scholarly journals Effect of Ocean Fluid Changes on Pressure on the Seafloor: Ocean Assimilation Data Analysis on Warm-Core Rings off the Southeastern Coast of Hokkaido, Japan on an Interannual Timescale

2021 ◽  
Vol 9 ◽  
Author(s):  
Takuya Hasegawa ◽  
Akira Nagano ◽  
Keisuke Ariyoshi ◽  
Toru Miyama ◽  
Hiroyuki Matsumoto ◽  
...  
Keyword(s):  
Sea Surface ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Plate Convergence ◽  
Southeastern Coast ◽  
Warm Core ◽  
Slow Earthquakes ◽  
The Relationship ◽  
Interannual Scale

The relationship between sea surface height (SSH) and seawater density anomalies, which affects the pressure on the seafloor (PSF) anomalies off the southeastern coast of Hokkaido, Japan, was analyzed using the eddy-resolving spatial resolution ocean assimilation data of the JCOPE2M for the period 2001–2018. On an interannual (i.e., year-to-year) timescale, positive SSH anomalies of nearly 0.1 m appeared off the southeastern coast of Hokkaido, Japan, in 2007, associated with a warm-core ring (WCR), while stronger SSH anomalies (∼0.2 m) related to a stronger WCR occurred in 2016. The results show that the effects of such positive SSH anomalies on the PSF are almost canceled out by the effects of negative seawater density anomalies from the seafloor to the sea surface (SEP; steric effect on PSF) due to oceanic baroclinic structures related to the WCRs, especially in offshore regions with bottom depths greater than 1000 m. This means that oceanic isostasy is well established in deep offshore regions, compared with shallow coastal regions. To further verify the strength of the oceanic isostasy, oceanic isostasy anomalies (OIAs), which represent the barotropic component of SSH anomalies, are introduced and analyzed in this study. OIAs are defined as the sum of the SSH anomalies and SEP anomalies. Our results indicate that the effect of oceanic fluid changes due to SSH and seawater density anomalies (i.e., OIAs) on PSF changes cannot be neglected on an interannual timescale, although the amplitudes of the OIAs are nearly 10% of those of the SSH anomalies in the offshore regions. Therefore, to better estimate the interannual-scale PSF anomalies due to crustal deformation related to slow earthquakes including afterslips, long-term slow slip events, or plate convergence, the OIAs should be removed from the PSF anomalies.

scholarly journals Stress state along the western Nankai Trough subduction zone inferred from b-values, long-term slow-slip events, and low-frequency earthquakes

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Keita Chiba
Keyword(s):  
Low Frequency ◽  
Value Distribution ◽  
Focal Region ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Megathrust Earthquakes ◽  
Source Regions ◽  
Slow Earthquakes ◽  
Subducting Plate

AbstractThe b-value of the Gutenberg–Richter law represents the ratio of earthquake magnitude to frequency of occurrence and is inversely proportional to differential stress. Repeating long-term slow-slip events (SSEs) and low-frequency earthquakes (LFEs) occur at subducting plate interfaces and have stress-dependent characteristics near the interface. In this study, a comprehensive regional b-value distribution is produced for the western Nankai Trough region, which highlights the relationship between b-values, SSEs, and LFEs. b-values vary along the strike direction of the subducting plate and are significantly lower $$ \left( {b \sim 0.6} \right) $$b∼0.6 in central Shikoku district than elsewhere, where LFEs frequently occur. However, b-values in the source regions of other LFEs are moderate to high. These findings imply that b-values in the focal region are controlled by more than the LFE source process; indeed, if this source process were solely responsible, then high b-values would be expected. Meanwhile, the $$ V_{P} /V_{S} $$VP/VS and QP around the plate interface in central Shikoku estimated from seismic velocity and attenuation structure are smaller and larger than those in other regions with LFEs, respectively. SSEs with the migration toward central Shikoku also occurred during the analysis period, suggesting significant accumulation of shear stresses in the focal region, which reduced the b-values. These findings suggest that the spatial distributions of b-values are influenced by complicated stress and shear strength perturbations caused by SSEs and LFEs. On the other hand, the b-values in the region that underwent the greatest slip during the 1946 Nankai earthquake are not necessarily low, although the area covered by the b-value distribution is small owing to the lack of events on the updip side. Whereas the asperity areas of huge earthquakes are characterized by low b-values, the b-value distribution in the Nankai megathrust area is more complicated. It is considered that slow earthquakes, including SSEs and LFEs, are related to megathrust earthquakes via stress transfer from slow earthquakes to adjacent megathrust source regions. A unified analysis of b-values in the source regions of slow and megathrust earthquakes may be required to make precise estimates of the seismic hazard produced by a megathrust event.

Observing seismic signatures of slow slip events with unsupervised learning

2021 ◽  
Author(s):  
Leonard Seydoux ◽  
Michel Campillo ◽  
René Steinmann ◽  
Randall Balestriero ◽  
Maarten de Hoop
Keyword(s):  
Clustering Algorithm ◽  
Low Frequency ◽  
Seismic Signal ◽  
Geodetic Data ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Slow Slip Event ◽  
Intermittent Behavior ◽  
Slow Earthquakes ◽  
Slip Event

