Nonlinear Fourier Analysis (NFA) is a powerful tool for the analysis of hydrodynamic processes. The unique capabilities of NFA include, but are not limited to, the detection of hidden solitons and the detection of modulation instability, which are essential for the understanding
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Nonlinear Fourier Analysis (NFA) is a powerful tool for the analysis of hydrodynamic processes. The unique capabilities of NFA include, but are not limited to, the detection of hidden solitons and the detection of modulation instability, which are essential for the understanding of nonlinear phenomena such as rogue waves. However, even though NFA has been applied to many interesting problems, it remains a non-standard tool. Recently, an open source software library called FNFT has been released to the public. (FNFT is short for “Fast Nonlinear Fourier Transforms”.) The library in particular contains code for the efficient numerical NFA of hydrodynamic processes that are approximately governed by the nonlinear Schroedinger equation with periodic boundary conditions. Waves in deep water are a prime example for such a process. In this paper, we use FNFT to perform an exemplary NFA of typhoon data collected by wave buoys at the coast of Taiwan. Our goals are a) to demonstrate the application of FNFT in a practical scenario, and b) to compare the results of a NFA to an analysis based on the conventional linear Fourier transform. The exposition is deliberately educational, hopefully enabling others to use FNFT for similar analyses of their own data.@en