1961—2017年京津冀地区极端气温指数时空变化分析
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摘要
基于京津冀地区25个气象站1961—2017年的逐日气温资料,计算了16个极端气温指数,通过旋转因子分析获得5个公因子,进而选取冰冻时间(ID0)、作物生长季(GSL)、暖昼时间(TX90p)、气温日较差(DTR)、日最高气温极小值(TXn)5个代表性极端气温指数,采用Sen斜率、Mann-Kendall突变检测、反距离权重插值(IDW)、Morlet小波分析方法进行研究.结果表明:1)近57a来,ID0、DTR分别以-2.4d、-0.23℃·(10a)-1的速率显著下降(P<0.05),GSL、TX90p分别以2.5d、2.1d·(10a)-1的速率显著增加(P<0.05),TXn则以0.28℃·(10a)-1的速率不显著上升,这表明,京津冀地区具有明显的暖化趋势.2)ID0、TXn、GSL分别在1987、1988、1996年发生突变,而TX90p、DTR均未发生突变.3)5个指数的第1主周期尺度为16～38a,相应的平均周期为8.2～18.5a.4)空间上,全域各站ID0均减少,减幅南高北低;各站GSL、TXn均呈增加趋势,GSL增幅西高东低,TXn与之相反;TX90p以增为主,京津以北增幅较大,仅东南部局地呈现减少趋势;DTR则以减为主,西南部减幅最大,仅东北局部呈现增加趋势.5)ID0、DTR在平均气温突变后减少,TX90p、GSL、TXn均在突变后增加,表明京津冀地区对区域升温有很好的响应.6)除ID0外,GSL、TX90p、DTR、TXn这4个指数与ENSO指数的相关性并不显著.
Sixteen(16)extreme temperature indices were calculated from daily temperature data at 25 meteorological stations in Beijing-Tianjin-Hebei region from 1961 to 2017.Five common factors were obtained by rotating factor analysis.Ice days(ID0),growing season length(GSL),warm days(TX90p),diurnal temperature range(DTR)and minimum value of daily maximum temperature(TXn)were selected as representative of extreme temperature indices.Sens slope,Mann-Kendall mutation detection,inverse distance weight interpolation(IDW)and Morlet wavelet analysis were done to elaborate the five representative extreme temperature indices.It was found that in the past 57 years,ID0 and DTR decreased significantly at rates of-2.4 d,-0.23℃·(10 a)~(-1)(P<0.05)respectively,GSL and TX90 p increased significantly at rates of 2.5 d,2.1 d·(10 a)~(-1)(P<0.05)respectively,while TXn exhibited rising trend at the rate of 0.28 ℃·(10 a)~(-1),indicating an obvious warming trend in the Beijing-Tianjin-Hebei region.Abrupt change points of ID0,TXn and GSL were found in 1987,1988,and 1996,respectively,but no abrupt change occurred for TX90 p and DTR.The first principal period scale of the 5 indices ranged from 16 to 38 years,and the corresponding average period ranged from 8.2 to 18.5 years.Spatially,ID0 at all meteorological stations in the BeijingTianjin-Hebei region showed a decreasing trend,more so in the South,less in the north.GSL and TXn at all meteorological stations showed an increasing trend.The increase of GSL was higher in the West and lower in the east-the spatial distribution of TXn being the reverse of GSL.TX90p in most areas in the region showed an increasing trend,the region north increased the most,the southeastern part showed a decreasing trend.DTR mainly showed a decreasing trend,the southwestern part decreased the most,the northeastern part showed an increasing trend.After a sudden change in mean temperature,ID0 and DTR showed a decreasing trend,while TX90p,GSL and TXn showed an increasing trend,indicating that the Beijing-Tianjin-Hebei region had a good response to regional warming.In contrast to ID0,the correlations between the 4 other extreme temperature indices(GSL,TX90p,DTR,TXn and ENSO indices)were not significant.
Sixteen(16)extreme temperature indices were calculated from daily temperature data at 25 meteorological stations in Beijing-Tianjin-Hebei region from 1961 to 2017.Five common factors were obtained by rotating factor analysis.Ice days(ID0),growing season length(GSL),warm days(TX90p),diurnal temperature range(DTR)and minimum value of daily maximum temperature(TXn)were selected as representative of extreme temperature indices.Sens slope,Mann-Kendall mutation detection,inverse distance weight interpolation(IDW)and Morlet wavelet analysis were done to elaborate the five representative extreme temperature indices.It was found that in the past 57 years,ID0 and DTR decreased significantly at rates of-2.4 d,-0.23℃·(10 a)~(-1)(P<0.05)respectively,GSL and TX90 p increased significantly at rates of 2.5 d,2.1 d·(10 a)~(-1)(P<0.05)respectively,while TXn exhibited rising trend at the rate of 0.28 ℃·(10 a)~(-1),indicating an obvious warming trend in the Beijing-Tianjin-Hebei region.Abrupt change points of ID0,TXn and GSL were found in 1987,1988,and 1996,respectively,but no abrupt change occurred for TX90 p and DTR.The first principal period scale of the 5 indices ranged from 16 to 38 years,and the corresponding average period ranged from 8.2 to 18.5 years.Spatially,ID0 at all meteorological stations in the BeijingTianjin-Hebei region showed a decreasing trend,more so in the South,less in the north.GSL and TXn at all meteorological stations showed an increasing trend.The increase of GSL was higher in the West and lower in the east-the spatial distribution of TXn being the reverse of GSL.TX90p in most areas in the region showed an increasing trend,the region north increased the most,the southeastern part showed a decreasing trend.DTR mainly showed a decreasing trend,the southwestern part decreased the most,the northeastern part showed an increasing trend.After a sudden change in mean temperature,ID0 and DTR showed a decreasing trend,while TX90p,GSL and TXn showed an increasing trend,indicating that the Beijing-Tianjin-Hebei region had a good response to regional warming.In contrast to ID0,the correlations between the 4 other extreme temperature indices(GSL,TX90p,DTR,TXn and ENSO indices)were not significant.
