Wavenumber Analysis of Azimuthally Distributed Data: Assessing Maximum Allowable Gap Size

Abstract

erforming wavenumber decomposition on azimuthally distributed data such as those in tropical cyclones can be challenging when data gaps exist in the signal. In the literature, ad hoc approaches are found to determine maximum gap size beyond which not to perform Fourier decomposition. The goal of the present study is to provide a more objective and systematic method to choose the maximum gap size allowed to perform a Fourier analysis on observational data. A Monte Carlo?type experiment is conducted where signals of various wavenumber configurations are generated with gaps of varying size, then a simple interpolation scheme is applied and Fourier decomposition is performed. The wavenumber decomposition is evaluated in a way that requires retrieval of at least 80% of the original amplitude with less than 20° phase shift. Maximum allowable gap size is then retrieved for wavenumbers 0?2. When prior assessment of signal configuration is available, the authors believe that the present study can provide valuable guidance for gap size beyond which Fourier decomposition is not advisable.