A statistical feature of anomalous seismic activities prior to large shallow earthquakes in Japan revealed by the Pattern Informatics method

Abstract. For revealing the preparatory processes of large inland earthquakes, we systematically applied the Pattern Informatics method (PI method) to the earthquake data of Japan. We focused on 12 large earthquakes with magnitudes larger than M = 6.4 (an official magnitude of the Japan Meteorological Agency) that occurred at depths shallower than 30 km between 2000 and 2010. We examined the relation between the spatiotemporal locations of such large shallow earthquakes and those of PI hotspots, which correspond to the grid cells of anomalous seismic activities in a designated time span. Based on a statistical test using Molchan's error diagram, we inquired into the existence of precursory anomalous seismic activities of the large earthquakes and, if any, their characteristic time span. The test indicated that the Japanese M &geqq; 6.4 inland earthquakes tend to be preceded by anomalous seismic activities of 8-to-10-yr time scales.

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A statistical feature of anomalous seismic activity prior to large shallow earthquakes in Japan revealed by the pattern informatics method

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-849-2014 ◽

2014 ◽

Vol 14 (4) ◽

pp. 849-859 ◽

Cited By ~ 4

Author(s):

M. Kawamura ◽

Y.-H. Wu ◽

T. Kudo ◽

C.-c. Chen

Keyword(s):

Seismic Activity ◽

Characteristic Time ◽

Statistical Test ◽

Time Span ◽

Japan Meteorological Agency ◽

Pi Method ◽

Pattern Informatics ◽

Shallow Earthquakes ◽

The Relationship ◽

Large Earthquakes

Abstract. To reveal the preparatory processes of large inland earthquakes, we systematically applied the pattern informatics (PI) method to earthquake data of Japan. We focused on 12 large earthquakes with magnitudes greater than M = 6.4 (based on the magnitude scale of the Japan Meteorological Agency) that occurred at depths shallower than 30 km between 2000 and 2010. We examined the relationship between the spatiotemporal locations of these large shallow earthquakes and the locations of PI hotspots, which correspond to grid cells of anomalous seismic activity during a designated time span. Based on a statistical test conducted using Molchan's error diagram, we investigated whether precursory anomalous seismic activity occurred in association with these large earthquakes and, if so, studied the characteristic time spans of such activity. Our results indicate that Japanese inland earthquakes with M ≥ 6.4 are typically preceded by anomalous seismic activity in timescales of 8–10 years.

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Earthquake forecasting and its verification

Nonlinear Processes in Geophysics ◽

10.5194/npg-12-965-2005 ◽

2005 ◽

Vol 12 (6) ◽

pp. 965-977 ◽

Cited By ~ 75

Author(s):

J. R. Holliday ◽

K. Z. Nanjo ◽

K. F. Tiampo ◽

J. B. Rundle ◽

D. L. Turcotte

Keyword(s):

Temporal Variations ◽

Earthquake Forecasting ◽

Earthquake Risk ◽

Decision Threshold ◽

New Approach ◽

Pi Method ◽

Time Prediction ◽

Short Time ◽

Large Earthquakes ◽

Proven Method

Abstract. No proven method is currently available for the reliable short time prediction of earthquakes (minutes to months). However, it is possible to make probabilistic hazard assessments for earthquake risk. In this paper we discuss a new approach to earthquake forecasting based on a pattern informatics (PI) method which quantifies temporal variations in seismicity. The output, which is based on an association of small earthquakes with future large earthquakes, is a map of areas in a seismogenic region ("hotspots'') where earthquakes are forecast to occur in a future 10-year time span. This approach has been successfully applied to California, to Japan, and on a worldwide basis. Because a sharp decision threshold is used, these forecasts are binary--an earthquake is forecast either to occur or to not occur. The standard approach to the evaluation of a binary forecast is the use of the relative (or receiver) operating characteristic (ROC) diagram, which is a more restrictive test and less subject to bias than maximum likelihood tests. To test our PI method, we made two types of retrospective forecasts for California. The first is the PI method and the second is a relative intensity (RI) forecast based on the hypothesis that future large earthquakes will occur where most smaller earthquakes have occurred in the recent past. While both retrospective forecasts are for the ten year period 1 January 2000 to 31 December 2009, we performed an interim analysis 5 years into the forecast. The PI method out performs the RI method under most circumstances.

