An assessment of the diversity in scenario-based tsunami forecasts for the Indian Ocean

Abstract

This work examines the extent to which tsunami forecasts from different numerical forecast systems might be expected to differ under real-time conditions. This is done through comparing tsunami amplitudes from a number of existing tsunami scenario databases for eight different hypothetical tsunami events within the Indian Ocean. Forecasts of maximum tsunami amplitude are examined at ten output points distributed throughout the Indian Ocean at a range of depths.The results show that there is considerable variability in the forecasts and on average, the standard deviation of the maximum amplitudes is approximately 62% of the mean value. It is also shown that a significant portion of this diversity can be attributed to the different lengths of the scenario time series. These results have implications for the interoperability of Regional Tsunami Service Providers in the Indian Ocean.

The effect of uncertainty in earthquake fault parameters on the maximum wave height from a tsunami propagation model

“…At the same time, hundreds to thousands of simulated scenarios of tsunami propagation have been created to inform real-time tsunami forecasting and alerts (e.g. Greenslade et al, 2007Greenslade et al, , 2013.…”

Time reverse imaging for far‐field tsunami forecasting: 2011 Tohoku earthquake case study

“…with Greenslade et al [2014] noting that the variation among forecasts of Indian Ocean tsunami warning systems has, on average, a standard deviation of the maximum amplitudes that is approximately 62% of its mean value.…”

“…As noted by Wang et al [], database forecast systems suffer from the fundamental limitation that they cannot accurately forecast tsunamis generated by earthquakes that are not well represented in the database, typically outer rise events or large, submarine strike‐slip events such as occurred in 2012 off northwest Sumatra. The parameterization of an event database also limits the ability to forecast an actual event, with Greenslade et al [] noting that the variation among forecasts of Indian Ocean tsunami warning systems has, on average, a standard deviation of the maximum amplitudes that is approximately 62% of its mean value.…”

Tsunami detection based on noisy sea surface height measurement

“…However, when approaching the coast, a Tsunami such as the one triggered by the 2011 earthquake can be a few tens of meters high, causing tremendous damage and much loss of life. That is why early Tsunami warning is so important and a number of Tsunami warning systems have been established worldwide [1][2][3]. A Tsunami can be directly detected using ocean buoy-based sensors or an altimetry satellite such as Jason-1 and Jason-2.…”

“…The real Tsunami waveforms were generated by Tsunami data measured by buoy-based sensors w earthquake. The data were obtained from [9], but the sampling interval is converted into distance based on Tsunami propagation velocity approximated by g v ( 1 ) where g is the acceleration of gravity and is the water depth. This approximation is appropriate for shallow-water waves such as Tsunamis, whose wavelength is more than twenty times the water depth so that the propagation velocity is dominated by the gravity and water depth.…”