The drastically changing climate system plays a critical role in modulating emission and distribution conditions of air pollutants including greenhouse gases, aerosols, and tracer gases, while these air pollutants exert significant feedback to the climate system through multiple biogeophysical, biogeochemical, and hydrological pathways. These interactions occur at different spatial and temporal scales that increase the difficulty for a clear and comprehensive understanding. To shed light on complex interactions between climate variability and air pollution, we used statistical and numerical modeling approaches to investigate the interactive relationship between climate variability and air pollution in the context of severe haze pollution in China and large wildfires worldwide. We identified the key climatic and meteorological forcing factors to the spatial and temporal variations of the two typical air pollution events including severe haze in China during the winter season and biomass burning in fire-prone regions using statistical analysis methods. We then improved and employed the state-of-the-art Community Earth System Model (CESM) to investigate the underlying mechanisms driving their variability as well as to understand interactive feedback pathways. Based on comprehensive statistical analysis, dynamic diagnosis, and numerical sensitivity simulations, we found a close connection between deteriorating winter air pollution ventilation in China and rapidly changing boreal cryosphere in preceding months. We proposed a physical mechanism to explain the teleconnection relationship in the China’s winter haze pollution problem. We also developed a region-specific fire model with climate and ecosystem feedback in CESM and utilized this new fire model to evaluate complex climate-fire-ecosystem interactions as well as to predict decadal climate variability with fully interactive fire disturbances. These studies represent the advanced efforts to answer the intriguing question of the interactive relationship between climate variability and air pollution, and the knowledge obtained through these efforts would benefit both the regulation practice of regional air pollution control and the design of mitigation strategies for future climate change risks.