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The variometric approach (VA) can estimate the coseismic displacement in real time using epoch-differenced carrier phase observations recorded from a high-rate Global Navigation Satellite System (GNSS) receiver. However, significant drift errors exist in the VA-derived coseismic displacement. We present the Variometric-B2b approach, which augments the traditional VA with precise satellite orbit and clock corrections from the B2b signal of the third generation BeiDou Global Navigation Satellite System (BDS3). The effectiveness of our method was validated using GNSS observations from the 2021 Mw 7.4 Maduo earthquake. Our results indicated that the station velocities derived from the Variometric-B2b were slightly better than those of traditional VA when the same GNSS phases were processed. Using coseismic displacement from precise point positioning (PPP) as a reference, the root mean square errors (RMSEs) of Variometric-B2b for combined GPS/BDS3 (Var-B2bGC) were 0.16 cm, 0.21 cm, and 0.41 cm in the east, north, and up directions, respectively; these results outperformed 0.52 cm, 0.37 cm, and 1.00 cm for BDS3-only Variometric-B2b (Var-B2bC) and 0.72 cm, 0.71 cm, and 1.53 cm for GPS-only Variometric-B2b (Var-B2bG) in three directions. The RMSEs of Var-B2bGC are corrected by approximately 69%, 43%, and 59% with respect to Var-B2bC and 78%, 70%, and 73% with respect to Var-B2bG in the east, north, and up directions, respectively. For the fault rupture process inversion, the main fracture characteristics of the earthquake could be clearly identified from the rupture models inverted with both Var-B2bGC and Var-B2bC coseismic displacements. [ABSTRACT FROM AUTHOR]

Retrieving the coseismic displacement in real time is essential when the high-rate Global Navigation Satellite System (GNSS) is used for the real-time earthquake source description. In 2020, the third generation of the BeiDou Global Navigation Satellite System (BDS-3) initiated a real-time precise point positioning service through the B2b signal (PPP-B2b), which provides a new possibility for real-time earthquake source description. In this study, the performance of the PPP-B2b on the real-time retrieval of coseismic displacement was first validated with GNSS observations collected during the 2021 Mw 7.4 Maduo earthquake. Then, the warning magnitude, focal mechanism and fault slip distribution were inverted with the derived PPP-B2b displacement in a simulated real-time model. Our results indicate that the accuracies of the coseismic displacements in the north, east and up components are 0.8 cm, 0.5 cm, and 1.4 cm for the single GPS PPP-B2b, 0.5 cm, 0.6 cm, and 0.9 cm for the single BDS-3 PPP-B2b and 0.4 cm, 0.3 cm, and 0.4 cm for the combined GPS/BDS-3 PPP-B2b, respectively, when compared with the coseismic displacements of the post-processing precise point positioning (PPP). Moreover, the warning magnitude, focal mechanism and fault slip distribution inverted with the PPP-B2b displacements are all in good agreement with those inverted with the PPP displacements. This study highlights the great possibility of the PPP-B2b to be used for earthquake early warning and rapid emergency responses. [ABSTRACT FROM AUTHOR]

The weighted mean temperature (Tm) is a function of atmospheric temperature and vertical humidity profiles. It plays a crucial role in the progress of retrieving water vapor information from the tropospheric delay of GNSS signals. The Tm estimated by the empirical models is always used to convert the zenith wet delay (ZWD) to precipitable water vapor (PWV) in GNSS meteorology. However, these empirical Tm models used trigonometric functions, making it difficult to describe Tm in detail and leading to an obvious accuracy difference with latitude changes. Thus, a global latitude zone augmentation mode was adopted for the empirical Tm models; the augmentation coefficients for each latitude zone were obtained by introducing the measured surface temperature and using the least-squares method. Using the Tm data of 2011–2015 derived from radiosonde, the GPT3 model, UNB3m model, and GWTMD model were augmented and analyzed. The results show that all augmentation models can improve the accuracy of the estimated Tm compared with their corresponding original models, and their levels of improvement are different. The three augmentation models achieved an average RMSE of 2.79 K, 3.47 K, and 3.22 K, which correspond to 22%, 49%, and 8% improvement against the GPT3 model, UNB3m model, and GWTMD model. In addition, the comparisons with the Tm linear formula were carried out and showed the superiority of the augmentation models. [ABSTRACT FROM AUTHOR]