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新疆温度和降水变化的CMIP6模式预估

张晓璐 王晓欣 华丽娟 姜大膀

张晓璐, 王晓欣, 华丽娟, 等. 2023. 新疆温度和降水变化的CMIP6模式预估[J]. 大气科学, 47(2): 387−398 doi: 10.3878/j.issn.1006-9895.2201.21182
引用本文: 张晓璐, 王晓欣, 华丽娟, 等. 2023. 新疆温度和降水变化的CMIP6模式预估[J]. 大气科学, 47(2): 387−398 doi: 10.3878/j.issn.1006-9895.2201.21182
ZHANG Xiaolu, WANG Xiaoxin, HUA Lijuan, et al. 2023. Projections of Temperature and Precipitation over Xinjiang Based on CMIP6 Models [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(2): 387−398 doi: 10.3878/j.issn.1006-9895.2201.21182
Citation: ZHANG Xiaolu, WANG Xiaoxin, HUA Lijuan, et al. 2023. Projections of Temperature and Precipitation over Xinjiang Based on CMIP6 Models [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 47(2): 387−398 doi: 10.3878/j.issn.1006-9895.2201.21182

新疆温度和降水变化的CMIP6模式预估

doi: 10.3878/j.issn.1006-9895.2201.21182
基金项目: 国家自然科学基金项目41991284
详细信息
    作者简介:

    张晓璐,女,1995年出生,硕士研究生,主要从事气候变化研究。E-mail: zhangxiaolu191@mails.ucas.ac.cn

    通讯作者:

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

  • 中图分类号: P467

Projections of Temperature and Precipitation over Xinjiang Based on CMIP6 Models

Funds: National Natural Science Foundation of China (NSFC) (Grant 41991284)
  • 摘要: 本文使用国际耦合模式比较计划第六阶段(CMIP6)中对新疆当代温度和降水模拟能力较好的20个模式的试验数据,在三种共享社会经济路径(SSPs)情景下,预估了新疆21世纪温度和降水的年和季节变化。根据多模式中位数,相对于1995~2014年,新疆21世纪不断升温,盆地增幅大于山区。在SSP1-2.6、SSP2-4.5和SSP5-8.5情景下,2015~2099年年平均增温趋势分别为0.1°C (10 a)−1、0.3°C (10 a)−1和0.7°C (10 a)−1;2080~2099年区域平均分别升温1.3°C、2.6°C和5.3°C,其中夏季增幅最大。各模式预估的年和季节温度变化符号的区域平均一致性大于90%,模式结果间不确定性范围随时间增加,SSP5-8.5情景下的不确定性较SS1-2.6和SSP2-4.5的更大;除春季外,模式对其它季节温度预估的不确定性高于年平均。新疆21世纪降水不断增加,降水百分比变化的大值区位于塔里木盆地中部,末期SSP5-8.5情景下增幅超过50%。在SSP1-2.6、SSP2-4.5和SSP5-8.5情景下,2015~2099年年降水增幅分别是0.2% (10 a)−1、2% (10 a)−1和4% (10 a)−1;2080~2099年区域平均降水分别增加5%、13%和25%,其中冬季降水增幅更大。各模式预估的新疆降水变化符号的一致性较好,且随时间有所提高,但仍较温度的小;对新疆降水百分比变化预估的不确定性范围随时间增加,其中在SSP5-8.5情景下的最大;各季节降水预估的不确定性较年平均偏大。
  • 图  1  新疆地理位置(红色矩形框内:34°N~50°N,71°E~99°E)及其地形分布(填色,单位:m)

    Figure  1.  Geographical location (curve in the red rectangle: 34°N–50°N, 71°E–99°E) and topography (shading, units: m) of Xinjiang

    图  2  相对于1995~2014年,在SSP1-2.6(蓝色)、SSP2-4.5(橙色)和SSP5-8.5(红色)情景下,20个CMIP6模式模拟的2015~2099年新疆区域平均年温度变化时间序列(左图,单位:°C)和2080~2099年的年温度变化(右图,单位:°C)。实线表示多模式中位数,阴影区为多模式模拟结果的5%~95%范围

