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121.
Sonia Pérez-Plaza Fernando Fernández-Palacín Manuel Berrocoso Raúl Páez Belén Rosado 《Mathematical Geosciences》2018,50(6):659-677
This paper demonstrates the usefulness of approaching the dynamic study of the precise positioning of a network of permanent global positioning system (GPS) stations through functional data analysis. The displacement data for each GPS station, obtained from observations of the global navigation satellite system, are a discrete sample of the positioning curve. The aim of this paper is to reconstruct the original functions in order to use them as functional data. In the method presented in this paper, the geodetic series are obtained first by processing the GPS data with respect to a reference station. Second, for each station, a cleaning process is applied to eliminate the values considered as outliers, and the missing values are imputed by using a Kalman filter. Finally, the original functions are reconstructed by using smoothing techniques and by evaluating several bases of functions. Moreover, these functions are treated with statistical techniques for functional data. This procedure is applied to the permanent stations of the south of the Iberian peninsula and the north of Africa (SPINA) network. The topocentric series: east, north and up are analysed. In the analysis of the positioning curves, there is observed a synchronized behaviour of the functions in those periods of time with important seismic activity. This behaviour also appears in the analysis of the second principal component of the East and up dimensions. Furthermore, the first two principal components of the East coordinate enable us to make a classification of the stations in the SPINA network. The classification made is consistent with the previous knowledge of the tectonic plates in the studied area. 相似文献
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It has been shown in various papers dealing with systems of colloding bodies in a Keplerian field that the dynamical evolution does not depend only on the initial orbital conditions. This is a consequence of the wide range of orbits generated by the collision process. From the study of a few pairs of orbits we examine what factors which produce that variety of orbits, and search for systematic effects. The role of the positions along the orbits, of inelasticity, of size, of mass and of relative inclination is emphasized. 相似文献
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Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We find a negative relationship between these controls that weakens the forecast skills, nevertheless there is a middle ground between both controls in several catchments, as shown by our results. 相似文献