Advanced tsunami detection and forecasting by radar on unconventional airborne observing platforms.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
12 02 2020
Historique:
received: 23 10 2019
accepted: 15 01 2020
entrez: 14 2 2020
pubmed: 14 2 2020
medline: 14 2 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 32051457
doi: 10.1038/s41598-020-59239-1
pii: 10.1038/s41598-020-59239-1
pmc: PMC7016180
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

2412

Références

Gonzalez, F. I. et al. The NTHMP tsunameter network. Natural Hazards 35(1), 25–39 (2005).
doi: 10.1007/s11069-004-2402-4
Kaneda, Y. et al. Development and application of an advanced ocean floor network system for megathrust earthquakes and tsunamis. In Seafloor Observatories, Springer: Berlin, Heidelberg, Germany, 643–662 (2015).
doi: 10.1007/978-3-642-11374-1_25
Kanazawa, T. Japan Trench earthquake and tsunami monitoring network of cable-linked 150 ocean bottom observatories and its impact to earth disaster science. In Underwater Technology Symposium (UT), 2013 IEEE International (pp. 1–5). IEEE (2013).
Barnes, C. R., Best, M. M. & Zielinski, A. The NEPTUNE Canada regional cabled ocean observatory. Technology (Crayford, England), 50(3) (2008).
Kawai, H., Satoh, M., Kawaguchi, K. & Seki, K. Characteristics of the 2011 Tohoku tsunami waveform acquired around Japan by NOWPHAS equipment. Coastal Engineering Journal 55(03), 1350008 (2013).
doi: 10.1142/S0578563413500083
Godin, O. A., Irisov, V. G., Leben, R. R., Hamlington, B. D. & Wick, G. A. Variations in sea surface roughness induced by the 2004 Sumatra-Andaman tsunami. Natural Hazards and Earth System Science 9, 1135–1147 (2009).
doi: 10.5194/nhess-9-1135-2009
Song, Y. T., Fukumori, I., Shum, C. K. & Yi, Y. Merging tsunamis of the 2011 Tohoku‐Oki earthquake detected over the open ocean. Geophysical Research Letters 39, L05606 (2012).
Stosius, R., Beyerle, G., Helm, A., Hoechner, A. & Wickert, J. Simulation of space-borne tsunami detection using GNSS-Reflectometry applied to tsunamis in the Indian Ocean. Natural Hazards and Earth System Sciences 10, 1359–1372 (2010).
doi: 10.5194/nhess-10-1359-2010
Foster, J. H., Brooks, B. A., Wang, D., Carter, G. S. & Merrifield, M. A. Improving tsunami warning using commercial ships. Geophysical Research Letters 39, L09603 (2012).
doi: 10.1029/2012GL051367
Inazu, D., Waseda, T., Hibiya, T. & Ohta, Y. Assessment of GNSS-based height data of multiple ships for measuring and forecasting great tsunamis. Geoscience Letters 3, 25 (2016).
doi: 10.1186/s40562-016-0059-y
Tsushima, H., Hino, R., Ohta, Y., Iinuma, T. & Miura, S. tFISH/RAPiD: Rapid improvement of near‐field tsunami forecasting based on offshore tsunami data by incorporating onshore GNSS data. Geophysical Research Letters 41(10), 3390–3397 (2014).
doi: 10.1002/2014GL059863
Gica, E., Spillane, M. C., Titov, V., Chamberlin, C. D. & Newman, J. C. Development of the forecast propagation database for NOAA’s Short-term Inundation Forecast for Tsunamis (SIFT). NOAA Technical Memorandum OAR PMEL 139, 89 (2008).
Maeda, T., Obara, K., Shinohara, M., Kanazawa, T. & Uehira, K. Successive estimation of a tsunami wavefield without earthquake source data: A data assimilation approach toward real‐time tsunami forecasting. Geophysical Research Letters 42(19), 7923–7932 (2015).
doi: 10.1002/2015GL065588
Gusman, A. R. et al. Tsunami data assimilation of Cascadia seafloor pressure gauge records from the 2012 Haida Gwaii earthquake. Geophysical Research Letters 43(9), 4189–4196 (2016).
doi: 10.1002/2016GL068368
Sheehan, A. F., Gusman, A. R. & Satake, K. Improving forecast accuracy with tsunami data assimilation: The 2009 Dusky Sound, New Zealand, tsunami. Journal of Geophysical Research: Solid Earth 124, 566–577 (2019).
Wang, Y., Satake, K., Sandanbata, O. & Su, H. Tsunami data assimilation of cabled ocean bottom pressure records for the 2015 torishima volcanic tsunami earthquake. Journal of Geophysical Research: Solid Earth 124(10), 10413–10422 (2019).
Mulia, I. E., Inazu, D., Waseda, T. & Gusman, A. R. Preparing for the future Nankai Trough tsunami: A data assimilation and inversion analysis from various observational systems. Journal of Geophysical Research: Oceans 122(10), 7924–7937 (2017).
Hirobe, T. et al. Observation of sea surface height using airborne radar altimetry: a new approach for large offshore tsunami detection. Journal of Oceanography 75, 57–73 (2019).
doi: 10.1007/s10872-019-00521-w
Central Disaster Management Council. Risk assessment results of Tokai-Tonankai-Nankai earthquake disaster, Cabinet Office, Government of Japan, Tokyo, http://www.bousai.go.jp/kaigirep/chuobou/9/pdf/zuhyou_2-2.pdf Accessed Sep. 2019 (2003).
Aida, I. Reliability of a tsunami source model derived from fault parameters. Journal of Physics of the Earth 26(1), 57–73 (1978).
doi: 10.4294/jpe1952.26.57
