高原气象

高原气象 >

2019 , Vol. 38 >Issue 4: 829 - 844

DOI: https://doi.org/10.7522/j.issn.1000-0534.2018.00107

论文

1971年以来安徽省秋季连阴雨特征及成因分析

  • 何冬燕 ,
  • 吴蓉 ,
  • 田红 ,
  • 邓汗青 ,
  • 罗连升
展开
  • 安徽省气候中心/安徽省大气科学与卫星遥感重点实验室, 安徽 合肥 230031

收稿日期: 2018-06-23

  网络出版日期: 2019-08-28

基金资助

国家重点研发计划项目（2017YFD0301301）；安徽省中央引导地方科技发展专项（709261838023）；安徽省气象局气象科技发展基金项目（KM201802）；上海城市气候变化应对重点开放实验室开放基金项目（QHBHSYS201901）；中国气象局气候变化专项（CCSF201809）

收起

Analysis on the Feature and Formation Mechanism of the Continuous Rain in Autumn in Anhui since 1971

  • HE Dongyan ,
  • WU Rong ,
  • TIAN Hong ,
  • DENG Hanqing ,
  • LUO Liansheng
Expand
  • Anhui Climate Center/Key Laboratory of Atmospheric Science and Satellite Remote Sensing, Hefei 230031, Anhui, China

Received date: 2018-06-23

  Online published: 2019-08-28

Fold

摘要

近年来安徽秋季连阴雨过程日数异常偏多、灾情严重，为此综合利用观测数据和NCEP\\NCAR再分析资料，通过综合运用线性倾向估计、功率谱、PMFT、REOF、相关分析和合成分析等多种统计方法，试图厘清其变化规律和气候成因。研究结果显示：（1）安徽秋季连阴雨呈现南多北少、山区多平原丘陵少的分布特征，主要可分为四个集中区：Ⅰ区位于淮北，Ⅱ区位于沿淮和江淮之间北部，Ⅲ区位于江淮之间南部、沿江东部和江南东北部，Ⅳ区位于皖南山区、大别山南麓和沿江西部。（2）历年区域性秋季连阴雨过程累计日数表现为：Ⅰ区略增加、Ⅲ和Ⅳ区略减少，Ⅰ区在2014年、Ⅱ区在2013年、Ⅳ区在2015年分别发生了突变，Ⅰ区具有明显的4年左右的变化周期。（3）影响安徽秋季区域性连阴雨过程的环流的垂直结构较深厚；弱冷空气反复渗透及充沛的水汽是其发生的必要条件，南海是主要的水汽源地，此外，来自东部沿海充沛的水汽是偏北地区发生区域性过程的重要原因，水汽的输送范围直接影响过程可能到达的北界。（4）夏季地表气温可以通过影响后期环流对秋季连阴雨产生作用，最明显的表现是夏季北非中部和西北印度洋气温偏低时，同年秋季巴尔喀什湖一带低压槽加深、西太平洋副高偏强，冷空气引导条件和水汽输送条件较好，有利于Ⅰ区区域性连阴雨过程的发生。

关键词： 秋季连阴雨过程; 分区; 年际变化; 环流形势; 地表气温关键区

本文引用格式

何冬燕 , 吴蓉 , 田红 , 邓汗青 , 罗连升 . 1971年以来安徽省秋季连阴雨特征及成因分析[J]. 高原气象, 2019 , 38(4) : 829 -844 . DOI: 10.7522/j.issn.1000-0534.2018.00107

