Explore the vast range of titles available.

The large tsunami of the 2011 Tohoku‐Oki earthquake was clearly recorded by the ocean bottom pressure and GPS wave gauges deployed in and around Japan. We estimated the initial tsunami water height distribution by inversion analysis of the waveforms based on dispersive tsunami simulations. The distribution is characterized by a peak height of 8 m located near the trench and the high‐water (>2m) region extending landward with a width of ∼100 km. A series of numerical simulations suggests that a relatively steep peak located near the trench is necessary in order to simultaneously reproduce the dispersive wave at a far‐field station and the near‐field waveforms. Furthermore, we estimated the coseismic slip distribution at the plate boundary, which indicates that large slip (∼30 m) occurred at a depth of 20 km, which corresponds to a large slip deficit area in the interseismic period. Another slip (∼25 m) occurred at the shallower part (<10 km) during the rupture. Key Points Tsunami analysis reveals the source of the 2011 Tohoku‐Oki earthquake Dispersive wave and nearfield records provide high‐resolution source estimation Large slip occurred at a deep location and a shallow location near the trench

Sustaining an accurate, timely, and global tsunami forecast system remains a challenge for scientific communities. To this end, various viable geophysical monitoring devices have been deployed. However, it is difficult to implement new observation networks in other regions and maintaining the existing systems is costly. This study proposes a new and complementary approach to monitoring the tsunami using existing moving platforms. The proposed system consists of a radar altimeter, Global Navigation Satellite Systems receiver, and an adequate communication link on airborne platforms such as commercial airplanes, drones, or dedicated high-speed aircraft, and a data assimilation module with a deterministic model. We demonstrated, through twin-data experiment, the feasibility of the proposed system in forecasting tsunami at the Nankai Trough of Japan. Our results demonstrated the potential of an airborne tsunami observation as a viable future technology through proxy observations and rigorous numerical experiments. The wide coverage of the tsunamigenic regions without a new observation network is an advantage while various regulatory constraints need to be overcome. This study offered a novel perspective on the developments in tsunami detection and forecasting technology. Such multi-purpose observation using existing platforms provides a promising and practical solution in establishing sustainable observational networks.

Ocean bottom pressure-gauge (OBP) records play an essential role in seafloor geodesy. Oceanographic fluctuations in OBP data, however, pose as a significant noise source in seafloor transient crustal deformation observations, including slow slip events (SSEs), making it crucial to evaluate them quantitatively. To extract the significant fluctuation phenomena common to multiple observation networks, including oceanographic fluctuations and tectonic signals, we applied principal component analysis (PCA) to the 3-year Dense Oceanfloor Network System for Earthquakes and Tsunamis (DONET) OBP time series for 40 stations during 2016–2019. PCA could separate several oceanographic signals based on the characteristics of their spatial distributions, although evident transient tectonic signals could not be confirmed from the observed pressure records during this observed period. The spatial distribution of the first four principal components (PCs) reflected the common component, inclined component along sea depth, longitude component, and parabola-like pattern, respectively. By subtracting each PC (in particular, PC-2 and PC-4) from the time series, we could significantly reduce the sea depth dependence of OBP records, which has been highlighted in several previous studies and is also evident in this region. We interpreted PCs 2–4 as the reflection of the strength and meandering of ocean geostrophic currents based on a comparison with the PC spatial distribution of the numerical oceanographic models. In addition, to evaluate the ability of PCA to separate transient tectonic signal from OBP time series, including oceanographic fluctuations, we conducted a synthetic ramp assuming an SSE by rectangular fault and then applied PCA. The assumed synthetic tectonic signal could be separated from the oceanographic signals and included in the principal component independently depending on its amplitude, suggesting that the spatial distribution of each PC would change if the amplitude of the synthetic signal were sufficiently large. We propose a transient event-detection method based on the spatial distribution difference of a specific PC with or without a tectonic signal. We used the normalized inner product (NIP) between these PCs as the indicator of their similarities. This method can detect transient tectonic signals more significantly than the moment-magnitude scale of 5.9 from OBP records.

