Error analysis of continuous GPS position time series

A total of 954 continuous GPS position time series from 414 individual sites in nine different GPS solutions were analyzed for noise content using maximum likelihood estimation (MLE). The lengths of the series varied from around 16 months to over 10 years. MLE was used to analyze the data in two ways. In the first analysis the noise was assumed to be white noise only, a combination of white noise plus flicker noise, or a combination of white noise plus random walk noise. For the second analysis the spectral index and amplitude of the power law noise were estimated simultaneously with the white noise. In solutions where the sites were globally distributed, the noise can be best described by a combination of white noise plus flicker noise. Both noise components show latitude dependence in their amplitudes (higher at equatorial sites) together with a bias to larger values in the Southern Hemisphere. In the regional solutions, where a spatially correlated (common mode) signal has been removed, the noise is significantly lower. The spectral index of the power law in regional solutions is more varied than in the global solutions and probably reflects a mixture of local effects. A significant reduction in noise can be seen since the first continuous GPS networks began recording in the early 1990s. A comparison of the noise amplitudes to the different monument types in the Southern California Integrated GPS Network suggests that the deep drill braced monument is preferred for maximum stability

Daily snow depth measurements from 195 stations in the United States

This document describes a database containing daily measurements of snow depth at 195 National Weather Service (NWS) first-order climatological stations in the United States. The data have been assembled and made available by the National Climatic Data Center (NCDC) in Asheville, North Carolina. The 195 stations encompass 388 unique sampling locations in 48 of the 50 states; no observations from Delaware or Hawaii are included in the database. Station selection criteria emphasized the quality and length of station records while seeking to provide a network with good geographic coverage. Snow depth at the 388 locations was measured once per day on ground open to the sky. The daily snow depth is the total depth of the snow on the ground at measurement time. The time period covered by the database is 1893--1992; however, not all station records encompass the complete period. While a station record ideally should contain daily data for at least the seven winter months (January through April and October through December), not all stations have complete records. Each logical record in the snow depth database contains one station`s daily data values for a period of one month, including data source, measurement, and quality flags

New approach to detect seismic surface waves in 1Hz-sampled GPS time series

Recently, co-seismic seismic source characterization based on GPS measurements has been completed in near- and far-field with remarkable results. However, the accuracy of the ground displacement measurement inferred from GPS phase residuals is still depending of the distribution of satellites in the sky. We test here a method, based on the double difference (DD) computations of Line of Sight (LOS), that allows detecting 3D co-seismic ground shaking. The DD method is a quasi-analytically free of most of intrinsic errors affecting GPS measurements. The seismic waves presented in this study produced DD amplitudes 4 and 7 times stronger than the background noise. The method is benchmarked using the GEONET GPS stations recording the Hokkaido Earthquake (2003 September 25th, Mw = 8.3)

Temperature Trends of the U.S. Historical Climatology Network Based on Satellite-Designated Land Use/Land Cover

The 1221 weather observation stations that compose the U.S. Historical Climatology Network were designated as either urban, suburban, or rural based on data from the Defense Meteorological Satellite Program Operational Linescan System (OLS)

Spatiotemporal Filtering Using Principal Component Analysis and Karhunen-Loeve Expansion Approaches for Regional GPS Network Analysis

Spatial filtering is an effective way to improve the precision of coordinate time series for regional GPS networks by reducing so-called common mode errors, thereby providing better resolution for detecting weak or transient deformation signals. The commonly used approach to regional filtering assumes that the common mode error is spatially uniform, which is a good approximation for networks of hundreds of kilometers extent, but breaks down as the spatial extent increases. A more rigorous approach should remove the assumption of spatially uniform distribution and let the data themselves reveal the spatial distribution of the common mode error. The principal component analysis (PCA) and the Karhunen-Loeve expansion (KLE) both decompose network time series into a set of temporally varying modes and their spatial responses. Therefore they provide a mathematical framework to perform spatiotemporal filtering.We apply the combination of PCA and KLE to daily station coordinate time series of the Southern California Integrated GPS Network (SCIGN) for the period 2000 to 2004. We demonstrate that spatially and temporally correlated common mode errors are the dominant error source in daily GPS solutions. The spatial characteristics of the common mode errors are close to uniform for all east, north, and vertical components, which implies a very long wavelength source for the common mode errors, compared to the spatial extent of the GPS network in southern California. Furthermore, the common mode errors exhibit temporally nonrandom patterns

Filling the Gap in Cascadia: The Emergence of Low‐Amplitude Long‐Term Slow Slip

Abstract Long‐term slow slip events have been observed at several subduction zones around the globe, where they play an integral part in strain release along megathrust faults. Nevertheless, evidence for long‐term slow slip has remained elusive in the Cascadia subduction zone. Here we conduct a systematic analysis of 13 years of GNSS time series data from 2006 to 2019 and present evidence of at least one low‐amplitude long‐term slow slip event on the Cascadia subduction zone, with the possibility of others that are less resolved. Starting in mid‐2012, a 1.5‐year transient is observed in southern Cascadia, with a group of coastal GNSS stations moving ∼2 mm to the west. The data are modeled as a Mw 6.4 slow slip event occurring at 15–35 km depth on the plate interface, just updip of previously recognized short‐term slow slip and tremor. The event shares many characteristics with similar long‐term transient events on the Nankai subduction zone. However, the total fault slip amplitude is an order‐of‐magnitude smaller in Cascadia when compared to large events elsewhere, making long‐term slow slip detection challenging in Cascadia. While there are other westward long‐duration transients in the refined data set, the surface displacements are below the level of the noise or are limited spatially to a few neighboring stations, making interpretation unclear