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The Global Navigation Satellite System–Radio Occultation (GNSS–RO) technique, offering high vertical resolution (approximately 100 m), all weather capability, global coverage, and temporal stability, has long served as a critical data source for weather forecasting and climate monitoring. However, the domestically produced satellite systems enabling GNSS–RO have advanced slowly, highlighting the need for continued development of cutting-edge technologies. This study evaluates the data quality of GNSS–RO observations gathered by Y005 through Y060 satellites in the domestically developed, independently operated YunYao (Cloud-Remote) networked constellation. Multiple metrics were assessed, including observation coverage, signal-to-noise ratio characteristics, precise orbit determination accuracy, and the precision of retrieved atmospheric parameters. The analysis covers the period from March to May 2025, examining occultation events from four navigation constellations: Global Positioning System (GPS), GLONASS (Global Navigation Satellite System), BeiDou Navigation Satellite System (BDS), and Galileo. The key findings include: (1) The YunYao constellation demonstrates excellent SNR, with an average open-loop signal strength of 250 V/V which is comparable to leading international systems. (2) Uniform occultation distribution was achieved worldwide, with 1.545 million events recorded in May 2025 alone; BDS-based events accounted for the largest share at 39.6%. (3) Observation depth correlates strongly with latitude, with high-latitude Antarctic regions reaching all the way to the surface. (4) Achieved centimeter-level precision, with 3-D root-mean-square (RMS) orbit errors on the order of centimeters. (5) Retrieved atmospheric profiles closely match ERA5 reanalysis data in terms of refractivity, temperature, and pressure. This research provides a solid scientific foundation supporting the operational deployment of YunYao constellation data. Moving forward, high-quality occultation observations will be assimilated into numerical weather prediction models using meteorological data assimilation techniques, with the goal of reducing forecast bias.

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YunYao GNSS-RO Constellation Data Quality Control and Product Evaluation

  • 会议论文

  • 发表日期：

    2026年

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  • Fenghui Li,
  • Liang Kan,
  • Zhuoma Mana,
  • Jinxiao Li,
  • Manyi Huang,
  • Pengcheng Wang,
  • Yan Cheng,
  • Chunyang Liu,
  • Sai Xia,
  • Yan Xu,
  • Hao Lv

摘要

The Global Navigation Satellite System–Radio Occultation (GNSS–RO) technique, offering high vertical resolution (approximately 100 m), all weather capability, global coverage, and temporal stability, has long served as a critical data source for weather forecasting and climate monitoring. However, the domestically produced satellite systems enabling GNSS–RO have advanced slowly, highlighting the need for continued development of cutting-edge technologies. This study evaluates the data quality of GNSS–RO observations gathered by Y005 through Y060 satellites in the domestically developed, independently operated YunYao (Cloud-Remote) networked constellation. Multiple metrics were assessed, including observation coverage, signal-to-noise ratio characteristics, precise orbit determination accuracy, and the precision of retrieved atmospheric parameters. The analysis covers the period from March to May 2025, examining occultation events from four navigation constellations: Global Positioning System (GPS), GLONASS (Global Navigation Satellite System), BeiDou Navigation Satellite System (BDS), and Galileo. The key findings include: (1) The YunYao constellation demonstrates excellent SNR, with an average open-loop signal strength of 250 V/V which is comparable to leading international systems. (2) Uniform occultation distribution was achieved worldwide, with 1.545 million events recorded in May 2025 alone; BDS-based events accounted for the largest share at 39.6%. (3) Observation depth correlates strongly with latitude, with high-latitude Antarctic regions reaching all the way to the surface. (4) Achieved centimeter-level precision, with 3-D root-mean-square (RMS) orbit errors on the order of centimeters. (5) Retrieved atmospheric profiles closely match ERA5 reanalysis data in terms of refractivity, temperature, and pressure. This research provides a solid scientific foundation supporting the operational deployment of YunYao constellation data. Moving forward, high-quality occultation observations will be assimilated into numerical weather prediction models using meteorological data assimilation techniques, with the goal of reducing forecast bias.