Evaluating Effectiveness of DART Buoy Networks

TL;DR

This paper develops a statistical performance measure for DART tsunami buoy networks, assessing forecast accuracy degradation when buoys are inoperative and guiding network improvements.

Contribution

It introduces a novel evaluation method using simulated tsunami forecasts to quantify buoy network effectiveness and robustness.

Findings

RMSE identifies optimal buoys for forecasting accuracy.

Forecast degradation quantified when buoys fail.

Proposed status indicator flags network reliability.

Abstract

A performance measure for a DART tsunami buoy network has been developed. The measure is based on a statistical analysis of simulated forecasts of wave heights outside an impact site and how much the forecasts are degraded in accuracy when one or more buoys are inoperative. The analysis uses simulated tsunami height time series collected at each buoy from selected source segments in the Short-term Inundation Forecast for Tsunamis (SIFT) 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 hrs. 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 also 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 U.S. West Coast (Crescent City CA and Port San Luis CA). 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.