The detection of cloud and aerosols using a modified retrieval algorithm solely for a ground-based micropulse lidar (MPL) is presented, based on one-year data at the Semi-Arid Climate Observatory and Laboratory (SACOL) site (35.57°N, 104.08°E, 1965.8 m), northwest of China, from March 2011 to February 2012. The work not only identifies atmosphere particle layers by means of the range-dependent thresholds based on elastic scattering ratio and depolarization ratio, but also discriminates the detected layers by combining empirical thresholds of the atmosphere's thermodynamics states and scattering properties and continuous wavelet transform (CWT) analyses. Two cases were first presented in detail that demonstrated that the modified algorithm can capture atmosphere layers well. The cloud macro-physical properties including cloud base height (CBH), cloud geometrical thickness (CGT), and cloud fraction (CF) were then analyzed in terms of their monthly and seasonal variations. It is shown that the maximum/minimum CBHs were found in summer (4.66 ± 1.95km)/autumn (3.34 ± 1.84km). The CGT in winter (1.05 ± 0.43km) is slightly greater than in summer (0.99 ± 0.44km). CF varies significantly throughout year, with the maximum value in autumn (0.68), and a minimum (0.58) in winter, which is dominated by single-layered clouds (81%). The vertical distribution of CF shows a bimodal distribution, with a lower peak between 1 and 4km and a higher one between 6and 9km. The seasonal and vertical variations in CF are important for the local radiative energy budget.