The parameterization of hybrid-mechanistic storm damage models is largely based on the results of tree pulling tests. The tree pulling tests are used for imitating the quasi-static wind load associated with the mean wind speed. The combined effect of dynamic and quasi-static wind loads associated with wind load maxima is considered by either linearly increasing the quasi-static wind load by a gust factor or by using a turning moment coefficient determined from the relationship between maxima of wind-induced tree response and wind speed. To improve the joint use of information on dynamic and quasi-static wind loading, we present a new method that uses the coupled components of momentum flux time series and time series of stem orientation of a plantation-grown Scots pine tree. First, non-oscillatory tree motion components, which respond to wind excitation, are isolated from oscillatory components that are not coupled to the wind. The non-oscillatory components are detected by applying a sequence of time series decomposition methods including bi-orthogonal decomposition and singular spectrum analysis. Then, the wind-excited tree response components are subjected to dynamic time warping, which maximizes the coincidence between the processed data. The strong coincidence of the time-warped data allows for the estimation of the wind-induced tree response as a function of the effective wind load using simple linear regression. The slope of the regression line represents the rate of change in the tree response as the effective wind load changes. Because of the strength of the relationship, we argue that the method described is an improvement for the analysis of storm damage in forests and to individual trees.
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