Bai et al. (2025) Real-time atmospheric precipitable water retrieval performance evaluation based on satellite-based precise point positioning

Identification

• Journal: Advances in Space Research
• Year: 2025
• Date: 2025-11-20
• Authors: Yunpeng Bai, Huizhong Zhu, Chunhua Jiang
• DOI: 10.1016/j.asr.2025.11.047

Research Groups

School of Geomatics, Liaoning Technical University (LNTU), Fuxin, China

Short Summary

This study systematically evaluates the real-time Zenith Tropospheric Delay (ZTD) and Precipitable Water Vapor (PWV) retrieval performance of mainstream satellite-based precise point positioning (PPP) services (BDS-3 PPP-B2b, Galileo HAS, and QZSS MADOCA-PPP) using Multi-GNSS Experiment (MGEX) data, concluding that MADOCA-PPP offers the best overall real-time performance and meets numerical weather prediction (NWP) accuracy requirements.

Objective

• To systematically evaluate the product accuracy and real-time Zenith Tropospheric Delay (ZTD) and Precipitable Water Vapor (PWV) retrieval performance of current mainstream satellite-based precise point positioning (PPP) services: BDS-3 PPP-B2b, Galileo HAS, and QZSS MADOCA-PPP.

Study Configuration

• Spatial Scale: Global, utilizing Multi-GNSS Experiment (MGEX) stations, with specific analyses of regional variability (e.g., European core service area, stations within China, regions farther from China).
• Temporal Scale: Real-time evaluation over a period sufficient to assess annual mean statistics and seasonal variability (winter vs. summer performance).

Methodology and Data

• Models used: The study evaluates the performance of satellite-based precise point positioning (PPP) services: BDS-3 PPP-B2b, Galileo HAS, and QZSS MADOCA-PPP. It also references WUM post-processed products and CNES-ZTD for comparison.
• Data sources:
  • Observation data from Multi-GNSS Experiment (MGEX) stations.
  • Reference baselines: Tropospheric products released by IGS centers, radiosonde data, and ERA5 reanalysis.

Main Results

• There is no systematic bias between ZTD estimates from all evaluated services and the IGS reference values.
• The WUM post-processed product demonstrates the highest overall accuracy for both ZTD and PWV retrieval, with annual mean PWV standard deviations (STDs) of 1.71 mm and 2.36 mm (under two reference baselines) and bias values within ±0.30 mm.
• Among real-time ZTD products, MADOCA-ZTD shows the highest accuracy with a mean STD of 9.03 mm, followed by CNES-ZTD with a mean STD of 11.81 mm. HAS-ZTD is slightly less accurate than MADOCA-ZTD. B2b-ZTD achieves high precision at several stations within China but has the lowest overall accuracy due to limited service coverage.
• For real-time PWV retrieval, MADOCA-PPP exhibits the best overall performance, with annual mean STDs of 2.01 mm and 2.77 mm (under two reference baselines) and bias values within ±0.50 mm. Its correlation coefficient reaches approximately 0.95, maintaining high stability even under complex water vapor conditions.
• The Galileo HAS service performs stably within its European core service area, but its accuracy significantly decreases in non-nominal regions, showing noticeable negative biases in summer.
• BDS-3 PPP-B2b PWV (B2b-PWV) shows significant regional dependence, with high precision (STD values below 2 mm) at stations within China, but marked accuracy decline in regions farther from China.
• All real-time services achieve their highest accuracy in winter and largest errors in summer, demonstrating clear seasonal dependence and a pronounced influence from geographical location, station latitude, observation quality, and the accuracy of orbit and clock products.
• Current satellite-based PPP services are capable of obtaining high spatiotemporal resolution real-time precise ZTD/PWV under all-weather conditions, with the MADOCA-PPP service reaching the accuracy required for NWP.

Contributions

• Provides a systematic and comprehensive evaluation of the real-time ZTD and PWV retrieval performance of the three mainstream satellite-based PPP services (BDS-3 PPP-B2b, Galileo HAS, QZSS MADOCA-PPP) using global MGEX data.
• Reveals the performance characteristics of each service under diverse geographical and climatic conditions, including analyses of spatiotemporal consistency, seasonal, and regional variability.
• Demonstrates the capability of these free, real-time PPP services for high spatiotemporal resolution ZTD/PWV acquisition, specifically highlighting MADOCA-PPP's suitability for numerical weather prediction applications.

Funding

Not specified in the provided text.

Citation

@article{Bai2025Realtime,
  author = {Bai, Yunpeng and Zhu, Huizhong and Jiang, Chunhua},
  title = {Real-time atmospheric precipitable water retrieval performance evaluation based on satellite-based precise point positioning},
  journal = {Advances in Space Research},
  year = {2025},
  doi = {10.1016/j.asr.2025.11.047},
  url = {https://doi.org/10.1016/j.asr.2025.11.047}
}