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GPS-based Zenith Tropospheric Delay (ZTD) estimation should be easily obtained in a cost-effective way, however, the most previous studies focus on post-processed ZTD estimates using satellite orbit and clock products with at least 3–9 hours latency provided by International GNSS Service (IGS), which limits the GNSS meteorological application for nowcasting. With the development of IGS’s real-time pilot project (RTPP), this limitation was removed by April, 2013 as real-time satellite orbit and clock products can be obtained on-line. In this paper, on the one hand, the GPS-derived ZTD estimation was evaluated using the IGS final and real-time satellite products based on independently developed PPP software. On the other hand, the analysis of the time series of GPS-derived ZTD by least-square fitting of a broken line tendency for a full year of observations, and a forecasting method for precipitation is proposed based on the ZTD slope in the ascending period. The agreement between ZTD slope and the ground rainfall records suggested that the proposed method is useful for the assisted forecasting, especially for short-term alarms.

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High-rate GNSS positioning has been widely investigated and applied in science and engineering. We extend it to high-rate attitude determination under a multi-GNSS constellation. A series of experiments of high-rate GNSS attitude determination has been conducted on a platform with three 50 Hz geodetic receivers and two high-grade inertial measurement units (IMU). The high-rate attitude solutions are computed for each of the multi-GNSS systems and the combined constellation by either using short baselines with correct ambiguity resolution or precise point positioning (PPP) and compared with the IMU measurements. In the case of a single GNSS system, the experimental results have shown that GPS is of the best accuracy, followed by GLONASS. The results with Beidou are the noisiest. The combined multi-GNSS constellation can significantly improve the high-rate attitude solutions from any single GNSS system alone, which is, in particular, most suitable for applications to any platform in slow or quasi-static motion. However, the improvement rate could depend on proper weightings of measurements from different GNSS systems in the dynamical experiments. The accuracy of baseline-based high-rate GNSS attitude solutions remains stable over time, while that of PPP-based solutions substantially degrades with time, as theoretically expected. Within a short period of time, the PPP-based high-rate yaw solutions with the combined multi-GNSS constellation are comparable in accuracy with those computed from baselines with correct ambiguity resolution in the dynamical experiments. The attitude results from either static or dynamical experiments have shown that high-rate GNSS attitude determination is sufficiently precise to measure rotatory motions. GNSS rotational seismology is applied to the 2011 Tohoku Mw9.0 earthquake, illustrating the potential of multi-GNSS to precisely detect seismic rotatory motions.

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Standardized precipitation evapotranspiration index (SPEI) is an acknowledged drought monitoring index, and the evapotranspiration (ET) used to calculated SPEI is obtained based on the Thornthwaite (TH) model. However, the SPEI calculated based on the TH model is overestimated globally, whereas the more accurate ET derived from the Penman–Monteith (PM) model recommended by the Food and Agriculture Organization of the United Nations is unavailable due to the lack of a large amount of meteorological data at most places. Therefore, how to improve the accuracy of ET calculated by the TH model becomes the focus of this study. Here, a revised TH (RTH) model is proposed using the temperature (T) and precipitable water vapor (PWV) data. The T and PWV data are derived from the reanalysis data and the global navigation satellite system (GNSS) observation, respectively. The initial value of ET for the RTH model is calculated based on the TH model, and the time series of ET residual between the TH and PM models is then obtained. Analyzed results reveal that ET residual is highly correlated with PWV and T, and the correlate coefficient between PWV and ET is −0.66, while that between T and ET for cases of T larger or less than 0 °C are −0.54 and 0.59, respectively. Therefore, a linear model between ET residual and PWV/T is established, and the ET value of the RTH model can be obtained by combining the TH-derived ET and estimated ET residual. Finally, the SPEI calculated based on the RTH model can be obtained and compared with that derived using PM and TH models. Result in the Loess Plateau (LP) region reveals the good performance of the RTH-based SPEI when compared with the TH-based SPEI over the period of 1979–2016. A case analysis in April 2013 over the LP region also indicates the superiority of the RTH-based SPEI at 88 meteorological and 31 GNSS stations when the PM-based SPEI is considered as the reference.