Surface-based temperature inversion climatology across China from microwave radiometer network and their relationship...

Despite significant emission controls, severe PM_2.5 pollution persists in China under unfavorable meteorological conditions. Surface-based inversions (SBIs) suppress vertical mixing, but their diurnal characteristics remain poorly understood due to the limited temporal resolution of conventional radiosondes. This study presents a comprehensive SBI climatology across mainland China using hourly microwave radiometer (MWR) temperature profiles from 33 stations during 2024-2025. MWR profiles were validated against radiosonde observations at 25 stations, showing strong correlations from surface to 5000 m. Results reveal pronounced seasonal and spatial variability, with winter SBI occurrence (39.2%) approximately three times summer values (12.1%). A distinct northwest-to-southeast gradient emerges, with the highest frequencies in the Tarim Basin and Hexi Corridor and lowest in subtropical South China. We further examined SBI-pollution relationships at monthly, daily, and hourly scales using Spearman regression and SHAP analysis across PM_2.5 hotspot stations. Boundary-layer variables, including effective mixing layer height and SBI heat deficit, consistently occupy the top predictor tier for PM_2.5 pollution. At hourly scale, effective mixing layer height is among the leading predictors of PM_2.5. These findings establish that SBI climatology is one of the dominant meteorological controls on PM_2.5 at the network scale, operating through consistent physical mechanisms across all time scales.