Cold waves are intense extratropical weather events characterized by rapid near-surface cooling. Their variability is commonly described in terms of frequency or intensity, while other intrinsic attributes of their life cycles remain poorly understood. To provide a more comprehensive portrait, we developed an objective event-based detection framework that characterizes cold waves from multiple dimensions, including but not limited to frequency, track, magnitude, intensity, duration, and spatial extent. We applied the framework to cold waves affecting China to investigate their climatological characteristics and long-term variability. During 1940–2021, a total of 1737 cold-wave events were identified, corresponding to a mean frequency of 21.2 yr⁻¹. Their seasonal cycle and spatial distribution are broadly consistent with prior knowledge, confirming the framework's reliability, while several new features are revealed. Two preferred track belts are identified, a west–east belt extending from Xinjiang Province to North China and a meridional belt from North China to South China. It revises the traditional view of central Siberia as a source region for cold waves affecting China and identifies three additional candidate regions over Mongolia, eastern China, and the northeastern Indian Peninsula. The multidimensional characteristics show clear seasonal contrasts. Winter events are moderately intense but persist the longest and affect the largest regions, whereas autumn events are the most intense, and spring events are the most frequent but shorter-lived and more localized. Temporal analysis reveals pronounced decadal variability and an overall decline in frequency, duration, spatial extent, and intensity, accompanied by a slight increase in magnitude, with substantial regional and seasonal differences. An intriguing decadal correspondence is found between a weak East Asian winter monsoon and larger cold-wave magnitude, higher intensity, and shorter duration.