大气与环境光学学报 ›› 2019, Vol. 14 ›› Issue (6): 419-430.

• 环境光学监测技术 • 上一篇    下一篇

合肥市霾日气象要素特征分析及预报方法研究

魏春璇, 黄鹤, 翟振芳, 张平   

  1. 合肥市气象局 安徽合肥  230041
  • 出版日期:2019-11-28 发布日期:2019-11-21

Analysis of Meteorological Elements and Forecast Method of Haze Day in Hefei, China

WEI Chunxuan, HUANG He, ZHAI Zhenfang, ZHANG Ping   

  • Published:2019-11-28 Online:2019-11-21

摘要: 利用合肥国家气象观测站建站以来历史观测资料(1952$\sim$2016年)及2004$\sim$2016年逐日地面观测资料和高空观测资料,
分析了合肥霾日及相关气象要素特征;并结合2004$\sim$2016年合肥空气质量数据,对合肥市霾的预报方法进行了研究,
初步得到了霾日和霾日能见度的预报方程;最后利用2017年的气象资料和空气质量资料对预报结果进行了检验。结果表明: 
合肥出现的霾以轻微霾和轻度霾为主;全市霾日逐月分布不均,其中1月和12月最多。霾的生消有比较明显的日变化,
霾出现的时间主要集中在每日的11:00$\sim$20:00。霾出现的有利气象条件是:风速$\leq$3 m/s,地面主导风向为
偏东风到偏南风,有负变压,正变温,相对湿度在50$\sim$70\%之间。低能见度的霾需要相对较高的相对湿度和负变压。
建立的霾日及霾日能见度方程预报准确度较高,可以为合肥市霾的预报预警提供一定参考。

关键词: 霾; , 能见度; , 气象要素, 预报

Abstract: Based on available observation data of Hefei Meteorological Station from 1952 to 2016 and the 
daily ground and altitude observation data from 2004 to 2016, the characteristics of haze day 
and related meteorological elements are analyzed. Then combining with the air pollution 
data of Hefei from 2004 to 2016, the prediction equations of haze day and the visibility in 
haze day are obtained preliminarily. Finally, the forecast results are verified by using the 
meteorological and air quality data of 2017. The results show that haze in Hefei is dominated 
by slight haze and mild haze, and the haze days distribute unevenly month by month, with the 
most haze days in January and December. The growth and elimination of haze have diurnal changes. 
Haze occurrs mainly at 11 to 20 o'clock every day. The favorable meteorological conditions for 
haze day are as follows: wind speed is less than 3 m/s, the leading wind direction is easterly 
or southerly, with negative pressure, positive temperature and relative humidity of 50$\sim$70\%. 
Low visibility haze requires high relative humidity and negative pressure. It is shown that the 
prediction equations have high accuracy, which can provide some reference for haze forecasting in Hefei.

Key words: haze, visibility, meteorological elements, forecast

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