Shuto, N. Numerical simulation of tsunamis – its present and near future. Natural Hazards 4, 171–191 (1991).
doi: 10.1007/BF00162786
Thompson, S. D. & Sinclair, K. A. Automatic dependent surveillance–broadcast in the gulf of mexico. Lincoln Laboratory Journal 17(2), 1–15 (2008).
de Leege, A. M. P., Van Paassen, M. M. & Mulder, M. Using automatic dependent surveillance-broadcast for meteorological monitoring. Journal of Aircraft 50(1), 249–261 (2012).
doi: 10.2514/1.C031901
Mulia, I. E., Gusman, A. R. & Satake, K. Alternative to non-linear model for simulating tsunami inundation in real-time. Geophysical Journal International. 214(3), 2002–2013 (2018).
doi: 10.1093/gji/ggy238
Gusman, A. R., Tanioka, Y., MacInnes, B. T. & Tsushima, H. A methodology for near‐field tsunami inundation forecasting: Application to the 2011 Tohoku tsunami. Journal of Geophysical Research: Solid Earth 119(11), 8186–8206 (2014).
Thompson, E., Henry, K. & Williams, L. Faster than a speeding bullet: Guinness recognizes NASA Scramjet. https://www.nasa.gov/home/hqnews/2005/jun/HQ_05_156_X43A_Guinness.html Accessed Sep. 2019 (2003).
Ehrhard, T. P. A F UAVs: the Secret History. The Mitchell Institute for Airpower Studies, Arlington, Virginia, USA (2010).
Watts, A. C., Ambrosia, V. G. & Hinkley, E. A. Unmanned aircraft systems in remote sensing and scientific research: Classification and considerations of use. Remote Sensing 4(6), 1671–1692 (2012).
doi: 10.3390/rs4061671
Mulia, I. E., Gusman, A. R. & Satake, K. Optimal design for placements of tsunami observing systems to accurately characterize the inducing earthquake. Geophysical Research Letters 44, 12106–12115 (2017).
doi: 10.1002/2017GL075791
Titov, V. et al. Consistent estimates of tsunami energy show promise for improved early warning. Pure Applied Geophysics 173, 3863–3880 (2016).
doi: 10.1007/s00024-016-1312-1
Nakazawa, T., Miyashita, K., Aoki, S. & Tanaka, M. Temporal and spatial variations of upper tropospheric and lower stratospheric carbon dioxide. Tellus, Ser. B. 43, 106–117 (1991).
doi: 10.3402/tellusb.v43i2.15254
Machida, T. et al. Worldwide measurements of atmospheric CO2 and other trace gas species using commercial airlines. Journal of Atmospheric and Oceanic Technology 25(10), 1744–1754 (2008).
doi: 10.1175/2008JTECHA1082.1
Nebylov, A. V. & Yanovsky, F. J. Radar Altimeters. In: Nebylov AV, Watson J (eds) Aerospace Sensors. Momentum Press, New York, pp 55–88 (2012).
MacInnes, B. T., Gusman, A. R., LeVeque, R. J. & Tanioka, Y. Comparison of earthquake source models for the 2011 Tohoku event using tsunami simulations and near‐field observations. Bulletin of the Seismological Society of America 103(2B), 1256–1274 (2013).
doi: 10.1785/0120120121
Wang, Y. et al. Tsunami data assimilation without a dense observation network. Geophysical Research Letters 46(4), 2045–2053 (2019).
doi: 10.1029/2018GL080930
Klocke, D. & Rodwell, M. J. A comparison of two numerical weather prediction methods for diagnosing fast‐physics errors in climate models. Quarterly Journal of the Royal Meteorological Society 140(679), 517–524 (2014).
doi: 10.1002/qj.2172
Løvholt F., Griffin J. & Salgado-Gálvez M. Tsunami Hazard and Risk Assessment on the Global Scale. In: Meyers R. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg (2015).
Howe, B. M. et al. SMART cables for observing the global ocean: science and implementation. Frontiers in Marine Science 6, 424 (2019).
doi: 10.3389/fmars.2019.00424
Kânoğlu, U., Titov, V., Bernard, E. & Synolakis, C. Tsunamis: bridging science, engineering and society. Philosophical Transactions of the Royal Society A 373, 20140369 (2015).
doi: 10.1098/rsta.2014.0369
Okal, E. A. The quest for wisdom: lessons from 17 tsunamis, 2004–2014. Philosophical Transactions of the Royal Society A 373, 20140370 (2015).
doi: 10.1098/rsta.2014.0370
Desai, S. D. & Haines, B. J. Precise near-real-time sea surface height measurements from the Jason-1 and Jason-2/OSTM missions. Marine Geodesy 33(S1), 419–434 (2010).
doi: 10.1080/01490419.2010.488968
Rozier, D. et al. A reduced-order Kalman filter for data assimilation in physical oceanography. SIAM Review 49(3), 449–465 (2007).
doi: 10.1137/050635717
Cosme, E., Brankart, J. M., Verron, J., Brasseur, P. & Krysta, M. Implementation of a reduced rank square-root smoother for high resolution ocean data assimilation. Ocean Modelling 33(1-2), 87–100 (2010).
doi: 10.1016/j.ocemod.2009.12.004
Song, H. J. & Lim, G. H. Improvement of retrospective optimal interpolation by incorporating eigen‐decomposition and covariance inflation. Quarterly Journal of the Royal Meteorological Society 138(663), 353–364 (2012).
doi: 10.1002/qj.911
Kalnay, E. Atmospheric Modeling, Data Assimilation, and Predictability. Cambridge Univ. Press, Cambridge (2003).
Satake, K. Linear and nonlinear computations of the 1992 Nicaragua earthquake tsunami. Pure and Applied Geophysics 144(3-4), 455–470 (1995).
doi: 10.1007/BF00874378