We investigated temperature records associated with seafloor pressure observations at eight stations that experienced the 2011 Mw 9 Tohoku earthquake near its epicenter. The temperature data were based on the temperature measured inside the pressure transducer. We proposed a method to estimate ambient water temperature from the internal temperature using an equation of heat conduction. The estimated seafloor water temperature showed remarkable anomalies, especially increases several hours after the Mw 9 earthquake. A station of P03 (sea depth of 1.1 km) showed an abrupt temperature increase of + 0.19 °C that occurred ~ 3 h after the earthquake, which lasted for several hours. At stations of GJT3 (sea depth of 3.3 km) and TJT1 (sea depth of 5.8 km), there were abrupt temperature anomalies of + 0.20 °C and + 0.10 °C that began to occur 3–4 h after the earthquake. These anomalies both decayed to their original levels over a few tens of days. During the decay processes, only TJT1 showed several intermittent temperature rises. A water temperature anomaly within + 0.03 °C was found up to ~ 500 m above TJT1 2 weeks after the earthquake. There was no significant anomaly at the other five stations. Processes to cause these seafloor temperature anomalies were discussed. The temperature anomaly of P03 was reasonably caused by a tsunami-generated turbidity current, as also suggested by a previous study. Meanwhile, we proposed a scenario that the abrupt temperature anomalies of GJT3/TJT1 and the intermittent anomalies of TJT1 were caused by warm water discharges from the subseafloor. The pathways of the warm water were probably composed of the branch normal fault between GJT3 and TJT1, the reverse fault near TJT1, the backstop interface, and perhaps reverse faults at the frontal prism. The proposed scenario was almost compatible with other studies based on epicentral observations. We estimated the heat properties of the initial temperature anomalies of GJT3/TJT1. The estimated heat source might be explained by that most of the geothermal fluids trapped in those fault pathways were discharged to the seafloor immediately after the earthquake. The onsets of the subsequent intermittent anomalies of TJT1 were possibly activated by low or falling ocean tidal loading.

We have explored tsunami current signals in maritime Automatic Identification System (AIS) data during the 2011 Tohoku, Japan, tsunami. The AIS data were investigated in detail taking into account ship motion and response to tsunami current. Ship velocity derived from AIS data was divided into two components in terms of the ship heading: heading-normal and heading-parallel directions. The heading-normal velocity showed good agreement with the simulated tsunami current, as mentioned in our former research. Here, we found the heading-normal velocity was contaminated by non-tsunami noises that were mostly related to the ship yaw motion around the pivot point. The noises due to the yaw motion were reasonably corrected in the heading-normal velocity. The corrected heading-normal velocity clearly showed better agreement with the simulated tsunami current. Although the heading-parallel velocity is basically the navigation speed, and is mostly controlled by ships’ captain, we could find the heading-parallel velocity was also drifted by tsunami currents. The corrected heading-normal velocity was still a ship response to the tsunami current. Based on an equation of a ship response to tsunami currents, we numerically estimated tsunami current from the corrected heading-normal velocity. We could find very slight improvements in estimating the tsunami currents, which indicated that this operation possibly worked as a secondary correction. Tsunami currents of tens of centimeters per second are expected to be suitably detected using AIS based on discussion on detection limit.

Tsunami propagation simulation over the full-global ocean with a finite-difference method is carried out using a grid rotation transformation in a latitude–longitude coordinate system. Two singular points (North/South Poles) that are antipodes with each other in the latitude–longitude coordinate are both moved to land using the grid rotation transformation. The moved singular points are also antipodes with each other. We provide algebra to represent the grid rotation and propose two candidates of the moved singular points for practical use. One is that the computational North Pole is moved to China, and the other is the computational pole moved to Greenland. We carry out tsunami propagation simulation over the global ocean for the different candidates of the moved singular points and evaluate numerical errors due to the grid rotation transformation. The numerical errors are found to be more reduced with finer resolution of the spatial grid for the simulation. When the spatial resolution is fixed, the numerical errors are reduced over most regions for the case with the computational North Pole moved to Greenland, more than the case with the pole moved to China. We indicate that the Coriolis force effect on the tsunamis that was expected to be minor even in far fields becomes significant after long propagation (>~1 day).

