Atmospheric turbulence is a key multi-scale motion affecting numerical weather prediction, aviation safety, and atmospheric mass-energy exchange. Thorpe analysis is a classic method for turbulence retrieval, but traditional observations are limited by low spatiotemporal resolution, the absence of a stratospheric turbulence inversion framework, and insufficient cross-layer comparisons between northern and southern China, restricting the understanding of turbulence modulation mechanisms. Based on the domestic round-trip intelligent sounding system, atmospheric observations at 12 stations in Guangdong and Inner Mongolia from December 2022 to March 2023 are collected, with ascending-phase profiles used in the turbulence analysis and synergistically analyzed with ERA5 reanalysis data, which provide the background wind fields for westerly jet identification and precipitation data for environmental modulation assessment. Results show that turbulence in the study area shows significant layered differentiation and a latitudinal contrast between the southern and northern stations: the troposphere is the main turbulent layer, southern tropospheric turbulence is mainly associated with solar radiation, and northern tropospheric turbulence is mainly related to large-scale dynamic processes; stratospheric turbulence occurs sporadically only at northern stations under westerly jet-induced wind shear and is nearly absent in the south. Precipitation modulates southern tropospheric turbulence, while the westerly jet acts as a key dynamic factor for northern stratospheric turbulence. By integrating in situ radiosonde profiling with reanalysis data, this work supports refined turbulence detection and parameterization model optimization, and provides a scientific basis for weather forecast improvement and aviation route planning.