Impact of Near-Field, Deep-Ocean Tsunami Observations on Forecasting the 7 December 2012 Japanese Tsunami
Following the devastating 11 March 2011 tsunami, two deep-ocean assessment and reporting of tsunamis (DART®)(DART® and the DART® logo are registered trademarks of the National Oceanic and Atmospheric Administration, used with permission) stations were deployed in Japanese waters by the Japanese Meteorological Agency. Two weeks after deployment, on 7 December 2012, a Mw 7.3 earthquake off Japan’s Pacific coastline generated a tsunami. The tsunami was recorded at the two Japanese DARTs as early as 11 min after the earthquake origin time, which set a record as the fastest tsunami detecting time at a DART station. These data, along with those recorded at other DARTs, were used to derive a tsunami source using the National Oceanic and Atmospheric Administration tsunami forecast system. The results of our analysis show that data provided by the two near-field Japanese DARTs can not only improve the forecast speed but also the forecast accuracy at the Japanese tide gauge stations. This study provides important guidelines for early detection and forecasting of local tsunamis.
Following the devastating 11 March 2011 Japanese tsunami, two papers by NOAA scientists were published: (1) far-field forecast and impact of the tsunami on the Pacific basin (Tanget al. 2012) and (2) the local impact on Japan (Weiet al. 2013). Both of these studies used the "method of splitting tsunami" model that has been previously validated and verified (Synolakiset al. 2008). For the far-field study, a methodology was presented for determining the energy of a tsunami using real-time, deep-ocean assessment and reporting of tsunamis (DART®) data within the NOAA tsunami forecast system (Tanget al. 2012). Results of this study showed that data from DART stations, near the tsunami-generation region, could help to accurately estimate the energy of a tsunami. For the local study, nested tsunami inundation models were developed that used the source information from Tanget al.'s (2012) far-field study as input to simulate the flooding along Japan’s coastline. The modeling results for tsunami inundation in the near-field along 600 km of Japan’s coastline were compared with observed tsunami time series, surveyed tsunami height and run-up, and the extent of tsunami inundation (Weiet al. 2013). This comparison indicated inundation-modeling accuracy was approximately 85.5 % for the affected area between latitudes 36–41°N of Japan’s coastline.
The existing DART network near Japan, consisting of DART stations owned by the United States and Russia (see Fig. 1), was not completely operational. The two DART stations closest to the 2011 tsunami source, namely DART stations 21418 (US) and 21401 (Russia), were not operational on 7 December 2012. However, US and Russian DART stations, namely 21413, 21415, 21416, and 21402, located to the southeast and northeast of the earthquake epicenter (see Fig. 1), were operational on 7 December 2102. In summary, six DART stations in the region of Japan, owned and operated by Japan, Russia, and the US, provided valuable measurements for us to constrain the tsunami source of the 7 December 2012 event.
2 The Tsunami Source of 7 December 2012 Earthquake
According to the USGS, the 7 December 2012 Mw 7.3 earthquake east of Sendai, Japan occurred as a result of reverse faulting within the oceanic lithosphere of the Pacific plate, approximately 20 km east of the plate boundary between the Pacific and North America plates where three Pacific plates subduct beneath Japan (see Fig. 1). At the epicenter of this earthquake, the Pacific plate moves west–northwestward with respect to the North America plate at a velocity of approximately 83 mm/year (http://earthquake.usgs.gov/earthquakes/map/). The Harvard Centroid Moment Tensor (CMT) project reported two earthquakes, the first, a thrust fault earthquake of Mw 7.2, followed 12 s later by a normal fault earthquake of equal magnitude approximately at the same location (http://www.globalcmt.org/).
Tsunami forecast sources constrained from 4-DARTs and 6-DARTs
4-DART constrained coefficient (m)
6-DART constrained coefficient (m)
By using the Japanese retrospective DART data in addition to the data from the other four stations, a second source was derived (source 2 in Table 1). A good solution was found when the model time series were shifted 2 min behind (red line in Fig. 2). It should be noted each unit source has a spatial resolution of 100 by 50 km. If an earthquake occurs in between of two adjacent unit sources, the model could introduce a travel time error of 2–4 min, depending on the orientation and water depth. Figure 2 shows that the 6-DART source (red line) gives an improved fit to the observations, particularly the period and amplitude of the first wave at the two Japanese DART stations.
