%0 Journal Article
%T 贵阳龙洞堡机场雾的气候特征与低能见度变化原因浅析
Analysis of Climatic Characteristics and Causes of Low Visibility Change of Fog at Longdongbao Airport in Guiyang
%A 邓小光
%J Climate Change Research Letters
%P 325-331
%@ 2168-5703
%D 2023
%I Hans Publishing
%R 10.12677/CCRL.2023.122033
%X 根据贵阳龙洞堡机场气象观测资料，运用统计学相关方法对2017~2022年龙洞堡机场的雾天气进行统计分析。结果表明：统计时段内龙洞堡机场年雾频次总体呈下降趋势，1月和11月是雾的重点高发期，2月、6月、12月则是雾的低发期。平均起雾时段为01~07点，平均雾散时段为07~09点并表现出起雾时间春季早、秋季晚，维持时间冬春季长、夏秋季短，雾散时间春夏季早、秋冬季晚的特征。相关分析指出低能见度天气下能见度和跑道视程对于表征低能见度天气强度变化具有较为一致的结果。多元线性回归分析指出冬春季地面风速和地面露点温度的变化会对其产生正效应，而地面气温的变化会对其产生负效应，夏秋季则与之相反，并且不同季节三个因素影响占比也会有所不同。
According to the meteorological observation data of Longdongbao Airport in Guiyang, the foggy weather of Longdongbao Airport in 2017~2022 was analyzed by statistical correlation method. The results showed that the annual fog frequency of Longdongbao Airport showed a decreasing trend in the statistical period. January and November were the key peak periods of fog, while February, June and December were the low peak periods of fog. The average fogging period is 01~07, and the average fogging period is 07~09. The fogging time is early in spring and late in autumn, and the maintenance time is long in winter and spring, short in summer and autumn, and the fogging time is early in spring and summer, and late in autumn and winter. Correlation analysis shows that visibility and runway visual range are consistent with the variation of weather intensity in low visibility weather. Multiple linear regression analysis indicated that the changes of surface wind speed and surface dew point temperature in winter and spring would have a positive effect on it, while the changes of surface air temperature would have a negative effect on it. It was the opposite in summer and autumn, and the proportion of the three factors would be different in different seasons.
%K 统计分析，相关性分析，多元线性回归分析
Statistical Analysis
%K Correlation Analysis
%K Multiple Linear Regression Analysis
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=62395