See also the more recent paper
Tsunami Early Warning from Global Navigation Satellite System Data using
Convolutional Neural Networks
by D. Rim et al. for a different approach
to forecasting using the same fakequakes as training data.
Shown below are the slip and seafloor displacements for each fakequakes realization used as test data, along with the predicted gauge results at gauges 901 (in Discovery Bay) and 911 (in Admiralty Inlet), based on observed data at gauge 702 (at the entrance of the Strait of Juan de Fuca) over a short time period (30 or 60 minutes). A prediction of the tsunami at gauge 702 at later times is also generated. Please see the paper for more discussion of the data and the methods used.
The paper shows sample results for realization #1127 of a CSZ earthquake. Here we show the corresponding results for all 193 realizations from the test set (a subset of the 1300 fakequakes realizations discussed in the paper).
Note that these are listed with roughly increasing moment magnitudes Mw based on the way they were generated, and the y-axes on the time series of surface water elevation (in meters) is scaled differently based on the maximum amplitude of each tsunami. Some smaller events gave tsunamis of less than a meter amplitude, while some of the larger events had amplitudes close to 10 meters. Keep this in mind when assessing the accuracy of the predictions.
In each case we show predictions made with the denoising autoencoder (DAE) first and then those made with the variational autoencoder (VAE). The plots on the left show predictions made using only 30 minutes of observed data at Gauge 702, while the plots on the right show the predictions based on 60 minutes of observed data.
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