马鞍山大雾气候特征分析与预报方法
|
摘要
为了提高马鞍山地区大雾预报准确率,分析1961—2010年近50年来马鞍山地区大雾的气候特征,并建立基于配料法的大雾预报方法。结果表明:马鞍山市雾日集中在11月—次年1月,为"冬半年雾日多于夏半年"型。潮湿的空气(相对湿度为90%~100%)、微弱的风速(风速≤3 m/s)和适宜的气温(≤20℃)均有利于大雾的形成。925 h Pa和1000 h Pa是否有逆温层,对于雾的形成与维持极其重要。马鞍山大雾地面形势具体分为四类:弱高压型、入海高压后部型、冷锋前暖区型、地面倒槽型。选取水汽条件、冷却条件、层结条件以及风力条件作为大雾预报的基本"配料",建立马鞍山大雾预报方法。利用EC细网格资料(2011年9月—2013年12月)对该方法验证的漏报和空报分析:TS评分42.86%,漏报率6.9%,空报率55.74%。
In order to improve the fog forecast accuracy in Ma'anshan, the authors analyzed the climaticcharacteristics of heavy fog in Ma'anshan from 1961 to 2010 and established a fog prediction method based onthe method of ingredients. The results showed that: the fog days of Ma'anshan focused on November to Januaryof the following year, the fog days in winter were more than that in summer; the humid air(relative humiditywas 90% to 100%), the weak wind(wind speed was equal or less than 3 m/s) and suitable temperature(equal orless than 20℃) were all beneficial to the formation of fog; whether there was an inversion layer in 925 h Pa and1000 h Pa was beneficial to the thermosphere and was extremely important for the formation and maintenanceof fog; the ground situation of heavy fog in Ma'anshan was divided into four categories: weak high pressuretype, the back type of the high-pressure sea-going, cold front warm area type, ground reverse grooved type.The authors chose the water vapor condition, cooling condition, stratification condition and wind conditions asthe basic ingredients of fog forecast and established the prediction method of Ma'anshan. Using the data of ECfine grid(September 2011-December 2013) to analyze the failure report and empty report for this validationmethod: TS score was 42.86%, non report rate was 6.9% and the empty report rate was 55.74%.
In order to improve the fog forecast accuracy in Ma'anshan, the authors analyzed the climaticcharacteristics of heavy fog in Ma'anshan from 1961 to 2010 and established a fog prediction method based onthe method of ingredients. The results showed that: the fog days of Ma'anshan focused on November to Januaryof the following year, the fog days in winter were more than that in summer; the humid air(relative humiditywas 90% to 100%), the weak wind(wind speed was equal or less than 3 m/s) and suitable temperature(equal orless than 20℃) were all beneficial to the formation of fog; whether there was an inversion layer in 925 h Pa and1000 h Pa was beneficial to the thermosphere and was extremely important for the formation and maintenanceof fog; the ground situation of heavy fog in Ma'anshan was divided into four categories: weak high pressuretype, the back type of the high-pressure sea-going, cold front warm area type, ground reverse grooved type.The authors chose the water vapor condition, cooling condition, stratification condition and wind conditions asthe basic ingredients of fog forecast and established the prediction method of Ma'anshan. Using the data of ECfine grid(September 2011-December 2013) to analyze the failure report and empty report for this validationmethod: TS score was 42.86%, non report rate was 6.9% and the empty report rate was 55.74%.
引文
[1]中国气象局.地面气象观测规范[M].北京:气象出版社,2003:17-27.
[2]孙奕敏.灾害性浓雾[M].北京:气象出版社,1994:67-71.
[3]刘小宁,张洪政,李庆祥,等.中国大雾的气候特征及变化初步解释[J].应用气象学报,2005,16(2):220-230.
[4]李子华,仲良喜,余香仁.西南地区和长江下游雾的时空分布和物理结构[J].地理学报,1992,47(3):243-250.
[5]贺皓,吕红,徐虹.陕西省大雾的气候特征[J].高原气象,2004,23(3):407-411.
[6]王丽萍,陈少勇,董安祥.中国雾区的分布及其季节变化[J].地理学报,2005,60(4):689-697.
[7]史军,穆海振,崔林丽.上海大雾气候特征及风险区划研究[J].自然灾害学报,2012,21(3):102-109.
[8]童尧青,银燕,许遐祯.南京地区雾的气候特征[J].南京气象学院学报,2009,32(1):115-120.
[9]唐信英,罗磊,王鸽,等.四川省大雾时空分布特征研究[J].高原山地气象研究,2009,29(3):60-65.
[10]陶云,段旭,段长春,等.云南近50a雾的变化特征[J].云南大学学报:自然科学版,2011,33(3):308-316.
[11]周贺玲,李丽平,乐章燕,等.河北省雾的气候特征及趋势研究[J].气象,2011,37(4):462-467.
[12]张春花,吴胜安,林建兴,等.1969—2008年海南省雾的气候特征与变化趋势[J].气候变化研究进展,2010,6(5):349-355.
[13]郑玉萍,李景林.乌鲁木齐近31年大雾天气气候特征分析[J].气象,2008,34(8):22-28.
[14]徐凤梅,康邵钧,余卫东.商丘雾变化的气候特征及天气分型[J].气象科技,2007,35(3):355-358.
