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Charles Richter's observation that 'only fools and charlatans predict earthquakes,' reflects the fact that despite more than 100 years of effort, seismologists remain unable to do so with reliable and accurate results. Meaningful prediction involves specifying the location, time, and size of an earthquake before it occurs to greater precision than expected purely by chance from the known statistics of earthquakes in an area. In this context, 'forecasting' implies a prediction with a specification of a probability of the time, location, and magnitude. Two general approaches have been used. In one, the rate of motion accumulating across faults and the amount of slip in past earthquakes is used to infer where and when future earthquakes will occur and the shaking that would be expected. Because the intervals between earthquakes are highly variable, these long-term forecasts are accurate to no better than a hundred years. They are thus valuable for earthquake hazard mitigation, given the long lives of structures, but have clear limitations. The second approach is to identify potentially observable changes in the Earth that precede earthquakes. Various precursors have been suggested, and may have been real in certain cases, but none have yet proved to be a general feature preceding all earthquakes or to stand out convincingly from the normal variability of the Earth's behavior. However, new types of data, models, and computational power may provide avenues for progress using machine learning that were not previously available. At present, it is unclear whether deterministic earthquake prediction is possible. The frustrations of this search have led to the observation that (echoing Yogi Berra) 'it is difficult to predict earthquakes, especially before they happen.' However, because success would be of enormous societal benefit, the search for methods of earthquake prediction and forecasting will likely continue. In this review, we note that the focus is on anticipating the earthquake rupture before it occurs, rather than characterizing it rapidly just after it occurs. The latter is the domain of earthquake early warning, which we do not treat in detail here, although we include a short discussion in the machine learning section at the end. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Large devastating events in systems such as earthquakes, typhoons, market crashes, electricity grid blackouts, floods, droughts, wars and conflicts, and landslides can be unexpected and devastating. Events in many of these systems display frequency-size statistics that are power laws. Previously, we presented a new method for calculating probabilities for large events in systems such as these. This method counts the number of small events since the last large event and then converts this count into a probability by using a Weibull probability law. We applied this method to the calculation of large earthquake probabilities in California-Nevada, USA. In that study, we considered a fixed geographic region and assumed that all earthquakes within that region, large magnitudes as well as small, were perfectly correlated. In the present article, we extend this model to systems in which the events have a finite correlation length. We modify our previous results by employing the correlation function for near mean field systems having long-range interactions, an example of which is earthquakes and elastic interactions. We then construct an application of the method and show examples of computed earthquake probabilities. [ABSTRACT FROM AUTHOR]

In this manuscript, we introduce a framework for developing earthquake forecasts usingVirtual 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 alertbased 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Parameters usually play a key role in statistical forecasting models and should be carefully determined because the physics of the system links to the statistical model through the parameters. To investigate the relations between parameters and pattern informatics (PI) migration, we developed a series of retrospective analyses. The results show that two parameters (i.e., cut magnitude and change interval) are essential factors of calculating PI migration. The cut magnitude is a lower cutoff magnitude applied to the catalog at the start of the analysis, and the result of the analysis shows that the PI migration hot spots are mostly distributed around the earthquakes with magnitude larger than target magnitude when the cut magnitude is 3.2-3.4 in most study regions. The change interval is a time span prior to the large event that we assumed to be the duration of the preparation process. In the retrospective analysis, the ability of PI migration hot spot to hit the target earthquake varies with change interval and the change interval that make PI migration hot spot to hit most target earthquakes varies with the study region. By using a retrospective analysis, we determined the optimal parameters for each study region, generating PI migration maps to show potential locations. [ABSTRACT FROM AUTHOR]

