The Global Reach of the 26 December 2004 Sumatra Tsunami Titov, Vasily; Rabinovich, Alexander B.; Mofjeld, Harold O. ...
Science (American Association for the Advancement of Science),
09/2005, Letnik:
309, Številka:
5743
Journal Article
Recenzirano
Odprti dostop
Numerical model simulations, combined with tide-gauge and satellite altimetry data, reveal that wave amplitudes, directionality, and global propagation patterns of the 26 December 2004 Sumatra ...tsunami were primarily determined by the orientation and intensity of the offshore seismic line source and subsequently by the trapping effect of mid-ocean ridge topographic waveguides.
We have developed a method to compute the total energy transmitted by tsunami waves, to the case where the earthquake source is unknown, by using deep‐ocean pressure measurements and numerical models ...(tsunami source functions). Based on the first wave recorded at the two closest tsunameters (Deep‐Ocean Assessment and Reporting of Tsunamis (DART)), our analysis suggests that the March 11, 2011 Tohoku‐Oki tsunami generated off Japan originated from a 300–400 km long and 100 km wide area, and the total propagated energy is 3 × 1015J (with 6% uncertainty). Measurements from 30 tsunameters and 32 coastal tide stations show excellent agreement with the forecasts obtained in real time. Our study indicates that the propagated energy and the source location are the most important source characteristics for predicting tsunami impacts. Interactions of tsunami waves with seafloor topography delay and redirect the energy flux, posing hazards from delayed and amplified waves with long duration. Seafloor topography also gives its spectral imprint to tsunami waves. Travel time forecast errors are path‐specific and correlated to the major wave scatterers in the Pacific. Numerical dissipation in the propagation modeling highlights the need of high‐resolution inundation models for accurate coastal predictions. On the other hand, it also can be used to account for physical dissipation to achieve efficiency. Our results provide guidelines for the earliest reliable tsunami forecast, warnings of long duration tsunami waves signals and enhancement of the experimental tsunami forecast system. We apply the method to quantify the energy of 15 past tsunamis, independently from earthquake magnitudes. The small tsunami to seismic radiation energy ratios, and their variability (0.01–0.8%), reinforce the importance of using deep‐ocean tsunami data, the direct measures of tsunamis, for estimates of tsunami energy and accurate forecasting.
Key Points
Deep‐ocean tsunami data provide a robust and direct measure of tsunami energy
Propagation energy is the key for accurate and effective tsunami forecasts
Energy for the past 15 tsunamis were quantified independently from seismic data
The ability to accurately forecast potential hazards posed to coastal communities by tsunamis generated seismically in both the near and far field requires knowledge of so-called source coefficients, ...from which the strength of a tsunami can be deduced. Seismic information alone can be used to set the source coefficients, but the values so derived reflect the dynamics of movement at or below the seabed and hence might not accurately describe how this motion is manifested in the overlaying water column. We describe here a method for refining source coefficient estimates based on seismic information by making use of data from Deep-ocean Assessment and Reporting of Tsunamis (DART
) buoys (tsunameters). The method involves using these data to adjust precomputed models via an inversion algorithm so that residuals between the adjusted models and the DART
data are as small as possible in a least squares sense. The inversion algorithm is statistically based and hence has the ability to assess uncertainty in the estimated source coefficients. We describe this inversion algorithm in detail and apply it to the November 2006 Kuril Islands event as a case study.
Instrumental surface air temperature (SAT) records beginning in the late 1800s from 59 Arctic stations north of 64°N show monthly mean anomalies of several degrees and large spatial teleconnectivity, ...yet there are systematic seasonal and regional differences. Analyses are based on time–longitude plots of SAT anomalies and principal component analysis (PCA). Using monthly station data rather than gridded fields for this analysis highlights the importance of considering record length in calculating reliable Arctic change estimates; for example, the contrast of PCA performed on 11 stations beginning in 1886, 20 stations beginning in 1912, and 45 stations beginning in 1936 is illustrated. While often there is a well-known interdecadal negative covariability in winter between northern Europe and Baffin Bay, long-term changes in the remainder of the Arctic are most evident in spring, with cool temperature anomalies before 1920 and Arctic-wide warm temperatures in the 1990s. Summer anomalies are generally weaker than spring or winter but tend to mirror spring conditions before 1920 and in recent decades. Temperature advection in the trough–ridge structure in the positive phase of the Arctic Oscillation (AO) in the North Atlantic establishes wintertime temperature anomalies in adjacent regions, while the zonal/annular nature of the AO in the remainder of the Arctic must break down in spring to promote meridional temperature advection. There were regional/decadal warm events during winter and spring in the 1930s to 1950s, but meteorological analysis suggests that these SAT anomalies are the result of intrinsic variability in regional flow patterns. These midcentury events contrast with the recent Arctic-wide AO influence in the 1990s. The preponderance of evidence supports the conclusion that warm SAT anomalies in spring for the recent decade are unique in the instrumental record, both in having the greatest longitudinal extent and in their associated patterns of warm air advection.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
A performance measure for a DART
®
tsunami buoy network has been developed. DART
®
buoys are used to detect tsunamis, but the full potential of the data they collect is realized through accurate ...forecasts of inundations caused by the tsunamis. The performance measure assesses how well the network achieves its full potential through a statistical analysis of simulated forecasts of wave amplitudes outside an impact site and a consideration of how much the forecasts are degraded in accuracy when one or more buoys are inoperative. The analysis uses simulated tsunami amplitude time series collected at each buoy from selected source segments in the Short-term Inundation Forecast for Tsunamis database and involves a set for 1000 forecasts for each buoy/segment pair at sites just offshore of selected impact communities. Random error-producing scatter in the time series is induced by uncertainties in the source location, addition of real oceanic noise, and imperfect tidal removal. Comparison with an error-free standard leads to root-mean-square errors (RMSEs) for DART
®
buoys located near a subduction zone. The RMSEs indicate which buoy provides the best forecast (lowest RMSE) for sections of the zone, under a warning-time constraint for the forecasts of 3 h. The analysis also shows how the forecasts are degraded (larger minimum RMSE among the remaining buoys) when one or more buoys become inoperative. The RMSEs provide a way to assess array augmentation or redesign such as moving buoys to more optimal locations. Examples are shown for buoys off the Aleutian Islands and off the West Coast of South America for impact sites at Hilo HI and along the US West Coast (Crescent City CA and Port San Luis CA, USA). A simple measure (coded green, yellow or red) of the current status of the network’s ability to deliver accurate forecasts is proposed to flag the urgency of buoy repair.