Abstract

In recent years, the continuous rain processes in Anhui turned anomalously longer in autumn, which leaded to more serious disasters. So it is necessary to find out its variation feature and climate formation mechanism. Based on the meteorological observational data and NCEP\\NCAR reanalysis data, using statistical methods such as the linear trend estimation, the power spectrum, the penalized maximal F-test (PMFT), the rotated empirical orthogonal function (REOF), the correlation analysis and the synthetic analysis and et al, the continuous rain process in Anhui in autumn has been analyzed. The results show:(1) From 1971 to 2017, the continuous rain processes in the southern and mountain area were more then that in the northern, plain and hilly area, according to which Anhui could be divided into 4 regions:the Region Ⅰ covered the Huaibei plain, the Region Ⅱ covered the Huaihe river basin and the northern Jiang-Huai region, the Region Ⅲ covered the southern Jiang-Huai region, the eastern Yangtze River basin and the southeastern Yangtze River, and the Region Ⅳ covered the southern Anhui Mountain, the southern Dabie Mountain and the western Yangtze River basin. (2) The annual accumulative process days increased slightly in the Region Ⅰ but decreased in the Region Ⅲ and Region Ⅳ. The accumulative process days in the Region Ⅰ, Region Ⅱ and Region Ⅳ have mutated obviously since 2014, 2013 and 2015 respectively. Moreovr, there was an obvious periodic change about 4 years in the Region Ⅰ. (3) The vertical circulation was deeper when there were continuous rain processes in autumn. Weak cold air affecting frequently and abundant water vapor over Anhui were the two most necessary factors for the continuous rain occuring. The South China Sea was the main source of water vapor, while water vapor from the East China Sea was also important to the northern processes, and its transmission range determined the northern boundary of the northern processes. (4) The land surface temperature (LST) in the northern hemisphere could influence the continuous rain processes in autumn by effecting the atmospheric circulation. When LST in summer was cooler in the middle northern Africa and the northwestern Indian Ocean, the low pressure trough over the Balkhash Lake turned deeper and the subtropical high over the western Pacific turned more strengthen in autumn, and the conditions of the cold air and water vapor transmission were better, which benefited to the continuous rain processes occuring in the Region Ⅰ.

Key words： Continuous rain proc; spatial partition; annual variation; atmospheric circulat; key area of land sur

