All instrumented basaltic caldera collapses have generated Mw > 5 very long period earthquakes. However, previous studies of source dynamics have been limited to lumped models treating the caldera block as rigid, leaving open questions related to how ruptures initiate and propagate around the ring fault, and the seismic expressions of those dynamics. We present the first 3D numerical model capturing the nucleation and propagation of ring fault rupture, the mechanical coupling to the underlying viscoelastic magma, and the associated seismic wavefield. We demonstrate that seismic radiation, neglected in previous models, acts as a damping mechanism reducing coseismic slip by up to half, with effects most pronounced for large magma chamber volume/ring fault radius or highly compliant crust/compressible magma. Viscosity of basaltic magma has negligible effect on collapse dynamics. In contrast, viscosity of silicic magma significantly reduces ring fault slip. We use the model to simulate the 2018 Kilauea caldera collapse. Three stages of collapse, characterized by ring fault rupture initiation and propagation, deceleration of the downward-moving caldera block and magma column, and post-collapse resonant oscillations, in addition to chamber pressurization, are identified in simulated and observed (unfiltered) near-field seismograms. A detailed comparison of simulated and observed displacement waveforms corresponding to collapse earthquakes with hypocenters at various azimuths of the ring fault reveals a complex nucleation phase for earthquakes initiated on the northwest. Our numerical simulation framework will enhance future efforts to reconcile seismic and geodetic observations of caldera collapse with conceptual models of ring fault and magma chamber dynamics. Plain Language Summary Caldera collapse manifests as the rapid subsidence of a kilometer-scale block of crust circumscribed by a near-circular fault on top of a volcano. The subsidence of the caldera block is caused by the eruption-induced withdrawal of magma and reduction in pressure in the underlying magma chamber. All scientifically instrumented caldera collapses at volcanoes with low-viscosity magma are accompanied by earthquakes of magnitude 5 and above. How do magma viscosity and the seismic wave radiation influence the amount of slip per earthquake on the fault? What can we learn about the dynamics of these earthquakes from seismic records? We address these questions by performing computer simulations of caldera collapse earthquakes and compare the results to the seismic records from the Kilauea caldera collapse of 2018.

Several studies have established that atmospheric flows have a finite range of predictability, which may be reasonably considered a consequence of the underlying dynamics. In the midlatitudes, error growth is predominantly associated with baroclinic disturbances. We consider midlatitude error growth in two models: an idealized dry dynamical core and a comprehensive atmospheric general circulation model (GCM). By systematically varying equator to pole temperature gradients in the dynamical core, we show that with increasing Eady growth rates, the time elapsed before errors saturate decreases, shortening the window in which weather predictions may be useful. We also consider the limits of midlatitude predictability in the comprehensive moist GCM in a range of climates. Our results show that the times to error saturation are shorter in warmer climates than colder climates, suggesting that warmer climates are inherently less predictable.

The spatial distribution of aftershocks following major earthquakes has received significant attention due to the shaking hazard these events pose for structures and populations in the affected region. Forecasting the spatial distribution of aftershock events is an important part of the estimation of future seismic hazard. A simple spatial shape for the zone of activity has often been assumed in the form of an ellipse having semimajor axis to semiminor axis ratio of 2.0. However, since an important application of these calculations is the estimation of ground shaking hazard, an effective criterion for forecasting future aftershock impacts is to use ground motion prediction equations (GMPEs) in addition to the more usual approach of using epicentral or hypocentral locations. Based on these ideas, we present an aftershock model that uses self-similarity and scaling relations to constrain parameters as an option for such hazard assessment. We fit the spatial aspect ratio to previous earthquake sequences in the studied regions, and demonstrate the effect of the fitting on the likelihood of post-disaster ground motion forecasts for eighteen recent large earthquakes. We find that the forecasts in most geographic regions studied benefit from this optimization technique, while some are better suited to the use of the a priori aspect ratio.

Utilizing earthquake source parameter scaling relations, we formulate an extensible slip weakening friction law for quasi-static earthquake simulations. This algorithm is based on the method used to generate fault strengths for a recent earthquake simulator comparison study of the California fault system. Here we focus on the application of this algorithm in the Virtual Quake earthquake simulator. As a case study we probe the effects of the friction law's parameters on simulated earthquake rates for the UCERF3 California fault model, and present the resulting conditional probabilities for California earthquake scenarios. The new friction model significantly extends the moment magnitude range over which simulated earthquake rates match observed rates in California, as well as substantially improving the agreement between simulated and observed scaling relations for mean slip and total rupture area.

The seismic belt along the Pacific Rim is the greatest earthquake zone in the world, generating more than 80% of the world’s largest earthquakes ( https://earthquake.usgs.gov/learn/topics/megaqk_facts_fantasy.php ). It is also susceptible to tsunamis and volcanic eruptions, which could generate serious multihazards. Since the beginning of the twenty-first century, most countries along the Pacific Rim have suffered from tremendous multi-hazards, especially earthquakes and tsunamis.

