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Russian Academy of Sciences Far East Branch Institute of Marine Geology & Geophysics Yu. Korolev THE RETROSPECTIVE SHORT-TERM TSUNAMI FORECAST Novosibirsk.

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Presentation on theme: "Russian Academy of Sciences Far East Branch Institute of Marine Geology & Geophysics Yu. Korolev THE RETROSPECTIVE SHORT-TERM TSUNAMI FORECAST Novosibirsk."— Presentation transcript:

1 Russian Academy of Sciences Far East Branch Institute of Marine Geology & Geophysics Yu. Korolev THE RETROSPECTIVE SHORT-TERM TSUNAMI FORECAST Novosibirsk 2009 24th International Tsunami Symposium of the IUGG Tsunami Commission

2 From the point of view of tsunami warning services the short-term forecast should consist in determination of detail features of a tsunami: time of tsunami attack, the number of waves and waves' heights, time intervals between them, expected time of tsunami alarm canceling, - for each points to be warned. T he short-term tsunami forecast should be implemented in real-time mode. The tsunami alarm should be declared only in those points, in which tsunamis are to be of actual threat. Such detail forecast based on magnitude criterion is impossible. For this reason the acting tsunami warning services, not passing practically any event, declare up to 80 % of false alarms. It is obvious, that false tsunami alarms are accompanied by various losses. Information, on which the forecast working-out is possible, are data on an ocean level in points, remote from coast. Just open-sea stations allow to make up an adequate forecast.

3 One of solutions of the tsunami early warning problem, using sea level data, is offered. The approximate solution is based on a known reciprocity principle of being outcome of a symmetry of Green's function of a wave equation. The presenting method may be applied to short-term tsunami forecast regardless of tsunami generation nature. Tsunami sources may be seismic one, subsea landslide one or others.

4 А – point near coast to be warned, M – point of level gauge, T – earthquake epicenter - sea level data in М (Laplace transform) - computed level in А from auxiliary axial source with center in Т (Laplace transform) -computed level in M from auxiliary axial source with center in Т (Laplace transform) Basic relation for tsunami estimation – method for early tsunami forecast The concrete nature of the tsunami source is of no importance

5 Necessary information for computation: Co-ordinates of earthquake epicenter. Computed level data from auxiliary source in level gauge point and in point to be warned. Tsunami level data in level gauge point. Co-ordinates of earthquake epicenter. Computed level data from auxiliary source in level gauge point and in point to be warned. Tsunami level data in level gauge point. Practically method consists in transfer function creation, allowing to compute a tsunami waveform in any specific point based on sea level data. The transfer function is formed during an event.

6 The presenting method was applied to retrospective short-term tsunami forecast in Northern Pacific. Events of 1996, 2006, 2007 and 2009 were simulated. The presenting method was applied to retrospective short-term tsunami forecast in Northern Pacific. Events of 1996, 2006, 2007 and 2009 were simulated. The information about earthquakes epicenters coordinates and ocean level data of BPR’s (first generation of deep-sea level stations) and data of DART system stations were used for modeling. The numerical modeling simulated forecast working- out in real-time mode. The information about earthquakes epicenters coordinates and ocean level data of BPR’s (first generation of deep-sea level stations) and data of DART system stations were used for modeling. The numerical modeling simulated forecast working- out in real-time mode.

7 Epicenter co-ordinates 51º33’48”N, 177º37’54”W Sea depth in epicenter 176.6 m (on bathymetry data) AK-700971751.91794.4 AK-711014831.84833.6 AK-721024943.14706.8 AK-731034872.04651.0 WC-671141564.91969.4 BPR Point on scheme Sea depth, real, mWater depth on bathymetry, m Auxiliary source: diameter 50 km, max amplitude 8 m. 1996 Andreanov tsunami.

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21 2006 Simushir tsunami Epicenter co-ordinates 46º48’N, 153º12’E Auxiliary source: diameter 75 km, max amplitude 10 m. Sea depth in epicenter 2802.7 m (on bathymetry data). 2006 Simushir tsunami Epicenter co-ordinates 46º48’N, 153º12’E Auxiliary source: diameter 75 km, max amplitude 10 m. Sea depth in epicenter 2802.7 m (on bathymetry data). 2007 Simushir tsunami Epicenter co-ordinates 46º30’N, 154º24’E Auxiliary source: diameter 75 km, max amplitude 10 m. Sea depth in epicenter 6876.8 m (on bathymetry data). 2007 Simushir tsunami Epicenter co-ordinates 46º30’N, 154º24’E Auxiliary source: diameter 75 km, max amplitude 10 m. Sea depth in epicenter 6876.8 m (on bathymetry data). 2009 Simushir tsunami Epicenter co-ordinates 46º50’18”N, 155º11’18”E Auxiliary source: diameter 50 km, max amplitude 8 m. Sea depth in epicenter 6644.7 m (on bathymetry data). 2009 Simushir tsunami Epicenter co-ordinates 46º50’18”N, 155º11’18”E Auxiliary source: diameter 50 km, max amplitude 8 m. Sea depth in epicenter 6644.7 m (on bathymetry data).

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27 C O N C L U S I O N The method of short-term tsunami forecast using level data in a one remote from a coast point: - permits to estimate a tsunami waveform in a good time at any given ocean point; - the only seismological information about earthquake epicenter coordinates and time of event is required; - the tsunami forecast can be executed in real-time mode; - transfer function can be created during event. No previously computed data base is required; - the method can be applied in any areas, especially in those which has no beforehand created synthetic mareograms database and in those in which warning system is developing; - the method can be used by local tsunami warning services, if they can receive sea level information on-line.

28 Aсknowledgements Author thanks Vasily Titov for given numerical level data of 1996 Andreanov tsunami and Victor Kaistrenko for useful discussions. The work was supported by Russian Foundation for Basic Research (grant 08-05-99098) and Far East Branch of Russian Academy of Sciences (grant 06-III-A-07-248).

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