参考文献

[1]Brunsell A, Young B C, 2008. Land surface response to precipitation events using MODIS and NEXRAD data[J]. International Journal of Remote Sensing, 29(7):1965-1982.
[2]Cattel R B, 1996. The scree test for the number of factors[J]. Multivariate Behavioral Research, 1:245-276.
[3]Chavas D R, Izaurralde R C, Thomson A M, et al, 2009. Long-term cliamte change impacts on agricultural productivity in eastern China[J]. Agricultural and Forest Meteorology, 149:1118-1128.
[4]Lin E D, Xiong W, Ju H, et al, 2005. Climate change impacts on crop yield and quality with CO<sub>2</sub> fertilization in China[J]. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 360(1463):2149-2154.
[5]Huang A, Kinter J L, 2002. The interannual variability in the tropical Indian Ocean and its relations to El Ni?o-Southern Oscillation[J]. Journal of Geophysical Research, 107:3199. DOI:10.1029/2001JL001278.
[6]North G R, Bell T L, Cahalan R F, et al, 1982. Sampling errors in the estimation of empirical orthogonal functions[J]. Monthly Weather Review, 110:699-706.
[7]Oki T, Kannae S, 2006. Global hydrological cycles and world water resources[J]. Science, 313:1068.
[8]Ueda H, Matsumoto J, 2000. A possible triggering process of east-west asymmetric anomalies over the Indian Ocean in relation to 1997/98 El Ni?o[J]. Journal of the Meteorological Society of Japan, 78:803-818.
[9]Wang X L, 2008. Penalized maximal F-test for detecting undocumented mean-shifts without trend-chang[J]. Journal of Atmospheric &amp; Oceanic Technology, 25(3):368-384.
[10]Yu L S, Rienecher M M, 1999. Mechanisms for the Indian Ocean warming during the 1997-1998 El Ni?o[J]. Geophysical Research Letters, 26:735-738.
[11]安徽省气候中心, 2017.2017年度气候公报[EB/OL].[2018-05-22]. <a href="http://www.ahqh.org.cn/ahqhproduct" target="_blank">http://www.ahqh.org.cn/ahqhproduct</a>.
[12]安徽省气象局, 2017.安徽省气象灾害年鉴·2017[M].北京:气象出版社, 80.
[13]安徽省气象局资料室, 1982.安徽气候[M].合肥:安徽科学技术出版社, 79.
[14]陈丽芳, 陈勇明, 2011.长江中下游两次罕见连阴雨强降水的对比分析[J].高原气象, 30(2):397-405.
[15]陈晓艺, 马晓群, 姚筠, 2009.安徽省秋季连阴雨发生规律及秋收秋种的影响[J].中国农业气象, 30(增刊):210-214.
[16]谌芸, 施能, 2003. ElNino/南方涛动与我国秋季气候异常[J].热带气象学报, 19(2):137-146.
[17]方建刚, 白爱娟, 陶建玲, 等, 2005.2003年陕西秋季连阴雨降水特点及环流条件分析[J].应用气象学报, 16(4):509-517.
[18]顾薇, 李维京, 陈丽娟, 等, 2012.我国秋季降水的年际变化及与热带太平洋海温异常分布的关系[J].气候与环境研究, 17(4):467-480.
[19]韩荣青, 陈丽娟, 李维京, 等, 2009.2-5月我国低温连阴雨和南方冷害时空特征[J].应用气象学报, 20(3):312-320.
[20]韩熠哲, 马伟强, 王炳赟, 等, 2017.青藏高原近30年降水变化特征分析[J].高原气象, 36(6):1477-1486. DOI:10.7522/j.issn.1000-0534.2016.00125.
[21]江志红, 丁裕国, 1994.近40年我国降水量年际变化区域性特征[J].南京气象学院学报, 17(1):73-78.
[22]李崇银, 穆明权, 潘静, 2001.印度洋海温偶极子和太平洋海温异常[J].科学通报, 46(20):1747.
[23]李崇银, 黎鑫, 杨辉, 2018.热带太平洋-印度洋海温联合模及其气候影响[J].大气科学, 42 (3):505-523.
