Central North Pacific SST anomalies linked late winter haze to Arctic sea ice

• Published in: International Journal of Climatology
• Main Authors: Yang, Quan, Yuan, Dongmin
• Other Authors: National Natural Science Foundation of China
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2020
• Subjects: Arctic; Chukchi Sea; East Siberian Sea; Pacific; Chukchi; Sea ice
• Online Access: http://dx.doi.org/10.1002/joc.6534; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.6534; https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6534; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/joc.6534; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6534

Abstract Haze pollution in the North China Plain is becoming more serious and consequently causes inconvenience in daily life and harms health. The inter‐annual variation of haze days in the North China Plain in late winter (February and March) is closely related to the East Siberian Sea and Chukchi Sea ice in October, and the Pacific sea surface temperature (SST) plays a key role in delivering the effects of the sea ice on the haze. When the East Siberian Sea and Chukchi Sea ice increases in October, the October and November SST in the region over Minami‐Tori Shima and Midway Atoll decreases. This reduced SST then lowers the January and February SST around the northwestern side of the Hawaiian Islands. The lower SST around the northwestern side of the Hawaiian Islands modulates the atmospheric circulation and makes the diffusion conditions and water vapour conditions in the North China Plain more conducive to the accumulation and growth of pollutants. Large ensemble simulations from the Community Earth System Model validate the process whereby the East Siberian Sea and Chukchi Sea ice affects the SST in the aforementioned regions. The effect of changes in the SST around the northwestern side of the Hawaiian Islands on the meteorological conditions over the North China Plain was verified by numerical experiments using version 4 of the Community Atmosphere Model.