Accuracy Evaluation and Analysis of GNSS Tropospheric Delay Inversion from Meteorological Reanalysis Data

Abstract

Accurate estimation of tropospheric delay is significant for global navigation satellite system’s (GNSS) high-precision navigation and positioning. However, due to the random and contingent changes in weather conditions and water vapor factors, the classical tropospheric delay model cannot accurately reflect changes in tropospheric delay. In recent years, with the development of meteorological observation/detection and numerical weather prediction (NWP) technology, the accuracy and resolution of meteorological reanalysis data have been effectively improved, providing a new solution for the inversion and modeling of regional or global tropospheric delays. Here, we evaluate the consistency and accuracy of three different types of reanalysis data (i.e., ERA5, MERRA2, and CRA40) used to invert the zenith tropospheric delay (ZTD) from 436 international GNSS service (IGS) stations in 2020, based on the integral method. The results show that the ZTD inversion of the three types of reanalysis data was consistent with the IGS ZTD, even in heavy rain conditions. Furthermore, the average precision of the ZTD inversion of the ERA5 reanalysis data was higher, where the mean deviation (bias), mean absolute error (MAE), and root mean square (RMS) were –3.39, 9.69, and 12.55 mm, respectively. The ZTD average precisions of the MERRA2 and CRA40 inversions were comparable, showing slightly worse performance than the ERA5. In addition, we further analyzed the global distribution characteristics of the ZTD errors inverted from the reanalysis data. The results show that ZTD errors inverted from the reanalysis data were highly correlated with station latitude and climate type, and they were mainly concentrated in the tropical climate zone at low latitudes. Compared to dividing error areas by latitude, dividing error areas by climatic category could better reflect the global distribution of errors and would also provide a data reference for the establishment of tropospheric delay models considering climate type.

ZPD Retrieval Performances of the First Operational Ship-Based Network of GNSS Receivers over the North-West Mediterranean Sea

“…A validation analysis, using as reference the ZPD values provided by a numerical weather reanalysis model, was conducted for the full 3-year dataset period. This approach partly recalls other previously developed works, such as [28], that involve comparison between ZPD computed with data from a set of globally distributed ground GNSS stations and with numerical weather prediction reanalysis, respectively. The important original contribution of the present work is that the proposed system is operational and was for the first time validated at sea.…”

A Hybrid Deep Learning Algorithm for Tropospheric Zenith Wet Delay Modeling with the Spatiotemporal Variation Considered

“…Tropospheric delay is greatly affected by location, season, and other factors. Current research focuses on improving the performance of ZWD models in low-latitude tropical regions [31]. However, the algorithm's structural characteristics and the adaptability of the atmospheric spatiotemporal characteristics are not considered in most studies.…”

Enhancing Atmospheric Monitoring Capabilities: A Comparison of Low- and High-Cost GNSS Networks for Tropospheric Estimations

“…This greatly improves our understanding of the troposphere's spatial and temporal variations [1]. Current GNSS networks, such as the International GNSS Service (IGS) [2] and the EUREF Permanent Network (EPN) [3], support various scientific efforts, such as the maintenance of reference systems [4] and the monitoring of atmospheric delays [1]. However, achieving a higher density of stations, which is required to estimate more detailed atmospheric dynamics, is constrained by significant financial barriers.…”