In this paper, we address the problem of verifying earthquake simulators with observed data. Earthquake simulators are a class of computational simulations which attempt to mirror the topological complexity of fault systems on which earthquakes occur. In addition, the physics of friction and elastic interactions between fault elements are included in these simulations. Simulation parameters are adjusted so that natural earthquake sequences are matched in their scaling properties. Physically based earthquake simulators can generate many thousands of years of simulated seismicity, allowing for a robust capture of the statistical properties of large, damaging earthquakes that have long recurrence time scales. Verification of simulations against current observed earthquake seismicity is necessary, and following past simulator and forecast model verification methods, we approach the challenges in spatial forecast verification to simulators; namely, that simulator outputs are confined to the modeled faults, while observed earthquake epicenters often occur off of known faults. We present two methods for addressing this discrepancy: a simplistic approach whereby observed earthquakes are shifted to the nearest fault element and a smoothing method based on the power laws of the epidemic-type aftershock (ETAS) model, which distributes the seismicity of each simulated earthquake over the entire test region at a decaying rate with epicentral distance. To test these methods, a receiver operating characteristic plot was produced by comparing the rate maps to observed m > 6.0 earthquakes in California since 1980. We found that the nearest-neighbor mapping produced poor forecasts, while the ETAS power-law method produced rate maps that agreed reasonably well with observations.

In this manuscript, we introduce a framework for developing earthquake forecasts using Virtual Quake (VQ), the generalized successor to the perhaps better known Virtual California (VC) earthquake simulator. We discuss the basic merits and mechanics of the simulator, and we present several statistics of interest for earthquake forecasting. We also show that, though the system as a whole (in aggregate) behaves quite randomly, (simulated) earthquake sequences limited to specific fault sections exhibit measurable predictability in the form of increasing seismicity precursory to large m > 7 earthquakes. In order to quantify this, we develop an alert-based forecasting metric, and show that it exhibits significant information gain compared to random forecasts. We also discuss the long-standing question of activation versus quiescent type earthquake triggering. We show that VQ exhibits both behaviours separately for independent fault sections; some fault sections exhibit activation type triggering, while others are better characterized by quiescent type triggering. We discuss these aspects of VQ specifically with respect to faults in the Salton Basin and near the El Mayor-Cucapah region in southern California, USA and northern Baja California Norte, Mexico.

The epidemic type aftershock sequence (ETAS) statistical model of aftershock seismicity combines various earthquake scaling relations to produce synthetic earthquake catalogs, or estimates of aftershock seismicity rates, based on recent earthquake activity. One challenge to ETAS-based hazard assessment is the large number of free parameters involved. In this paper, we introduce an approach to constrain this parameter space from canonical scaling relations, empirical observations, and fundamental physics. We show that ETAS parameters can be estimated as a function of an earthquake's magnitude m based on the finite temporal and spatial extents of the rupture area. This approach facilitates fast ETAS-based estimates of seismicity from large "seed" catalogs, and it is particularly well suited to web-based deployment and otherwise automated implementations. It constitutes a significant improvement over contemporary ETAS by mitigating variability related to instrumentation and subjective catalog selection.

With the ever increasing number of geodetic monitoring satellites, it is vital to have a variety of geophysical simulations produce synthetic datasets. Furthermore, just as hurricane forecasts are derived from the consensus among multiple atmospheric models, earthquake forecasts cannot be derived from a single comprehensive model. Here we present the functionality of Virtual Quake (formerly known as Virtual California), a numerical simulator that can generate sample co-seismic deformations, gravity changes, and InSAR interferograms in addition to producing probabilities for earthquake scenarios.Virtual Quake is now hosted by the Computational Infrastructure for Geodynamics. It is available for download and comes with a user manual. The manual includes a description of the simulator physics, instructions for generating fault models from scratch, and a guide to deploying the simulator in a parallel computing environment. http://geodynamics.org/cig/software/vq/.

We introduce a framework for forecasting earthquakes using Virtual Quake (VQ), the generalized successor to the perhaps better known Virtual California earthquake simulator. We briefly introduce the VQ simulator, including its availability to research organizations and statistics relevant to earthquake forecasting applications. We discuss contemporary, regional type, forecasts and also show that forecasts can be significantly improved by partitioning catalogs along fault sections.

Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing new capabilities for decision making utilizing remote sensing data and modeling software to provide decision support for earthquake disaster management and response. E-DECIDER incorporates the earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools allows us to provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). This in turn is delivered through standards-compliant web services for desktop and hand-held devices.

The Gorkha earthquake (magnitude 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing ~9000 people and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes’ induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and lithologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision-makers. We mapped 4312 coseismic and postseismic landslides. We also surveyed 491 glacier lakes for earthquake damage but found only nine landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities correlate with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.

We introduce a method of resolving temporal incidence trends in earthquake sequences. We have developed a catalog partitioning method based on canonical earthquake scaling relationships, and have further developed a metric based on record-breaking interval (RBI) statistics to resolve increasing and decreasing seismicity in time series of earthquakes. We calculated the RBI metric over fixed-length sequences of earthquake intervals and showed that the length of those sequences is related to the magnitude of the earthquake to which the method is sensitive—longer sequences resolve large earthquakes, shorter sequences resolve small-magnitude events. This sequence length effectively constitutes a local temporal catalog constraint, and we show that spatial constraints can be defined from rupture length scaling. We have applied the method to several high-profile earthquakes and have shown that it consistently resolves aftershock sequences after a period of accelerating seismicity before the targeted mainshock. The method also suggests a minimum detectable (forecastable) mainshock magnitude on the basis of the catalog’s minimum completeness magnitude \(m_{\rm c}\).