Detiding DART® Buoy Data for Real-Time Extraction of Source Coefficients for Operational Tsunami Forecasting
- 281 Downloads
US Tsunami Warning Centers use real-time bottom pressure (BP) data transmitted from a network of buoys deployed in the Pacific and Atlantic Oceans to tune source coefficients of tsunami forecast models. For accurate coefficients and therefore forecasts, tides and background noise at the buoys must be accounted for through detiding. In this study, five methods for coefficient estimation are compared, each of which handles detiding differently. The first three subtract off a tidal prediction based on (1) a localized harmonic analysis involving 29 days of data immediately preceding the tsunami event, (2) 68 preexisting harmonic constituents specific to each buoy, and (3) an empirical orthogonal function fit to the previous 25 h of data. Method (4) is a Kalman smoother that uses method (1) as its input. These four methods estimate source coefficients after detiding. Method (5) estimates the coefficients simultaneously with a two-component harmonic model that accounts for the tides. The five methods are evaluated using archived data from 11 DART® buoys, to which selected artificial tsunami signals are superimposed. These buoys represent a full range of observed tidal conditions and background BP noise in the Pacific and Atlantic, and the artificial signals have a variety of patterns and induce varying signal-to-noise ratios. The root-mean-square errors (RMSEs) of least squares estimates of source coefficients using varying amounts of data are used to compare the five detiding methods. The RMSE varies over two orders of magnitude among detiding methods, generally decreasing in the order listed, with method (5) yielding the most accurate estimate of the source coefficient. The RMSE is substantially reduced by waiting for the first full wave of the tsunami signal to arrive. As a case study, the five methods are compared using data recorded from the devastating 2011 Japan tsunami.
KeywordsTsunami forecasting Tsunami source estimation DART® data inversion Tsunameter 2011 Honshu tsunami 2011 Japan tsunami 2011 Tohoku tsunami
This work was funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement No. NA17RJ1232 and is JISAO Contribution No. 2185. This work is also Contribution No. 4089 from NOAA/Pacific Marine Environmental Laboratory. The authors thank George Mungov of NOAA’s National Geophysical Data Center for supplying DART® buoy data and predictions based upon harmonic analyses with 68 sinusoidal constituents. The authors also thank the editor and three anonymous referees for helpful comments.
- Brockwell, P.J., and Davis, R.A. (2002), Introduction to Time Series and Forecasting, 2nd Edition. Springer, 448 p.Google Scholar
- Cartwright, D.E., Spencer, R., and Vassie, J.M. (1987), Pressure variations on the Atlantic equator, J. Geophys. Res. 92(C1), 725–741, doi: 10.1029/JC092iC01p00725.
- Chambers, J.M., Cleveland, W.S., Kleiner, B., and Tukey, P.A. (1983), Graphical Methods for Data Analysis. Wadsworth & Brooks/Cole, 409 p.Google Scholar
- Consoli, S., Recupero, D.R., and Zavarella, V. (2014), A survey of tidal analysis and forecasting methods for tsunami detection, J. Tsunami Soc. Int. 33(1), 1–56.Google Scholar
- Cummins, P.F., Cherniawsky, J.Y., and Foreman, M.G.G. (2001), North Pacific internal tides from the Aleutian Ridge: Altimeter observations and modeling, J. Marine Res. 59(2), 167–191.Google Scholar
- Durbin, J., and Koopman, S.J. (2012), Time Series Analysis by State Space Methods, 2nd Edition. Oxford University Press, 368 p.Google Scholar
- Foreman, M.G.G. (1977, revised 2004), Manual for Tidal Heights Analysis and Prediction. Pacific Marine Science Report. 77–10. Institute of Ocean Sciences, Patricia Bay, 58 pp. http://www.pac.dfo-mpo.gc.ca/science/oceans/tidal-marees/index-eng.htm.
- Gica, E., Spillane, M.C., Titov, V.V., Chamberlin, C.D., Newman, J.C. (2008), Development of the forecast propagation database for NOAA’s Short-term Inundation Forecast for Tsunamis (SIFT). NOAA Tech. Memo. OAR PMEL-139, 89 pp. http://nctr.pmel.noaa.gov/pubs.html.
- González, F.I., Bernard, E.N., Meinig, C., Eblé, M.C., Mofjeld, H.O., and Stalin, S. (2005), The NTHMP tsunameter network, Natural Hazards 35(1), Special Issue, US National Tsunami Hazard Mitigation Program, 25–39.Google Scholar
- Mofjeld, H.O. (2009), Tsunami measurements. In The Sea, Volume 15: Tsunamis (eds. E.N. Bernard and A.R. Robinson), Harvard University Press, Cambridge, MA, pp. 201–235.Google Scholar
- Mofjeld, H.O., Venturato, A.J., González, F.I., Titov, V.V., and Newman, J.C. (2004), The harmonic constant datum method: Options for overcoming datum discontinuities at mixed-diurnal tidal transitions. J. Atmos. Ocean. Tech. 21(1), 95–104.Google Scholar
- Mofjeld, H.O., Whitmore, P.M., Eblé, M.C., González, F.I., and Newman, J.C. (2001), Seismic-wave contributions to bottom pressure fluctuations in the North Pacific-Implications for the DART Tsunami Array. Proceedings of the International Tsunami Symposium 2001 (ITS 2001), Session 5–10, Seattle, WA, 7–10 August 2001, 633–641.Google Scholar
- Mungov, G., Elbé, M., and Bouchard, R (2012), DART ® tsunameter retrospective and real-time data: a reflection on 10 years of processing in support of tsunami research and operations, Pure Appl. Geophys. 170(9–10), 1369–1384, doi: 10.1007/s00024-012-0477-5.