[15]常军,黄玉超,李素平,等.河南省大雾的时空分布特征及500h Pa环流特点分析[J].气象,2007,33(6):82-88.
[16]林建,杨贵名,毛冬艳.中国大雾的时空分布特征及其发生的环流形势[J].气候与环境研究,2008,13(2):171-181.
[17]赵繁盛,李燕,程航.大连地区夏季大雾天气特征及诊断分析[J].中国农学通报,2015,31(24):228-236.
[18]景学义,张雪梅,兰博文.哈尔滨市区雾的特征分析及预报指标研究[J].自然灾害学报,2005,14(2):47-49.
[19]陈晓红,方翀.安徽省县级大雾预报业务系统[J].气象,2005,31(4):61-64.
[20]滕卫平,杜惠良,项云法,等.浙江省大雾的气候特征及其与气象要素的关系[J].浙江大学学报:理学版.2009,36(5):594-602.
[21]田华,王亚伟.京津唐高速公路雾气候特征与气象条件分析[J].气象,2008,34(1):66-71.
[22]明惠青,孙丽,王艳丽,等.沈阳近60年大雾发生规律及与气象条件关系[J].中国农学通报,2014,30(26):248-252.
[23]毛冬艳,杨贵名.华北平原雾发生的气象条件[J].气象,2006,32(1):78-83.
[24]魏文华,王体健,石春娥,等.合肥市雾日气象条件分析[J].气象科学,2012,32(4):437-442.
[25]陶寅,王胜,田红,等.安徽省大雾时空分布特征及其发生的气象条件[J].地理科学,2012,32(3):374-379.
[26]俞小鼎.基于构成要素的预报方法——配料法[J].气象,2011,37(8):913-918.
[2]孙奕敏.灾害性浓雾[M].北京:气象出版社,1994:67-71.
[3]刘小宁,张洪政,李庆祥,等.中国大雾的气候特征及变化初步解释[J].应用气象学报,2005,16(2):220-230.
[4]李子华,仲良喜,余香仁.西南地区和长江下游雾的时空分布和物理结构[J].地理学报,1992,47(3):243-250.
[5]贺皓,吕红,徐虹.陕西省大雾的气候特征[J].高原气象,2004,23(3):407-411.
[6]王丽萍,陈少勇,董安祥.中国雾区的分布及其季节变化[J].地理学报,2005,60(4):689-697.
[7]史军,穆海振,崔林丽.上海大雾气候特征及风险区划研究[J].自然灾害学报,2012,21(3):102-109.
[8]童尧青,银燕,许遐祯.南京地区雾的气候特征[J].南京气象学院学报,2009,32(1):115-120.
[9]唐信英,罗磊,王鸽,等.四川省大雾时空分布特征研究[J].高原山地气象研究,2009,29(3):60-65.
[10]陶云,段旭,段长春,等.云南近50a雾的变化特征[J].云南大学学报:自然科学版,2011,33(3):308-316.
[11]周贺玲,李丽平,乐章燕,等.河北省雾的气候特征及趋势研究[J].气象,2011,37(4):462-467.
[12]张春花,吴胜安,林建兴,等.1969—2008年海南省雾的气候特征与变化趋势[J].气候变化研究进展,2010,6(5):349-355.
[13]郑玉萍,李景林.乌鲁木齐近31年大雾天气气候特征分析[J].气象,2008,34(8):22-28.
[14]徐凤梅,康邵钧,余卫东.商丘雾变化的气候特征及天气分型[J].气象科技,2007,35(3):355-358.
[15]常军,黄玉超,李素平,等.河南省大雾的时空分布特征及500h Pa环流特点分析[J].气象,2007,33(6):82-88.
[16]林建,杨贵名,毛冬艳.中国大雾的时空分布特征及其发生的环流形势[J].气候与环境研究,2008,13(2):171-181.
[17]赵繁盛,李燕,程航.大连地区夏季大雾天气特征及诊断分析[J].中国农学通报,2015,31(24):228-236.
[18]景学义,张雪梅,兰博文.哈尔滨市区雾的特征分析及预报指标研究[J].自然灾害学报,2005,14(2):47-49.
[19]陈晓红,方翀.安徽省县级大雾预报业务系统[J].气象,2005,31(4):61-64.
[20]滕卫平,杜惠良,项云法,等.浙江省大雾的气候特征及其与气象要素的关系[J].浙江大学学报:理学版.2009,36(5):594-602.
[21]田华,王亚伟.京津唐高速公路雾气候特征与气象条件分析[J].气象,2008,34(1):66-71.
[22]明惠青,孙丽,王艳丽,等.沈阳近60年大雾发生规律及与气象条件关系[J].中国农学通报,2014,30(26):248-252.
[23]毛冬艳,杨贵名.华北平原雾发生的气象条件[J].气象,2006,32(1):78-83.
[24]魏文华,王体健,石春娥,等.合肥市雾日气象条件分析[J].气象科学,2012,32(4):437-442.
[25]陶寅,王胜,田红,等.安徽省大雾时空分布特征及其发生的气象条件[J].地理科学,2012,32(3):374-379.
[26]俞小鼎.基于构成要素的预报方法——配料法[J].气象,2011,37(8):913-918.