Abstract

This note outlines the development of a multivariate linear regression model to predict peak lightning activity a year in advance. Using cloud-to-ground lightning strike data from the inception of the National Lightning Detection Network in 1985, a predictive model is proposed for the peak monthly strike total for the Pacific Northwest. Six climate indices were evaluated as potential predictors of the lightning. From these, a multivariate linear model was developed, based on the year-in-advance values of two of the indices—The El Nino-Southern Oscillation Index, and the Western North Pacific Monsoon Index. The 2007 prediction of 56,618 strikes was tested against the measured value of 38,591 strikes. The values are in agreement within the expected accuracy of the model. The model prediction represents an improvement relative to the expectation based on the past statistical history of the data and should be most useful in predicting extreme events. The model parameters have been updated to include the 2007 ...

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