由 张 云飞 From GNSS Zenith Tropospheric Delay to Precipitable Water Vapor: Accuracy Assessment Using In-Situ and Reanalysis Meteorological Data Over China
基于原位与再分析气象数据的中国地区GNSS天顶对流层延迟至可降水汽转换精度评估
引文格式 | Citation:
Wang H, Yang F, Zheng J, et al. From GNSS Zenith Tropospheric Delay to Precipitable Water Vapor: Accuracy Assessment Using In-Situ and Reanalysis Meteorological Data Over China[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2025, 18: 14582-14593.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing （中科院2区，IF：5.3）
Atmosphericreanalysisdata
NOAA
precipitable water vapor (PWV)
zenith tropospheric delay (ZTD)
NOAA
precipitable water vapor (PWV)
zenith tropospheric delay (ZTD)
Abstract | 摘要
With the continuous development of Global Navigation Satellite System (GNSS) and the abundance of ground-based observation sites, the research and practice of GNSS water vapor retrieval are becoming increasingly prosperous. However, how to convert the zenith tropospheric delay obtained from GNSS data processing into the precipitable water vapor (PWV) for stations without meteorological sensors is a key issue. In this study, five schemes using different meteorological data, including NOAA data, fifth-generation European Center for Medium-Range Weather Forecasts reanalysis (ERA5) pressure-level data, ERA5 single-level data, CRA40 pressure-level data, and CRA40 single-level data, were proposed to complete the above conversion. The numerical results give a comprehensive comparison between the performance of GNSS PWV conversion using colocated meteorological stations and reanalysis data. Moreover, the accuracy of PWV conversion using different types of reanalysis data has also been evaluated, especially the performance of CRA40 data, which has been assessed for the first time to the best of the authors’ knowledge. In addition, the analysis of the pressure level and the single level of the two reanalysis data used for PWV conversion is also conducted. Specifically, the average root-mean-square error were 1.745, 1.584, 1.535, 1.403, and 1.823 mm for the five schemes listed above, respectively. Their different performances in different geographical locations, seasons, months, and epochs have also been explored in detail.
随着全球导航卫星系统（GNSS）的持续发展与地基观测站点数量的增加，GNSS水汽反演的研究与实践日益蓬勃发展。然而，如何为未配备气象传感器的测站将GNSS数据处理获得的天顶对流层延迟转换为可降水量（PWV）仍是一个关键问题。本研究提出采用五种不同气象数据源的方案完成该转换，包括：NOAA数据、欧洲中期天气预报中心第五代再分析资料（ERA5）气压层数据、ERA5单层数据、CRA40气压层数据和CRA40单层数据。数值结果系统比较了采用同址气象站与再分析资料进行GNSS PWV转换的性能，并评估了不同类型再分析资料的PWV转换精度——特别是首次对CRA40数据的性能进行了评估。此外，还分析了两种再分析资料在气压层与单层数据用于PWV转换的表现。具体而言，上述五种方案的平均均方根误差分别为1.745、1.584、1.535、1.403和1.823毫米。研究还详细探讨了这些方案在不同地理位置、季节、月份和时段的性能差异。