Continuous Global Positioning System (GPS) networks record station position changes with millimeter‐level accuracy and have revealed transient deformations on various spatial and temporal scales. However, the transient deformation may not be easily identified from the position time series because of the large number of sites in a network, low signal‐to‐noise ratios (SNR) and correlated noise in space and time. Here we apply state estimation and principal component analysis to the daily GPS position time series measured in Alaska sites of the Plate Boundary Observatory network. Our algorithm detects a transient signal, whose maximum displacement is ∼9 mm in horizontal and ∼11 mm in vertical, that occurred at Akutan volcano during the first half of 2008. A simple Mogi source inversion suggests inflation at shallow depth (∼3.9 km) beneath the volcano. Although the detection was not easy because the signal was aseismic, non‐eruptive and weak (not apparent in raw daily time series), our detection method improves the SNR and therefore provides higher resolution for detecting the transient signal.

Recent studies have indicated that for the first time since 1950, intense geophysical activity is occurring at the Santorini volcano. Here, we present and discuss the surface deformation associated with this activity, spanning from January 2011 to February 2012. Analysis of satellite interferometry data was performed using two well‐established techniques, namely, Persistent Scatterer Interferometry (PSI) and Small Baseline Subset (SBAS), producing dense line‐of‐sight (LOS) ground deformation maps. The displacement field was compared with GPS observations from 10 continuous sites installed on Santorini. Results show a clear and large inflation signal, up to 150 mm/yr in the LOS direction, with a radial pattern outward from the center of the caldera. We model the deformation inferred from GPS and InSAR using a Mogi source located north of the Nea Kameni island, at a depth between 3.3 km and 6.3 km and with a volume change rate in the range of 12 million m3 to 24 million m3 per year. The latest InSAR and GPS data suggest that the intense geophysical activity has started to diminish since the end of February 2012.

Changes in groundwater levels cause water‐bearing basins to deform. Here we provide a detailed history of horizontal surface displacements in the San Gabriel Valley, California, which we show are highly correlated with the water level changes measured at a nearby well: correlation coefficient of 0.96 ± 0.01. We use the surface response from a one year period during which water level change in the nearby well was over 16 m, to monitor the deformations over a 14 year period from 1998 to 2011. The water level changes lead surface deformation by 21 days, but the significance of the offset is only weakly supported (p‐value = 0.129). The projection method can be used as a real‐time monitoring or detection system for deformation caused by a variety of mechanisms such as fluid injection and removal (groundwater development, oil production, carbon sequestration), and by seismic and volcanic activity.

Long Valley Caldera in eastern California is an active volcanic area and has shown continued unrest in the last three decades. We have monitored surface deformation from Global Positioning System (GPS) data by using a projection method that we call Targeted Projection Operator (TPO). TPO projects residual time series with secular rates and periodic terms removed onto a predefined spatial pattern. We used the 2009–2010 slow deflation as a target spatial pattern. The resulting TPO time series shows a detailed deformation history including the 2007–2009 inflation, the 2009–2010 deflation, and a recent inflation that started in late‐2011 and is continuing at the present time (November 2012). The recent inflation event is about four times faster than the previous 2007–2009 event. A Mogi source of the recent event is located beneath the resurgent dome at about 6.6 km depth at a rate of 0.009 km3/yr volume change. TPO is simple and fast and can provide a near real‐time continuous monitoring tool without directly looking at all the data from many GPS sites in this potentially eruptive volcanic system.

No abstract