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Pan Wei, Zuo Zhiyan, Xiao Dong, et al. Interdecadal variation of haze days over China with atmospheric causes in recent 50 years. J Appl Meteor Sci, 2017, 28(3): 257-269. DOI: 10.11898/1001-7313.20170301.
Citation: Pan Wei, Zuo Zhiyan, Xiao Dong, et al. Interdecadal variation of haze days over China with atmospheric causes in recent 50 years. J Appl Meteor Sci, 2017, 28(3): 257-269. DOI: 10.11898/1001-7313.20170301.
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Interdecadal Variation of Haze Days over China with Atmospheric Causes in Recent 50 Years

  • State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing 100081

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    Abstract
  • Characteristics of interdecadal variations of haze days over China and plausible meteorological causes during 1961 to 2013 are analyzed, using observations from 745 meteorological stations in China. Results show that most haze weather occurs over the east part of China from South China to North China where haze days exhibit an increasing trend especially in economically developed areas, such as North China, the Huanghuai and Jianghuai Plains. Haze days are fewer in large parts of Northeastern China and Western China, and haze days show decreasing tendency in these regions. Generally, haze days are more frequent in autumn and winter than those in spring and summer. Also, autumn and winter are seasons that variation of haze days is most significant. Haze days occur more frequently in January and December than other months. The first mode of EOF reflects a monotonically increasing trend in the east part of China. The second mode shows that the region from South China to the Huaihe River and the region from the Huaihe River to North China present opposite variation tendency of phase. Focusing on regions from South China to the Huaihe River and from the Huaihe River to North China, haze days show an increasing trend year by year over the region from South China to the Huaihe River in autumn and winter before 2000, and then the trend is smoother. In the region from the Huaihe River to North China, however, haze days change gently in recent 30 years in autumn and winter. The variation of haze days relate to surface wind speed and relative humidity. Haze days show a significant negative relationship with surface wind speed before 1990s. Haze days may be influenced by variations of east wind in the region from South China to the Huaihe River in autumn, while northeast wind in the winter. For region from the Huaihe River to North China, haze days is concerned with south wind in autumn, while haze days have nothing to do with wind in winter. The relativity between haze days and surface wind speed weakens, but haze days have significant relationship with relative humidity after 1990s. Haze days experience an increasing tendency because of the reduced surface wind before 1990s and the decrease of relative humidity after 1990s over the region from South China to the Huaihe River in autumn and winter. In comparison, haze days show moderate variations in the region from the Huaihe River to North China, which are probably related to the moderate variability in surface speed and relative humidity in autumn and winter.
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  • Fig  1.   The distribution of annually mean haze days (the shaded) and standard deviations (contour, unit:d) in China during 1961-2013

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    Fig  2.   Trend of annual haze days passing the test of 0.05 level in China during 1961-2013(the shaded)

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    Fig  3.   The EOF analysis of haze days in autumn and winter during 1961-2013

    (a) the spatial distribution of the first characteristic vector in autumn, (b) the temporal variation of the first characteristic vector in autumn, (c) the spatial distribution of the second characteristic vector in autumn, (d) the temporal variation of the second characteristic vector in autumn, (e) the spatial distribution of the first characteristic vector in winter, (f) the temporal variation of the first characteristic vector in winter, (g) the spatial distribution of the second characteristic vector in winter, (h) the temporal variation of the second characteristic vector in winter

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    Fig  4.   Time series of normalized haze days over southern and northern China in autumn and winter during 1961-2013

    (a) haze days in southern China, (b) haze days in northern China

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    Fig  5.   Climatological surface horizontal wind in autumn and winter during 1961-2013

    (a) wind in autumn, (b) wind in winter

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    Fig  6.   21-year sliding correlation coefficients between haze days and surface wind speed over southern and northern China in autumn and winter during 1961-2013

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    Fig  7.   Time series of surface wind speed over southern and northern China in autumn and winter during 1961-2013

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    Fig  8.   Time series of specific humidity, saturation specific humidity and relative humidity over southern and northern China in autumn and winter during 1961-2013

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    Fig  9.   21-year sliding correlation coefficients between haze days and relative humidity over southern and northern China in autumn and winter during 1961-2013

