Climate modulation of Nino3.4 SST-anomalies on air quality change in southern China: Application to seasonal forecast of haze pollution

doi:10.1016/j.atmosres.2019.04.002

	Climate modulation of Nino3.4 SST-anomalies on air quality change in southern China: Application to seasonal forecast of haze pollution
	Cheng, Xugeng 2,3; Boiyo, Richard 4; Zhao, Tianliang 3; Xu, Xiangde 5; Gong, Sunling 1; Xie, Xiaoning 2; Shang, Ke 2
刊名	ATMOSPHERIC RESEARCH
	2019-09-01
卷号	225 页码:157-164
关键词	Air quality Haze Southern China Random forest SSTA
ISSN号	0169-8095
DOI	10.1016/j.atmosres.2019.04.002
通讯作者	Zhao, Tianliang(tlzhao@nuist.edu.cn)
英文摘要	Air stagnation modulates the frequency and duration of haze events. Based on meteorological and environmental observation data during 1980 to 2013, the present study analyzed the relationship between the interannual variations of Sea Surface Temperature (SST) over tropical central-eastern Pacific and the number of winter haze days (WHD) over the Southern China (SC) region. The potential preceding signal of Sea Surface Temperature anomalies (SSTAs) in Nino3.4 region associated with ENSO can be used as a predictor of haze occurrences in winter. Results indicate that the detrended WHD in the SC is significantly correlated (r = -0.55) with the contemporary SSTAs in Nino3.4 region. The winters with warm Nino3.4 SSTAs in (El Nino) tend to be accompanied with less haze events in the SC, resulting from more local precipitation and enhanced mid-level winds, which helps to build an unstable condition that is conductive for the decrease of haze occurrence. The precursory signal of WHD variability can be detected in the tropical central-eastern Pacific SST, which is amplified since August to winter season. Based on the August October mean SSTAs in Nino3.4 and three other identified predictors, we developed a seasonal prediction model of the WHD using RF regression method. The model accounted for 90% of the total variance of the WHD in the SC and ranked the SSTAs in Nino3.4 as the most important predictor. This implies that the SSTAs tropical Pacific play a significant role in the variability of WHD in the SC. Since the predictors can be readily monitored in real time, the model provides a real time forecast tool and could brighten the prospects for seasonal forecast of haze anomalies in vulnerable regions such as the SC.
资助项目	National Key R&D Program of China[2016YFC0203304] ; National Natural Science Foundation of China[91744209] ; National Natural Science Foundation of China[91644223] ; National Natural Science Foundation of China[41830965] ; Program for Postgraduates Research and Innovation in Universities of Jiangsu Province[KYLX15_0863] ; Program for Postgraduates Research and Innovation in Universities of Jiangsu Province[KYLX16_0937]
WOS关键词	SEA-SURFACE TEMPERATURE ; EAST ASIAN TELECONNECTION ; WINTER HAZE ; EL-NINO ; WEATHER CONDITIONS ; AEROSOL VARIATIONS ; UNITED-STATES ; RIVER DELTA ; MONSOON ; VARIABILITY
WOS研究方向	Meteorology & Atmospheric Sciences
语种	英语
出版者	ELSEVIER SCIENCE INC
WOS记录号	WOS:000470049300014
资助机构	National Key R&D Program of China ; National Natural Science Foundation of China ; Program for Postgraduates Research and Innovation in Universities of Jiangsu Province
内容类型	期刊论文
源URL	[http://ir.ieecas.cn/handle/361006/13858]
专题	地球环境研究所_古环境研究室
通讯作者	Zhao, Tianliang
作者单位	1.Chinese Acad Meteorol Sci, Inst Atmospher Composit, Key Lab Atmospher Chem, CMA, Beijing 100081, Peoples R China 2.Chinese Acad Sci, Inst Earth Environm, SKLLQG, Xian 710061, Shaanxi, Peoples R China 3.Nanjing Univ Informat Sci & Technol, Sch Atmospher Phys,Key Lab Meteorol Disaster,Coll, Key Lab Aerosol Cloud Precipitat,Minist Educ KLME, China Meteorol Adm,Int Joint Lab Climate & Enviro, Nanjing 210044, Jiangsu, Peoples R China 4.Meru Univ Sci & Technol, Dept Phys Sci, POB 972-60200, Meru, Kenya 5.Chinese Acad Meteorol Sci, State Key Lab Severe Weather, Beijing 100081, Peoples R China
推荐引用方式 GB/T 7714	Cheng, Xugeng,Boiyo, Richard,Zhao, Tianliang,et al. Climate modulation of Nino3.4 SST-anomalies on air quality change in southern China: Application to seasonal forecast of haze pollution[J]. ATMOSPHERIC RESEARCH,2019,225:157-164.
APA	Cheng, Xugeng.,Boiyo, Richard.,Zhao, Tianliang.,Xu, Xiangde.,Gong, Sunling.,...&Shang, Ke.(2019).Climate modulation of Nino3.4 SST-anomalies on air quality change in southern China: Application to seasonal forecast of haze pollution.ATMOSPHERIC RESEARCH,225,157-164.
MLA	Cheng, Xugeng,et al."Climate modulation of Nino3.4 SST-anomalies on air quality change in southern China: Application to seasonal forecast of haze pollution".ATMOSPHERIC RESEARCH 225(2019):157-164.