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.

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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
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article

Impact of Sea-Ice Thickness and Permittivity on Polarimetric GNSS-Reflectometry Data Acquired During the MOSAiC Expedition

Ruibo Lei, Gunnar Spreen, Jie Zhang, Maximilian Semmling et al.
IEEE Transactions on Geoscience and Remote Sensing
Soil Moisture and Remote Sensing
article

Impact of Sea-Ice Thickness and Permittivity on Polarimetric GNSS-Reflectometry Data Acquired During the MOSAiC Expedition

Ruibo Lei, Gunnar Spreen, Jie Zhang, Maximilian Semmling, Junming Xia, Yue Xu, Baojian Liu, Yueqiang Sun, Wei Wan
article en

Abstract

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.

IEEE Transactions on Geoscience and Remote SensingVol. 63
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)
National Natural Science Foundation of China, Beijing Nova Program
Life below water
Openalex Percentile: Top 93%
Soil Moisture and Remote Sensing
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