Abstract: Objective　The atmospheric boundary layer (ABL) governs the vertical transport of pollutants, heat, and moisture, with its height (ABLH) being a critical parameter for air quality management and climate research. Jinan, the capital of Shandong Province, features complex terrain with mountains to the east and south and frequent local industrial emissions, yet longterm, high-resolution ABLH observations in this region remain limited. 2023 is the hottest year on record globally. Especially for Jinan, this year is marked by frequent spring dust storms, record-breaking summer heatwaves, and abrupt autumn-winter temperature fluctuations, which provides a unique opportunity to investigate the ABLH characteristics under extreme climatic conditions. This study aims to develop an optimized lidar retrieval framework for ABLH under complex atmospheric scenarios to quantify the seasonal, monthly, and diurnal variations of ABLH in Jinan throughout 2023, and explore the linkages between ABLH dynamics, extreme weather events, and local pollutant accumulation, ultimately providing scientific evidence for urban ventilation corridor planning and air pollution control strategies. Methods　A 1.5 μm (1550 nm) single-photon lidar was deployed at the Jinan Institute of Quantum Technology (117° 7′48″E、36°40′48″N) in 2023 for a year of continuous unattended observations. The key parameters of the lidar include a single pulse energy of 70 μJ, pulse width of 100 ns, vertical resolution of 30 m, and temporal resolution of 1 s. A total of 232 days of valid minute-level observational data were obtained. A comprehensive retrieval workflow was established to address the issues of low-cloud interference and multi-layer aerosol complexities, where a differential enhancement algorithm was first used to identify cloud base height as the upper limit for ABLH retrieval, and two core algorithms, wavelet transform and two-dimensional matrix methods, were then applied in parallel below the cloud base, while the gradient method was only served as an auxiliary reference due to its instability in complex conditions. Clear divergence rules guided the determination of results. If the retrieved ABLH values of the two core methods differed by ≤ 90 m, the matrix result was adopted; for differences of 90–180 m, the arithmetic mean of the two methods was used; and for differences > 180 m, manual judgment with reference to L-band radiosonde data and ERA5 reanalysis data was triggered. The retrieved ABLH data were validated against radiosonde observations from Zhangqiu National Basic Weather Station (36 km away) using the critical Richardson number (Ri = 0.26). Results and Discussion　The optimized retrieval framework combining cloud base exclusion and dual core algorithms exhibited high stability and accuracy, with validation errors between lidar and radiosonde results ranging from 1.76% to 3.66%. The ABLH in Jinan displayed a consistent diurnal pattern throughout the four seasons. It rose rapidly 2–3 hours after sunrise, peaked at 14:00–15:00, and then declined sharply, with minor nighttime fluctuations. The seasonal average ABLH ranked highest in summer (1.411 km), followed by autumn (1.202 km), spring (1.078 km), and winter (1.010 km), while the peak monthly average ABLH of July was 1.742 km, driven by record high temperatures. Statistically, 62.0% of ABLH values concentrated in the range of 600–1500 m, and only 12.1% exceeded 2.100 km. Extreme weather events strongly modulated ABLH. Specifically, spring drought fostered deep nocturnal ABLs and enhanced the dispersion of pollutants, whereas stable autumn conditions (low wind, high humidity) suppressed the development of ABL and exacerbated the accumulation of pollutants. These findings further revealed that the complex terrain and weak dispersion capacity of Jinan exacerbated pollution episodes, highlighting the necessity of targeted urban planning interventions. Conclusion　This study developed a robust lidar retrieval method for ABLH in complex atmospheric environments, filling the gap of continuous minute-level ABLH observations in Jinan in 2023. The dual-algorithm framework with low-cloud exclusion significantly improved retrieval accuracy, which was validated by consistent agreement with radiosonde data. The systematic analysis revealed distinct seasonal, monthly, and diurnal ABLH variations closely related to extreme climate events in 2023. The identified relationships between ABLH dynamics and pollutant behavior confirm that the atmospheric dispersion capacity of Jinan is inherently limited, especially in autumn. The findings provide critical observational evidence for designing urban ventilation corridors to channel clean air from southern mountains to mitigate urban heat islands and air pollution. Additionally, the high-resolution ABLH dataset offers valuable insights for assessing the long-term climate impacts on atmospheric stability and environmental carrying capacity in northern China.

Key words: atmosphere boundary layer, Jinan, single-photon lidar, exceptionally warm year