"As I mused, the fire burned"

Reflection on life as a person of faith.

Science and Tsunamis

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Just listening to the reporting from Hawaii, which is now under a Tsunami warning as a result of the earthquake off Haida Gwaii, BC. The State scientist was just interviewed on the television and explained why they went suddenly from no watch right to a warning.

We’ll keep them in our prayers that the model is grossly overpredicting the wave amplitude.

He used a good metaphor – that of a log rolling into the water. When a log rolls into the water, there are large waves generated off the centre of the log, and smaller waves off the end. The sea level data they have for their modelling software is only off the ends of the earthquake zone, that is the small waves off the end of the log. The earthquake was in an unusual location.

Once they started running the models, they noticed that the energy from the BC earthquake was focused on Hawaii. He also said they are not confident as to the accuracy of the models because of the input data, and the rare nature of earthquakes in that area.

This is very interesting, particularly given the six scientists just convicted in Italy for not providing adequate warning. Here is a clear explanation, from an expert, about the limitations of their prediction software. It’s presently showing a wave amplitude as high as seven feet (which is huge for a Tsunami), but their confidence is low.

What that means is the seven foot number may be high, or it may be low. Their model has not been tested for the particular input conditions that they are faced with. The lack of any buoys in the deep ocean between BC and Hawaii means the next real-world data point they obtain will be when the wave front arrives.

I was watching a local journalist who lives on the water (south shore of Ohau) who had decided to stay put. He commented that after hearing the scientist hedge his predictions he was very uncertain as to what he should do.

A model is only as good as the data that is input, and a model is only tested to the extent that there is real-world data to compare against the model prediction.

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Written by sameo416

October 28, 2012 at 2:07 am

Posted in Uncategorized

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