Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China; Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China; Nansen-Zhu International Research Centre, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China.
Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change (ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD), Nanjing University of Information Science & Technology, Nanjing 210044, China.
Sci Total Environ. 2021 Feb 10;755(Pt 1):143017. doi: 10.1016/j.scitotenv.2020.143017. Epub 2020 Oct 19.
North China suffers from severe haze pollution and has received widespread attentions since the winter of 2012. In addition to human activities, climate variability also plays an important role, particularly in the interannual-decadal variations in the number of haze days in North China (HD). Many previous studies separately explored numerous preceding climate drivers, including Arctic sea ice, Eurasia snow and soil moisture, sea surface temperature in Pacific and Atlantic and forcing of Tibetan Plateau, but lacked assessment and analysis of the joint effects. In this study, we reviewed their impacts on HD and associated physical mechanisms. Beyond that, the synergetic effects were newly revealed by the observations and numerical experiments with fixed emissions. The preceding signals explained approximately 66% of the interannual-decadal variations in HD by exciting teleconnection patterns in winter and influencing the local dispersion conditions in North China. Furthermore, some future research directions were identified, such as the subseasonal variations in HD, subseasonal-seasonal prediction of haze by numerical climate models, and changing relationships between HD and climate conditions.
华北地区饱受雾霾污染之苦，自 2012 年冬季以来，一直受到广泛关注。除了人类活动之外，气候变率也起着重要作用，特别是在华北地区雾霾日数的年际-年代际变化方面（HD）。许多先前的研究分别探讨了许多先前的气候驱动因素，包括北极海冰、欧亚雪和土壤湿度、太平洋和大西洋的海面温度以及青藏高原的强迫，但缺乏对联合效应的评估和分析。在这项研究中，我们回顾了它们对 HD 及其相关物理机制的影响。除此之外，通过固定排放的观测和数值实验，新揭示了协同效应。先前的信号通过激发冬季的遥相关模式并影响华北地区的当地扩散条件，解释了 HD 的年际-年代际变化的约 66%。此外，还确定了一些未来的研究方向，例如 HD 的亚季节变化、数值气候模式对雾霾的亚季节-季节预测，以及 HD 与气候条件之间关系的变化。
