Pure and Applied Geophysics

, Volume 168, Issue 11, pp 2121–2131 | Cite as

A New Tool for Inundation Modeling: Community Modeling Interface for Tsunamis (ComMIT)

  • V. V. Titov
  • C. W. Moore
  • D. J. M. Greenslade
  • C. Pattiaratchi
  • R. Badal
  • C. E. Synolakis
  • U. Kânoğlu


Almost 5 years after the 26 December 2004 Indian Ocean tragedy, the 10 August 2009 Andaman tsunami demonstrated that accurate forecasting is possible using the tsunami community modeling tool Community Model Interface for Tsunamis (ComMIT). ComMIT is designed for ease of use, and allows dissemination of results to the community while addressing concerns associated with proprietary issues of bathymetry and topography. It uses initial conditions from a precomputed propagation database, has an easy-to-interpret graphical interface, and requires only portable hardware. ComMIT was initially developed for Indian Ocean countries with support from the United Nations Educational, Scientific, and Cultural Organization (UNESCO), the United States Agency for International Development (USAID), and the National Oceanic and Atmospheric Administration (NOAA). To date, more than 60 scientists from 17 countries in the Indian Ocean have been trained and are using it in operational inundation mapping.


Tsunami inundation modeling ComMIT graphical interface OPeNDAP 



We thank USAID, AusAID, the Australian Bureau of Meteorology, the Chulalongkorn University of Bangkok, Thailand, the Agency for Technology and Implementation Assessment (BPPT) of Indonesia, the Department of Risk and Disaster Management of Seychelles, and other institutions for support and hosting ComMIT training courses. We also thank Antony K. Joseph for providing us the Yanam, India tide gage data. We thank Nick Kalligeris and Baran Aydin for contributing to the Mediterranean ComMIT interface which is under development. This publication is partially funded by the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement No. NA17RJ1232, Contribution number: 1818; PMEL Contribution number: 3547, and the National Science Foundation of the USA.


