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Although the statistical significances for the trends of integrated water vapor (IWV) are essential for a correct interpretation of climate change signals, obtaining accurate IWV trend estimates with realistic uncertainties remains a challenge. This study evaluates the feasibility of the IWV trends derived from the newly released fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) for climate change analysis in continental Europe. This is achieved by comparing the trends derived from in-situ ground-based Global Positioning System (GPS)’s daily IWV series from 1994 to 2019 at 109 stations. The realistic uncertainties and statistical significances of the IWV trends are evaluated with the time series analysis on their noise characteristics and proper noise models. Results show that autoregressive moving average ARMA(1,1) noise model is preferred rather than the commonly assumed white noise (WN) or first-order autoregressive AR(1) noise for about 68% of the ERA5 and GPS IWV series. An improper noise model would misevaluate the trend uncertainty of an IWV time series, compared with its specific preferred noise model. For example, ARMA(1,1) may misevaluate the standard deviations of their trend estimates (0.1–0.3 kg m−2 decade−1) by 10%. Nevertheless, ARMA(1,1) is recommended as the default noise model for the ERA5 and GPS IWV series. However, the preferred noise model for each ERA5 minus GPS (E-G) IWV series should be specifically determined, because the AR(1)-related models can result in an underestimation on its trend uncertainty by 90%. In contrast, power-law (PL) model can lead to an overestimation by up to nine times. The E-G IWV trends are within −0.2–0.4 kg m−2 decade−1, indicating that the ERA5 is a potential data source of IWV trends for climate change analysis in continental Europe. The ERA5 and GPS IWV trends are consistent in their magnitudes and geographical patterns, lower in Northwest Europe (0–0.4 kg m−2 decade−1) but higher around the Mediterranean Sea (0.6–1.4 kg m−2 decade−1).

The South Scotia Ridge Transform (SSRT) plate boundary between the Scotia and Antarctic plates experienced large strike-slip earthquakes on August 4, 2003 (M w 7.6) and November 17, 2013 (M w 7.8). These events have overlapping aftershock zones, which is unusual. A 36°–45° southward dipping fault zone ruptured with left-lateral displacements in each event along the northern margin of the South Orkney micro-continent near 60°S. Slip distributions for the two events are determined using teleseismic body and surface wave recordings along with constraints from GPS ground motion recordings at station BORC on Laurie Island (South Orkney Islands), just south of the SSRT. The aftershock distributions, high-frequency back-projections, and unconstrained body wave finite-fault inversions permit significant overlap of the 2003 and 2013 slip zones; however, the GPS static displacements resolve differences in the large-slip regions of the two ruptures. The 2013 earthquake sequence along the SSRT initiated with M w 6.1 (November 13) and M w 6.8 (November 16) foreshocks located ∼ 50 km west of the mainshock hypocenter, and had aftershocks extending ∼ 250 km eastward. The rupture spread primarily eastward at ∼ 2.5 km / s with a total rupture duration of about 120 s, with two distinct patches of large-slip located northwest and northeast of the South Orkney Islands. The rupture swept past BORC, with high-rate GPS (HRGPS) ground motion recordings capturing the time-varying slip history of the faulting. Traditional GPS data require that the largest-slip region of the shorter rupture in 2003 is located in the gap NNE of BORC between the two patches that ruptured in 2013. There appears to be some overlap of lower slip regions. The complementary slip distributions comprise a relatively uniform offset along this portion of the SSRT, which is one of the most seismically active regions of the entire Antarctic plate boundary.

Integer ambiguity resolution at a single station can be achieved by introducing predetermined uncalibrated phase delays (UPDs) into the float ambiguity estimates of precise point positioning (PPP). This integer resolution technique has the potential of leading to a PPP-RTK (Real-Time Kinematic) model where PPP provides rapid convergence to a reliable centimeter-level positioning accuracy based on an RTK reference network. Nonetheless, implementing this model is technically subject to how rapidly we can fix wide-lane ambiguities, stabilize narrow-lane UPD estimates, and achieve the first ambiguity-fixed solution. To investigate these issues, we used seven days of 1-Hz sampling GPS data at 91 stations across Europe. We find that at least 10 minutes of observations are required for most receiver types to reliably fix about 90% of wide-lane ambiguities corresponding to high elevations, and over 20 minutes to fix about 90% of those corresponding to low elevations. Moreover, several tens of minutes are usually required for a regional network before a narrow-lane UPD estimate stabilizes to an accuracy of far better than 0.1 cycles. Finally, for hourly data, ambiguity resolution can significantly improve the accuracy of epoch-wise position estimates from 13.7, 7.1 and 11.4 cm to 0.8, 0.9 and 2.5 cm for the East, North and Up components, respectively, but a few tens of minutes is required to achieve the first ambiguity-fixed solution. Therefore, from the timeliness aspect, our PPP-RTK model currently cannot satisfy the critical requirement of instantaneous precise positioning where ambiguity-fixed solutions have to be achieved within at most a few seconds. However, this model can still be potentially applied to some near-real-time remote sensing applications, such as the GPS meteorology.

CGPS coordinate time series analysis strategy was evaluated to determine highly accurate vertical station velocity estimates with realistic uncertainties. This strategy uses a combination of techniques to (1) obtain the most accurate parameter estimates of the station motion model, (2) infer the stochastic properties of the time series in order to compute more realistic error bounds for all parameter estimates, and (3) improve the understanding of apparent common systematic variations in the CGPS coordinate time series, which are believed to be of geophysical and/or technical origin. The strategy provided a pre-processing of the coordinate time series in which outliers and discontinuities were identified. Subsequent parameterization included a mean value, a constant rate, periodic terms with annual and semi-annual frequencies, and offset magnitudes for identified discontinuities. All parameters plus the magnitudes of different stochastic noise were determined using maximum likelihood estimation (MLE). Empirical orthogonal function (EOF) analysis was used to study both the temporal and spatial variability of the common modes determined by this technique. After outlining the CGPS coordinate time series analysis strategy this paper shows initial results for coordinate time series for a four year (2000–2003) period from a selection of CGPS stations in Europe that are part of the European Sea Level Service (ESEAS) CGPS network

Recently the concept of using dual-continuous GPS (dual-CGPS) stations for monitoring vertical land movements at tide gauge sites was proposed by a working group of the European Sea Level Observing System (EOSS). In this concept, one CGPS station is established at the tide gauge, in order to monitor the local vertical land movements, and a second CGPS station is established on stable rock, within a few kilometers of the tide gauge further inland. Since 1997, a network of CGPS stations has been established to monitor vertical land movements in the UK. For the dual-CGPS station concept, pairs formed by the CGPS stations at Newlyn tide gauge and Camborne and at Lowestoft tide gauge and Hemsby, have been analyzed over a time span of approximately 2.7 and 2.0 years respectively. It has been shown by numerous authors that temporal and spatial correlations in CGPS coordinate time series can introduce biases in the estimated station velocities and their uncertainties. By analyzing the coordinate time series of two CGPS stations close to each other, spatial correlations can be removed successfully by differencing and a cleaner, difference time series for each coordinate component can be obtained. In this paper, the observed coordinate time series of four CGPS stations have been used to produce synthetic coordinate time series of 6 years in length. Station velocities and their uncertainties have been derived for both observed and synthetic coordinate time series and compared in order to assess the capabilities of the dual-CGPS concept to better describe local and geophysical vertical land movements.