Spatiotemporal Climatic Signal Denoising Based on Spatiotemporal Variability Index

Spatiotemporal (ST) climatic signals are used exclusively in the analysis and prediction of weather and climate. These signals are prone to noise due to sensor defects, environmental interference and so on. A novel ST signal denoising method is presented that computes ST signal variability measure at multiple data scales obtained from multivariate variational mode decomposition algorithm. This aids in joint multi-zonal climatic signal denoising directly in multidimensional space $\mathbb {R}^{Z\times N}$ where input signal resides, with the usage of interval thresholding applied on multiple data scales in $\mathbb {R}^{Z\times N}$. The performance of the proposed method is assessed and compared against closely related state-of-the-art methods using qualitative and quantitative analysis.