标题:
近三年福建省霾分布特征与天气成因分析The Analysis of Haze Distribution and Weather Causes in Fujian Province during the Last Three Years
作者:
王宏, 谢祖欣, 郑秋萍, 陈彬彬
关键字:
霾天气过程, 分布特征, 天气成因, 福建省Haze Process, Distribution Characteristics, Weather Causes, Fujian Province
期刊名称:
《Climate Change Research Letters》, Vol.5 No.4, 2016-10-18
摘要:
本文利用2014年10月~2016年5月福建省9个设区城市常规地面气象观测资料、3个探空站资料与环境监测国控点PM2.5小时浓度资料，综合研判了全省17次典型的霾天气过程，并对比了近两年霾高发期2014年10月~2015年5月与2015年10月~2016年5月全省霾天气的出现次数、影响范围、持续时间、等级强度、天气成因等的不同点。结果表明：在极强的厄尔尼诺事件背景下，2015年10月~2016年5月福建的霾天气过程并没有因降水异常偏多而减少，反而出现次数略有增加，持续时间明显增长，主要以轻度~中度为主，重度霾发生的时次有所增加；除人为排放外，积累型霾天气约占25%，区域输送型霾天气约占75%，这与历史(2005~2014年)资料统计的比例趋势相反，区域输送过程数明显增多。将日均相对湿度在80%以下的干霾与日均相对湿度80%~95%的湿霾天气区别分析其生成、维持、消散的天气成因，建立霾的天气学概念模型和预报判别指标，对提高霾天气的预报准确率有一定帮助。
Surface meteorological data of 9 cities in Fujian, 3 radiosonde stations’ data and hourly PM2.5 concentration data monitored by Environmental Monitoring Station of China from October 2014 to May 2016 were applied to investigate 17 typical haze processes in Fujian province. It compared the frequency, influence, duration, grade and weather causes during the favorable incidence of haze processes in recent 2 years (from October 2014 to May 2015, and from October 2015 to May 2016). The analysis indicated that: in the El Nio background, the frequency of haze processes had not reduced by more precipitation during October 2015 - May 2016. Rather, the frequency of haze processes had slightly increased and its duration had obvious growth. Pollution level was mainly light-moderate pollution, and the frequency of heavy pollution had increased. Beside human pollution, local accumulation haze weather accounted for about 25%, while regional transportation haze weather was about 75%. Contrary to the history (2005-2014) statistics, regional transportation had increased obviously. It has certain help to improve the prediction of haze weather by analyzing its formation, maintenance, and dissipation of the weather causes respectively, and to establish a haze weather conceptual model and prediction index.