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安徽省区域性强浓雾气候特征及影响因子

石春娥 张浩 杨关盈 王苏瑶

石春娥,张浩,杨关盈,王苏瑶. 2022. 安徽省区域性强浓雾气候特征及影响因子. 气象学报,80(6):924-939 doi: 10.11676/qxxb2022.062
引用本文: 石春娥,张浩,杨关盈,王苏瑶. 2022. 安徽省区域性强浓雾气候特征及影响因子. 气象学报,80(6):924-939 doi: 10.11676/qxxb2022.062
Shi Chun'e, Zhang Hao, Yang Guanying, Wang Suyao. 2022. Climatic characteristics and influencing factors of regional extremely dense fog in Anhui province. Acta Meteorologica Sinica, 80(6):924-939 doi: 10.11676/qxxb2022.062
Citation: Shi Chun'e, Zhang Hao, Yang Guanying, Wang Suyao. 2022. Climatic characteristics and influencing factors of regional extremely dense fog in Anhui province. Acta Meteorologica Sinica, 80(6):924-939 doi: 10.11676/qxxb2022.062

安徽省区域性强浓雾气候特征及影响因子

doi: 10.11676/qxxb2022.062
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)
详细信息
    作者简介:

    石春娥,主要从事大气物理与大气环境研究。E-mail:shichune@sina.com

  • 中图分类号: P426.4

Climatic characteristics and influencing factors of regional extremely dense fog in Anhui province

  • 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。

     

  • 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91046.13.315.0
    区域2:淮河以北东部773(2+2)6.23.419.5
    区域3:沿淮地区121453.92.414.3
    区域4:沿江地区293466.33.314.3
    区域5:江南111256.74.317.0
     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。
    下载: 导出CSV

    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)39.9324.4516.7812.239.057.104.882.881.55
    浓雾日数(d)26.6815.8010.908.155.784.282.801.550.73
    强浓雾日数(d)21.3512.258.2756.0754.302.951.950.8250.325
    偏度系数−0.050.470.79*0.530.600.510.76*1.71*1.61*
    峰度系数−0.300.100.83−0.17−0.16−0.300.343.54*1.75*
    区域2大雾日数(d)33.2819.7013.088.405.333.601.95
    浓雾日数(d)22.1012.537.884.953.302.051.18
    强浓雾日数(d)17.139.485.733.652.351.680.756.18
    偏度系数0.600.400.79*0.600.570.671.10*0.64
    峰度系数−0.44−0.710.09−0.70−0.62−0.650.21−0.22
    区域3大雾日数(d)44.5825.8518.2013.089.537.105.203.752.736.40
    浓雾日数(d)29.2016.47511.758.105.904.1252.851.901.2750.625
    强浓雾日数(d)23.1512.588.785.503.902.681.831.050.600.18
    偏度系数0.190.510.100.300.410.700.650.74*1.44*2.64*
    峰度系数−0.75−0.06−0.89−0.82−0.49−0.09−0.71−0.331.60*6.87*
    区域4大雾日数(d)80.0547.4034.3525.42520.0016.47513.52510.9259.3017.95
    浓雾日数(d)50.97529.67520.97515.1011.6259.157.656.0755.0754.275
    强浓雾日数(d)40.1822.1014.8511.108.356.355.103.883.102.53
    偏度系数−0.40−0.24−0.030.350.240.290.060.220.280.35
    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)99.9560.6041.8029.4321.1814.259.355.402.505.40
    浓雾日数(d)72.22541.47528.0019.12512.708.204.202.0751.0250.325
    强浓雾日数(d)55.5030.3818.3811.556.733.631.730.680.150.05
    偏度系数−0.84−0.64−0.35−0.130.160.431.74*1.93*3.01*4.29*
    峰度系数−0.41−0.54−0.90−1.26*−0.96−0.893.50*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。
    下载: 导出CSV

    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110.61**0.63**0.110.33*
    区域210.77**0.41**0.43**
    区域310.48**0.46**
    区域410.49**
    区域51
    区域平均0.910.930.900.860.85
     注:*、**分别表示通过α=0.05和0.01的信度t检验。
    下载: 导出CSV

    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1y=0.23x+3.010.557**0.646**0.706**(沿淮淮北)0.484**(淮河以北)
    区域2y=0.18x+4.270.413*0.578**0.389*(沿淮淮北)0.623**(淮河以北)
    区域3y=0.11x+2.700.3450.559**0.528**(江淮之间)0.688**(沿淮)
    区域4y=−0.01x+7.290.0320.2650.372*(沿江江南)0.322(沿江)
    区域5y=0.03x+8.080.0600.1640.353*(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。
    下载: 导出CSV

    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10.463***0.398**0.380**0.622***0.374**0.227−0.0310.060
    区域20.318**0.314*0.273*0.374**0.277*0.222−0.2040.108
    区域30.2110.284*0.278*0.315*0.1550.103−0.0580.073
    区域4−0.0260.0660.0330.2460.1470.194−0.304**0.255
    区域50.0760.0450.0130.1950.0380.120−0.240−0.131
     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。
    下载: 导出CSV

    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)0.1790.345**0.339**0.357**0.451***
    东亚槽位置指数0.2420.429***0.2400.1870.060
    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0.0440.0140.0680.058−0.037
     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。
    下载: 导出CSV

    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54423145.0 9.8
    2013年33331156.511.1
    2017年52210147.512.4
    雾少2005年10011143.0 6.1
    2010年00032145.0 8.5
    2015年10001145.514.4
    下载: 导出CSV
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  • 收稿日期:  2022-02-28
  • 录用日期:  2022-09-30
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  • 网络出版日期:  2022-06-15

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