- Munk, W.H., and Cartwright, D.E. (1966), Tidal spectroscopy and prediction, Phil. Trans. Roy. Soc. London, Series A, Mathematical and Physical Sciences 259, 533–581.Google Scholar
- Niiler, P.P., Filloux, J., Liu, W.T., Samelson, R.M., Paduan, J.D., and Paulson, C.A. (1993), Wind-forced variability of the deep eastern North Pacific: Observations of seafloor pressure and abyssal currents, J. Geophys. Res. 98(C12), 22589–22602, doi: 10.1029/93JC01288.
- NOAA Data Management Committee (2008), Tsunami data management: An initial report on the management of environmental data required to minimize the impact of tsunamis in the United States, Version 1.0, 87 pp. http://www.ngdc.noaa.gov/noaa_pubs/index.shtml.
- Papazachos, B.C., Scordilis, E.M., Panagiotopoulos, D.G., Papazachos, C.B., and Karakaisis, G.F. (2004), Global relations between seismic fault parameters and earthquake moment, horizontal.Google Scholar
- Parker, B.P. (2007), Tidal Analysis and Prediction. NOAA Special Publication NOS CO-OPS 3; 378 p.Google Scholar
- Percival, D.B., Denbo, D.W., Elbé, M.C., Gica, E., Mofjeld, H.O., Spillane, M.C., Tang, L., and Titov, V.V. (2011), Extraction of tsunami source parameters via inversion of DART ® buoy data, Natural Hazards 58(1), 567–590, doi: 10.1007/s11069-010-9688-1.
- Percival, D.M., Percival, D.B., Denbo, D.W., Gica, E., Huang, P.Y., Mofjeld, H.O., and Spillane, M.C. (2014), Automated tsunami source modeling using the sweeping window positive elastic net, J. Amer. Stat. Assoc. 109(506), 491–499, doi: 10.1080/01621459.2013.879062.
- Ray, R.D., and Luthcke, S.B. (2006), Tide model errors and GRACE gravimetry: towards a more realistic assessment, Geophys. J. Int. 167(3), 1055–1059, doi: 10.1111/j.1365-246X.2006.03229.x.
- Shumway, R.H., and Stoffer, D.S. (2011), Time Series Analysis and Its Applications with R Examples, 3rd Edition. Springer, 608 p.Google Scholar
- Spillane, M.C., Gica, E., Titov, V.V., Mofjeld, H.O. (2008), Tsunameter network design for the US DART® arrays in the Pacific and Atlantic Oceans. NOAA Tech. Memo. OAR PMEL-143, 165 pp. http://nctr.pmel.noaa.gov/pubs.html.
- Tang, L., Titov, V.V., Bernard, E.N., Wei, Y., Chamberlin, C.D., Newman, J.C., Mofjeld, H.O., Arcas, D., Eble, M.C., Moore, C., Uslu, B., Pells, C., Spillane, M., Wright, L., and Gica, E. (2012), Direct energy estimation of the 2011 Japan tsunami using deep-ocean pressure measurements, J. Geophys. Res. 117(C8), C08008, doi: 10.1029/2011JC007635.
- Titov, V.V. (2009), Tsunami forecasting. In The Sea, Volume 15: Tsunamis (eds. E.N. Bernard and A.R. Robinson), Harvard University Press, Cambridge, MA, pp. 371–400.Google Scholar
- Titov, V.V., González, F.I., Bernard, E.N., Eblé, M.C., Mofjeld, H.O., Newman, J.C., and Venturato, A.J. (2005), Real-time tsunami forecasting: Challenges and solutions, Natural Hazards 35(1), Special Issue, US National Tsunami Hazard Mitigation Program, 41–58.Google Scholar
- Titov, V.V., Mofjeld, H.O., González, F.I., Newman, J.C. (1999), Offshore forecasting of Hawaiian tsunamis generated in Alaskan-Aleutian Subduction Zone. NOAA Tech. Memo. OAR PMEL-114, 22 pp. http://nctr.pmel.noaa.gov/pubs.html.
- Tolkova, E. (2009), Principal component analysis of tsunami buoy record: tide prediction and removal, Dyn. Atmos. Oceans 46(1–4), 62–82, doi: 10.1016/j.dynatmoce.2008.03.001.
- Tolkova, E. (2010), EOF analysis of a time series with application to tsunami detection, Dyn. Atmos. Oceans 50(1), 35–54, doi: 10.1016/j.dynatmoce.2009.09.001.
- Webb, S.C. (1998), Broadband seismology and noise under the ocean, Rev. Geophys. 36(1), 105–142.Google Scholar
- Wei, Y., Chamberlin, C., Titov, V.V., Tang, L., and Bernard, E.N. (2013), Modeling of the 2011 Japan tsunami: Lessons for near-field forecast, Pure Appl. Geophys. 170(6–8), pp. 1309–1331, doi: 10.1007/s00024-012-0519-z.
- Wei, Y., Newman, A.V., Hayes, G.P., Titov, V.V., Tang, L. (2014), Improving tsunami forecast by joint inversion of real time tsunami waveforms and seismic or GPS data: Application to the Tohoku 2011 tsunami, Pure Appl. Geophys. in press.Google Scholar
- Zhao, Z., and Alford, M.H. (2009), New altimetry estimates of mode-1 M2 internal tides in the central North Pacific Ocean, J. Phys. Ocean. 39(7), 1669–1684, doi: 10.1175/2009JPO3922.1.