Numerical modelling concepts for tsunami warning systems
Bibliographic record
Abstract
Summary The four global oceans, namely the Pacific, Atlantic, I ndian and Arctic, have different tsunami characteristics. Using the concept of the method of characteristics, it is su ggested Luettich, R. A., ADCIRC that the following methods be used respectively, for n umerical models for tsunami warning systems: the hyperbolic method for the Pacific Ocean, parabolic for the Atlantic Ocean, elliptic for the Indian Ocean and the parabolic–elliptic for the Arctic Ocean. 1. Murty, T. S., Seismic Seawaves – Tsunamis , Bull. No. 198, Fishe r-ies Research Board of Canada, Ottawa, 1977, p. 337. 2. Murty, T. S., Nirupama, N., Nistor, I. and Hamdi, S., Ts unamis in the Atlantic Ocean. J. Indian Soc. Earthquake Technology (sub-mitted) , 2005. 3. Foreman, M. G . G., An analysis of the ‘Wave Equ ation’ model for finite element tidal computations. J. Comput. Phys. , 1983, 52 , 290–312.4. Murty, T. S., Nirupama, N., Nistor, I. and Hamdi, S., Far fieldcharacteristics of the tsunami of 26 December 2004. J. Indian Soc. Ea rthquake Technol. (accepted). 5. Murty, T. S., Rao, A. D. and Nirupama, N., Inconsi stencies in travel times and amplitudes of the 26th December 2004 ts unami. J. Mar. Med. Soc. , 2005, 7, 7–14. 6. Murty, T. S., Rao, A. D., Nirupama, N. and Nistor, I., Tsunami warn ing systems for the hyperbolic (Pacific), parabolic (Atlantic) J. Indian Geophys. Union , 2006, 10 , 69 –78. 7. Flather, R. A., A numerical model investigation of tides and diu rnal -period continental shelf waves along Vancouver Island. J. Phys. Oceanogr. , 1988, 18 , 115 –139. 8. Foreman, M. G. G., A comparison of tidal models for the sout h-west coast of Vancouver Island. In Proc. 7th Int. Conf. on Co m put . Methods in Water Resour, Elsevier, 1988. 9. Hendershott, M. C., Long waves and ocean tid es. In Evol ution of Physical Oceanography (eds Wa rren, B. A. and Wunsch, C.), MIT Press, Cambridge, Mass., 1981, pp. 292 –346. 10. Murty, T. S., Storm surges – meteorological ocean tides. Can. J. Fish. Aquat. Sci. , 1984, 212 , 897.11. Crandall, S. H., Engineering Analysis – A Survey of Numerical Procedures , McGraw Hill, New York, 1956, p. 417. 12. Ann, B. C., Modeling methodologies for the prediction of hurr icane storm surge. In Recent Advances in Marine Science and Techno -logy (ed. Saxena, N. K.), PACON International, Hon olulu, 1997, pp. 177 –189.13. Kowa lik, Z. and Murty, T. S., Numerical simulation of two-dimen -sional tsunami runup. Mar. G eod. , 1993, 16 , 87 –100. 14. Cialone, M. A., Coastal Modelling System (CMS) User’s Manual, Instruction Report CERC-91 -1, Coastal Engineering Research Centre, US Army Engineer Waterways Experiment Station, Vick s-15. Luettich, R. A., Westerink, J. J. and Scheffner, N. W., ADCIRC: An advanced three-dimensional circulation model for shelves, coasts and estuaries; Report 1: Theory and methodology of ADCIRD -2DDI and ADCIRC -3DL. Coastal Engineering Research Centre, US Army Engineer Waterways Experiment Station, Vick s-burg, MS, USA, 1991.16. Luettich, R. A., Westerink, J. J. and Scheffner, N. W., ADCIRC: An advanced three -dimensional circul ation model for shelves, coasts and estuaries; Report 1: Theory and methodology of ADCIRD-2DDI and ADCIRC-3DL. Technical Report DRP Coastal Engi-neering Research Centre, US Army Engineer Waterways Experi-ment Station, Vicksburg, MS, USA, 1992. 17. Mark, D. J. an d Scheffner, N. W., Validation of a contine ntal-scale storm surge model for the coast of Delaware. Third International Conference on Estuarine and Coastal Modelling, Chicago, IL, 8 –10 Se ptember 1993. 18. Scheffner, N. W., Mark, D. J., Blain, C. A., Westerink, J. J. and – An advanced three -dimensional circ u-
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".