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CMIP5模式对中国东部夏季不同强度降水气候态和年代际变化的模拟能力评估

林朝晖 杨笑宇 吴成来 王雨曦 陈红

林朝晖, 杨笑宇, 吴成来, 王雨曦, 陈红. CMIP5模式对中国东部夏季不同强度降水气候态和年代际变化的模拟能力评估[J]. 气候与环境研究, 2018, 23(1): 1-25. doi: 10.3878/j.issn.1006-9585.2017.16207
引用本文: 林朝晖, 杨笑宇, 吴成来, 王雨曦, 陈红. CMIP5模式对中国东部夏季不同强度降水气候态和年代际变化的模拟能力评估[J]. 气候与环境研究, 2018, 23(1): 1-25. doi: 10.3878/j.issn.1006-9585.2017.16207
Zhaohui LIN, Xiaoyu YANG, Chenglai WU, Yuxi WANG, Hong CHEN. Capability Assessment of CMIP5 Models in Reproducing Observed Climatology and Decadal Changes in Summer Rainfall with Different Intensities over Eastern China[J]. Climatic and Environmental Research, 2018, 23(1): 1-25. doi: 10.3878/j.issn.1006-9585.2017.16207
Citation: Zhaohui LIN, Xiaoyu YANG, Chenglai WU, Yuxi WANG, Hong CHEN. Capability Assessment of CMIP5 Models in Reproducing Observed Climatology and Decadal Changes in Summer Rainfall with Different Intensities over Eastern China[J]. Climatic and Environmental Research, 2018, 23(1): 1-25. doi: 10.3878/j.issn.1006-9585.2017.16207

CMIP5模式对中国东部夏季不同强度降水气候态和年代际变化的模拟能力评估

doi: 10.3878/j.issn.1006-9585.2017.16207
基金项目: 

国家重点研发项目 2016YFC0402702

国家自然科学基金项目 41575095

国家自然科学基金项目 41575080

中国科学院国际合作一带一路专项 134111KYSB20160010

详细信息
    作者简介:

    林朝晖, 男, 1968年出生, 博士, 研究员, 从事地球系统模式研制及气候水文模拟与预测研究。E-mail:lzh@mail.iap.ac.cn

  • 中图分类号: P435.2

Capability Assessment of CMIP5 Models in Reproducing Observed Climatology and Decadal Changes in Summer Rainfall with Different Intensities over Eastern China

Funds: 

National Key Research and Development Program of China 2016YFC0402702

National Natural Science Foundation of China 41575095

National Natural Science Foundation of China 41575080

Chinese Academy of Sciences "The Belt and Road Initiatives" Program on International Cooperation 134111KYSB20160010

  • 摘要: 利用东亚地区逐日降水资料,评估了17个CMIP5气候模式对中国东部夏季不同强度降水的时空分布、不同强度降水对1970年代末中国东部夏季总降水量年代际转折的贡献的模拟能力。从夏季不同强度降水占总降水的比重来看,在中国东北和华北地区,小雨和中雨占主导;而在华南和江淮地区,大雨和暴雨则相对更为重要。CMIP5模式可大致模拟出中国东部小雨、大雨和暴雨占总降水比重的空间分布,但对中雨占比的空间分布模拟较差。总体说来,多数CMIP5模式高估了小雨和中雨的比重,但低估了大雨和暴雨的比重,从而导致大多数模式高估东北和华北的总降水量,而低估华南和江淮的总降水量。对1970年代末我国华北和江淮地区夏季降水量的年代际转折,观测资料表明该转折主要体现为大雨和暴雨雨量的年代际转折;仅有少数CMIP5模式能模拟出华北大雨和暴雨年代际减少的特征,使得这些模式对华北地区总降水的年代际变化也有较好的模拟能力。对于江淮区域,由于大雨和暴雨的比重被严重低估,尽管部分模式能模拟出夏季总降水量年代际增加的特征,但却多以小雨、中雨的年代际变化为主。多模式集合并不能显著提高模式对不同强度降水的空间分布的模拟能力,尤其是降水年代际变化的模拟能力。
  • 图  1  1962~2005年观测与17个CMIP5模式模拟的中国东部夏季平均降水总量空间分布(Obs代表观测,MME代表多模式集合)