<p>Slow slip events are observed in geodetic data, and are occasionally associated with seismic signatures such as slow earthquakes (low-frequency earthquakes, tectonic tremors). In particular, it was shown that swarms of slow earthquake can correlate with slow slip events occurrence, and allowed to reveal the intermittent behavior of several slow slip events. This observation was possible thanks to detailed analysis of slow earthquakes catalogs and continuous geodetic data, but in every case, was limited to particular classes of seismic signatures. In the present study, we propose to infer the classes of seismic signals that best correlate with the observed geodetic data, including the slow slip event. We use a scattering network (a neural network with wavelet filters) in order to find meaningful signal features, and apply a hierarchical clustering algorithm in order to infer classes of seismic signal. We then apply a regression algorithm in order to predict the geodetic data, including slow slip events, from the occurrence of inferred seismic classes. This allow to (1) identify seismic signatures associated with the slow slip events as well as (2) infer the the contribution of each classes to the overall displacement observed in the geodetic data. We illustrate our strategy by revisiting the slow-slip event of 2006 that occurred beneath Guerrero, Mexico.</p>

scholarly journals Detection of Deep Low-frequency Earthquakes in the Nankai Subduction Zoneover 11 Years Usingamatched Filter Technique

2020 ◽  
Author(s):  
Aitaro Kato ◽  
Shigeki Nakagawa
Keyword(s):  
Matched Filter ◽  
Low Frequency ◽  
Slow Slip ◽  
Slow Slip Events ◽  
Filter Technique ◽  
Strike Direction ◽  
Episodic Tremor And Slip ◽  
Spatio Temporal ◽  
Episodic Tremor

Abstract To improve our understanding of the long-term behavior of low-frequency earthquakes (LFEs) along the tremor belt of the Nankai subduction zone, we applied a matched filter technique to continuous seismic data recorded by a dense and highly sensitive seismic network over an 11year window, April 2004 to August 2015. We detected a total of ~510,000 LFEs, or ~23× the number of LFEs in the JMA catalog for the same period. During long-term slow slip events (SSEs) in the Bungo Channel, a series of migrating LFEbursts intermittently occurred along the fault-strike direction, with slow hypocenter propagation. Elastic energy released by long-term SSEs appears to control the extent of LFE activity. We identify slowlymigrating fronts of LFEs during major episodic tremor and slip (ETS)events, which extend over distances of up to 100 km and follow diffusion-like patterns of spatial evolution with a diffusion coefficient of ~104 m2/s. This migration pattern closely matches the spatio-temporal evolution of tectonictremors reported by previous studies. At shorter distances, up to 15 km, we discovered rapid diffusion-like migrationof LFEs with a coefficient of ~105 m2/s. We also recognize that rapid migration of LFEs occurred intermittently in many streaks during major ETS episodes. These observations suggest that slow slip transients contain a multitude of smaller, temporally clustered fault slip events whose evolution is controlled by a diffusional process.

The 2016 Mw 7.8 Kaikoura earthquake and its relationship to tremors.

2020 ◽  
Author(s):  
Pierre Romanet ◽  
Florent Aden-Antoniow ◽  
Satoshi Ide
Keyword(s):  
Cross Correlation ◽  
Seismic Energy ◽  
Slow Slip ◽  
Unexpected Events ◽  
Slow Slip Event ◽  
Slow Earthquakes ◽  
Slip Event ◽  
Kaikoura Earthquake ◽  
The Relationship

<p>The relationship between slow earthquake and regular earthquake is fundamental question in seismology. It was already shown that some slow slip event may have led to some megathrust event. In return, passing surface wave from earthquake may also trigger tremors and slow slip event. Documenting these possible triggering effects between slow and fast events is of primary importance to understand them.</p><p>In this study we will focus more particularly on Marlborough region, in a region that was subject to the Mw 7.8 2016 Kaikoura earthquake. Two years before Kaikoura earthquake, we observed a Northeast to Southwest migration of tremors, getting closer to the hypocenter of Kaikoura earthquake. Despite being speculative, this may indicate that a slow slip event is happening shortly before Kaikoura earthquake, which is also supported by a small signal in two GPS stations nearby. After the earthquake, the rate of tremors increased in the region. Studying the relationship between tremors and the Kaikoura earthquake may provide some information on the role of the subduction in the region, as well as provide a new documented interaction of slow earthquakes with a crustal earthquake.</p><p>To detect and locate tremors, we use broadband and shortband velocity traces from the GeoNet network. The traces are bandpass filtered between 2-8Hz, and transform into envelope. Then we apply a classic cross-correlation technic to detect and locate the events. To remove unexpected events (i.e.: earthquakes), we used a criteria base on seismic energy and duration. Finally, we manually check each velocity traces and spectrograms.</p>

Slow Earthquakes Linked Along Dip in the Nankai Subduction Zone: Fig. 1

Science ◽  
2010 ◽  
Vol 330 (6010) ◽  
pp. 1502-1502 ◽  
Author(s):  
Hitoshi Hirose ◽  
Youichi Asano ◽  
Kazushige Obara ◽  
Takeshi Kimura ◽  
Takanori Matsuzawa ◽  
...  
Keyword(s):  
Low Frequency ◽  
Temporal Correlation ◽  
Rupture Zone ◽  
Slow Slip ◽  
Southwest Japan ◽  
Slow Earthquakes ◽  
Slip Event ◽  
Nankai Subduction Zone ◽  
Stress Buildup

We identified a strong temporal correlation between three distinct types of slow earthquakes distributed over 100 kilometers along the dip of the subducting oceanic plate at the western margin of the Nankai megathrust rupture zone, southwest Japan. In 2003 and 2010, shallow very-low-frequency earthquakes near the Nankai trough as well as nonvolcanic tremor at depths of 30 to 40 kilometers were triggered by the acceleration of a long-term slow slip event in between. This correlation suggests that the slow slip might extend along-dip between the source areas of deeper and shallower slow earthquakes and thus could modulate the stress buildup on the adjacent megathrust rupture zone.

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