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We use GPS data to show synchronization between the 2011 and 2016 drought cycle in California, accelerated uplift of the Sierra Nevada Mountains, and enhanced magmatic inflation of the Long Valley Caldera (LVC) magmatic system. The drought period coincided with faster uplift rate, changes in gravity seen in the Gravity Recovery and Climate Experiment (GRACE), and changes in standardized relative climate dryness index. These observations together suggest that the Sierra Nevada elevation is sensitive to changes in hydrological loading conditions, which subsequently influences the LVC magmatic system. We use robust imaging of horizontal GPS velocities to derive time‐variable shear and dilatational strain rates in a region with highly variable station distribution. The results show that the highest strain rates are near the eastern margin of the Sierra Nevada and western edge of the Central Walker Lane (CWL) passing directly through LVC. The drought period saw geographic shifts in the distribution in active shear strain in the CWL more than 60 km from the LVC, delineating the minimum extent over which the active magmatic system affects the CWL tectonic environment. We analyze declustered seismicity data to show that locations with higher seismicity rates tend to be (1) areas with higher strain rates and (2) areas in which strain rates increased during drought‐enhanced inflation. We hypothesize that drought conditions reduce vertical surface mass loading, which decreases pressure at depth in the LVC system, in turn enhances magmatic inflation, and drives horizontal elastic stress changes that redistribute active CWL strain and modulate seismicity. We show that there were connections between the recent drought in California to changes in uplift rate of the Sierra Nevada, magmatic inflation at the Long Valley Caldera near Mammoth, CA, and earthquakes in the region. We use GPS, seismic, gravity, and climate data to show that the speed of uplift of the Sierra Nevada is sensitive to big changes in surface and groundwater (e.g., in snow, streams, lakes, and aquifers) and that these changes correlate with movements within the large volcano. A plausible explanation is that the weight of snow and water loads the surface and changes pressures deep in the Earth. As the Sierra Nevada was unloaded during recent drought, there was less pressure on the magmatic system, allowing fluids to rise or expand more easily. When that occurred, it provided an outward horizontal push on the crust, influencing small‐ to moderate‐sized earthquakes up to 60 km away. We show where and when these changes occurred and specific examples of earthquakes that may have been triggered by this inflation. Faster Sierra Nevada uplift during the 2011–2016 drought in California coincided with faster magmatic inflation at the Long Valley CalderaFaster magmatic inflation changed the rate and distribution of crustal strain in the Central Walker Lane, >60 km from Long ValleySeismicity patterns in the Central Walker Lane suggest that long‐term crustal strain may be driven in part by Long Valley magmatic inflation

After approximately 2 months of swarm‐like earthquakes in the Mogul neighborhood of west Reno, NV, seismicity rates and event magnitudes increased over several days culminating in an Mw4.9 dextral strike‐slip earthquake on 26 April 2008. Although very shallow, the Mw4.9 main shock had a different sense of slip than locally mapped dip‐slip surface faults. We relocate 7549 earthquakes, calculate 1082 focal mechanisms, and statistically cluster the relocated earthquake catalog to understand the character and interaction of active structures throughout the Mogul, NV earthquake sequence. Rapid temporary instrument deployment provides high‐resolution coverage of microseismicity, enabling a detailed analysis of swarm behavior and faulting geometry. Relocations reveal an internally clustered sequence in which foreshocks evolved on multiple structures surrounding the eventual main shock rupture. The relocated seismicity defines a fault‐fracture mesh and detailed fault structure from approximately 2–6 km depth on the previously unknown Mogul fault that may be an evolving incipient strike‐slip fault zone. The seismicity volume expands before the main shock, consistent with pore pressure diffusion, and the aftershock volume is much larger than is typical for an Mw4.9 earthquake. We group events into clusters using space‐time‐magnitude nearest‐neighbor distances between events and develop a cluster criterion through randomization of the relocated catalog. Identified clusters are largely main shock‐aftershock sequences, without evidence for migration, occurring within the diffuse background seismicity. The migration rate of the largest foreshock cluster and simultaneous background events is consistent with it having triggered, or having been triggered by, an aseismic slip event. Mapped complex spatiotemporal seismicity and fault patterns within a well‐recorded shallow urban earthquake swarmAdapted regional statistical clustering approach to objectively isolate space‐time substructures within an individual earthquake sequenceIdentified fault‐fracture mesh geometry and seismicity migration rates consistent with pore pressure changes related to fluid flow

Tokachi-oki earthquake in northern Japan, September 25, 2003, magnitude 8.1, was predicted six months in advance by a short-term earthquake precursor “chain” that reflects an increase of the correlation range among small earthquakes. This prediction is part of the ongoing test of a new short-term prediction method; the test covers territories of Japan, California, and Eastern Mediterranean. Qualitatively, precursory chain is a dense sequence of small earthquakes that had quickly extended over a long distance. A strong earthquake is expected within nine months after such chain is formed, in its formally defined vicinity. Chains are analyzed in conjunction with intermediate-term precursors, emerging with characteristic lead time of years. Methodology of prediction is named “Reverse Tracing of Precursors” (RTP), since precursors are considered in the reverse order of their appearance. That allows detecting short-term precursors not detectable with direct order of analysis. RTPwas tested retrospectively for California, Japan, and Eastern Mediterranean, where 22 more strong earthquakes occurred during the time considered. The concept underlying RTPis interaction of lithosphere dynamics on different temporal scales. The described results enhance our fundamental understanding of lithosphere dynamics and, on the practical side, our capability for earthquakes preparedness.