000004292 001__ 4292
000004292 005__ 20191113082823.0
000004292 037__ $$aCTALK-2019-0128
000004292 100__ $$aGobron, K.
000004292 245__ $$aSpatial Behavior of Time-Correlated Noise in the Position Time Series of 10,000 GPS Stations
000004292 260__ $$c2019
000004292 269__ $$c2019-12-13
000004292 520__ $$aObtaining reliable estimates about geophysical processes from GPS products requires considering time-correlated noise in position time series. For about two decades, the time dependence of noise has been actively investigated. The most common noise model consists of the combination of power-law processes with various spectral indexes, including white noise. However, the origin of such power-law time correlations in position time series remains unclear. Analyzing the spatial dependence of noise provides a way to investigate the causes of power-law processes but requires a dense GPS network. Here, we analyze the data products of 10 000 GPS stations processed by the Nevada Geodetic Laboratory (NGL). We first iteratively detected outliers and offsets using a modified multivariate Detection Identification and Adaptation (DIA) method. Then, we used the Non-Negative Least Squares Variance Component Estimation method (NNLS-VCE) to assess the white noise and correlated noise amplitudes for each component of each station, i.e., a total of 30 000 time series. Our analysis evidences a multi-scale spatial variability of noise for the three North, East, and Up components. In particular, short spatial variations (a few hundred kilometers) of power-law amplitudes across the USA and Europe might point to either the presence of non-modeled regional geophysical signals or the influence of regional networks in the observations.
000004292 594__ $$aNO
000004292 6531_ $$aGPS network
000004292 6531_ $$aWhite and colored noise
000004292 6531_ $$aSpatial variation of the noise
000004292 6531_ $$aUSA
000004292 6531_ $$aEurope
000004292 700__ $$ade Viron, O.
000004292 700__ $$aVan Camp, M.
000004292 700__ $$aDemoulin, A.
000004292 773__ $$tAGU Fall Meeting 2019, San Francisco
000004292 8560_ $$fmichel.vancamp@observatoire.be
000004292 906__ $$aContributed
000004292 980__ $$aCTALKCONT