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中国干湿变化的高分辨率区域气候模式预估

王恺曦 姜大膀 华维

王恺曦, 姜大膀, 华维. 2020. 中国干湿变化的高分辨率区域气候模式预估[J]. 大气科学, 44(6): 1203−1212 doi:  10.3878/j.issn.1006-9895.1912.19176
引用本文: 王恺曦, 姜大膀, 华维. 2020. 中国干湿变化的高分辨率区域气候模式预估[J]. 大气科学, 44(6): 1203−1212 doi:  10.3878/j.issn.1006-9895.1912.19176
WANG Kaixi, JIANG Dabang, HUA Wei. 2020. Dry/Wet Climate Projections over China Using a High-Resolution Regional Climate Model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1203−1212 doi:  10.3878/j.issn.1006-9895.1912.19176
Citation: WANG Kaixi, JIANG Dabang, HUA Wei. 2020. Dry/Wet Climate Projections over China Using a High-Resolution Regional Climate Model [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(6): 1203−1212 doi:  10.3878/j.issn.1006-9895.1912.19176

中国干湿变化的高分辨率区域气候模式预估

doi: 10.3878/j.issn.1006-9895.1912.19176
基金项目: 国家重点研发计划项目2016YFA0600704,国家自然科学基金项目41421004
详细信息
    作者简介:

    王恺曦,女,1994年出生,博士研究生,主要从事气候变化研究。E-mail: 605259856@qq.com

    通讯作者:

    姜大膀,E-mail: jiangdb@mail.iap.ac.cn

  • 中图分类号: P467

Dry/Wet Climate Projections over China Using a High-Resolution Regional Climate Model

Funds: Research and Development Program of China (Grant 2016YFA0600704), National Natural Science Foundation of China (Grant 41421004)
  • 摘要: 本文使用三个全球气候模式驱动下的高分辨率区域气候模式RegCM4的试验数据,首先评估了RegCM4对参考时段(1986~2005年)中国干燥度指数(AI)的模拟能力,而后根据典型浓度路径中等排放(RCP4.5)情景下RegCM4试验对中国未来干湿变化进行了预估研究。结果表明,RegCM4能够合理模拟中国区域AI的空间分布。两种潜在蒸散发计算方法得到的参考时段AI在空间分布和数值上存在一定差异,尤其是在中国西部高海拔地区和北方地区。在三个全球气候模式驱动场作用下的RegCM4预估试验中,21世纪中期(2046~2065年)和末期(2081~2098年)中国区域平均AI较参考时段分别减小2%~4%和2%~5%,其中西北中部变湿,其他地区均变干。不同地区未来干湿变化的主要影响因素存在差异,西北中部降水变化为主导因素,其他地区主要受控于升温所引起的潜在蒸散发变化。
  • 图  1  1986~2005年(a)观测以及使用PETPM算法所得的干燥度指数AI气候态分布:(b、e、h)三个全球模式试验及其(d)集合平均;(c、f、i)相应的三个RegCM4试验及其(g)集合平均。

    Figure  1.  AI (aridity index) climatology based on (a) observations and the PETPM method for the period 1986–2005: (b, e, h) Results obtained from three global climate models and (d) their ensemble mean; (c, f, i) results obtained from the corresponding simulations by RegCM4 and (g) their ensemble mean

    图  2  RCP4.5情景下RegCM4预估的21世纪中期(第一、三列)和末期(第二、四列)AI相对于1986~2005年的变化,从上至下依次为:CdR、HdR、MdR及其集合平均MME;第一和第二列基于PETPM,第三和第四列基于PETTH。在最下行图中,红色斜线代表三个模拟结果变化一致的区域,黑色圆点表示通过95%置信水平检验(下同);黑色框表示AI变化较为显著的重点研究区域,分别是(1)西北中部(37°~42°N,79°~95°E)、(2)东北南部和华北北部(35°~45°N,116.5°~130°E)、(3)西南(21°~32.5°N,97.5°~107.5°E)、(4)东南(17.5°~32.5°N,107.5°~125°E)

