李金洁,王爱慧,郭东林,王丹. 2019. 高分辨率统计降尺度数据集NEX-GDDP对中国极端温度指数模拟能力的评估[J]. 气象学报, 77(3):579-593, doi:10.11676/qxxb2019.032
高分辨率统计降尺度数据集NEX-GDDP对中国极端温度指数模拟能力的评估
Evaluation of extreme temperature indices over China in the NEX-GDDP simulated by high-resolution statistical downscaling models
投稿时间:2018-05-08  修订日期:2018-12-08
DOI:10.11676/qxxb2019.032
中文关键词:  NEX-GDDP  极端温度指数  模式评估  优选模式  CMIP5
英文关键词:NEX-GDDP  Extreme temperature indices  Models evaluation  Selected models  CMIP5
基金项目:国家重点研发计划项目(2016YFA0602401)。
作者单位E-mail
李金洁 中国科学院大气物理研究所竺可桢-南森国际研究中心, 北京, 100029
中国科学院大学, 北京, 100049 
 
王爱慧 中国科学院大气物理研究所竺可桢-南森国际研究中心, 北京, 100029 wangaihui@mail.iap.ac.cn 
郭东林 中国科学院大气物理研究所竺可桢-南森国际研究中心, 北京, 100029  
王丹 中国科学院大气物理研究所竺可桢-南森国际研究中心, 北京, 100029
中国科学院大学, 北京, 100049 
 
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中文摘要:
      利用1986—2005年中国地面气象台站观测的格点化逐日气温资料(CN05.1)评估了高分辨率统计降尺度数据集NASA Earth Exchange/Global Daily Downscaled Projections(NEX-GDDP)中21个全球气候模式对中国极端温度指数的模拟能力。在选用了日最低温度最大值(TNx)、日最高温度最大值(TXx)、暖夜指数(TN90p)和暖昼指数(TX90p)来研究极端温度事件的变化。结果显示:(1)除MRI-CGCM3模拟的日最高温度最大值外,其余模式对4个指数的模拟结果均表现出与观测一致的上升趋势,但模拟结果的平均值相对观测平均低0.26℃/(10 a)(日最低温度最大值)、0.19℃/(10 a)(日最高温度最大值)、2.21%/(10 a)(暖夜指数)、1.04%/(10 a)(暖昼指数)。(2)不同模式对各指数变化趋势空间分布特征的模拟存在较大差别,对日最低温度最大值、日最高温度最大值、暖夜指数和暖昼指数模拟能力最优模式分别为CCSM4、CESM1-BGC、MIROC-ESM-CHEM和bcc-csm1-1。模式模拟的日最低温度最大值和日最高温度最大值气候态平均值与观测值的相关系数在0.97以上。暖夜指数和暖昼指数模拟结果与观测值的标准差比值为0.34—1.58,均方根误差变化为1.6%—3.47%,对这两个指数模拟能力较优的模式分别为MIROC-ESM-CHEM(暖夜指数)和CESM1-BGC(暖昼指数)。(3)综合模式对4个指数在气候态平均值和变化趋势模拟能力的评估结果来看,CanESM2、CESM1-BGC和MIROC-ESM-CHEM显示了相对较高的模拟能力。因此,在利用GDDP-NEX研究未来极端温度事件时,建议将它们作为优选模式。
英文摘要:
      The gridded observational air temperature dataset (CN05.1) for the period 1986-2005 over China is used to evaluate daily extreme temperature indices simulated by 21 models that participate the NASA Earth Exchange/Global Daily Downscaled Projections (NEX-GDDP). Four extreme temperature indices, including the lowest daily temperature maximum (TNx), the highest daily temperature (TXx), the warm night frequency (TN90p) and warm day frequency (TX90p), are adopted to investigate the change of extreme temperature. The major conclusions are as follows. (1) Except for TXx from the MRI-CGCM3, the four indices from other models show an upward tendency, which is consistent with observations. However, the magnitudes of their linear trends are less than that from observations with the values of 0.26℃/decade (TNx), 0.19℃/decade (TXx), 2.21% decade (TN90p), 1.04%/decade (TX90p), respectively. (2) There are large differences in spatial patterns of those indices between models. For the simulation of all the four indices, CCSM4 performs the best, CESM1-BGC, MIROC-ESM-CHEM ranking next in order of performance. The spatial patterns of climatological extreme indices can be simulated perfectly with the correlation coefficients of observations with TNx and TXx from all models exceeding 0.97. The ratios of standard deviations between simulations and observations for TN90p and TX90p vary from 0.34 to 1.58, and the root mean square errors are within 1.6%-3.47%. (3) Synthetical evaluation of the four extreme indices in term of their climatological means and linear trends indicates that the performances of three models (i.e., CanESM2, CESM1-BGC and MIROC-ESM-CHEM) are relatively better. Therefore, it is suggested that results of the above three models in the NEX-GDDP can be used to investigate the extreme temperature change in the future.
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