Adaptive Variational Mode Decomposition Method for Eliminating Instrument Noise in Turbulence Detection

Abstract Noise removal is a key issue in the retrieval of turbulence from meteorological radiosonde data using method proposed by Thorpe. Only reducing as much possible influence noise potential temperature fluctuations can results reflect characteristics real atmosphere. In this paper, an adaptive variational mode decomposition (VMD) that used to remove profile, and particle swarm optimization mutual information are optimize preset VMD parameters. The Thorpe applied denoised profile identify characterize turbulent regions. show very effective for denoising both simulation experiments actual detection data. overturn be selected inversions optimal smoothing statistical tests. This improvement on Wilson allows daytime sounding data, avoiding confusion between distortion scale.