Table 1 summarizes the source parameters and coefficients for the 4- and 6-DART inverted sources. A positive source coefficient implies an initial tsunami triggered by a thrust fault rupture, while a negative coefficient indicates the cause of a normal-fault rupture. Clearly, the source coefficients obtained through both inversions indicate the complexity of the 7 December 2012 event that involved both normal- and thrust-fault ruptures, as indicated by the CMT solutions.
Development in processing technology and the availability of robust seismic measurements have identified multiple source mechanisms in recent tsunamis. For example, the 29 September 2009 Samoa tsunami was caused by a M8.1 normal faulting in the outer trench followed by two M7.8 under thrusting sub events (Layet al. 2010), or thrust-fault triggered outer-rise earthquake (Beavanet al. 2010). The 12 January 2010 Haiti tsunami may have been generated by complex rupture from both strike-slip and thrust faults (Hayeset al. 2011; Calaiset al. 2011). In addition, the 11 March 2011 Japan tsunami may have even involved contribution from a seabed failure that was responsible for the high run-up along Sanriku’s coasts (Grilliet al. 2012). At present, these earthquake complexities are hard to identify until rigorous, post-event, seismic analysis is performed. However, these complex earthquake processes that produce tsunamis are reflected in the tsunami wave measurements, and can be estimated through inversion of the recorded tsunami time series in real-time (Titov2009; Weiet al. 2008). The advantage of DART-inversion allows the models to capture the characteristics of the tsunami, including its energy content, in real time necessary for effective warnings (Tanget al. 2012).
3 Near-Field Inundation Model
During the 7 December 2012 event, JMA’s tsunami information bulletin No. 8 described the recorded wave amplitudes (initial and maximum) at Ayukawa and Sendai-Ko tide stations (the time series of observation at Ayukawa and Sendai-Ko are not available for us to be used in this study). The bulletin reported the initial waves were both depressions, −0.3 and −0.1 m at Ayukawa and Sendai-Ko, respectively. Our model computation at these two locations (Fig. 4b) fits well with the observations, although the amplitude of the depression is slightly larger than recorded at Sendai-Ko. The model results indicate that the maximum tsunami amplitude near Ayukawa is >0.7 m, and 0.4 m at Sendai-Ko, which both agree with the reported values, 1 m at Ayukawa and 0.4 m at Sendai-Ko. These results further validate the tsunami energy projection shown in Fig. 4a that the highest tsunami waves are focusing on the coastline of Sendai Bay between Soma and Ayukawa. More interestingly, the focusing and bifurcation of the tsunami energy towards Sendai Bay (Fig. 4a) can be attributed to an interaction of two factors: the tsunami energy focusing from a strip source (Kânoğluet al. 2013), and the energy focusing and bifurcation caused by bathymetric features over the continental shelf. These results highlight the value of obtaining the correct source estimate from offshore tsunami measurements.
It is worth noting that all of our model results for tide gage comparison were extracted from offshore points close to the tide gage locations. Due to the lack of accurate tide gage coordinates, the model might underestimate the wave amplitudes recorded at the tide gages. The lack of accurate bathymetric and topographic data can also affect the modeling results, since many coastal structures near tide gages, such as breakwaters and seawalls, are not reflected in the 50-m resolution model (Weiet al. 2013).
Hence, we are able to conclude that the two Japanese DART stations performed as designed during a tsunami and improved the accuracy of the tsunami source. The more accurate tsunami source led to more accurate model simulations of tsunami dynamics along Japan’s coastlines.
