As a high-resolution time-frequency algorithm, the synchrosqueezed wavelet transform (SSWT) is used in this paper to study the well-known periodic variation of the solar surface. The extraction of the solar period signal is performed by studying the cycles of sunspot area and number in the northern and southern hemispheres of the Sun. The solar data were processed using SSWT to extract some well-known periodic signals from solar activity over 19-23 cycles periods by comparison with the complete ensemble empirical mode decomposition (CEEMD). In addition to the ~27-days rotation period and the ~11-years solar period, there are some intermediate periods in the solar data, especially ~170 days (Rieger-Type period) and ~365days (Annual period). Compared with the traditional methods for solar period extraction, SSWT is further used to extract the period signal in solar daily data to improve the accuracy, and the respective advantages and disadvantages of both for solar data processing are demonstrated by comparing with CEEMD. © 2023 IEEE.