  1. Ambraseys, N. and Synolakis, C. (2010), Tsunami catalogs for the Eastern Mediterranean revisited, J. Earthq. Eng., 14(3), 309–330. doi: 10.1080/13632460903277593
  2. Borrero, J., Sieh, K., Chlieh, M., and Synolakis, C. (2006), Tsunami forecasts for western Sumatra, Proc. Nat. Acad. Sci. USA, 103(52), 19673–19677.Google Scholar
  3. Borrero, J.B., McAdoo, B., Jaffe, B., Dengler, L., Gelfenbaum, G., Higman, B., Hidayat, R., Moore, A., Kongko, W., Lukijanto, Peters, R., Prasetya, G., Titov, V., and Yulianto, E. (2011), Field survey of the March 28, 2005 Nias-Simeulue earthquake and tsunami, Pure Appl. Geophys. doi: 10.1007/s00024-010-0218-6
  4. Behrens, J., Androsov, A., Babeyko, A.Y., Harig, S., Klaschka, F., and Mentrup, L. (2010), A new multi-sensor approach to simulation assisted tsunami early warning, Nat. Hazards Earth Syst. Sci. 10, 1085–1100. doi: 10.5194/nhess-10-1085-2010
  5. Bernard, E.N., Mofjeld, H.O., Titov, V., Synolakis, C.E., and González, F.I. (2006), Tsunami: scientific frontiers, mitigation, forecasting, and policy implications, Philos. T. R. Soc. A 364, 1989–2007.Google Scholar
  6. Fritz, H.M., Borrero, J.C., Suwargadi, B., Qiang L.L, Pranantyo, I.R., Skanavis V.L., and Synolakis, C.E. (2011) Reconnaissance of the 25 October 2010 Mentawai Islands tsunami in Indonesia, EGU2011-9512Google Scholar
  7. González, F.I., Geist, E.L., Jaffe, B., Kânoğlu, U., Mofjeld, H., Synolakis, C.E., Titov, V.V., Arcas, D., Bellomo, D., Carlton, D., Horning, T., Johnson, J., Newman, J., Parsons, T., Peters, R., Peterson, C., Priest, G., Venturato, A., Weber, J., Wong, F., and Yalciner, A. (2009), Probabilistic tsunami hazard assessment at Seaside, Oregon for near- and far-field seismic sources, J. Geophys. Res. 114, C11023. doi: 10.1029/2008JC005132
  8. Greenslade, D.J.M., Simanjuntak, M.A., Stewart, C., and Allen, R. (2011), An evaluation of tsunami forecasts from the T2 scenario database, Pure Appl. Geophys. doi: 10.1007/s00024-010-0229-3
  9. Greenslade, D.J.M., Simanjuntak, M.A., and Allen, S.C.R. (2009), An enhanced tsunami scenario database: T2, CAWCR Technical Report No. 014.Google Scholar
  10. Greenslade, D.J.M. and Titov V.V. (2008), A comparison study of two numerical tsunami forecasting systems, Pure Appl. Geophys. 165(11-12), 1991–2001. doi: 10.1007/s00024-008-0413-x.
  11. Greenslade, D.J.M., Simanjuntak, M.A., Chittleborough, J., and Burbidge, D. (2007), A first-generation realtime tsunami forecasting system for the Australian region, BMRC Research Report No. 126, Bur. Met., Australia.Google Scholar
  12. Gica, E., Spillane, M., Titov, V.V., Chamberlin, C.D., and 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, NTIS: PB2008-109391, 89 pp.Google Scholar
  13. Harig, S., Chaeroni, Pranowo, W. S. and Behrens, J. (2008), Tsunami simulations on several scales: Comparison of approaches with unstructured meshes and nested grids, Ocean Dynamics. 58, 429–440. doi: 10.1007/s10236-008-0162-5
  14. Imamura, F. (1995), Tsunami numerical simulation with the staggered leap-frog scheme, manuscript for TUNAMI code. School of Civil Engineering, Asian Inst. Tech., 45 p.Google Scholar
  15. Kânoğlu, U. and Synolakis, C.E. (2006), Initial value problem solution of nonlinear shallow water-wave equations, Phys. Rev. Lett., 97(14), 148501. doi: 10.1103/PhysRevLett.97.148501.
  16. Kerr, R.A. (2005), Model shows islands muted tsunami after latest Indonesian quake, Science 308, 341. doi: 10.1126/science.308.5720.341
  17. Løvholt, F., Pedersen, G., and Glimsdal, S. (2010), Coupling of dispersive tsunami propagation and shallow water coastal response, The Open Oceanography Journal, In Caribbean Waves Special Issue (Ed. E. Pelinovsky), 4, 71–82.Google Scholar
  18. Normile, D. (2007), Tsunami warning system shows agility - and gaps in Indian Ocean network, Science, 137(5845), 1661–1661.Google Scholar
  19. Okada, Y. (1985), Surface deformation due to shear and tensile faults in a half-space, Bull. Seismol. Soc. Am. 75, 1135–1154.Google Scholar
  20. Omira, R., Baptista, M.A., Matias, L., Miranda, J.M., Catita, C., Carrilho, F., and Toto, E. (2009), Design of a sea-level tsunami detection network for the Gulf of Cadiz, Nat. Hazards Earth Syst. Sci. 9, 1327–1338.Google Scholar
