Climatic characteristics and influencing factors of regional extremely dense fog in Anhui province
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摘要: 根据强浓雾发生的同步性，可将安徽分为5个不同的区域。为了解安徽区域性强浓雾的演变规律及成因，首先利用1980—2019年安徽省68个资料完整的国家级气象观测站08时能见度、相对湿度和天气现象资料，探讨了各区域区域性强浓雾的判定标准，建立各区域40 a的区域性强浓雾日时序资料，分析了区域性强浓雾的年际和年代际变化趋势；然后利用2016—2019年77个国家级气象观测站逐时资料分析了不同区域区域性强浓雾的年变化、日变化及持续时间分布等特征；最后，探讨了冬季区域性强浓雾年际变化的成因。结果表明：（1）1980—2019年，沿淮淮北3个区域区域性强浓雾日数都有先升后降的变化趋势，转折点在2006/2007年；1980—2007年区域性强浓雾日数呈明显的上升趋势，应归因于气溶胶粒子浓度升高。年代际比较，各区域区域性强浓雾日数都是20世纪90年代或21世纪最初10年最多，21世纪第2个10年最少；各区域区域性强浓雾出现日数年际变化大，最少的年份0—1 d，最多年份可超过10 d。（2）2016—2019年，各区域年均区域性强浓雾日数14—17 d，主要集中在仲秋到仲春；持续1 h的强浓雾日占比最高，持续3 h的样本是另一个峰值；淮河以北2个区域年均区域性强浓雾日数最多、且持续时间达到3 h及以上的区域性强浓雾占比最高。（3）淮河以北冬季区域性强浓雾日数与降水日数、降水量、相对湿度和08时气温均呈较为显著的正相关，而与风速和小风日数相关不显著；沿江地区冬季区域性强浓雾日数主要受地面风速影响；而江南冬季强浓雾日数与各地面因子均不存在明显相关。（4）以1月为例，各区域区域性强浓雾日数都与纬向环流指数呈正相关，沿淮淮北3个区域区域性强浓雾日数都与东亚槽位置呈正相关，而与东亚槽强度相关不明显。说明纬向型环流、东亚槽位置偏东有助于安徽沿淮淮北形成强浓雾。进一步分析发现，雾多的1月海平面气压中40°N以北的1030 hPa等值线位置偏东（如在120°E以东），近地层偏东风较强，地面湿度偏高。Abstract: According to the synchronization of extremely dense fog (EDF) at individual stations, Anhui province can be divided into five regions with different statistical characteristics of fog. To understand the evolution and causes of regional extremely dense fog (REDF) in Anhui province, the criteria to identify REDF days in Anhui province are determined first based on the 08:00 BT visibility data and daily weather phenomenon records collected at 68 national meteorological stations that have complete data in Anhui province from 1980 to 2019. Time series of REDF days in each region over the 40-year period are obtained, and the interannual and interdecadal variation trends of REDF are analyzed. Monthly and daily variations and duration of REDF in different regions are then analyzed using hourly data collected at 77 national meteorological stations from 2016 to 2019. Finally, the causes of interannual variation of REDF in winter are investigated. Results are as follows: (1) From 1980 to 2019, annual REDF in the three regions along and to the north of the Huaihe river first increases and then decreases with the turning point in 2006/2007. The obvious annual REDF increase from 1980 to 2007 may be attributed to the increase in aerosol particles during the same period. Decadal average number of REDF in all the regions is the highest in the 1990s and/or 2000s and the lowest in the 2010s. The number of REDF in each region varies greatly from year to year, with a minimum of 0—1 d and a maximum of more than 10 d. (2) From 2016 to 2019, the number of annual average REDF days in each region is 14—17 d, and these days are mainly concentrated from mid-autumn to mid-spring. Those REDF days with fog lasting for only 1 h account for the largest proportion of total sample days, followed by those with fog lasting for 3 h. The two regions to the north of the Huaihe river have the largest number of annual REDF days and also the largest percentage of REDF days with fog lasting for at least 3 h. (3) The number of REDF in winter in regions to the north of the Huaihe river is significantly positively correlated with the number of precipitation days, seasonal precipitation, relative humidity and air temperature at 08:00 BT. But the correlation with wind speed and the number of light wind days (daily average wind speed less than 2 m/s) is not significant. The number of winter REDF days in the region along the Yangtze river is mainly determined by ground level wind speed. However, there is no significant correlation between the number of winter REDF days and any ground level meteorological factors in the region to the south of the Yangtze river. (4) Taking January as an example, REDF days are positively correlated with zonal circulation index in each region. The REDF days in the three regions, including one region along the Huaihe river and two regions to the north of the Huaihe river, are positively correlated with the location of the East Asian trough but not with its intensity, suggesting that zonal circulation and eastward location of the East Asian trough contribute to the formation of REDF therein. Further comparative analysis of the circulations in January between more REDF days and less REDF days in consecutive years in the region to the north of the Huaihe river shows that, when the 1030 hPa isoline of sea level pressure to the north of 40°N is located to the east (e.g. to the east of 120°E) in January, more REDF days could occur with stronger easterly winds and higher relative humidity at ground level.
