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Abstract

Over the last few decades, sea level rise due to global warming has become a global issue, with polar and coastal regions being the most vulnerable. This study will focus on polar regions as they have a significant impact on the global climate and ecosystem. Sea level height is traditionally observed using in-situ tide gauges and satellite altimetry. However, both methods face challenges in polar regions. Tide gauges are difficult to set up and maintain, and satellite altimetry is limited by the design of its orbital inclination. To overcome these difficulties, Global Navigation Satellite System Reflectometry (GNSS-R) is adopted to monitor sea level and sea ice changes in polar regions. A sea ice detection algorithm will be developed to avoid the contamination for sea level measurements, and the impact of sea state bias error will also be taken into account to improve accuracy. On the other hand, this study will integrate multi-constellation and multi-frequency signal-to-noise ratio (SNR) data to enhance temporal resolution of GNSS-R retrievals. As the original design of GNSS continuous stations is for positioning applications, we will also analyze different signal processing methods to effectively extract reflected signals from SNR data and the accuracy will be verified using observations from nearby tide gauges or tidal models. Further analysis of the relationship between the climate indicators and the variations in the sea level and sea ice will be conducted. Finally, this study will provide general recommendations for establishing GNSS-R stations in the polar regions.