We consider implications of the Regional Earthquake Likelihood Models (RELM) test results with regard to earthquake forecasting. Prospective forecasts were solicited for M ⩾ 4.95 earthquakes in California during the period 2006-2010. During this period 31 earthquakes occurred in the test region with M ⩾ 4.95.We consider five forecasts that were submitted for the test. We compare the forecasts utilizing forecast verification methodology developed in the atmospheric sciences, specifically for tornadoes. We utilize a "skill score" based on the forecast scores λfi of occurrence of the test earthquakes. A perfect forecast would have λfi = 1, and a random (no skill) forecast would have λfi = 2.86×10-3. The best forecasts (largest value of λfi) for the 31 earthquakes had values of λfi = 1.24 × 10-1 to λfi = 5.49 × 10-3. The best mean forecast for all earthquakes was λf = 2.84 × 10-2. The best forecasts are about an order of magnitude better than random forecasts. We discuss the earthquakes, the forecasts, and alternative methods of evaluation of the performance of RELM forecasts. We also discuss the relative merits of alarm-based versus probability-based forecasts. [ABSTRACT FROM AUTHOR]

The Regional Earthquake Likelihood Models (RELM) test of earthquake forecasts in California was the first competitive evaluation of forecasts of future earthquake occurrence. Participants submitted expected probabilities of occurrence of M ≥ 4.95 earthquakes in 0.1° × 0.1° cells for the period 1 January 1, 2006, to December 31, 2010. Probabilities were submitted for 7,682 cells in California and adjacent regions. During this period, 31 M ≥ 4.95 earthquakes occurred in the test region. These earthquakes occurred in 22 test cells. This seismic activity was dominated by earthquakes associated with the M = 7.2, April 4, 2010, El Mayor-Cucapah earthquake in northern Mexico. This earthquake occurred in the test region, and 16 of the other 30 earthquakes in the test region could be associated with it. Nine complete forecasts were submitted by six participants. In this paper, we present the forecasts in a way that allows the reader to evaluate which forecast is the most "successful" in terms of the locations of future earthquakes. We conclude that the RELM test was a success and suggest ways in which the results can be used to improve future forecasts. [ABSTRACT FROM AUTHOR]

We describe an application to interactively create and manipulate digital fault maps, either by tracing existing (paper) fault maps created from geological surveys, or by directly observing fault expressions and earthquake hypocenters in remote sensing data such as high-resolution (⩾100k × 100k elevation postings) digital elevation models with draped color imagery. Such fault maps serve as input data to finite-element-method simulations of fault interactions, and are crucial to understand regional tectonic processes causing earthquakes, and have tentatively been used to forecast future seismic events or to predict the shaking from likely future earthquakes. This fault editor is designed for immersive virtual reality environments such as CAVEs, and presents users with visualizations of scanned 2D fault maps and textured 3D terrain models, and a set of 3D editing tools to create or manipulate faults. We close with a case study performed by one of our geologist co-authors (Yikilmaz), which evaluates the use of our fault editor in creating a detailed digital fault model of the North Anatolian Fault in Turkey, one of the largest, seismically active strike-slip faults in the world. Yikilmaz, who was directly involved in program development, used our fault editor both in a CAVE and on a desktop computer, and compares it to the industry-standard software package ArcGIS. Copyright © 2009 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The objective of this paper is to quantify the use of past seismicity to forecast the locations of future large earthquakes and introduce optimization methods for the model parameters. To achieve this the binary forecast approach is used where the surface of the Earth is divided into l° × l° cells. The cumulative Benioff strain of m ≥ m c earthquakes that occurred during the training period, Δ Ttr, is used to retrospectively forecast the locations of large target earthquakes with magnitudes ≥ m T during the forecast period, Δ Tfor. The success of a forecast is measured in terms of hit rates (fraction of earthquakes forecast) and false alarm rates (fraction of alarms that do not forecast earthquakes). This binary forecast approach is quantified using a receiver operating characteristic diagram and an error diagram. An optimal forecast can be obtained by taking the maximum value of Pierce’s skill score. [ABSTRACT FROM AUTHOR]

Estimates the usefulness of the time-to-failure analysis in predicting earthquakes. Test of accuracy of the error estimates produced by the standard least square fitter; Indication of underestimated least-squares fitter in time-to-failure functions; Significance of the linearized version of the functions fitted.

This special issue presents work stemming from collaboration in the APEC Cooperation for Earthquake Simulation (ACES) project. Here, the guest editors discuss how each article tackles significant challenges, with various approaches for studying earthquakes and mitigating earthquakes' effects. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one regarding the pattern informatics method for earthquake forecasting, another on the numerical simulations of earthquake faults and numerical methods, and one on testing earthquake forecasting method.