The Central segment of San Andreas Fault (CSAF) is characterized by a nearly continuous right‐lateral aseismic slip. However, observations of the creep rate obtained using small characteristically repeating earthquakes (CREs) show pulses of creep along the CSAF, which may indicate spatially and temporally variable seismic hazard along the CSAF. Therefore, the goal of this study is to obtain a high‐resolution time‐dependent model of creep along the CSAF to examine this hypothesis. To this end, we apply a time‐dependent creep modeling approach, which combines interferometric synthetic aperture radar (InSAR) surface deformation time series and observations of fault creep obtained from CREs. The SAR data set includes C band scenes acquired by the ERS‐2 and Envisat satellites between 2003 and 2011. The resulting creep rate distribution implies a peak rate up to 32 mm/yr along the central part of the CSAF. Afterslip due to the 2004 Parkfield earthquake on the southeastern segment of the CSAF is also manifest in the model, and there is clear evidence of creep pulsing along strike and depth of the CSAF. Estimated annual rate of slip deficit accumulation is equivalent to a magnitude 5.6–5.7 earthquake. Taking advantage of the time‐dependence of our model, we also refine the scaling relationship, which associates the released seismic moment due to a CRE event with the amount of creep on the fault, surrounding the CRE patches. This study provides the first kinematic model of creep pulsing, constrained using geodetic and seismic data, which can enhance time‐dependent seismic hazard maps and improve earthquake operational forecast models.

Recent seismic and geodetic observations indicate that interseismic creep rate varies in both time and space. The spatial extent of creep pinpoints locked asperities, while its temporary accelerations, known as slow-slip events, may trigger earthquakes. Although the conditions promoting fault creep are well-studied, the mechanisms for initiating episodic slow-slip events are enigmatic. Here we investigate surface deformation measured by radar interferometry along the central San Andreas Fault between 2003 and 2010 to constrain the temporal evolution of creep. We show that slow-slip events are ensembles of localized creep bursts that aseismically rupture isolated fault compartments. Using a rate and state friction model, we show that effective normal stress is temporally variable on the fault, and support this using seismic observations. We propose that, compaction-driven elevated pore fluid pressure in hydraulically isolated fault zone and subsequent frictional dilation cause the observed slow slip episodes. We further suggest that the 2004 M6 Parkfield earthquake might have been triggered by a slow-slip event, which increased the Coulomb failure stress by up to 0.45 bar per year. This implies that while creeping segments are suggested to act as seismic rupture barriers, slow-slip events on these zones might promote seismicity on adjacent locked segments.

Understanding the evolution of aseismic slip enables constraining the fault's seismic budget and provides insight into dynamics of creep. Inverting the time series of surface deformation measured along the Central San Andreas Fault obtained from interferometric synthetic aperture radar in combination with measurements of repeating earthquakes, we constrain the spatiotemporal distribution of creep during 1992–2010. We identify a new class of intermediate‐term creep rate variations that evolve over decadal scale, releasing stress on the accelerating zone and loading adjacent decelerating patches. We further show that in short‐term (<2 year period), creep avalanches, that is, isolated clusters of accelerated aseismic slip with velocities exceeding the long‐term rate, govern the dynamics of creep. The statistical properties of these avalanches suggest existence of elevated pore pressure in the fault zone, consistent with laboratory experiments.

Time Series SAR interferometry (InSAR) (TS-InSAR) has been widely applied to monitor the crustal deformation with centimeter-to millimeter-level accuracy. Phase unwrapping (PU) errors have proven to be one of the main sources of bias that hinder achieving such high accuracy. In this article, a new time series PU approach is developed to improve the unwrapping accuracy. The rationale behind the proposed method is to first improve the sparse unwrapping by mitigating the phase gradients in a 2-D network and then correcting the unwrapping errors in time, based on the triplet phase closure. Rather than the commonly used Delaunay network, we employ the all-pairs-shortest-path (APSP) algorithm from graph theory to maximize the temporal coherence of all edges and to approach the phase continuity assumption in the 2-D spatial domain. Next, we formulate the PU error correction in the 1-D temporal domain as compressed sensing (CS) problem, according to the sparsity of the remaining phase ambiguity cycles. We finally estimate phase ambiguity cycles by means of integer linear programming (ILP). The comprehensive comparisons using synthetic and real Sentinel-1 data covering Lost Hills, California, confirm the validity of the proposed 2-D + 1-D unwrapping approach and its superior performance compared to previous methods. Index Terms-All-pairs-shortest-path (APSP), compressed sensing (CS), graph theory, phase unwrapping (PU), SAR interferometry (InSAR), time series. I. INTRODUCTIONP HASE unwrapping (PU) is a key step in SAR interferometry (InSAR) time series processing for high-precision deformation monitoring. The aim of PU is to recover the proper ambiguity number of the 2π phase cycles from the Manuscript

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