Computation of changes in explosive weather systems during the 20th century

Stacey Lee Osbrough, Jorgen Segerlund Fredericksen


We present a new computational technique for extracting growing weather modes of different frequencies and growth rates from instantaneous six hourly observed atmospheric data. The methodology is applied to examine the changes in the statistics of growing storms and extreme weather events between the mid and late 20th century. The structures of weather modes in different frequency and growth rate bands are determined from the leading (maximum variance) eigenvectors of the associated covariance matrices. A matrix stochastic model is also fitted to the data, with the associated leading eigenvectors related to the dynamical developments.

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instability; stochastic models; filtering; atmospheric flows

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