    Figure  1.  Summer mean total rainfall from CMIP5 models and observations averaged during 1962-2005 over eastern China (Obs denotes observations and MME is for multi-model ensemble)

    图  2  图 1,但为平均降水日数

    Figure  2.  Same as Fig. 1, but for the summer total rainy days

    图  3  图 1,但为平均小雨总量

    Figure  3.  Same as Fig. 1, but for the summer mean light rainfall

    图  4  图 1,但为平均小雨总量占降水总量的比重

    Figure  4.  Same as Fig. 1, but for the percentage of summer mean light rainfall in the total rainfall

    图  5  图 1,但为平均中雨总量

    Figure  5.  Same as Fig. 1, but for the summer mean medium rainfall

    图  6  图 1,但为平均中雨总量占降水总量的比重

    Figure  6.  Same as Fig. 1, but for the percentage of summer mean medium rainfall in the total rainfall

    图  7  图 1,但为平均大雨总量

    Figure  7.  Same as Fig. 1, but for the summer mean large rainfall

    图  8  图 1,但为平均大雨总量占降水总量的比重

    Figure  8.  Same as Fig. 1, but for the percentage of summer mean large rainfall in the total rainfall

    图  9  图 1,但为平均暴雨总量

    Figure  9.  Same as Fig. 1, but for the summer mean heavy rainfall

    图  10  观测和CMIP5模式模拟的1962~2005年夏季华北地区不同等级降水量的时间序列(黑色曲线为总降水;橘色曲线为小雨;绿色曲线为中雨;蓝色曲线为大雨;红色曲线为暴雨。两段蓝色直线分别为总降水1962~1978年和1979~1995年夏季均值线)

    Figure  10.  Time series of summer mean total (black curved line), light (orange curved line), medium (green curved line), large (blue curved line), and heavy (red curved line) rainfall from observations and CMIP5 models over North China during 1962-2005 (bold blue lines in the figures show the average values of total summer rainfall during 1962-1978 and 1979-1995, respectively)

    图  11  图 10,但为江淮地区

    Figure  11.  Same as Fig. 10, but for Yangtze-Huaihe River basin

    表  1  17个CMIP5气候模式基本信息简介

    Table  1.   Description of the 17 CMIP5 climate models used in the present study

    模式简称 空间分辨率 研发国家
    ACCESS1.0 1.3°(纬度)×1.9°(经度) 澳大利亚
    BCC-CSM1.1 2.8°(纬度)×2.8°(经度) 中国
    BNU-ESM 2.8°(纬度)×2.8°(经度) 中国
    CanESM2 2.8°(纬度)×2.8°(经度) 加拿大
    CCSM4 0.94°(纬度)×1.3°(经度) 美国
    CSIRO-MK3.6.0 1.9°(纬度)×1.9°(经度) 澳大利亚
    FGOALS-g2 3.0°(纬度)×2.8°(经度) 中国
    IPSL-CM5A-LR 1.9°(纬度)×3.8°(经度) 法国
    IPSL-CM5A-MR 1.3°(纬度)×2.5°(经度) 法国
    IPSL-CM5B-LR 1.9°(纬度)×3.8°(经度) 法国
    MIROC5 1.4°(纬度)×1.4°(经度) 日本
    MIROC-ESM 2.8°(纬度)×2.8°(经度) 日本
    MIROC-ESM-CHEM 2.8°(纬度)×2.8°(经度) 日本
    MPI-ESM-LR 1.9°(纬度)×1.9°(经度) 德国
    MPI-ESM-P 1.9°(纬度)×1.9°(经度) 德国
    MRI-CGCM3 1.1°(纬度)×1.1°(经度) 日本
    NorESM1-M 1.9°(纬度)×2.5°(经度) 挪威
    下载: 导出CSV

    表  2  华北地区各类降水量值年代际变化

    Table  2.   Decadal variabilities of total, large, and heavy rainfall over North China

    表  3  江淮地区各类降水量值年代际变化

    Table  3.   Decadal variabilities of total, light, medium, large, and heavy rainfall over the Yangtze-Huaihe River basin

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  • 收稿日期:  2016-11-23
  • 网络出版日期:  2017-09-13
  • 刊出日期:  2018-01-20

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