東京大学 · 地球惑星科学
Yokota教授の研究室は、地震・津波の発生機構を解明するため、地上・海底をカバーする高精度な測位データ(GNSS-A、強震動、津波記録など)を統合的に解析する研究を推進しています。特に、日本海溝・伊豆諸島・千島海溝など、活発なプレート境界域におけるプレート沈み込み帯の変動を、時系列的・空間的変動を捉えることで解明しています。近年では、長期間にわたる海底変位の変動を検出し、慢性的なプレートすべり(SSE)の存在を示すなど、地震予測に資する新しい地殻変動の検出技術を開発しています。
Figures are computed from collected data and may differ slightly.
[1] The 2011 Tohoku earthquake was observed by dense strong motion, teleseismic, geodetic, and tsunami networks. We first inverted each of the datasets obtained by the networks separately, for the rupture process of the earthquake. We then performed checkerboard resolution tests for assessing the resolving power of these datasets. In order to overcome the limited resolutions of the separate inversions and differences in their results, we performed a quadruple joint inversion of all these data to
Various slow earthquakes (SEQs), including tremors, very low frequency events, and slow slip events (SSEs), occur along megathrust zones. In a shallow plate boundary region, although many SEQs have been observed along pan-Pacific subduction zones, SSEs with a duration on the order of a year or with a large slip have not yet been detected due to difficulty in offshore observation. We try to statistically detect transient seafloor crustal deformations from seafloor geodetic data obtained by the Gl
Geodetic transients have been observed in various subduction zones. The 2011 Tohoku earthquake occurred in one of the most active subduction zones globally, the Japan Trench subduction zone (JTSZ). However, no geodetic transient (except afterslip and so on) had been reported in the JTSZ before the Tohoku earthquake. Here we show that a large transient event, with duration longer than any reported previously, occurred in the JTSZ preceding the Tohoku earthquake. We calculate tectonic deformations
Crustal deformation data obtained by geodetic observation networks are foundations in the fields of geodesy and seismology. These data are essential for understanding plate motion and earthquake sources and for simulating earthquake and tsunami scenarios. Although relatively scarce, seafloor geodetic data are particularly important for monitoring the behaviour of undersea interplate boundary regions. Since the mid-1990s, we have been developing the combined Global Navigation Satellite System-Aco
The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) is a seafloor geodetic technique that enables precise global seafloor positioning to detect subseafloor geophysical phenomena. The technique requires a sea surface observation platform that combines GNSS positioning and acoustic ranging. Currently, a survey vessel is used as the platform, which entails substantial financial and human resources costs, which makes increasing observation frequency difficult. It i
We demonstrate the ability of 1‐Hz Global Positioning System (GPS) data to infer a medium‐sized (M6 class) earthquake source process through an inversion study of the 2008 Iwate‐Miyagi Nairiku, Japan, earthquake (M∼6.9). 1‐Hz GPS waveforms for this earthquake are compared, and show good agreement with strong motion waveforms. Ground motions are well recorded at a sufficient number of GPS stations in and around source region, allowing us to perform waveform inversion using 1‐Hz GPS data only. The
The recurring devastating earthquake that occurs in the Nankai Trough subduction zone between the Philippine Sea plate and the Eurasian plate has the potential to cause an extremely dangerous natural disaster in the foreseeable future. Many previous studies have assumed interplate-coupling ratios for this region along the trench axis using onshore geodetic data in order to understand this recursive event. However, the offshore region that has the potential to drive a devastating tsunami cannot b
Abstract Underwater disturbances are the largest error source in Global Navigation Satellite System ‐ Acoustic ranging combination technique (GNSS‐A) seafloor geodetic observation. In particular, the gradient of sound speed structure (SSS) directly affects the horizontal accuracy and needs to be examined. Previous studies have not investigated its temporal change component. In this paper, we verified the assumption that the underwater gradient structure does not change significantly during GNSS‐
The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) is the only geodetic observation method that can precisely detect absolute horizontal and vertical seafloor crustal deformations at the centimetre scale. GNSS-A has detected many geophysical phenomena and is expected to make great contributions to earthquake disaster prevention science and geodesy. However, current observation methods that use vessels and buoys suffer from high cost or poor real-time performan
To monitor ocean and seafloor properties in detail, sensors are generally installed on autonomous underwater vehicles (AUVs). An AUV cannot accurately determine its absolute position and needs to communicate with a sea-surface vehicle. However, sea-surface vehicles cannot perform high-speed observations with high efficiency due to their low mobility and high labor and equipment costs, e.g., vessel charter charges, operator restraint time on the sea surface during observations, etc. From this per
The Global Navigation Satellite System-Acoustic ranging combination technique (GNSS-A) is a recently developed technology to precisely detect seafloor crustal deformation. This method can also estimate km-scale underwater sound speed structure (SSS) as a by-product of monitoring seafloor crustal deformation. This paper evaluates the validity of the spatial gradient and its temporal variation of the SSS estimated by GNSS-A observations off the Kii channel before and after Kuroshio meandering. Acc
We have examined the rupture process of the 2010 Yushu, China, earthquake, which occurred in the eastern Tibetan plateau. Based on the results of centroid location grid searches, the aftershock distribution, and InSAR observations, we first constructed a left-lateral strike-slip bending fault model. We then carried out joint inversions of the teleseismic waveform data and InSAR data using various rupture front velocities. We obtained the optimum source model with a seismic moment of 2.3 × 1019 N
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