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Christophersen, Annemarie
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- PublicationRestrictedDevelopment of the Global Earthquake Model’s neotectonic fault database(2015-06)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;Christophersen, A.; GNS Science, Lower Hutt, New Zealand ;Litchfield, N.; GNS Science, Lower Hutt, New Zealand ;Berryman, K.; GNS Science, Lower Hutt, New Zealand ;Thomas, R.; GNS Science, Lower Hutt, New Zealand ;Basili, R.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia ;Wallace, L.; The University of Texas at Austin, Austin, TX, USA ;Ries, W.; GNS Science, Lower Hutt, New Zealand ;Hayes, G. P.; USGS, Golden, CO, USA ;Haller, K. M.; USGS, Golden, CO, USA ;Yoshioka, T.; National Institute of Advanced Industrial Science and Technology, Tsukuba, Japan ;Koehler, R. D.; State of Alaska, Geological and Geophysical Surveys, Fairbanks, AK, USA ;Clark, D.; Geoscience Australia, Canberra, Australia ;Wolfson-Schwehr, M.; Department of Earth Sciences, University of New Hampshire, Durham, NH, USA ;Boettcher, M. S.; Department of Earth Sciences, University of New Hampshire, Durham, NH, USA ;Villamor, P.; GNS Science, Lower Hutt, New Zealand ;Horspool, N.; GNS Science, Lower Hutt, New Zealand ;Ornthammarath, T.; Department of Civil and Environmental Engineering, Mahidol University, Bangkok, Thailand ;Zuñiga, R.; Centro de Geociencias, UNAM, Juriquilla, Queretaro, Mexico ;Langridge, R. M.; GNS Science, Lower Hutt, New Zealand ;Stirling, M. W.; GNS Science, Lower Hutt, New Zealand ;Goded, T.; GNS Science, Lower Hutt, New Zealand ;Costa, C.; Universidad Nacional de San Luis, San Luis, Argentina ;Yeats, R.; Oregon State University, Corvallis, OR, USA; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ; The Global Earthquake Model (GEM) aims to develop uniform, openly available, standards, datasets and tools for worldwide seismic risk assessment through global collaboration, transparent communication and adapting state-of-the-art science. GEM Faulted Earth (GFE) is one of GEM’s global hazard module projects. This paper describes GFE’s development of a modern neotectonic fault database and a unique graphical interface for the compilation of new fault data. A key design principle is that of an electronic field notebook for capturing observations a geologist would make about a fault. The database is designed to accommodate abundant as well as sparse fault obser- vations. It features two layers, one for capturing neotectonic faults and fold observations, and the other to calculate potential earthquake fault sources from the observations. In order to test the flexibility of the database structure and to start a global compilation, five preexisting databases have been uploaded to the first layer and two to the second. In addition, the GFE project has characterised the world’s approximately 55,000 km of subduction interfaces in a globally consistent manner as a basis for generating earthquake event sets for inclusion in earthquake hazard and risk modelling. Following the subduction interface fault schema and including the trace attributes of the GFE database schema, the 2500-km-long frontal thrust fault system of the Himalaya has also been characterised. We propose the database structure to be used widely, so that neotectonic fault data can make a more complete and beneficial contribution to seismic hazard and risk characterisation globally.346 57 - PublicationOpen AccessHighlights from the First Ten Years of the New Zealand Earthquake Forecast Testing CenterThe Collaboratory for the Study of Earthquake Predictability (CSEP) is a global cyberinfrastructure for prospective evaluations of earthquake forecast models and prediction algorithms. CSEP’s goals are to improve our understanding of earthquake predictability, advance forecasting model development, test key scientific hypotheses and their predictive power, and improve seismic hazard assessments. Since its inception in California in 2007, the global CSEP collaboration has been conducting forecast experiments in a variety of tectonic settings and at a global scale and now operates four testing centers on four continents to automatically and objectively evaluate models against prospective data. These experiments have provided a multitude of results that are informing operational earthquake forecasting systems and seismic hazard models, and they have provided new and, sometimes, surprising insights into the predictability of earthquakes and spurned model improvements. CSEP has also conducted pilot studies to evaluate ground-motion and hazard models. Here, we report on selected achievements from a decadeof CSEP, and we present our priorities for future activities.
66 167 - PublicationOpen AccessSetting up an earthquake forecast experiment in Italy(2010)
; ; ; ; ; ; ;Schorlemmer, D.; University of Southern California ;Christophersen, A.; GNS Science, Avalon, Lower Hutt, New Zealand ;Rovida, A.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Milano-Pavia, Milano, Italia ;Mele, F.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione CNT, Roma, Italia ;Stucchi, M.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Milano-Pavia, Milano, Italia ;Marzocchi, W.; Istituto Nazionale di Geofisica e Vulcanologia, Sezione Roma1, Roma, Italia; ; ; ; ; We describe the setting up of the first earthquake forecasting experiment for Italy within the Collaboratory for the Study of Earthquake Predictability (CSEP). CSEP conducts rigorous and truly prospective forecast experiments for different tectonic environments in several forecast testing centers around the globe; forecasts are issued for a future period and also tested only against future observations to avoid any possible bias. As such, experiments need to be completely defined. This includes exact definitions of the testing area, of learning data for the forecast models, and of observation data against which forecasts will be tested to evaluate their performance. Here we present the rules, as taken from the Regional Earthquake Likelihood Models experiment and extended or changed for the Italian experiment. We also present characterizations of learning and observational catalogs that describe the completeness of these catalogs and illuminate inhomogeneities of magnitudes between these catalogs. A particular focus lies on the stability of earthquake recordings of the observational network. These catalog investigations provide guidance for CSEP modelers for developing earthquakes forecasts for submission to the forecast experiment in Italy.386 286 - PublicationRestrictedThe Forecasting Skill of Physics‐Based Seismicity Models during the 2010–2012 Canterbury, New Zealand, Earthquake Sequence(2018)
; ; ; ; ; ; ; ; ; ; ; ; ; ; ;; ; ; ; ; ; ; ; ; ;The static coulomb stress hypothesis is a widely known physical mechanism for earthquake triggering and thus a prime candidate for physics-based operational earthquake forecasting (OEF). However, the forecast skill of coulomb-based seismicity models remains controversial, especially compared with empirical statistical models. A previous evaluation by the Collaboratory for the Study of Earthquake Predictability (CSEP) concluded that a suite of coulomb-based seismicity models were less informative than empirical models during the aftershock sequence of the 1992 Mw 7.3 Landers, California, earthquake. Recently, a new generation of coulomb-based and coulomb/statistical hybrid models were developed that account better for uncertainties and secondary stress sources. Here, we report on the performance of this new suite of models compared with empirical epidemic-type aftershock sequence (ETAS) models during the 2010–2012 Canterbury, New Zealand, earthquake sequence. Comprising the 2010 M 7.1 Darfield earthquake and three subsequent M ≥ 5:9 shocks (including the February 2011 Christchurch earthquake), this sequence provides a wealth of data (394 M ≥ 3:95 shocks). We assessed models over multiple forecast horizons (1 day, 1 month, and 1 yr, updated after M ≥ 5:9 shocks). The results demonstrate substantial improvements in the coulomb-based models. Purely physics-based models have a performance comparable to the ETAS model, and the two coulomb/statistical hybrids perform better or similar to the corresponding statistical model. On the other hand, an ETAS model with anisotropic (fault-based) aftershock zones is just as informative. These results provide encouraging evidence for the predictive power of coulomb-based models. To assist with model development, we identify discrepancies between forecasts and observations.65 5