4.1 Our Analysis Leads Us to Two Important Findings
4.1.1 Improvements in Tsunami Forecast Accuracy in the Near and Far-Fields
The two recently deployed Japanese DART stations provided data that improved tsunami forecasting in the near and far-fields. Near-field improvements can be seen in Fig. 4 where the tsunami amplitude time series (represented by red lines) shows a better agreement to the observations at three tide gauges. Specifically at Ofunato, the shorter wave period of the model amplitude time series and the 15 cm maximum amplitude and 15 cm maximum drawdown serve as an accurate forecast of maximum and minimum amplitude range. The model results, however, did not simulate well the second tsunami packet that arrived about 1 h after the first energy packet. Improvements can also be seen in Fig. 2 in model simulations at the six DART stations that recorded the tsunami. For the two Japanese DART stations, one can see a better agreement between model results and observations at DART JP2 and JP1. Specifically, the 6-DART derived source, represented by the amplitude time series (red line), has a a shorter wave period that matches the observations of the first tsunami wave at these two stations. This shorter-period wave also improves the match with observations at the far-field DARTs, namely 21413, 21415, 21416, and 21402. At 21416 and 21402, northwest of the tsunami source location, the amplitude time series (red line) agrees well with the observed amplitudes of the initial wave. However, at the southernmost DART station, 21413, the amplitude agreement is not as good. Overall, the 6-DART source provides a better simulation of the observed tsunami time series at six different DART stations and at least one coastal tide gauge. The 6-DART source contained 27 % more energy than the 4-DART source, and using this source provided better model agreement with observations at five tide gauges.
4.1.2 Reduced Detection Time Leads to a Faster Assessment of the Tsunami’s Destructive Power
The greatest benefit of the recently deployed Japanese DART stations was the close proximity to the tsunami source. The locations of JP2 and JP1 enabled the detection of the 7 December 2012 Japanese tsunami 11–20 min after generation. The fact that the tsunami was only 1.0 cm in amplitude at DART JP2 meant that no destructive tsunami had been generated. In Fig. 1, which illustrates the comparison between the devastating 2011 and the non-destructive 2012 tsunamis, the tsunami amplitude at DART station 21413 in 2011 was measured to be 78 cm, or nearly 80 times the amplitude the 2012 tsunami. Five minutes later, the 0.5 cm amplitude tsunami was detected at DART station JP1, confirming that no destructive tsunami was approaching Japan’s coastline.
At 08:51:46 UTC (33 min after the earthquake origin time) JMA had a full tsunami waveform from JP2 as shown in the red line of the lower left panel of Fig. 2. At 08:52:46 UTC (34 min after the earthquake origin time), JMA had a full tsunami waveform from JP1 as shown in the red line of the lower right panel of Fig. 2. Visual analysis of these waveforms would have confirmed that the 7 December 2012 tsunami was not destructive and posed no flooding hazard to Japan’s coastline. Since the tsunami arrived at the Ofunato tide gauge 40 min after the earthquake origin time, an accurate forecast could have been provided between 7 and 23 min before the tsunami’s arrival at Ofunato. Such fast, accurate assessments of tsunami danger are the foundation blocks in building confidence in tsunami warning accuracy.
The 7 December 2012 tsunami has provided a good test of the tsunami mode performance for the newly deployed Japanese DART stations JP1 and JP2. The bottom pressure sensor worked within stated accuracy while the tsunami reporting mode worked properly in acquiring and sending near real-time data to JMA within the designed time frames. Data from DART stations JP1 and JP2 have been analyzed within the NOAA forecast system and found to be working properly for tsunami forecast and warning applications. The Japanese data from DART stations JP1 and JP2 improved the accuracy of the tsunami source derived from the NOAA forecast system. This more accurate source was used to improve forecast accuracy at coastal tide gauge in Ofunato, Japan. The inclusion of DART stations JP1 and JP2 into the JMA tsunami warning system will improve tsunami forecast speed and accuracy.
4.2 Future Opportunities
The addition of two deep-water tsunami detectors by Japan to the global network of DART stations (see Fig. 3, black triangles) is an excellent example of international cooperation among tsunami threatened nations. By sharing data from these two Japanese DART stations, the Pacific coastal nations benefit from faster detection of tsunamis and more accurate forecasts. Further, the tsunami research community benefits from more data available immediately following tsunami generation. We encourage other nations to follow the leads of Australia, Chile, India, Japan, Russia, Thailand, and the United States in deploying DART stations off their coastlines and sharing their data with all nations. Such international cooperation leads to faster and more accurate tsunami warnings, which, in turn, save lives from the destructive power of tsunamis.
Produced by Science Applications International Corporation (SAIC) using DART® Technology.