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图 1 安徽省强浓雾分区 （绿色表示地形高低，红线为各区分界线） （石春娥等，2021a）
Figure 1. Partition results of Anhui province based on the consistency of extremely dense fog （the green color indicates the elevation of the terrain，the red lines are the regional boundaries）（Shi，et al，2021a）
图 2 1980—2019年各区区域性强浓雾日数的年际变化
Figure 2. Interannual variations of REDF days in each region from 1980 to 2019
图 3 1980—2019年各区区域性强浓雾日数年代际变化
Figure 3. Interdecadal variations of REDF days in various regions from 1980 to 2019
图 4 2016—2019年各区域平均区域性强浓雾日数年变化
Figure 4. Annual variations of REDF days in various regions averaged over 2016 to 2019
图 5 2016—2019年各区域年平均区域性强浓雾出现次数日变化
Figure 5. Diurnal variations of occurrence time of REDF in each region averaged over 2016 to 2019
图 6 2016—2019年各区域不同持续时间的区域性强浓雾频率分布
Figure 6. Frequency distributions of REDF with different durations in each region from 2016 to 2019
图 7 多雾1月 （a. 2006年，c. 2013年，e. 2017年） 与少雾1月 （b. 2005年，d. 2010年，f. 2015年） 500 hPa平均位势高度 （单位：dagpm；图中黑色实心圆点为蒙城气象站大致位置，代表沿淮淮北中心位置）
Figure 7. Average geopotential height （unit：dagpm） at 500 hPa in January of more fog days （a. 2006，c. 2013，e. 2017） and January of fewer fog days （b. 2005，d. 2010，f. 2015） （the black spot is the Mengcheng weather station）
图 8 同图7，但为925 hPa的平均风 （矢量） 和1000 hPa平均相对湿度 （色阶） （黑点和三角分别为蒙城和合肥的大致位置）
Figure 8. Same as Fig. 7 but for average winds at 925 hPa （vector） and average relative humidity （color shaded） at 1000 hPa （the black dot and triangle are the locations of Mengcheng and Hefei，respectively）
图 9 同图7，但为平均海平面气压 （等值线，单位：hPa） 和10 m风速 （矢线） （色阶为平均风速）
Figure 9. Same as Fig. 7 but for average sea level pressure （isoline，unit：hPa） and 10 m wind （the color shade represents the average wind speed）
表 1 不同区域区域性强浓雾统计结果
Table 1. Statistical results of regional extremely dense fog （REDF） in each region
名称 有效站数 总站数 区域性强浓雾要求
的最少站数年均区域性强
浓雾日数（d）*年区域性强浓雾
日数标准差（d）*年均区域性强
浓雾日数（d）**区域1：淮河以北西部 9 10 4 6.1 3.3 15.0 区域2：淮河以北东部 7 7 3（2+2） 6.2 3.4 19.5 区域3：沿淮地区 12 14 5 3.9 2.4 14.3 区域4：沿江地区 29 34 6 6.3 3.3 14.3 区域5：江南 11 12 5 6.7 4.3 17.0 注：*代表统计时段为1980—2019年08时，**代表统计时段为2016—2019年；已剔除各区域有资料缺失的站点。 
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表 2 各区域08时单站或多站同时出现雾、浓雾和强浓雾的年均日数及1980—2019年强浓雾日数序列的偏度和峰度系数
