Extraction of tsunami source coefficients via inversion of DART \circledR^{\circledR} buoy data

The ability to accurately forecast potential hazards posed to coastal communities by tsunamis generated seismically in both the near and far field requires knowledge of so-called source coefficients, from which the strength of a tsunami can be deduced. Seismic information alone can be used to set the source coefficients, but the values so derived reflect the dynamics of movement at or below the seabed and hence might not accurately describe how this motion is manifested in the overlaying water column. We describe here a method for refining source coefficient estimates based on seismic information by making use of data from Deep-ocean Assessment and Reporting of Tsunamis (DART ^\circledR^{\circledR}) buoys (tsunameters). The method involves using these data to adjust precomputed models via an inversion algorithm so that residuals between the adjusted models and the DART ^\circledR^{\circledR} data are as small as possible in a least squares sense. The inversion algorithm is statistically based and hence has the ability to assess uncertainty in the estimated source coefficients. We describe this inversion algorithm in detail and apply it to the November 2006 Kuril Islands event as a case study.     

Field Survey of the March 28, 2005 Nias-Simeulue Earthquake and Tsunami

On the evening of March 28, 2005 at 11:09?p.m. local time (16:09 UTC), a large earthquake occurred offshore of West Sumatra, Indonesia. With a moment magnitude (M _w) of 8.6, the event caused substantial shaking damage and land level changes between Simeulue Island in the north and the Batu Islands in the south. The earthquake also generated a tsunami, which was observed throughout the source region as well as on distant tide gauges. While the tsunami was not as extreme as the tsunami of December 26th, 2004, it did cause significant flooding and damage at some locations. The spatial and temporal proximity of the two events led to a unique set of observational data from the earthquake and tsunami as well as insights relevant to tsunami hazard planning and education efforts.     

Deterioration in the accuracy of GPS system positioning due to the effect of ionospheric bubbles

The state of the ionosphere affects the operational stability of satellite radio navigation systems. The dense network of GEONET GPS sites on the territory of Japan allows to conduct a thorough investigation of the stability of system operation at mid-latitudes in different heliogeophysical conditions. This paper considers deterioration in the accuracy of GPS system positioning due to the effect of a large-scale ionospheric disturbance (an ionospheric bubble) over Japan on February 12, 2000.     

Ionospheric super-bubble effects on the GPS positioning relative to the orientation of signal path and geomagnetic field direction

Using GPS data of the Japanese network GEONET, we analyze occurrence of GPS-phase slips and positioning errors during the geomagnetic storm of February 12, 2000. Although the storm was not intensive, registering a minimum Dst excursion of −133 nT and a maximum Kp = 6.7 value, it attracted the attention of researchers because of the appearance of a super-bubble at mid-latitudes. We identified numerous GPS-phase slips in the area of the super-bubble. By the time of the bubble’s appearance, a total of 33% of GPS receivers experienced positioning errors of more than 500 m. Around 13:00 UT, the positioning quality was worse than 100 m almost all of Japan. We also found that the occurrence of phase slips of the satellite signals depends on the angle γ between the receiver-satellite line of sight and geomagnetic field lines. The maximum value of GPS-phase slips corresponds to γ = 0° and 90°. For the satellites positioned close to the magnetic zenith region, the density of phase slips reached 32%. In addition to carrier-phase slips, the super-bubble caused sharp increases in positioning errors of several hundred meters at receiver locations below 38°N latitude. As a result, precise positioning was not possible for about 2 h.     

How well do we understand production of 36Cl in limestone and dolomite?

We have evaluated all parameters for the calculation of cosmogenic ³⁶Cl production rates and thus surface exposure ages in dolomite and limestone. We found that we can use either of both published negative muon stopping rates until more information is available. The largest uncertainty of the age estimation in the upper meter of rock comes from the ³⁶Cl production rate from Ca spallation and, in the case of 50–100 ppm Cl content, from the production rate of epithermal neutrons, which we estimate at 760 ± 150 neutrons/g_air/yr (1σ). For a sample with representative amounts of Ca and Cl (20 wt% Ca and 50 ppm Cl, or 40 wt% Ca and 100 ppm Cl), the age can be calculated with a precision of 7–10% in the top 1.5 m of the depth profile. Further improvement of ³⁶Cl calculations depends on new calibration of ³⁶Cl production from Ca spallation, re-evaluation of ³⁶Cl production by low-energy neutron capture on ³⁵Cl, as well as of the muon flux and muon capture based on the most recent measurement data.