivity on GNSS-R data, with observations from October 2019 to January 2020, the onset period of ice growth. First, the reflectivity is simulated by a four-layer model, and the sensitivity of multi-polarization GNSS-R to sea ice is qualitatively analyzed. Subsequently, a simplified model reveals a linear relationship between reflectivity and ice thickness, with regression showing a correlation of 0.74 (P<0.01). The retrieval error (RMSE) of sea ice thickness retrieval is 0.13 m for first-year ice (0.3–1.0 m thick). Additionally, the imaginary component of sea ice permittivity is estimated, between 0.018 and 0.039. This study provides valuable insights for the GNSS-R community, which could be summarized as: (1) the “H-polarization advantage”, which is first proposed in sea ice GNSS-R, (2) the validity of a simplified model, reinforcing the feasibility of satellite-based sea ice thickness estimations using Left-hand-circular, V, and H polarizations, and (3) a lower apparent permittivity of GNSS-R than previously reported, corresponding to a deeper penetration depth.
Authors
- Ruibo Lei (ORCID: https://orcid.org/0000-0001-8525-8622)
- Gunnar Spreen (ORCID: https://orcid.org/0000-0003-0165-8448)
- Jie Zhang (ORCID: https://orcid.org/0000-0001-7821-4808)
- Maximilian Semmling (ORCID: https://orcid.org/0000-0002-5228-8072)
- Junming Xia (ORCID: https://orcid.org/0000-0002-3876-1708)
- Yue Xu (ORCID: https://orcid.org/0000-0003-4205-5109)
- Baojian Liu (ORCID: https://orcid.org/0000-0002-2390-2889)
- Yueqiang Sun
- Wei Wan (ORCID: https://orcid.org/0000-0002-7925-1210)
Institutions
- Polar Research Institute of China (CN)
- University of Bremen (DE)
- Chinese Academy of Sciences (CN)
- Peking University (CN)
- Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE)
- Beijing Forestry University (CN)
- National Space Science Center (CN)
Publication Details
- Journal
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tgrs.2025.3558804
- Primary Topic
- Soil Moisture and Remote Sensing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Beijing Nova Program