摘要
根据1960—2013年每日02、08、14时和20时4个时次的能见度、相对湿度以及逐日天气现象资料,利用趋势分析和分段线性拟合等方法对辽宁省14个城市霾日的时空特征进行分析。结果表明:辽宁省月平均霾日1月最多,为13.1 d;14个城市相比,沈阳明显多于其他城市。全省平均冬季霾日最多,为34.4 d;14个城市相比,沈阳最多,为60.3 d。全省平均年霾日呈明显的下降趋势,其趋势率为-7.2 d/10 a;各城市相比,除葫芦岛、丹东、阜新和抚顺外,其他各城市年霾日均呈下降趋势。1979年前,除盘锦、营口、本溪和沈阳外,其他城市年霾日均呈上升趋势;1980年后,除葫芦岛、抚顺、朝阳和营口外,其他城市年霾日均呈下降趋势。全省平均年代霾日20世纪70年代最多,为108.5 d,而后呈逐渐下降趋势;14个城市平均年代霾日变化可分为剧变型、波动型和稳定型3个类型。从空间变化看,月、季、年、年代霾日呈多中心态势,空间差异明显。不同时段,区域霾日空间变化各不相同。
Based on visibility and relative humidity data at 02：00,08：00,14：00 and 20：00 in a day as well as daily weather phenomenon during 1960 to 2013 in 14 urban stations of Liaoning province, spatial and temporal charac- teristics of haze day were analyzed by methods of a trend analysis and a piecewise linear fitting. The results indi- cate that for temporal variation of haze day,the maximum mean monthly haze day of 13.1 d in Liaoning province occurs in January. The number of haze day in Shenyang is highest among the 14 urban stations. The maximum mean seasonal haze day of 34. 4 d in Liaoning province occurs in winter. Among the 14 urban stations, the maxi- mum seasonal haze day appears in Shenyang and it is 60. 3 d. Mean annual haze day in Liaoning province is in a decreasing trend,and its trend ratio is -7.2 d/10 a. Among the 14 urban stations,it is in an increasing trend ex- cept in Huludao, Dandong, Fuxin and Fushun stations, while it is contrary in the other stations. Annual haze day is in an increasing trend except in Panjin, Yingkou, Benxi and Shenyang stations before 1979, while it is contrary ex- cept in Huludao,Fushun,Chaoyang and Yingkou station after 1980. The maximum mean interdecadal haze day in Liaoning province occurs in 1970s,and it is 108.5 d. Since then,it is in a decreasing trend. There are three types for variation of mean interdecadal haze day, i. e. sharp, fluctuant and stable types. For spatial variation of haze day, there is significant difference for monthly, seasonal, annual, interdecadal haze day, and each has several centers. Re- gional spatial distribution is different in different periods.
出处
《气象与环境学报》
2015年第6期115-122,共8页
Journal of Meteorology and Environment
基金
辽宁省科技攻关项目"辽宁省大气灰霾的污染形成机制及预报预警技术研究"(2013229031)
中央公益性科研院所基本科研业务费(2015IAE-CMA06)共同资助
关键词
霾日
趋势分析
分段线性拟合
Haze day
Trend analysis
Piecewise linear fitting
