Abstract. We use 2 decades of data from a dense geodetic network to extract regionally coherent velocities and deformation rates in France and neighboring western European countries. This analysis is combined with statistical tests on synthetic data to quantify the deformation detection thresholds and significance levels. By combining two distinct methods – Gaussian smoothing and k-means clustering – we extract horizontal deformations with a 95 % confidence level of ca. 0.1–0.2 mm yr−1 (ca. 0.5–1×10-9 yr−1) on spatial scales of 100–200 km or more. From these analyses, we show that the regionally average velocity and strain rate fields are statistically significant in most of our study area. The first-order deformation signal in France and neighboring western European countries is a belt of N–S to NE–SW shortening of ca. 0.2–0.4 mm yr−1 (1–2×10-9 yr−1) in central and eastern France. In addition to this large-scale signal, patterns of orogen-normal extension are observed in the Alps and the Pyrenees, but methodological biases, mainly related to GPS (Global Positioning System) solution combinations, limit the spatial resolution and preclude associations with specific geological structures. The patterns of deformation in western France show either tantalizing correlation (Brittany) or anticorrelation (Aquitaine Basin) with the seismicity. Overall, more detailed analyses are required to address the possible origin of these signals and the potential role of aseismic deformation.

Abstract. We use statistical analyses of synthetic position time series to estimate the potential precision of GPS (Global Positioning System) velocities. The synthetic series represent the standard range of noise, seasonal, and position offset characteristics, leaving aside extreme values. This analysis is combined with a new simple method for automatic offset detection that allows an automatic treatment of the massive dataset. Colored noise and the presence of offsets are the primary contributor to velocity variability. However, regression tree analyses show that the main factors controlling the velocity precision are first the duration of the series, second the presence of offsets, and third the noise level (dispersion and spectral index). Our analysis allows us to propose guidelines, which can be applied to actual GPS data, that constrain velocity precisions, characterized as a 95 % confidence limit of the velocity biases, based on simple parameters: (1) series durations over 8.0 years result in low-velocity biases in the horizontal (0.2 mm yr−1) and vertical (0.5 mm yr−1) components; (2) series durations of less than 4.5 years are not suitable for studies that require precisions lower than mm yr−1; (3) series of intermediate durations (4.5–8.0 years) are associated with an intermediate horizontal bias (0.6 mm yr−1) and a high vertical one (1.3 mm yr−1), unless they comprise no offset. Our results suggest that very long series durations (over 15–20 years) do not ensure a significantly lower bias compared to series of 8–10 years, due to the noise amplitude following a power-law dependency on the frequency. Thus, better characterizations of long-period GPS noise and pluri-annual environmental loads are critical to further improve GPS velocity precisions.