余锐, 刘洋, 王清泉, 高建伟, 张郁, 胡羽丰. 长时序多模多频GNSS-IR潮位反演综合比较分析[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20240057
引用本文: 余锐, 刘洋, 王清泉, 高建伟, 张郁, 胡羽丰. 长时序多模多频GNSS-IR潮位反演综合比较分析[J]. 武汉大学学报 ( 信息科学版). DOI: 10.13203/j.whugis20240057
YU Rui, LIU Yang, WANG Qingquan, GAO Jianwei, ZHANG Yu, HU Yufeng. The Comprehensive Comparative Analysis of Long-Term, Multimode, and Multi-frequency GNSS-IR Tide Inversion[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240057
Citation: YU Rui, LIU Yang, WANG Qingquan, GAO Jianwei, ZHANG Yu, HU Yufeng. The Comprehensive Comparative Analysis of Long-Term, Multimode, and Multi-frequency GNSS-IR Tide Inversion[J]. Geomatics and Information Science of Wuhan University. DOI: 10.13203/j.whugis20240057

长时序多模多频GNSS-IR潮位反演综合比较分析

The Comprehensive Comparative Analysis of Long-Term, Multimode, and Multi-frequency GNSS-IR Tide Inversion

  • 摘要: 海平面变化对海岸生态环境和人类生存发展有着重要影响,对海平面进行监测是全球气候变化和海洋灾害监测的重要内容。本文利用 GNSS-IR 技术分析了四大卫星导航系统 11个频段的数据, 反演了中国香港 HKQT 和美国西雅图 SC02 测站 2018-2022 年长时序的潮位结果并进行了潮汐调和分析和长期变化趋势估计。 结果表明: 不同频段反演海面高的精度有所差异,经过海面动态误差改正后,精度在 10 cm 左右,不同接收机和不同环境会导致同一频段有不同的精度表现。海面动态改正能有效降低 GNSS-IR 潮位反演误差,以 ubRMSE 计平均精度提升了 20.5%。通过多模多频数据提高了海面高反演的时间分辨率,并在一定程度上提升了数据的精度和连续性。潮汐调和分析结果表明, 11 个频段的振幅结果能够与验潮站结果很好吻合,总体差异小于 1 cm。但是,部分频段部分潮汐项的相位结果存在较大差异,这与单一频率潮位反演结果的时间分辨率较低有关。长期趋势分析结果表明, 香港近海存在约 6.0 mm/a 的海平面上升,西雅图近海存在约-4.0 mm/a 的海平面下降,与验潮站结果吻合较好。本文结果不仅评估了多模多频 GNSS-IR 技术在监测海平面变化上的性能,而且揭示了海平面的长期变化趋势,这对于海洋灾害监测和海洋学研究具有一定的参考意义。

     

    Abstract: Objectives: Sea level changes have significant impacts on coastal ecosystems and human survival and development. Monitoring sea level is an essential part of global climate change and marine disaster surveillance. Methods: This study uses GNSS-IR technology to analyze data from 11 frequency bands across four major satellite navigation systems, inverting for long time series of tidal level results from 2018 to 2022 at the Hong Kong HKQT and Seattle SC02 stations, and performs tidal harmonic analysis and estimates long-term change trends. Results: The results indicate that the accuracy of sea level inversion varies among frequency bands. After correcting for dynamic sea level errors, the accuracy is around 10 cm. Different receivers and environments can lead to varying accuracy performances in the same frequency band. Dynamic sea level correction effectively reduces GNSS-IR sea level inversion errors, with an average precision improvement of 20.5% in terms of ubRMSE. Using multi-mode multi-frequency data has enhanced the temporal resolution of sea level inversion, and to some extent, improved the data's accuracy and continuity. Tidal harmonic analysis shows that the amplitude results across 11 frequency bands align well with the tide gauge results, with overall differences less than 1 cm. However, some frequency bands show significant phase discrepancies in certain tidal components, related to the lower temporal resolution of single-frequency sea level inversion results. Long-term trend analysis indicates a sea level rise of approximately 6.0 mm/year near Hong Kong and a sea level decline of about -4.0 mm/year near Seattle, which aligns well with tide gauge results. Conclusions: The findings of this paper not only assess the performance of multi-mode multi-frequency GNSS-IR technology in monitoring sea level changes but also reveal long-term trends in sea level, providing valuable references for marine disaster monitoring and oceanographic research.

     

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