On December 7, 2012, an earthquake occurred within the Pacific Plate near the Japan Trench, which was composed of deep reverse- and shallow normal-faulting subevents (Mw 7.2 and 7.1, respectively) with a time interval of ~10 s. It had been known that the stress state within the plate was characterized by shallow tensile and deep horizontal compressional stresses due to the bending of the plate (bending stress). This study estimates the fault model of the doublet earthquake utilizing tsunami, teleseismic, and aftershock data and discusses the stress state within the incoming plate and spatiotemporal changes seen in it after the 2011 Tohoku-Oki earthquake. We obtained the vertical extents of the fault planes of deep and shallow subevents as ~45–70 km and ~5 (the seafloor)–35 km, respectively. The down-dip edge of the shallow normal-faulting seismic zone (~30–35 km) deepened significantly compared to what it was in 2007 (~25 km). However, a quantitative comparison of the brittle strength and bending stress suggested that the change in stress after the Tohoku-Oki earthquake was too small to deepen the down-dip end of the seismicity by ~10 km. To explain the seismicity that occurred at a depth of ~30–35 km, the frictional coefficient in the normal-faulting depth range required would have had to be ~0.07 ≤ μ ≤ ~0.2, which is significantly smaller than the typical friction coefficient. This suggests the infiltration of pore fluid along the bending faults, down to ~30–35 km. It is considered that the plate had already yielded to a depth of ~35 km before 2011 and that the seismicity of the area was reactivated by the increase in stress from the Tohoku-Oki earthquake.

A magnitude 7.3 foreshock occurred at the subducting Pacific plate interface on March 9, 2011, 51 h before the magnitude 9.0 Tohoku earthquake off the Pacific coast of Japan. We propose a coseismic and postseismic afterslip model of the magnitude 7.3 event based on a global positioning system network and ocean bottom pressure gauge sites. The estimated coseismic slip and afterslip areas show complementary spatial distributions; the afterslip distribution is located up‐dip of the coseismic slip for the foreshock and northward of hypocenter of the Tohoku earthquake. The slip amount for the afterslip is roughly consistent with that determined by repeating earthquake analysis carried out in a previous study. The estimated moment release for the afterslip reached magnitude 6.8, even within a short time period of 51h. A volumetric strainmeter time series also suggests that this event advanced with a rapid decay time constant compared with other typical large earthquakes. Key Points Afterslip located in up‐dip extension of coseismic slip of foreshock Time series data indicate rapid decay time constants Aftershocks triggered by strain may have nucleated the Tohoku earthquake

We investigated ship navigation records known as Automatic Identification System (AIS) data near the source region of the 2011 Tohoku, Japan, tsunami. The AIS data of 16 ships in the offshore navigation could be compiled by about 40 min after the tsunami generation. Most of the AIS data showed notable deviation of the ship heading from the course over ground during the tsunami passage. There was good agreement in terms of amplitude/phase between the ship velocity and the simulated tsunami velocity in the direction normal to the ship heading. An equation of motion due to wave drag and inertia forces was examined for an offshore movable floating body. We explain that the ship movement in the direction normal to the heading immediately responds to the tsunami current, and relative velocity between the ship and the tsunami current asymptotically become zero. This indicates the movement velocity of navigating ships in the direction normal to the heading derived from AIS data will work as an offshore tsunami current meter. We examined the AIS data during the 2011 Tohoku tsunami and showed these data could be useful for tsunami source estimation and forecast. The AIS data in the current framework will possibly be a crowd-sourced tool for monitoring offshore tsunami current and tsunami forecast.

We have developed a near-field tsunami forecast system based on an automatic centroid moment tensor (CMT) estimation using regional broadband seismic observation networks in the regions of Indonesia, the Philippines, and Chile. The automatic procedure of the CMT estimation has been implemented to estimate tsunamigenic earthquakes. A tsunami propagation simulation model is used for the forecast and hindcast. A rectangular fault model based on the estimated CMT is employed to represent the initial condition of tsunami height. The forecast system considers uncertainties due to two possible fault planes and two possible scaling laws and thus shows four possible scenarios with these associated uncertainties for each estimated CMT. The system requires approximately 15 min to estimate the CMT after the occurrence of an earthquake and approximately another 15 min to make the tsunami forecast results including the maximum tsunami height and its arrival time at the epicentral region and near-field coasts available. The retrospectively forecasted tsunamis were evaluated by the deep-sea pressure and tide gauge observations, for the past eight tsunamis ( M w 7.5–8.6) that occurred throughout the regional seismic networks. The forecasts ranged from half to double the amplitudes of the deep-sea pressure observations and ranged mostly within the same order of magnitude as the maximum heights of the tide gauge observations. It was found that the forecast uncertainties increased for greater earthquakes (e.g., M w  > 8) because the tsunami source was no longer approximated as a point source for such earthquakes. The forecast results for the coasts nearest to the epicenter should be carefully used because the coasts often experience the highest tsunamis with the shortest arrival time (e.g., <30 min).