In this thesis, the Hilbert-Huang Transform will be introduced and applied to study various environmental datasets. Hilbert-Huang Transform (HHT) is an empirically based data analysis tool that can produce physically meaningful representations of nonlinear and nonstationary type of datasets. The empirical mode decomposition (EMD) method will be used to decompose the dataset into intrinsic mode functions. Then, the Hilbert Spectral Analysis will be applied to compute instantaneous frequency and amplitudes and to describe the signal more locally to obtain the physical meaning of the dataset. HHT is applied to analyze Tibet Plateau snow cover data from February 4, 1997 to March 15, 2012. The same method is also applied to investigate the snow cover and ice cover over the Northern Hemisphere.