Table 2. Annual average number of days with fog，dense fog and extremely dense fog at single station or multiple stations at 08：00 in each region and skewness and kurtosis coefficients of series of extremely dense fog days from 1980 to 2019
站数 ≥1 ≥2 ≥3 ≥4 ≥5 ≥6 ≥7 ≥8 ≥9 ≥10 区域1 大雾日数（d） 39.93 24.45 16.78 12.23 9.05 7.10 4.88 2.88 1.55 浓雾日数（d） 26.68 15.80 10.90 8.15 5.78 4.28 2.80 1.55 0.73 强浓雾日数（d） 21.35 12.25 8.275 6.075 4.30 2.95 1.95 0.825 0.325 偏度系数 −0.05 0.47 0.79* 0.53 0.60 0.51 0.76* 1.71* 1.61* 峰度系数 −0.30 0.10 0.83 −0.17 −0.16 −0.30 0.34 3.54* 1.75* 区域2 大雾日数（d） 33.28 19.70 13.08 8.40 5.33 3.60 1.95 浓雾日数（d） 22.10 12.53 7.88 4.95 3.30 2.05 1.18 强浓雾日数（d） 17.13 9.48 5.73 3.65 2.35 1.68 0.75 6.18 偏度系数 0.60 0.40 0.79* 0.60 0.57 0.67 1.10* 0.64 峰度系数 −0.44 −0.71 0.09 −0.70 −0.62 −0.65 0.21 −0.22 区域3 大雾日数（d） 44.58 25.85 18.20 13.08 9.53 7.10 5.20 3.75 2.73 6.40 浓雾日数（d） 29.20 16.475 11.75 8.10 5.90 4.125 2.85 1.90 1.275 0.625 强浓雾日数（d） 23.15 12.58 8.78 5.50 3.90 2.68 1.83 1.05 0.60 0.18 偏度系数 0.19 0.51 0.10 0.30 0.41 0.70 0.65 0.74* 1.44* 2.64* 峰度系数 −0.75 −0.06 −0.89 −0.82 −0.49 −0.09 −0.71 −0.33 1.60* 6.87* 区域4 大雾日数（d） 80.05 47.40 34.35 25.425 20.00 16.475 13.525 10.925 9.30 17.95 浓雾日数（d） 50.975 29.675 20.975 15.10 11.625 9.15 7.65 6.075 5.075 4.275 强浓雾日数（d） 40.18 22.10 14.85 11.10 8.35 6.35 5.10 3.88 3.10 2.53 偏度系数 −0.40 −0.24 −0.03 0.35 0.24 0.29 0.06 0.22 0.28 0.35 峰度系数 −1.04 −0.95 −0.65 −0.39 −0.22 −0.43 −0.59 −0.79 −0.39 −1.01 区域5 大雾日数（d） 99.95 60.60 41.80 29.43 21.18 14.25 9.35 5.40 2.50 5.40 浓雾日数（d） 72.225 41.475 28.00 19.125 12.70 8.20 4.20 2.075 1.025 0.325 强浓雾日数（d） 55.50 30.38 18.38 11.55 6.73 3.63 1.73 0.68 0.15 0.05 偏度系数 −0.84 −0.64 −0.35 −0.13 0.16 0.43 1.74* 1.93* 3.01* 4.29* 峰度系数 −0.41 −0.54 −0.90 −1.26* −0.96 −0.89 3.50* 3.22* 9.23* 17.29* 注：*表示超过临界值，不满足正态分布；加粗表示认定的标准；临界偏度系数和峰度系数分别为0.70和1.26。
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表 3 各区域之间年区域性强浓雾日数的相关系数
Table 3. Correlation coefficients of annual REDF days between regions
区域1 区域2 区域3 区域4 区域5 区域1 1 0.61** 0.63** 0.11 0.33* 区域2 1 0.77** 0.41** 0.43** 区域3 1 0.48** 0.46** 区域4 1 0.49** 区域5 1 区域平均 0.91 0.93 0.90 0.86 0.85 注：*、**分别表示通过α=0.05和0.01的信度t检验。