[24]李德, 景元书, 祁宦, 2015a.安徽省冬小麦灌浆期连阴雨灾害等级指标的确定[J].中国农学通报, 3(9):56-62
[25]李德, 景元书, 祁宦, 2015b. 1980-2012年安徽淮北平原冬小麦灌浆期连阴雨灾害风险分析[J].资源科学, 37(4):700-709.
[26]李辉, 董彬, 2012.周口秋季连阴雨天气气候特征[J].安徽农业科学, 40(28):13900-13902.
[27]梁邦云, 王效瑞, 郭秀云, 等, 2003.安徽春季(低温)连阴雨气候特征分析[J].安徽气象, 3(4):10-11.
[28]林纾, 章克俭, 2003.西北地区东部2000年与2001年秋季连阴雨分析[J].气象, 29(2):34-38.
[29]刘维成, 张强, 傅朝, 2017.近55年来中国西北地区降水变化特征及影响因素分析[J].高原气象, 36(6):1533-1545. DOI:10.7522/j.issn.1000-0534.2017.00081.
[30]刘瑞娜, 杨太明, 陈金华, 等, 2012.安徽省春季连阴雨分布特征及其对油菜产量影响评估[J].中国农学通报, 28(34):252-256.
[31]刘瑞娜, 杨太明, 陈鹏, 等, 2016.安徽省油菜花期连阴雨灾害损失评估指标[J].中国农业气象, 37(4):471-478.
[32]刘月辉, 1981.秋季连阴雨中短期预报[J].山东气象, 1(2):15-17.
[33]马玲, 陈玲玲, 汪翔, 2011.一次盛夏罕见连阴雨过程分析[J].安徽农业科学, 39(34):21284-21286.
[34]马魁侠, 董凌, 陈新治, 2007.2005年亳州秋季长连阴雨天气主要成因及其预报[J].安徽农业科学, 35(7):2038-2040.
[35]钱正安, 蔡英, 宋敏红, 等, 2018.中国西北旱区暴雨水汽输送研究进展[J].高原气象, 37(3):577-590. DOI:10.7522/j.issn.1000-0534.2018.00032.
[36]阙志萍, 吴凡, 吴菲菲, 2017.江西近55年秋季降水时空分布及异常环流特征分析[J].中国农学通报, 33(18):103-115.
[37]史宝秀, 瞿汶, 2002.甘肃省年秋季连阴雨特征分析[J].甘肃气象, 20(2):12-13.
[38]施能, 1990.厄尔尼诺南方涛动与我国秋季大尺度降水预报[J].南京气象学院学报, 13(2):174-183.
[39]施能, 2002.气象科研与预报中的多元分析方法[M].北京:气象出版社, 244.
[40]史瑞琴, 李兰, 温泉沛, 等, 2013.华中三省秋季连阴雨时空变化特征及风险分析[J].华中农业大学学报, 2(6):91-98.
[41]孙照渤, 黄艳艳, 倪东鸿, 2016.我国秋季连阴雨的气候特征及大气环流特征[J].大气科学学报, 39(4):480-489.
[42]王丹, 盛立芳, 黄少妮, 等, 2015.孟加拉湾感热净通量与陕西秋季降水的联系[J].高原气象, 34(6):1658-1667. DOI:10.7522/j.issn.1000-0534.2014.00073.
[43]王荣, 邹旭恺, 2015.长江中下游地区连阴雨变化特征分析[J].长江流域资源与环境, 24(9):1483-1490.
[44]王顺久, 2017.青藏高原积雪变化及其对中国水资源系统影响研究进展[J].高原气象, 36(5):1153-1164. DOI:10.7522/j.issn.1000-0534.2016.00117.
[45]魏凤英, 1999.现代气候统计诊断与预测技术[M].北京:气象出版社, 211.
[46]吴国雄, 孟文, 1998.赤道印度洋-太平洋地区海汽系统的齿轮式耦合和ENSO事件Ⅰ.资料分析[J].大气科学, 22(4):470-480.
[47]吴有训, 赵俊华, 张民蓓, 等, 2003.皖东南地区春播期连续低温阴雨天气分析[J].安徽农业科学, 31(4):569-570.
[48]肖子牛, 晏红明, 李崇银, 2002.印度洋地区异常海温的偶极振荡与中国降水及温度的关系[J].热带气象学报, 18(4):335-344.
[49]谢亦峰, 任敏, 尚瑜, 2007.安徽省秋季连阴雨天气形成条件分析[J].安徽农业科学, 35(27):8603-8604.
[50]魏锋, 白虎志, 孙秉强, 2005.甘肃省近35年连阴雨天气气候特征分析[J].成都信息工程学院学报, 20(4):479-482.
[51]熊敏诠, 2015.近30年中国地面风速分区及气候特征[J].高原气象, 34(1):39-49. DOI:10.7522/j.issn.1000-0534.2013.00159.
[52]于波, 鲍文忠, 吴必文, 等, 2013.安徽农业气象业务服务手册[M].北京:气象出版社, 176.
[53]于凤英, 常平, 杨学斌, 2009.鲁西北罕见的秋季连阴雨环流特征分析[J].气象, 35(10):71-78.
[54]袁明奎, 严昀, 2017.滁州市连阴雨气候对农业的影响[J].农业灾害研究, 7(4/5):43-45.
[55]袁晓玉, 施能, 顾俊强, 2002.浙江省秋季降水趋势及旱涝年特征[J].南京气象学院学报, 25(5):677-684.
[56]翟治国, 周晓天, 叶丽, 等, 2017.皖东地区秋季连阴雨天气对农作物的影响及防控对策[J].安徽农学通报, 23(20):116-127.
[57]张爱民, 马晓群, 杨太明, 等, 2007.安徽省旱涝灾害及其对农作物产量影响[J].应用气象学报, 18(5):619-626.
[58]支蓉, 陈丽娟, 竺夏英, 2018.2017年秋季我国北方地区降水异常偏多成因分析[J].气象, 44(4):572-581.
[59]钟元, 吴钟浚, 1992.长江中下游地区春季连阴雨-连晴天气过程的中期振荡[J].气象学报, 50(2):199-208.
Options
文章导航

/

〈 〉

本系统由北京玛格泰克科技发展有限公司设计开发 技术支持：support@magtech.com.cn