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Characteristics of Large-Scale Orographic Precipitation in a Linear Perspective

Journal of Hydrometeorology ◽

10.1175/2010jhm1231.1 ◽

2011 ◽

Vol 12 (1) ◽

pp. 27-44 ◽

Cited By ~ 8

Author(s):

Michael Kunz

Keyword(s):

Time Scales ◽

Characteristic Time ◽

Large Scale ◽

Linear Perspective ◽

Horizontal Wind ◽

Small Scale ◽

Orographic Precipitation ◽

Observation Data ◽

Horizontal Wind Speed ◽

Precipitation Patterns

Abstract Simulations of orographic precipitation over the low mountain ranges of southwestern Germany and eastern France with two different physics-based linear precipitation models are presented. Both models are based on 3D airflow dynamics from linear theory and consider advection of condensed water and leeside drying. Sensitivity studies for idealized conditions and a real case study show that the amount and spatial distribution of orographic precipitation is strongly controlled by characteristic time scales for cloud and hydrometeor advection and background precipitation due to large-scale lifting. These parameters are estimated by adjusting the model results on a 2.5-km grid to observed precipitation patterns for a sample of 40 representative orography-dominated stratiform events (24 h) during a calibration period (1971–80). In general, the best results in terms of lowest rmse and bias are obtained for characteristic time scales of 1600 s and background precipitation of 0.4 mm h−1. Model simulations of a sample of 84 events during an application period (1981–2000) with fixed parameters demonstrate that both models are able to reproduce quantitatively precipitation patterns obtained from observations and reanalyses from a numerical model [Consortium for Small-scale Modeling (COSMO)]. Combining model results with observation data shows that heavy precipitations over mountains are restricted to situations with strong atmospheric forcings in terms of synoptic-scale lifting, horizontal wind speed, and moisture content.

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Test of the Predictability of the PI Method for Recent Large Earthquakes in and near Tibetan Plateau

Earthquakes and Multi-hazards Around the Pacific Rim, Vol. I - Pageoph Topical Volumes ◽

10.1007/978-3-319-71565-0_15 ◽

2017 ◽

pp. 217-232

Author(s):

Yongxian Zhang ◽

Caiyun Xia ◽

Cheng Song ◽

Xiaotao Zhang ◽

Yongjia Wu ◽

...

Keyword(s):

Tibetan Plateau ◽

Pi Method ◽

Large Earthquakes

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Superconducting fluctuations and characteristic time scales in amorphous WSi

Physical Review B ◽

10.1103/physrevb.97.174502 ◽

2018 ◽

Vol 97 (17) ◽

Cited By ~ 4

Author(s):

Xiaofu Zhang ◽

Adriana E. Lita ◽

Mariia Sidorova ◽

Varun B. Verma ◽

Qiang Wang ◽

...

Keyword(s):

Time Scales ◽

Characteristic Time ◽

Superconducting Fluctuations

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Properties of Phase Solitons in an Optically Driven Semiconductor Ring Laser

Applied Sciences ◽

10.3390/app9204351 ◽

2019 ◽

Vol 9 (20) ◽

pp. 4351

Author(s):

Ghafour Hashemvand Shakarab ◽

Reza Kheradmand ◽

Mohammad Agha Bolorizadeh ◽

Franco Prati

Keyword(s):

Time Scales ◽

Propagation Velocity ◽

Ring Laser ◽

Characteristic Time ◽

Carrier Lifetime ◽

Large Range ◽

Semiconductor Ring Laser

A semiconductor ring laser with a long cavity supports propagating localised structures with a chiral charge, named phase solitons. In this paper we study the dependence of the velocity and of the duration of the phase solitons on the characteristic time scales of the laser, namely the photon lifetime and the carrier lifetime. We show numerically that phase solitons are stable over a large range of those parameters and verify that the propagation velocity decreases linearly with the ratio of the carrier lifetime to the photon lifetime, while the duration is proportional to the ratio of the carrier lifetime to the cavity roundtrip time.

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