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  • 张小曳, 孙俊英, 王亚强, 等.我国雾-霾成因及其治理的思考.科学通报, 2013, 58(13):1178-1187. http://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201313003.htm
    中国气象局.地面气象观测规范.北京:气象出版社, 2003.
    徐晓斌.我国霾和光化学污染观测研究进展.应用气象学报, 2016, 27(5):604-619. DOI: 10.11898/1001-7313.20160509
    Ma J, Xu X, Zhao C, et al.A review of atmospheric chemistry research in China:Photochemical smog, haze pollution, and gas-aerosol interactions.Adv Atmos Sci, 2012, 29(5):1006-1025. DOI: 10.1007/s00376-012-1188-7
    廖国莲, 曾鹏, 郑凤琴, 等.1960-2009年广西霾日时空变化特征.应用气象学报, 2011, 22(6):732-739. DOI: 10.11898/1001-7313.20110611
    黄健, 吴兑, 黄敏辉, 等.1954-2004年珠江三角洲大气能见度变化趋势.应用气象学报, 2008, 19(1):61-70. DOI: 10.11898/1001-7313.20080111
    吴兑, 吴晓京, 李菲, 等.1951-2005年中国大陆霾的时空变化.气象学报, 2010, 68(5):680-688. DOI: 10.11676/qxxb2010.066
    高歌.1961-2005年中国霾日气候特征及变化分析.地理学报, 2008, 63(7):761-768. DOI: 10.11821/xb200807010
    宋连春, 高荣, 李莹, 等.1961-2012年中国冬半年霾日数的变化特征及气候成因分析.气候变化研究进展, 2013, 9(5):313-318. http://www.cnki.com.cn/Article/CJFDTOTAL-QHBH201305001.htm
    Zhang X Y, Wang Y Q, Niu T, et al.Atmospheric aerosol compositions in China:Spatial/temporal variability, chemical signature, regional haze distribution and comparisons with global aerosols. Atmospheric Chemistry and Physics, 2012, 12(2):779-799. DOI: 10.5194/acp-12-779-2012
    尹志聪, 王会军, 郭文利.华北黄淮地区冬季雾和霾的时空气候变化特征.地球科学, 2015, 45(5):649-655. http://www.cnki.com.cn/Article/CJFDTOTAL-JDXK201505009.htm
    尹志聪, 王会军, 袁东敏.华北黄淮冬季霾年代际增多与东亚冬季风的减弱.科学通报, 2015, 60(15):1395-1400. http://www.cnki.com.cn/Article/CJFDTOTAL-KXTB201515008.htm
    张雅斌, 林琳, 吴其重, 等."13·12"西安重污染气象条件及影响因素.应用气象学报, 2016, 27(1):35-46. DOI: 10.11898/1001-7313.20160104
    颜鹏, 刘桂清, 周秀骥, 等.上甸子秋冬季雾霾期间气溶胶光学特性.应用气象学报, 2010, 21(3):257-265. DOI: 10.11898/1001-7313.20100301
    Song Y F, Liu Y J, Ding Y H.A study of surface humidity change in China during the recent 50 years.Acta Meteor Sin, 2012, 26:541-553. DOI: 10.1007/s13351-012-0501-9
    丁一汇, 柳艳菊.近50年我国雾与霾的长期变化特征及其与大气湿度的关系.中国科学 (地球科学), 2014, 44(1):37-48. http://www.cnki.com.cn/Article/CJFDTOTAL-JDXK201401005.htm
    Li Q, Zhang R H, Wang Y.Interannual variation of the wintertime fog-haze days across central and eastern China and its relation with east Asian winter monsoon.Int J Clim, 2016, 36(1):346-354. DOI: 10.1002/joc.4350
    Lin C G, Yang K, Huang J P, el at.Impacts of wind stilling on solar radiation variability in China.Nature Scientific Reports, 2015, 5, 15135, DOI: 10.1038/srep15135.
    Xiao D, Li Y, Fan S J, et al.Plausible influence of Atlantic Ocean SST anomalies on winter haze in China.Theoretical and Applied Climatology, 2015, 122(1):249-257.
    Zhao S, Li J P, Sun C.Decadal variability in the occurrence of wintertime haze in central eastern China tied to the Pacific Decadal Oscillation.Sci Rep, 2016, 6, 27424, DOI: 10.1038/srep27424.
    Feng J, Liao H, Li J P.The impact of monthly variation of Pacific-North America (PNA) teleconnection pattern on wintertime surface-layer aerosol concentrations in the United States.Atmospheric Chemistry and Physics, 2016, 16:4927-4943. DOI: 10.5194/acp-16-4927-2016
    靳军莉, 严鹏, 马志强, 等.北京及周边地区2013年1-3月PM2.5变化特征.应用气象学报, 2014, 25(6):690-700. DOI: 10.11898/1001-7313.20140605
    司鹏, 高润祥.天津雾和霾自动观测与人工观测的对比评估.应用气象学报, 2015, 26(2):240-246. DOI: 10.11898/1001-7313.20150212
    吴兑, 廖国莲, 邓雪娇.珠江三角洲霾天气的近地层输送条件研究.应用气象学报, 2008, 19(1):1-9. DOI: 10.11898/1001-7313.20080101
    史军, 崔林丽, 贺千山, 等.华东雾和霾日数的变化特征及成因分析.地理学报, 2010, 65(5):533-541. DOI: 10.11821/xb201005003
    张利, 吴涧, 张武.1955-2000年中国能见度变化趋势分析.兰州大学学报 (自然科学版), 2011, 47(6):46-55. http://www.cnki.com.cn/Article/CJFDTOTAL-LDZK201106011.htm
    吴兑.再论相对湿度对区别都市霾与雾 (轻雾) 的意义.广东气象, 2006(1):9-13. http://www.cnki.com.cn/Article/CJFDTOTAL-GDCX200601002.htm
    Schichtel B A, Husar R B, Falker S R, et al.Hzae trends over the United Sates 1980-1995.Atmos Environ, 2001, 35:5205-5210. DOI: 10.1016/S1352-2310(01)00317-X
    Doyle M, Dorling S.Visibility trends in the UK 1950-1997.Atmos Environ, 2001, 36:3161-3172.
    吴兑, 吴晓京, 朱小祥.雾与霾.北京:气象出版社, 2009.
    赵普生, 徐晓峰, 孟伟, 等.京津冀区域霾天气特征.中国环境科学, 2012, 32(1):31-36. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGHJ201201004.htm
    胡亚旦, 周自江.中国霾天气的气候特征分析.气象, 2009, 35(7):73-78. DOI: 10.7519/j.issn.1000-0526.2009.07.011
    孙彧, 马振锋, 牛涛.最近40年中国雾日数和霾日数的气候变化特征.气候与环境研究, 2013, 18(3):397-406. DOI: 10.3878/j.issn.1006-9585.2013.12170
    张人禾, 李强, 张若楠.2013年1月中国东部持续性强雾霾天气产生的气象条件分析.中国科学 (地球科学), 2014, 44(1):27-36. http://www.cnki.com.cn/Article/CJFDTOTAL-JDXK201401004.htm
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    • Received : 2016-11-30
    • Accepted : 2017-03-08
    • Published : 2017-05-30
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