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表 4 1980—2007年各区域区域性强浓雾日数的线性拟合方程及决定系数
Table 4. Linear fitting equation and determination coefficient of REDF days in each region from 1980 to 2007
区域 线性拟合方程 决定系数R2 与全省平均霾日数的相关系数
（石春娥等，2016）与区域性霾日数的相关
系数（石春娥等，2018）与区域平均霾日数的相关
系数（石春娥等，2016）区域1 y=0.23x+3.01 0.557** 0.646** 0.706**（沿淮淮北） 0.484**（淮河以北） 区域2 y=0.18x+4.27 0.413* 0.578** 0.389*（沿淮淮北） 0.623**（淮河以北） 区域3 y=0.11x+2.70 0.345 0.559** 0.528**（江淮之间） 0.688**（沿淮） 区域4 y=−0.01x+7.29 0.032 0.265 0.372*（沿江江南） 0.322（沿江） 区域5 y=0.03x+8.08 0.060 0.164 0.353*（沿江江南） 0.306（江南） 注：*、**分别表示通过α=0.05和0.01的信度t检验。y表示强浓雾日数，x表示年份序号，1980年为第一年；右2列括号内的文字说明所对应引用论文中的区域名称。
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表 5 冬季 （12月—次年2月） 各区域区域性强浓雾日数与局地气象因子的相关系数
Table 5. Correlation coefficients between REDF days and local meteorological parameters in winter （December—next February）
区域 总降水日数 5 mm以上降水日数 降水量 相对
湿度08时气温 平均气温 风速 小风日数 区域1 0.463*** 0.398** 0.380** 0.622*** 0.374** 0.227 −0.031 0.060 区域2 0.318** 0.314* 0.273* 0.374** 0.277* 0.222 −0.204 0.108 区域3 0.211 0.284* 0.278* 0.315* 0.155 0.103 −0.058 0.073 区域4 −0.026 0.066 0.033 0.246 0.147 0.194 −0.304** 0.255 区域5 0.076 0.045 0.013 0.195 0.038 0.120 −0.240 −0.131 注：*、**、***分别指通过α=0.1、0.05和0.01信度t检验；自由度为37，α=0.1、0.05、0.01对应临界相关系数分别为0.267、0.316和0.408。
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表 6 各区域1月区域性强浓雾日数与一些气候指数的相关系数
Table 6. Correlation coefficients between the number of REDF days in January and various climate indexes in each region
区域 区域1 区域2 区域3 区域4 区域5 亚洲纬向环流指数（西风指数） 0.179 0.345** 0.339** 0.357** 0.451*** 东亚槽位置指数 0.242 0.429*** 0.240 0.187 0.060 亚洲经向环流指数 −0.108 −0.075 −0.124 −0.135 −0.249 东亚槽强度指数 0.044 0.014 0.068 0.058 −0.037 注：**和***分别指通过α=0.05和0.01信度t检验；自由度为38，α=0.1、0.05、0.01对应临界相关系数分别为0.264、0.312和0.403。
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表 7 选取的对比年份1月各区域区域性强浓雾日数 （d） 及东亚大槽位置指数 （°E） 和纬向环流指数
Table 7. Number of REDF days （d） in January in the years selected for comparison and corresponding IEATP （°E） and IZ
年份 区域1 区域2 区域3 区域4 区域5 东亚大槽位置指数 纬向环流指数 雾多 2006年 5 4 4 2 3 145.0 9.8 2013年 3 3 3 3 1 156.5 11.1 2017年 5 2 2 1 0 147.5 12.4 雾少 2005年 1 0 0 1 1 143.0 6.1 2010年 0 0 0 3 2 145.0 8.5 2015年 1 0 0 0 1 145.5 14.4
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