Impacts of climate anomalies on the interannual and interdecadal variability of autumn and winter haze in North China: A review

• Published in: International Journal of Climatology
• Main Authors: Wang, Jing, Liu, Yanju, Ding, Yihui, Wu, Ping, Zhu, Zhiwei, Xu, Ying, Li, Qiaoping, Zhang, Yingxian, He, Jinhai, Wang, Julian X. L., Qi, Li
• Other Authors: National Key Research and Development Program, National Natural Science Foundation of China
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: Sea ice
• Online Access: http://dx.doi.org/10.1002/joc.6471; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.6471; https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6471; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.6471; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6471

Abstract From the perspectives of remote sensing and climatic factors like surface meteorological parameters, large‐scale atmospheric circulations, and external forcing factors (EFFs), the authors synthesize and review spatiotemporal variations of PM 2.5 over North China and how climate anomalies affect autumn and winter haze variability in North China according to recent studies. This review focuses on both interannual and interdecadal timescales. It is shown that circulations play an important role in influencing haze variability. Atmospheric circulations, which would be modulated by EFFs like sea surface temperature, sea ice, and snowpack, can affect the climate variability in haze over North China via modulation of surface‐layer parameters that are closely connected with the haze phenomenon. Therefore, EFFs are deemed significant factors impacting the climate variability of haze over North China, serving as paramount precursory signals for haze prediction. Furthermore, this paper suggests potential future research directions for haze variability studies in North China on the basis of summarizing and concluding the associated processes/mechanisms on how climatic factors affect haze variability, which could provide reference for treating and forecasting in situ hazy conditions.