  21. Percival, D.B., Arcas, D., Denbo, D.W., Eble, M.C., Gica, E., Mofjeld, H.O., Spillane, M.C., Tang, L., and Titov, V.V. (2009), Extracting tsunami source parameters via inversion of DART® buoy data, NOAA Tech. Memo. OAR PMEL-144, 22 pp.Google Scholar
  22. Prabhudesai, R.G., Joseph, A., Agarvadekar, Y., Dabholkar, N., Mehra, P., Gouveia, A., Tengali, S., Vijaykumar, and Parab, A. (2006), Development and implementation of cellular-based real-time reporting and Internet accessible coastal sea level gaugeA vital tool for monitoring storm surge and tsunami, Current Science, 90(10), 1413–1418.Google Scholar
  23. Schiermeier, Q. and Witze, A. (2009), Tsunami watch: Five years after the Indian Ocean disaster, the technology is in place, but local preparedness is less advanced, Nature 462, 968–969. doi: 10.1038/462968a
  24. Spillane, M.C., Gica, E., Titov, V.V., and Mofjeld, H.O. (2008), Tsunameter network design for the U.S. DART® arrays in the Pacific and Atlantic Oceans, NOAA Tech. Memo. OAR PMEL-143, 165 pp.Google Scholar
  25. Synolakis, C.E. and Bernard, E.N. (2006), Tsunami science before and after Boxing Day 2004, Phil. Trans. R. Soc. A 364(1845), 2231–2265. doi: 10.1098/rsta.2006.1824
  26. Synolakis, C.E. and Kânoğlu, U. (2009), Chapter 8: Tsunami modeling: Development of benchmark models, The SEA, Tsunamis, vol. 15, Harvard University Press, p. 237–293. ISBN 978-0-674-03173-9.Google Scholar
  27. Synolakis, C.E., Bernard, E.N., Titov, V.V., Kânoğlu, U., and González, F. (2007), Standards, criteria, and procedures for NOAA evaluation of tsunami numerical models, NOAA OAR Special Report, Contribution No 3053, NOAA/OAR/PMEL, Seattle, Washington, 55 pp.Google Scholar
  28. Synolakis, C.E., Bernard, E.N., Titov, V.V., Kânoğlu, U., and González, F.I. (2008), Validation and verification of tsunami numerical models, Pure Appl. Geophys. 165(11-12), 2197–2228.Google Scholar
  29. Tang, L., Titov, V.V., and Chamberlin, C.D. (2009), Development, testing, and applications of site-specific tsunami inundation models for real-time forecasting, J. Geophys. Res., 114, C12025, doi: 10.1029/2009JC005476
  30. Titov, V.V. (2009), Chapter 12: Tsunami forecasting, The SEA, Tsunamis, vol. 15, Harvard University Press, p. 371–400. ISBN 978-0-674-03173-9.Google Scholar
  31. Titov, V.V., González, F.I., Bernard, E.N., Eble, M.C., Mofjeld, H.O., Newman, J.C., and Venturato, A.J. (2005), Real-time tsunami forecasting: Challenges and solutions, Nat. Haz. 35(1), 41–58. Special Issue, US National Tsunami Hazard Mitigation Program. doi: 10.1007/s11069-004-2403-3
  32. Titov, V.V. and Synolakis, C.E. (1995), Modeling of breaking and nonbreaking long-wave evolution and runup using VTCS-2, J. Waterw. Port Ocean Coast. Eng. 121(6), 308–316.Google Scholar
  33. Titov, V.V. and Synolakis, C.E. (1997), Extreme inundation flows during the Hokkaido-Nansei-Oki tsunami, Geophys. Res. Lett. 24(11), 1315–1318. doi: 10.1029/97GL01128
  34. Titov, V.V. and Synolakis, C.E. (1998), Numerical modeling of tidal wave runup, J. Waterw. Port Ocean Coast. Eng. 124(4), 157–171.Google Scholar
  35. Wei, Y., Bernard, E.N., Tang, L., Weiss, R., Titov, V.V., Moore, C., Spillane, M., Hopkins, M., and Kânoğlu, U. (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

Copyright information

© Springer Basel AG (outside the USA) 2011

Authors and Affiliations

  • V. V. Titov
    • 1
  • C. W. Moore
    • 2
  • D. J. M. Greenslade
    • 3
  • C. Pattiaratchi
    • 4
  • R. Badal
    • 5
  • C. E. Synolakis
    • 6
    • 7
  • U. Kânoğlu
    • 8
  1. 1.NOAA/Pacific Marine Environmental LaboratorySeattleUSA
  2. 2.Joint Institute for the Study of the Atmosphere and Ocean (JISAO)University of WashingtonSeattleUSA
  3. 3.Centre for Australian Weather and Climate ResearchBureau of MeteorologyMelbourneAustralia
  4. 4.School of Environmental Systems EngineeringThe University of Western AustraliaCrawleyAustralia
  5. 5.Mauritius Oceanography InstituteQuatre BornesMauritius
  6. 6.Viterbi School of EngineeringUniversity of Southern CaliforniaLos AngelesUSA
  7. 7.Hellenic Center of Marine ResearchAnavyssosGreece
  8. 8.Department of Engineering SciencesMiddle East Technical UniversityAnkaraTurkey

Personalised recommendations