| 安徽省区域性强浓雾气候特征及影响因子 |
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| 引用本文： | 石春娥,张浩,杨关盈,王苏瑶. 安徽省区域性强浓雾气候特征及影响因子[J]. 气象学报, 2022, 80(6): 924-939. DOI: 10.11676/qxxb2022.062 |
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| 作者姓名： | 石春娥 张浩 杨关盈 王苏瑶 |
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| 作者单位： | 安徽省气象科学研究所/大气科学与卫星遥感安徽省重点实验室,合肥, 230031;寿县国家气候观象台/中国气象局淮河流域典型农田生态气象野外科学试验基地,寿县, 232200;淮北市气象局,淮北, 235000 |
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| 基金项目： | 国家自然科学基金项目（41875171）、安徽省重点研究和开发计划项目（1804a0802215） |
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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。
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| 关 键 词： | 区域性强浓雾 判断标准 年际变化 局地气象因子 大尺度环流 |
| 收稿时间： | 2022-02-28 |
| 修稿时间： | 2022-06-14 |
Climatic characteristics and influencing factors of regional extremely dense fog in Anhui province |
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| Affiliation: | 1.Anhui Institute of Meteorological Sciences/Anhui Province Key Laboratory of Atmospheric Sciences and Satellite Remote Sensing,Hefei 230031,China2.Shouxian National Climatology Observatory/Huaihe River Basin Typical Farm Eco-meteorological Experiment Field of CMA,Shouxian 232200,China3.Huaibei Meteorological Bureau,Huaibei 235000,China |
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| 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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