Results 61 to 70 of about 272 (140)

Developing, Testing, and Communicating Earthquake Forecasts: Current Practices and Future Directions

Reviews of Geophysics, Volume 62, Issue 3, September 2024.
Abstract While deterministically predicting the time and location of earthquakes remains impossible, earthquake forecasting models can provide estimates of the probabilities of earthquakes occurring within some region over time. To enable informed decision‐making of civil protection, governmental agencies, or the public, Operational Earthquake ...
Leila Mizrahi, Irina Dallo, Nicholas J. van der Elst, Annemarie Christophersen, Ilaria Spassiani, Maximilian J. Werner, Pablo Iturrieta, José A. Bayona, Iunio Iervolino, Max Schneider, Morgan T. Page, Jiancang Zhuang, Marcus Herrmann, Andrew J. Michael, Giuseppe Falcone, Warner Marzocchi, David Rhoades, Matt Gerstenberger, Laura Gulia, Danijel Schorlemmer, Julia Becker, Marta Han, Lorena Kuratle, Michèle Marti, Stefan Wiemer   +24 more
wiley   +1 more source

Early warning processing results for June 15，2023 Qingpu，Shanghai M3.1 earthquake

地震科学进展
A M3.1 earthquake occurred in Qingpu District of Shanghai at 1:39 on June 15，2023. The Shanghai Earthquake Early Warning Network successfully received the earthquake early warning information released by the China Earthquake Early Warning Network，and the
Yongqian Shao, Chengrui Wang, Wei Wei, Peng Wang, Bo Bi   +4 more
doaj   +1 more source

GRAPES: Earthquake Early Warning by Passing Seismic Vectors Through the Grapevine

Geophysical Research Letters, Volume 51, Issue 9, 16 May 2024.
Abstract Estimating an earthquake's magnitude and location may not be necessary to predict shaking in real time; instead, wavefield‐based approaches predict shaking with few assumptions about the seismic source. Here, we introduce GRAph Prediction of Earthquake Shaking (GRAPES), a deep learning model trained to characterize and propagate earthquake ...
T. Clements, E. S. Cochran, A. Baltay, S. E. Minson, C. E. Yoon   +4 more
wiley   +1 more source

Automatic hypocenter determination with the IPFx method for the 2018 Hualien earthquake sequence

Terrestrial, Atmospheric and Oceanic Sciences, 2022
The extended integrated particle filter (IPFx) method is an automatic source determination algorithm designed for the Japanese earthquake early warning (EEW) system.
Masumi Yamada, Da-Yi Chen
doaj   +1 more source

Quantitative Evaluations of Earthquake Early Warning Performance Using “Did You Feel It?” and Post-Alert Surveys

The Seismic Record
We examine responses to the U.S. Geological Survey’s “Did You Feel It?” (DYFI) survey and its companion earthquake early warning (EEW) questionnaire to assess the performance of the U.S.
Jessie K. Saunders, David J. Wald
doaj   +1 more source

Validation framework for semi-stochastic simulations in Cascadia earthquake early warning

Seismica
We generate a synthetic earthquake dataset for the Cascadia region and present a framework for validating simulations for use in testing earthquake early warning (EEW) performance.
Tara Nye, Valerie J. Sahakian, Angela Schlesinger, Diego Melgar, Alireza Babaie Mahani, Amy Williamson, Eli Ferguson, Angela Lux, Benoît Pirenne   +8 more
doaj   +1 more source

Multi-parameter algorithm for Earthquake Early Warning

Geomatics, Natural Hazards & Risk, 2016
Earthquake Early Warning (EEW) system is a real-time earthquake damage mitigation system. It detects, analyzes and transmits information of the impending event at the potential user sites. In the present study, an attempt has been made to develop a multi-
Rakhi Bhardwaj, Mukat Lal Sharma, Ashok Kumar   +2 more
doaj   +1 more source

Feasibility study of earthquake early warning (EEW) in Hawaii [PDF]

Open-File Report, 2016
Weston A. Thelen, Alicia J. Hotovec-Ellis, Paul Bodin   +2 more
openaire   +1 more source

Earthquake early warning: what does “seconds before a strong hit” mean?

Progress in Earth and Planetary Science, 2018
An earthquake early warning (EEW) system is designed to detect an event, determine its parameters (hypocenter, magnitude, and origin time), and issue an alert to sites/areas where necessary actions should be taken before destructive seismic energy ...
Fumiko Tajima, Takumi Hayashida
doaj   +1 more source

Multimodal deep learning network for fast seismic discrimination and magnitude classification

Geoscience Letters
Quickly and accurately identifying seismic events from background noise and classifying earthquake magnitudes is extremely important for improving the performance of earthquake early warning (EEW) systems.
Jingbao Zhu, Shanyou Li, Jindong Song
doaj   +1 more source