Estimation and evaluation of real-time precipitable water vapor from GLONASS and GPS

Abstract

Abstract:The revitalized Russian GLONASS system provides new potential for real-time retrieval of zenith tropospheric delays (ZTD) and precipitable water vapor (PWV) in order to support time-critical meteorological applications such as nowcasting or severe weather event monitoring. In this study, we develop a method of real-time ZTD/PWV retrieval based on GLONASS and/or GPS observations. The performance of ZTD and PWV derived from GLONASS data using real-time precise point positioning (PPP) technique is carefully investigated and evaluated. The potential of combining GLONASS and GPS data for ZTD/PWV retrieving is assessed as well. The GLONASS and GPS observations of about half a year for 80 globally distributed stations from the IGS (International GNSS Service) network are processed. The results show that the real-time GLONASS ZTD series agree quite well with the GPS ZTD series in general: the RMS of ZTD differences are about 8 mm (about 1.2 mm in PWV). Furthermore, for an inter-technique validation, the real-time ZTD estimated from GLONASS-only, GPS-only, and the GPS/GLONASS combined solutions are compared with those derived from Very Long Baseline Interferometry (VLBI) at co-located GNSS/VLBI stations. The comparison shows that GLONASS can contribute to real-time meteorological applications, with almost the same accuracy as GPS. More accurate and reliable water vapor values, about 1.5-2.3 mm in PWV, can be achieved when GLONASS observations are combined with the GPS ones in the real-time PPP data processing. The comparison with radiosonde data further confirms the performance of GLONASS-derived real-time PWV and the benefit of adding GLONASS to stand-alone GPS processing.

Comprehensive assessment of positioning and zenith delay retrieval using GPS+Glonass precise point positioning

“…The averaged ZTD accuracy was 7.8 mm for GPS-only, 8.1 mm for GLONASS-only, and 7.7 mm for GPS+GLONASS. No obvious biases between GPS-and GLONASSonly PPP-derived ZTD were observed, which were also confirmed by Lu et al (2016) and Dousa and Vaclavovic (2016). Unlike positioning, we found that the ZTD accuracy improved by adding GLONASS observations is not obvious.…”

“…With the model updated (from igs05.atx to igs08.atx), Dousa and Vaclavovic (2016) found that the ZTD biases between GPS and GLONASS did not exist any longer. More recently, Lu et al (2016) analyzed the ZTD derived from GPS-, GLONASS-only, and the combined GPS+GLONASS solutions in a simulated real-time mode and suggested that the ZTD estimates derived from GPS-, GLONASS-only, and the combined GPS+GLONASS solutions agree well with each other.…”

Precipitable Water Vapor Retrieval and Analysis by Multiple Data Sources: Ground-Based GNSS, Radio Occultation, Radiosonde, Microwave Satellite, and NWP Reanalysis Data

“…But the radiosonde has been thought to be a useful reference tool for atmospheric sounding [10]. In contrast, the ground-based GNSS technique has several advantages: it has been recognized as an efficient approach to estimate PWV change situations in nearly real time, and it can keep tracking and sensing continuously [11][12][13][14][15][16]. However, GNSS stations, for example, IGS stations, still have low spatial resolution, especially in the ocean area.…”

Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island

“…Since Bevis et al (1992) [5] first proposed Global Positioning System (GPS) meteorology to remote sensing atmospheric water vapor, GPS meteorology has become an important approach for water vapor detection with high accuracy, all-weather capability, high spatial temporal resolution, and low costs [6][7][8]. With the rapid development of the current global navigation satellite systems (GNSS) constellation, GNSS meteorology has the potential to provide precise PW values with high temporal resolution and is indeed widely used in many meteorological applications, such as numerical weather prediction, water vapor tomography, nowcasting, and severe weather event monitoring [9][10][11][12][13][14][15]. Moreover, water vapor not only contributes significantly to the opacity of the atmosphere in the infrared wavelengths as a greenhouse gas but is also the dominant source of phase fluctuations in radio sciences [16,17].…”