中国农业气象

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典型浓度路径(RCP)情景下长江中下游地区气温变化预估

刘文茹,居辉,陈国庆,刘恩科,刘勤   

  1. 1.山东农业大学农学院作物生物学国家重点实验室,泰安 271018;2.中国农业科学院农业环境与可持续发展研究所/农业部旱作节水农业重点实验室,北京 100081
  • 收稿日期:2016-06-11 出版日期:2017-02-20 发布日期:2017-02-15
  • 作者简介:刘文茹(1992-),硕士生,研究方向为农业信息化。E-mail: liuwenru1206307296@163.com
  • 基金资助:
    国家重点基础研究发展计划(973计划)(2012CB955904);国家自然科学基金项目(41401510);国家“十二五”科技支撑计划(2012BAD09B01)

Prediction on the Possible Air Temperature Change over the Middle and Lower Yangtze River Basin under the RCP Scenarios

LIU Wen-ru, JU Hui, CHEN Guo-qing, LIU En-ke, LIU Qin   

  1. 1.State Key Laboratory of Crop Biology, Agronomy College, Shandong Agricultural University, Tai’an 271018, China; 2.Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Science/Key Laboratory of Dryland Agriculture, Ministry of Agriculture, Beijing 100081
  • Received:2016-06-11 Online:2017-02-20 Published:2017-02-15

摘要: 为探明典型浓度路径下(高端路径RCP8.5和稳定路径RCP4.5)长江中下游地区未来30a平均气温的时空变化趋势和分布特征,运用联合国政府间气候变化委员会(IPCC)AR5提出的模拟能力较强的BCC-CSM1-1(Beijing Climate Center Climate System Model version1-1)气候系统模式,基于典型浓度情景RCP(Representative Concentration Pathway)输出的2021-2050年0.5×0.5格点主要气象要素的逐日模式模拟数据资料,应用双线性内插法降尺度到长江中下游及邻近区域62个基本气象站点。以1961-1990为基准年,根据同期等长模拟数据和观测数据的非线性函数关系建立订正模型,并利用方差订正法对2021-2050年模拟数据进行误差订正。结果表明:RCP情景输出数据的模拟效果良好,方差订正可降低模拟值与观测值的相对误差和方差,更加真实反应未来气候变化趋势。RCP8.5 和RCP4.5两种排放情景下,长江中下游地区2021-2050年年平均气温均呈显著上升趋势,增温幅度总体表现为自南向北逐渐减少。就季节而言,四季均呈现升温趋势,夏季增温幅度最高,变化倾向率大,春冬两季RCP8.5情景下增温幅度大于RCP4.5下,夏秋季则相反;RCP8.5情景下,研究区域年平均气温呈现自中部向东西递减,春夏季增温幅度高于秋季,冬季增温幅度最小,且变化倾向率低,大部分地区未通过0.05水平的显著性检验。RCP4.5情景下,研究区年平均气温自北向南逐渐降低,变化倾向率则表现为北部大于南部,夏季变化速率较大,增温幅度达1.2℃·10a-1(P<0.01),冬季较小且未通过显著性检验。

关键词: RCP情景, 气温模拟, 数据订正, 长江中下游地区

Abstract: The spatio-temporal characteristics of mean temperature was investigated under high-end path Representative Concentration Pathway (RCP) 8.5 and stable path RCP4.5 scenarios based on the 0.5°×0.5° grid daily meteorological data output by the scenario of RCP of BCC-CSM1-1 (Beijing Climate Center Climate System Model version1-1) over the middle and lower Yangtze River during from 2021-2050, which was selected to downscale the model data to 62 national weather stations by the bilinear interpolation method. Subsequently, the RCPs scenarios data during 2021-2050 was corrected using variance correction method from non-linear equation of the simulated and observed data over the reference period of 1961-1990. The results described that the simulation of RCP scenario output data was detected to be satisfactory. The annual mean temperature would significantly increase over the middle and lower Yangtze River, whereas the amplitude of the temperature increase gradually reduced overall from south to north under the RCP8.5 and RCP4.5 scenarios. For both scenarios, the trend of temperature increased in four selected seasons with the higher change rate in summer. Accordingly, for the RCP8.5 scenario, the increasing rate of spring and winter was found to be higher than that in the RCP4.5 scenario. Under the RCP8.5 scenario, the highest value was depicted in the central of research area for annual mean temperature, and the warming rate was found to be higher in spring and summer than other seasons and the most of station without passed the significant level (P<0.05) in winter. While for the RCP4.5 scenario, the annual mean temperature was detected to reduce gradually from north to south. Thereby, the increasing rate was found to be higher significantly in summer than in winter.

Key words: Representative concentration pathway scenario, Prediction of temperature, Data correction, Bilinear interpolation method, Middle and lower Yangtze River