For further improvements of gravity field models based on Gravity Recovery and Climate Experiment (GRACE) observations, it is necessary to identify the error sources within the recovery process. Observation residuals obtained during the gravity field recovery contain most of the measurement and modeling errors and thus can be considered as a realization of actual errors. In this work, we investigate the ability of wavelets to help in identifying specific error sources in GRACE range rate residuals. The Multi-Resolution Analysis (MRA) using Discrete Wavelet Transform (DWT) is applied to decompose the residual signal into different scales with corresponding frequency bands. Temporal, spatial, and orbit-related features of each scale are then extracted for further investigations. The wavelet analysis has proved to be a practical tool to find the main error contributors. Beside the previously known sources such as K-Band Ranging (KBR) system noise and systematic attitude variations, this method clearly shows effects which the classic spectral analysis is hardly able or unable to represent. These effects include long-term signatures due to satellite eclipse crossings and dominant ocean tide errors.