We thank Rob Lawson of SAIC for providing 15 s data from DART stations 21436 (JP1) and 21437 (JP2); Michael Spillane and Jean C. Newman for assistance with the propagation database. We are grateful for UNESCO and IOC sea level station monitoring facility (http://www.ioc-sealevelmonitoring.org/) that provide access to the tide gage data along Japan’s coastline. We also acknowledge the hard work of JMA, Toho Mercantile, and Oyo Corporation for initiating and completing the purchase of DART stations 21436 and 21437. Special acknowledgement goes to the SAIC deployment team who successfully deployed two DART buoys in the hostile, dangerous, November seas off Japan’s coastline. This publication was (partially) funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement No. NA10OAR4320148, Contribution No. 2116; PMEL Contribution 4009.
- Beavan, J., X. Wang, C. Holden, K. Wilson, K. Power, G. Prasetya, M. Bevis, and R. Kautoke, (2010), Near-simultaneous great earthquakes at Tongan megathrust and outer rise in September 2009, Nature, 466, 959–963.Google Scholar
- Calais, E., A. Freed, G. Mattioli, F. Amelung, S. Jónsson, P. Jasma, S.-H. Hong, T. Dixon, C. Prépetit, R. Momplaisir (2011), Transpressional rupture of an unmapped fault during the 2010 Haiti earthquake, Nature Geoscience, 3(11), 794–799.Google Scholar
- Grilli, S.T., J. Harris, Tappin, D.R., Masterlark, J.T. Kirby, F. Shi and G. Ma (2012), Modeling of the Tohoku-oki 2011 tsunami coastal hazard: effects of a mixed co-seismic and seabed failure source, EOS Trans. AGU, 93(52), Fall Meet. Suppl., Abstract NH42A-06.Google Scholar
- Hayes, G.P., R.W. Briggs, A. Sladen, E.J. Fielding, C. Prentice, K. Hudnut, P. Mann, F.W. Taylor, A.J. Crone, R. Gold, T. Ito, and M. Simmons (2011), Complex rupture during the 12 January 2010 Haiti earthquake, Nature Geoscience, 3(11):800–805.Google Scholar
- Kânoğlu U., V.V. Titov, B. Aydın, C. Moore, T.S. Stefanakis, H. Zhou, M. Spillane, C.E. Synolakis (2013), Focusing of long waves with finite crest over constant depth, Proc R Soc A 20130015. http://dx.doi.org/10.1098/rspa.2013.0015.
- Lay, T., C.J. Ammon, H. Kanamori, L. Rivera, K.D. Koper and A.R. Hutko (2010), The 2009 Samoa-Tonga great earthquake triggered doublet, Nature, 466, 964–968, doi:10.1038/nature09214.
- Synolakis, C.E., Bernard, E.N., Titov, V.V., Kanoglu, U., and Gonzalez, F. (2008), Validation and verification of tsunami numerical models. Pure and Applied Geophysics 165(11–12), 2197–2228. doi:10.1007/s00024-004-0427-y.
- Tang, L., V.V. Titov, E. Bernard, Y. Wei, C. Chamberlin, J.C. Newman, H. Mofjeld, D. Arcas, M. Eble, C. Moore, B. Uslu, C. Pells, M.C. Spillane, L.M. Wright, and E. Gica (2012), Direct energy estimation of the 2011 Japan tsunami using deep-ocean pressure measurements, J. Geophys. Res., 117, C08008, doi:10.1029/2011JC007635.
- Titov, V.V. (2009), Tsunami forecasting, Chapter 12 in The Sea, Volume 15: Tsunamis, Harvard University Press, Cambridge, MA and London, England, 371–400.Google Scholar
- Wei, Y., E.N. Bernard, L. Tang, R. Weiss, V.V. Titov, C. Moore, M. Spillane, M. Hopkins and U. Kânoğlu (2008), Real-time experimental forecast of the Peruvian tsunami of August 2007 for U.S. coastlines, Geophys. Res. Lett. 35, L04609, doi:10.1029/2007GL032250.
- Wei, Y., C. Chamberlin, V.V. Titov, L. Tang, and E.N. Bernard (2013), Modeling of 2011 Japan Tsunami—lessons for near-field forecast, Pure Appl. Geophys., 170, 1309–1331, doi:10.1007/s00024-012-0519-z.
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