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近30多年江淮流域极端气温指数的时空变化分析:站点观测和再分析的对比
引用本文:吴晶璐,朱红芳,宗培书,惠品宏,汤剑平. 近30多年江淮流域极端气温指数的时空变化分析:站点观测和再分析的对比[J]. 气象科学, 2018, 38(4): 464-476
作者姓名:吴晶璐  朱红芳  宗培书  惠品宏  汤剑平
作者单位:南京大学大气科学学院;常州市气象局;安徽省气象台;江苏省气象台;江苏省气候中心
基金项目:国家重点研发计划(2017YFA0603803);国家自然科学基金资助项目(41375075);常州市气象局科研开发项目(1501);常州市科技项目(CE20155057)
摘    要:利用1979—2011年江淮流域的区域站点、NCEP/DOE和ERA-Interim再分析资料中的逐日最高、最低气温资料集,对比分析了近33 a江淮流域极端气温指数的时空变化特征,对再分析资料的再现能力进行检验和评估。结果表明:(1)近33 a来大部分极端气温指数及其趋势系数的空间分布都表现出南北向梯度分布特征,而极端最高、最低气温的极值区分布在长江三角洲地区;(2)夏日指数、作物生产指数、极端最高、极端最低、暖期长度指数和高百分位指数在年际变化中均有上升趋势,而且多次出现异常低值和异常高值;近10多年来,极端气温频率指数和百分位指数的年际变化趋势有所减缓;(3)月最高气温在近30 a中不断被突破,最低气温不断上升,而且高温天气日数也在不断增加,但低温日数逐渐减少;(4)再分析资料能较合理地再现大部分极端指数的时空变化和线性趋势特征,ERA-Interim比NCEP/DOE具有更好的再现能力。

关 键 词:极端气温指数  变化特征  再分析资料
收稿时间:2017-09-06
修稿时间:2017-09-06

Analysis on the spatial-temporal features of temperature extremes in the Yangtze-Huaihe river basin over the past decades: Comparison between observation and reanalysis
WU Jinglu,ZHU Hongfang,ZONG Peishu,HUI Pinhong and TANG Jianping. Analysis on the spatial-temporal features of temperature extremes in the Yangtze-Huaihe river basin over the past decades: Comparison between observation and reanalysis[J]. Journal of the Meteorological Sciences, 2018, 38(4): 464-476
Authors:WU Jinglu  ZHU Hongfang  ZONG Peishu  HUI Pinhong  TANG Jianping
Affiliation:School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China;Changzhou Meteorological Bureau, Jiangsu Changzhou 213022, China,Anhui Meteorological Observatory, Hefei 230031, China,Jiangsu Meteorological Observatory, Nanjing 210008, China,The Climate Center of Jiangsu Province, Nanjing 210009, China and School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Abstract:The spatial-temporal features of extreme temperature indices in Yangtze-Huaihe river basin from1979 to 2011 were analyzed to assess the retrieval ability of reanalysis datasets of NCEP/DOE and ERA-Interim, using the observational data from meteorological stations as reference. The results are as follows:(1) Most of the extreme temperature indices and their linear trends are distributed with a south-north gradient, except that the TXx and TNn show peaks in Yangtze River Delta. (2) SU, GSL, TXx, TNn, WSDI and the high percentile indices tend to increase in the interannual variation, with several anomalous high and low values during the analysis period. The interannual variation of frequency index and percentile index is slowing down in the recent decade. (3) Both the maximum and minimum monthly temperatures as well as the days of extreme high temperature are increasing over the past 30 years, while the days of extreme low temperature tend to decrease. (4) The reanalysis datasets can well reproduce the spatial and temporal features of most extreme indices, and ERA-Interim outperforms NCEP/DOE in many aspects.
Keywords:Extreme temperature indices  Spatial-temporal features  Reanalysis datasets
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