Probabilistic prediction of rupture length, slip and seismic ground motions for an ongoing rupture: implications for early warning for large earthquakes

Earthquake EarlyWarning (EEW) predicts future ground shaking based on presently available data. Long ruptures present the best opportunities for EEW since many heavily shaken areas are distant from the earthquake epicentre and may receive long warning times. Predicting the shaking from large earthquakes, however, requires some estimate of the likelihood of the future evolution of an ongoing rupture. An EEW system that anticipates future rupture using the present magnitude (or rupture length) together with the Gutenberg-Richter frequencysize statistics will likely never predict a large earthquake, because of the rare occurrence of ‘extreme events’. However, it seems reasonable to assume that large slip amplitudes increase the probability for evolving into a large earthquake. To investigate the relationship between the slip and the eventual size of an ongoing rupture, we simulate suites of 1-D rupture series from stochastic models of spatially heterogeneous slip. We find that while large slip amplitudes increase the probability for the continuation of a rupture and the possible evolution into a ‘Big One’, the recognition that rupture is occurring on a spatially smooth fault has an even stronger effect.We conclude that anEEWsystem for large earthquakes needs some mechanism for the rapid recognition of the causative fault (e.g., from real-time GPS measurements) and consideration of its ‘smoothness’. An EEW system for large earthquakes on smooth faults, such as the San Andreas Fault, could be implemented in two ways: the system could issue a warning, whenever slip on the fault exceeds a few metres, because the probability for a large earthquake is high and strong shaking is expected to occur in large areas around the fault. A more sophisticated EEW system could use the present slip on the fault to estimate the future slip evolution and final rupture dimensions, and (using this information) could provide probabilistic predictions of seismic ground motions along the evolving rupture. The decision on whether an EEW system should be realized in the first or in the second way (or in a combination of both) is user-specific

PreSEIS: A Neural Network-Based Approach to Earthquake Early Warning for Finite Faults

The major challenge in the development of earthquake early warning (EEW) systems is the achievement of a robust performance at largest possible warning time. We have developed a new method for EEW—called PreSEIS (Pre-SEISmic)—that is as quick as methods that are based on single station observations and, at the same time, shows a higher robustness than most other approaches. At regular timesteps after the triggering of the first EEW sensor, PreSEIS estimates the most likely source parameters of an earthquake using the available information on ground motions at different sensors in a seismic network. The approach is based on two-layer feed-forward neural networks to estimate the earthquake hypocenter location, its moment magnitude, and the expansion of the evolving seismic rupture. When applied to the Istanbul Earthquake Rapid Response and Early Warning System (IERREWS), PreSEIS estimates the moment magnitudes of 280 simulated finite faults scenarios (4.5≤M≤7.5) with errors of less than ±0.8 units after 0.5 sec, ±0.5 units after 7.5 sec, and ±0.3 units after 15.0 sec. In the same time intervals, the mean location errors can be reduced from 10 km over 6 km to less than 5 km, respectively. Our analyses show that the uncertainties of the estimated parameters (and thus of the warnings) decrease with time. This reveals a trade-off between the reliability of the warning on the one hand, and the remaining warning time on the other hand. Moreover, the ongoing update of predictions with time allows PreSEIS to handle complex ruptures, in which the largest fault slips do not occur close to the point of rupture initiation. The estimated expansions of the seismic ruptures lead to a clear enhancement of alert maps, which visualize the level and distribution of likely ground shaking in the affected region seconds before seismic waves will arrive

the development of an approach to online category management with Unilever's e-commerce drugstore trade partners in Germany

This paper encompasses implications for retailers and manufacturers on how to encounter the complex and emerging e-commerce market for fast-moving-consumer-goods by building up consumer-focused competitive advantages, such as Online Category Management (OCM). Research was conducted to learn about shoppers’ needs and expectations for a satisfactory online shopping experience, and to indicate that the current online shops in Germany lack convenience and shopper orientation. Results imply that aspects of experience can be positively influenced by measures of Category Management, provided that they are adapted to online characteristics. This suggests that the development of OCM should be considered an important tool to contribute to shopper loyalty and to the growth of the online channel in Germany

Real-time testing of the on-site warning algorithm in southern California and its performance during the July 29 2008 M_w5.4 Chino Hills earthquake

The real-time performance of the τ_c -P_d on-site early warning algorithm currently is being tested within the California Integrated Seismic Network (CISN). Since January 2007, the algorithm has detected 58 local earthquakes in southern California and Baja with moment magnitudes of 3.0 ≤ M_w ≤ 5.4. Combined with newly derived station corrections the algorithm allowed for rapid determination of moment magnitudes and Modified Mercalli Intensity (MMI) with uncertainties of ±0.5 and ±0.7 units, respectively. The majority of reporting delays ranged from 9 to 16 s. The largest event, the July 29 2008 M_w5.4 Chino Hills earthquake, triggered a total of 60 CISN stations in epicentral distances of up to 250 km. Magnitude predictions at these stations ranged from M_w4.4 to M_w6.5 with a median of M_w5.6. The closest station would have provided up to 6 s warning at Los Angeles City Hall, located 50 km to the west-northwest of Chino Hills

Cretaceous Ammonites from Texas and northern Mexico

Accompanied by 1 foldout plate -- Plate 19 : Composite Paleographic Map of Rio Grande Drainage Basin and Gulf Coast Region Mexico Descriptive letterpress on versos facing the plates. List of literature cited in the second paper : p. 306-312UT Librarie

Chronology of Weichselian main ice marginal positions in north-eastern Germany

Bisher basierte die Chronologie des Weichsel-Pleniglazials in Nord-Ost-Deutschland im Wesentlichen auf morphostratigraphischen Befunden und Radiokohlenstoffdatierungen organischer Sedimente aus dem Liegenden glazigener Ablagerungen. Im Laufe der letzen Jahre kamen im Rahmen verschiedener Studien Datierungsmethoden zum Einsatz, mit deren Hilfe es möglich war, die glazigenen Sedimente direkt zu datieren: Optisch Stimulierte Lumineszenz (OSL) von glazifluvialen Sedimenten und Oberflächen-Expositionsdatierungen (surface exposure dating, SED) von erratischen Blöcken. Wir fassen die Ergebnisse dieser Studien zusammen und bewerten sie auf der Grundlage eines prozessbasierten Interpretationsschemas neu, um somit eine neue Chronologie für die weichselzeitlichen Haupteisrandlagen in Nord-Ost-Deutschland vorstellen zu können. Auf der Grundlage der verfügbaren Daten lassen sich zwei Phasen während des letzten Glazials nachweisen, wobei die Brandenburger Phase einen Eisvorstoß im späten Marinen Isotopenstadium (MIS) 3 bis frühen MIS 2 repräsentiert, während die Pommersche Phase einen Eisvorstoß widerspiegelt, der seinen Maximalstand um ~20 ka erreichte. Hinsichtlich der endgültigen Stabilisierung der Geländeoberflächen nach der initialen Eisfreiwerdung zeigt sich eine hohe Abhängigkeit von Phasen aktiver Transformation unter periglazialen Bedingungen. Erste Ergebnisse numerischer Datierungen deuten auf eine solche Aktivitätsphase um ~15 ka hin.researc