引文
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[35]张雷,任国玉,刘江,等.城市化对北京气象站极端气温指数趋势变化的影响[J].地球物理学报,2011,54(5):1150
[2]李双双,杨赛霓.1960-2014年北京极端气温事件变化特征[J].地理科学,2015,35(12):1640
[3]YOU Q,KANG S,AGUILAR E,et al.Changes in daily climate extremes in China and their connection to the large scale atmospheric circulation during 1961-2003[J].Climate Dynamics,2010,36(11/12):2399
[4]HU L,HUANG G,QU X.Spatial and temporal features of summer extreme temperature over China during 1960-2013[J].Theoretical and Applied Climatology,2017,128(3/4):821
[5]ZHANG Y J,GAO Z Q,PAN Z T,et al.Spatiotemporal variability of extreme temperature frequency and amplitude in China[J].Atmospheric Research,2017,185:131
[6]谢志祥,李亚男,秦耀辰,等.1960-2012年淮河流域极端气温变化特征[J].中国农业气象,2017,38(7):407
[7]吴灿,赵景波,王格慧.黄河流域极端气温指数的气候演变特征分析[J].中国农业气象,2015,36(5):525
[8]贾艳青,张勃,张耀宗,等长江三角洲地区极端气温事件变化特征及其与ENSO的关系[J].生态学报2017,37(19):6402
[9]王冀,蒋大凯,张英娟.华北地区极端气候事件的时空变化规律分析[J].中国农业气象,2012,33(2):166
[10]陈虹颖,徐峰,李晓惠,等.近65年ENSO事件强度变化及时频特征研究[J].热带气象学报,2017,33(5):683
[11]李芬,张建新,郝智文,等.山西降水与ENSO的相关性研究[J].地理学报,2015,70(3):420
[12]厄尔尼诺/拉尼娜事件判别方法QX/T 370-2017:[S].北京:中国气象局,2017
[13]张扬,白红英,苏凯,等.1960-2013年秦岭陕西段南北坡极端气温变化空间差异[J].地理学报,2018,73(7):1296
[14]王钰,冯起.陕北地区1960-2013年极端气温指数[J].中国沙漠,2016,36(4):1097
[15]郭湘宇,吴正方,杜海波,等.福建省极端降水时空变化特征及其环流因素分析[J].资源科学,2017,39(6):1084
[16]武文博,游庆龙,王岱.基于均一化降水资料的中国极端降水特征分析[J].自然资源学报,2016,31(6):1015
[17]刘维成,张强,傅朝.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,2017,36(6):1533
[18]刘蓉,文军,王欣.黄河源区蒸散发量时空变化趋势及突变分析[J].气候与环境研究,2016,21(5):503
[19]李玮,段利民,刘廷玺等.1961-2015内蒙古高原内陆河东部流域极端降水时空变化特征分析[J].资源科学,2017,39(11):2153
[20]苗正伟,徐利岗,张薇.京津冀地区参考作物蒸散量变化特征与成因分析[J].灌溉排水学报,2018,37(5):39
[21]魏凤英.现代气候统计诊断与预测技术[M].2版北京:气象出版社,2007:58-66
[22]胡毅鸿,李景保.1951-2015年洞庭湖区旱涝演变及典型年份旱涝急转特征分析[J].农业工程学报,2017,33(7):107
[23]任正果,张明军,王圣杰,等.1961-2011年中国南方地区极端降水事件变化[J].地理学报,2014,69(5):640
[24]周雅清,任国玉.城市化对华北地区极端气温事件频率的影响[J].高原气象,2014,33(6):1589
[25]苗正伟,徐利岗,韩会玲.京津冀地区近55年气候演变特征分析[J].南水北调与水利科技,2018,16(3):125
[26]ALEXANDER L V,ZHANG X,PETERSON T C,et al.Global observed changes in daily climate extremes of temperature and precipitation[J].Journal of Geophysical Research,2006,111(D5):1042
[27]GUAN Y,ZHANG X,ZHENG F,et al.Trends and variability of daily temperature extremes during 1960-2012in the Yangtze River Basin,China[J].Global and Planetary Change,2015,124:79
[28]王琼,张明军,王圣杰,等.1962-2011年长江流域极端气温事件分析[J].地理学报,2013,68(5):611
[29]赵安周,刘宪锋,朱秀芳,等.1965-2013年黄土高原地区极端气温趋势变化及空间差异[J].地理研究,2016,35(4):639
[30]高文华,李开封,崔豫.1960-2014年河南极端气温事件时空演变分析[J].地理科学,2017,37(8):1259
[31]黄小燕,王小平,王劲松,等.1960-2013年中国沿海极端气温事件变化特征[J].地理科学,2016,36(4):612
[32]丁之勇,董义阳,鲁瑞洁.1960-2015年中国天山南、北坡与山区极端气温时空变化特征[J].地理科学,2018,38(8):1379
[33]丁之勇,葛拥晓,吉力力·阿不都外力,等.1957-2012年新疆艾比湖流域极端气温与降水变化趋势[J].中国科学院大学学报,2018,35(2):160
[34]刘青娥,吴孝情,陈晓宏,等.珠江流域1960-2012年极端气温的时空变化特征[J].自然资源学报,2015,30(8):1356
[35]张雷,任国玉,刘江,等.城市化对北京气象站极端气温指数趋势变化的影响[J].地球物理学报,2011,54(5):1150
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