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基于再分析资料与观测资料的中国低温阈值变化特征研究
引用本文:高庆九,余汶樯,周小艳.基于再分析资料与观测资料的中国低温阈值变化特征研究[J].大气科学学报,2018,41(3):308-317.
作者姓名:高庆九  余汶樯  周小艳
作者单位:南京信息工程大学气象灾害教育部重点实验室/气候与环境变化国际合作联合实验室/气象灾害预报预警与评估协同创新中心/大气科学学院气候动力学研究中心;江苏阜宁农村商业银行
基金项目:国家自然科学基金资助项目(41475045)
摘    要:采用1979—2013年中国192站逐日最低温度观测资料和NCEP/NCAR、NCEP/DOE、JRA-55、ERA-Interim再分析资料及1979—2004年均一化资料,分别计算低温阈值并对比分析其气候态、年际和年代际变化、长期趋势等特征。结果表明:与观测结果相比,均一化资料阈值在东北、内蒙古西部和两广等地偏低,在青藏高原东侧、新疆北部和黄河中下游偏高,线性趋势则相反;再分析资料阈值在南方偏低、东北偏高,在东部的可信度高于西部;再分析资料能显示内蒙古中西部的降温趋势和青藏高原的增温趋势,但在数值和范围上有差异,且均低估了观测资料反映的华北地区的显著升温现象;再分析资料能体现观测资料阈值的全区一致性、东北与其他地区反相的空间分布及其年际变化特征,仅JRA-55和ERA-Interim可再现低温阈值的年代际变化特征。

关 键 词:低温阈值  观测资料  均一化资料  再分析资料  适用性评估
收稿时间:2017/9/3 0:00:00
修稿时间:2017/11/16 0:00:00

Research on variation characteristics of low temperature threshold in China based on reanalysis data and observation data
GAO Qingjiu,YU Wenqiang and ZHOU Xiaoyan.Research on variation characteristics of low temperature threshold in China based on reanalysis data and observation data[J].大气科学学报,2018,41(3):308-317.
Authors:GAO Qingjiu  YU Wenqiang and ZHOU Xiaoyan
Institution:Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Climate Dynamics Research Center(CDRC) of School of Atmospheric Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China;Key Laboratory of Meteorological Disaster, Ministry of Education(KLME)/Joint International Research Laboratory of Climate and Environment Change(ILCEC)/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD)/Climate Dynamics Research Center(CDRC) of School of Atmospheric Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China;Jiangsu Funing Rural Commercial Bank, Funing 224400, China
Abstract:Low temperature event is one of many meteorological disasters,which always causes much loss in agriculture,transportation,electricity and so on.The analysis of extreme low temperature can improve our understanding.As a powerful complement to observation data,the reanalysis data play an important role in related researches.Hence,the quality of reanalysis data is related to the accuracy of research results.Therefore,it is necessary to explore the performance of reanalysis data on low temperature filed.Based on the daily minimum temperature data of 192 gauge stations in China and the reanalysis minimum temperature data of NCEP/NCAR,NCEP/DOE,JRA-55,ERA-Interim from 1979 to 2013,and the homogenization temperature data from 1979 to 2004,this study calculates low temperature threshold,and explores the features and differences between reanalysis data and observation data on climatology,interannual and interdecadal variations,and long-term trend.The following conclusions are obtained by calculating correlation coefficient and linear trend,and by using EOF analysis and other methods.Results show that:(1) Compared with the observations,the thresholds of homogenization data are lower in Northeast China,western Nei Mongol,Guangdong and Guangxi while higher in the east side of the Tibetan Plateau,northern Xinjiang and the middle and lower reaches of the Yellow River,but the linear trends are the opposite.(2) The thresholds of reanalysis data are lower in the south of China while higher in the northeast.The correlation coefficients display that the credibility is better in the east of China than that in the west,which may be related to the terrain and the number of gauge stations.(3) The reanalysis data can capture the features of cooling trend over the central and western Nei Mongol and warming trend over the Tibetan Plateau,but there are differences in values and ranges,and the data underestimate the significant warming trend in North China Plain based on the observations.(4) The thresholds derived from the four reanalysis data can depict the observed characteristics of nationwide consistent and reverse between the northeast and other regions.The features of interannual variation can be inferred from the four reanalysis data,but only JRA-55 and ERA-Interim can reappear the interdecadal variation of the low temperature thresholds.(5) Counting the number of low temperature days by threshold value,the results of reanalysis data are generally less than those of the observation data.From the results,we can conclude that the applicability of reanalysis data is better in eastern China,and the effect of ERA and JRA is better than that of NCEP products.
Keywords:low temperature threshold  observation data  homogenization data  reanalysis data  applicability evaluation
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