Regime shifts and red noise in the North Pacific Overland, James E.; Percival, Donald B.; Mofjeld, Harold O.
Deep-sea research. Part I, Oceanographic research papers,
04/2006, Letnik:
53, Številka:
4
Journal Article
Recenzirano
Odprti dostop
Regimes and regime shifts are important concepts for understanding decadal variability in the physical system of the North Pacific because of the potential for an ecosystem to reorganize itself in ...response to such shifts. There are two prevalent senses in which these concepts are taken in the literature. The first is a formal definition and posits
multiple stable states and rapid transitions between these states. The second is more data-oriented and identifies local regimes based on
differing average climatic levels over a multi-annual duration, i.e. simply interdecadal fluctuations. This second definition is consistent with realizations from stochastic red noise processes to a degree that depends upon the particular model. Even in 100 year long records for the North Pacific a definition of regimes based solely on distinct multiple stable states is difficult to prove or disprove, while on interdecadal scales there are apparent local step-like features and multi-year intervals where the state remains consistently above or below the long-term mean. The terminologies
climatic regime shift, statistical regime shift or
climatic event are useful for distinguishing this second definition from the first.
To illustrate the difficulty of advocating one definition over the other based upon a relatively short time series, we compare three simple models for the Pacific Decadal Oscillation (PDO). The 104-year PDO record is insufficient to statistically distinguish a single preference between a square wave oscillator consistent with the formal definition for regime shifts, and two red noise models that are compatible with
climatic regime shifts. Because of the inability to distinguish between underlying processes based upon data, it is necessary to entertain multiple models and to consider how each model would impact resource management. In particular the persistence in the fitted models implies that certain probabilistic statements can be made regarding
climatic regime shifts, but we caution against extrapolation to future states based on curve fitting techniques.
The NTHMP Tsunameter Network Gonzalez, Frank I; Bernard, Eddie N; Meinig, Christian ...
Natural hazards (Dordrecht),
05/2005, Letnik:
35, Številka:
1
Journal Article
Recenzirano
A tsunameter (soo-NAHM-etter) network has been established in the Pacific by the National Oceanic and Atmospheric Administration. Named by analogy with seismometers, the NOAA tsunameters provide ...early detection and real-time measurements of deep-ocean tsunamis as they propagate toward coastal communities, enabling the rapid assessment of their destructive potential. Development and maintenance of this network supports a State-driven, high-priority goal of the U.S. National Tsunami Hazard Mitigation Program to improve the speed and reliability of tsunami warnings. The network is now operational, with excellent reliability and data quality, and has proven its worth to warning center decision-makers during potentially tsunamigenic earthquake events; the data have helped avoid issuance of a tsunami warning or have led to cancellation of a tsunami warning, thus averting potentially costly and hazardous evacuations. Optimizing the operational value of the network requires implementation of real-time tsunami forecasting capabilities that integrate tsunameter data with numerical modeling technology. Expansion to a global tsunameter network is needed to accelerate advances in tsunami research and hazard mitigation, and will require a cooperative and coordinated international effort.
Subtidal coastal sea level fluctuations affect coastal ecosystems and the consequences of destructive events such as tsunamis. We analyze a time series of subtidal fluctuations at Crescent City, ...California, during 1980-1991 using the maximal overlap discrete wavelet transform (MODWT). Our analysis shows that the variability in these fluctuations depends on the season for scales of 32 days and less. We show how the MODWT characterizes nonstationary behavior succinctly and how this characterization can be used to improve forecasts of inundation during tsunamis and storm surges. We provide pseudocode and enough details so that data analysts in other disciplines can readily apply MODWT analysis to other nonstationary time series.
In response to hazards posed by earthquake-induced tsunamis, the National Oceanographic and Atmospheric Administration developed a system for issuing timely warnings to coastal communities. This ...system, in part, involves matching data collected in real time from deep-ocean buoys to a database of precomputed geophysical models, each associated with a geographical location. Currently, trained operators must handpick models from the database using the epicenter of the earthquake as guidance, which can delay issuing of warnings. In this article, we introduce an automatic procedure to select models to improve the timing and accuracy of these warnings. This procedure uses an elastic-net-based penalized and constrained linear least-squares estimator in conjunction with a sweeping window. This window ensures that selected models are close spatially, which is desirable from geophysical considerations. We use the Akaike information criterion to settle on a particular window and to set the tuning parameters associated with the elastic net. Test data from the 2006 Kuril Islands and the devastating 2011 Japan tsunamis show that the automatic procedure yields model fits and verification equal to or better than those from a time-consuming hand-selected solution.
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