Auteurs

Iyan E Mulia (IE)

UTokyo Ocean Alliance, The University of Tokyo, Tokyo, Japan. iyan@eri.u-tokyo.ac.jp.
Earthquake Research Institute, The University of Tokyo, Tokyo, Japan. iyan@eri.u-tokyo.ac.jp.

Tomoyuki Hirobe (T)

UTokyo Ocean Alliance, The University of Tokyo, Tokyo, Japan.
Japan Weather Association, Tokyo, Japan.

Daisuke Inazu (D)

Department of Marine Resources and Energy, Tokyo University of Marine Science and Technology, Tokyo, Japan.

Takahiro Endoh (T)

Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan.

Yoshihiro Niwa (Y)

UTokyo Ocean Alliance, The University of Tokyo, Tokyo, Japan.
Center for Ocean Literacy and Education, The University of Tokyo, Tokyo, Japan.

Aditya Riadi Gusman (AR)

GNS Science, Lower Hutt, New Zealand.

Hidee Tatehata (H)

UTokyo Ocean Alliance, The University of Tokyo, Tokyo, Japan.
Japan Weather Association, Tokyo, Japan.

Takuji Waseda (T)

UTokyo Ocean Alliance, The University of Tokyo, Tokyo, Japan.
Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan.

Toshiyuki Hibiya (T)

UTokyo Ocean Alliance, The University of Tokyo, Tokyo, Japan.
Graduate School of Science, The University of Tokyo, Chiba, Japan.

Classifications MeSH