    Figure  2.  Projected AI changesrelative to the reference period 1986–2005 in the middle (the first and third columns) and end (the second and fourth columns) of the 21st century, obtained using RegCM4 under the RCP4.5 scenario. The panels from the top to bottom indicate results from CdR (downscaling results of CSIRO-Mk3-6-0), HdR (downscaling results of HadGEM2-ES), and MdR (downscaling results of MPI-ESM-MR) and their ensemble mean MME. The potential evapotranspiration is calculated by PETPM (the first and second columns) and PETTH (the third and fourth columns). In the bottom panels, the red slash represents the results of three models agreeing in sign with each other, and the black dots represent the 95% confidence level (the same below); the black boxes show key regions where large AI changes occur: (1) Central Northwest China (CNW: 37°−42°N, 79°−95°E), (2) southern Northeast China and northern–central North China (SNE plus NN: 35°−45°N, 116.5°−130°E), (3) Southwest China (SW: 21°–32.5°N, 97.5°–107.5°E), and (4) Southeast China (SE: 17.5°–32.5°N, 107.5°–125°E)

    图  3  在RCP4.5情景下的RegCM4试验中,降水(左列)和PET(中间列)及其区域平均(右列)对21世纪中期AI变化的贡献,从上至下依次为三个RegCM4试验及其集合平均。直方图中每个重点研究区域的三个柱形从左至右依次为区域平均的AI变化、降水引起的AI变化和PET引起的AI变化

    Figure  3.  The contributions of precipitation (left column), potential evapotranspiration (middle column), and their regional average (right column) to AI changes during the mid-21st century under the RCP4.5 scenario, obtained using RegCM4. The three columns of figures from top to bottom indicate results from three sets of RegCM4 experiments and their ensemble mean. The three bars of each key region in the histogram, from left to right, are the regional average AI changesand the contributions of precipitation and potential evapotranspiration

    图  4  在RCP4.5情景下的RegCM4试验中,平均温度(第一列)、有效能量(第二列)、2 m风速(第三列)和相对湿度(第四列)对21世纪中期PETPM变化的贡献,从上至下依次为三个RegCM4及其试验集合平均

    Figure  4.  The contributions of temperature (first column), available energy (second column), 2-m wind speed (third column), and relative humidity (fourth column) to PETPM changes during the mid-21st century under the RCP4.5 scenario, obtained using RegCM4. The figures from top to bottom indicate results from three sets of RegCM4 experiments and their ensemble mean

    图  5  在RCP4.5情景下的(a, b, c)三套RegCM4试验及其(d)集合平均中,中国及其四个重点地区的平均温度(蓝)、相对湿度(红)、2 m风速(绿)、有效能量(紫)和降水(橙)对21世纪中期AI(黑)变化的贡献

    Figure  5.  Regionally averaged AI (black) changes over China and its four key regions in the mid-21st century under the RCP4.5 scenario and the associated contributions of mean temperature (blue), relative humidity (red), 2-m wind speed (green), effective energy (purple), and precipitation (orange) as obtained from (a, b, c) three sets of RegCM4 experiments; (d) their ensemble mean

    表  1  RegCM4预估的21世纪中期(2046~2065年)和末期(2081~2098年)中国各区域AI相对于1986~2005年的变化

    Table  1.   Projected AI changes in regions of China in the middle (2046–2065) and the end (2081–2098) of the 21st century relative to the reference period 1986–2005, obtained using RegCM4

    地区PET计算方法2046~2065年AI相对变化2081~2098年AI相对变化
    CdR数据HdR数据MdR数据集合平均CdR数据HdR数据MdR数据集合平均
    西北中部PETPM12%14%12%13%13%22%9%15%
    PETTH−2%−1%5%1%−2%2%1%0%
    东北南部和华北北部PETPM−5%−9%−7%−7%−7%−10%−15%−10%
    PETTH−7%−11%−8%−9%−10%−14%−15%−13%
    西南PETPM−6%−4%−3%−4%−10%−7%−8%−8%
    PETTH−10%−9%−6%−8%−16%−13%−10%−13%
    东南PETPM−5%−11%−5%−7%−6%−5%0%−4%
    PETTH−12%−16%−10%−13%−16%−14%−6%−12%
    全国平均PETPM−3%−4%−2%−3%−5%−2%−4%−4%
    PETTH−8%−10%−5%−8%−11%−10%−7%−10%
    下载: 导出CSV
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    [6] 李东欢, 周天军, 邹立维, 马双梅.  RegCM3 CORDEX东亚试验模拟和预估的中国夏季温度变化, 大气科学. doi: 10.3878/j.issn.1006-9895.1607.16153
    [7] 童尧, 高学杰, 韩振宇, 徐影.  基于RegCM4模式的中国区域日尺度降水模拟误差订正, 大气科学. doi: 10.3878/j.issn.1006-9895.1704.16275
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出版历程
  • 收稿日期:  2019-12-07
  • 网络出版日期:  2020-04-27
  • 刊出日期:  2020-11-15

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