以天津地区两次典型雾霾低能见度过程为例,通过发展适用于雾霾能见度观测的资料同化方法,实现PM2.5浓度、相对湿度及雾水含量等影响要素的模拟优化,提升模式能见度数值预报效果.研究表明,典型霾过程能见度变化主要受PM2.5浓度影响,最低值1km左右,随相对湿度日变化幅度为2~3km,雾霾混合过程相对湿度高,夜间雾显著影响导致局地能见度低于50m,能见度日变幅大、过程极值低是其典型特征;通过能见度观测资料同化应用,雾霾低能见度模拟效果有显著提升,两次过程的能见度均方根误差分别由7km和4km减小至2km左右,间隔6h同化可以及时修正模拟偏差,部分时段提升效果更优;通过同化实现PM2.5浓度和相对湿度模拟优化,霾能见度模拟偏差下降幅度最大达到6~8km;通过增加雾水含量修正,结合相对湿度同化改进,能够进一步改善雾霾混合过程夜间雾水含量考虑不足的问题,能见度模拟偏差由1~2km减小至300~500m,低能见度影响程度、影响范围均有明显提升;一个月模拟试验显示,低于10km的能见度模拟均方根误差由4.4km减小至3.2km.
Abstract
The present study took the two typical haze/fog low visibility episodes in Tianjin as a point of departure for the following investigation, developed data assimilation methods applicable to visibility observations, in order to improve the numerical forecast effect of visibility through the simulation optimization of PM2.5 concentration, relative humidity and fog water content. Theresults showed that the visibility change of typical haze episode was primarily influenced by PM2.5 concentration, the minimum value of visibilitywas approximately 1km, with the daily change about 2~3km in the result of relative humidity change. The relative humidity of the haze-fog mixing episode was high, and visibility was lower than 50min localities due to the significant influence of fog during nighttime. The typical characteristic of the haze-fog episode were largedaily change and extreme value being low in visibility. The simulation of haze-fog low visibilitywas significantly enhanced with assimilation of visibility observation, root mean square error of the two episodes reduced from 7km and 4km to approximately 2km. Furthermore, the simulation deviation was corrected in time with 6-hour interval assimilation, with an enhancement effect observed to be more pronounced during specific time periods. Through the assimilation to achieve the optimization of the PM2.5 concentration and the relative humidity simulation, the deviation of the haze visibility simulation was reduced by a maximum of 6~8km.By adding fog water content correction, combined with relative humidity assimilation improvement, the underestimate of fog water content was reduced during nocturnal periods, the visibility simulation deviation was reduced from 1~2km to 300~500m and the degree and range of the low visibility was significantly improved. One-month simulation showed that the root mean square error of visibility below 10 km was reduced from 4.4 km to 3.2 km.
关键词
雾霾 /
能见度 /
资料同化 /
三维变分 /
数值预报
Key words
haze/fog /
visibility /
data assimilation /
3-DVAR /
numerical forecast
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基金
国家自然科学基金资助项目(42130513);天津市气象局科研项目(202424ybxm17)
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