    Figure  2.  Time series of regionally averaged annual temperature changes over Xinjiang from 2015 to 2099 (left-hand side panel) and annual temperature changes during 2080–2099 (right panel) relative to 1995–2014 (units: °C), as derived from 20 CMIP6 models under SSP1-2.6 (blue), SSP2-4.5 (orange), and SSP5-8.5 (red), respectively. The solid line and the shading represent the multimodel median and the range of 5%–95% of individual models, respectively

    图  3  相对于1995~2014年,在SSP1-2.6、SSP2-4.5和SSP5-8.5情景下,基于20个CMIP6模式的中位数预估,21世纪近期(左列)、中期(中间列)和末期(右列)新疆年温度变化(填色,单位:°C)及多模式预估结果的不确定性(阴影,单位:°C)。黑色实心点表示大于80%的模式通过95%的显著性检验;各图左上角数字代表区域平均的年温度变化(不确定性)

    Figure  3.  Changes in annual temperature (color, units: °C) in the near- (left column), the middle- (middle column), and the long- (right column) terms during the 21st century relative to 1995–2014 over Xinjiang as derived from the median of 20 CMIP6 models under SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively, and inter-model uncertainty (shading, units: °C) of temperature projections from individual models. The black solid dots indicate that more than 80% of individual models are statistically significant at the 95% confidence level. The regionally averaged annual temperature change (inter-model uncertainty) is provided in the top-left corner of each panel

    图  4  图3,但为SSP5-8.5情景下的春季(MAM)、夏季(JJA)、秋季(SON)和冬季(DJF)温度变化(单位:°C)。空心点表示50%~80%的模式通过95%的显著性检验

    Figure  4.  Same as Fig. 3, but for the temperature changes in spring (MAM), summer (JJA), autumn (SON), and winter (DJF) under SSP5-8.5 (units: °C). The hollow dots indicate that 50%–80% of individual models are statistically significant at the 95% confidence level

    图  5  图2,但为年降水变化

    Figure  5.  Same as Fig. 2, but for the changes in annual precipitation

    图  6  图3,但为年降水变化(填色)及多模式预估结果的不确定性(阴影)

    Figure  6.  Same as Fig. 3, but for the changes in annual precipitation (color) and associated inter-model uncertainty (shading)

    图  7  图6,但为SSP5-8.5情景下季节降水变化(填色)

    Figure  7.  Same as Fig. 6, but for the changes of seasonal precipitation under SSP5-8.5 (color)

    表  1  本文使用的20个CMIP6全球气候模式的基本信息

    Table  1.   Basic information of the 20 CMIP6 (Coupled Model Intercomparison Project Phase 6) global climate models used in this study

    序号模式名称所属国家或地区所属机构简称水平分辨率(纬向×经向)积分时段
    01AWI-CM-1-1-MR德国  AWI0.9375°×~0.9°2015~2100
    02BCC-CSM2-MR中国  BCC1.125°×~1.1°2015~2100
    03CAMS-CSM-1-0中国  CAMS1.125°×~1.1°2015~2099
    04CESM2-WACCM美国  NCAR1.25°×~0.9°2015~2100
    05CanESM5加拿大 CCCma2.8125°×~2.8°2015~2100
    06EC-Earth3-Veg欧洲十国EC-Earth-Consortium0.703125°×~0.7°2015~2100
    07EC-Earth3欧洲十国EC-Earth-Consortium0.703125°×~0.7°2015~2100
    08FGOALS-f3-L中国  CAS1.25°×1.0°2015~2100
    09FGOALS-g3中国  CAS2.0°×~2.0°2015~2100
    10GFDL-ESM4美国  NOAA-GFDL1.25°×1.0°2015~2100
    11INM-CM4-8俄罗斯 INM2.0°×1.5°2015~2100
    12INM-CM5-0俄罗斯 INM2.0°×1.5°2015~2100
    13IPSL-CM6A-LR法国  IPSL2.5°×~1.3°2015~2100
    14KACE1.0-G韩国  NIMS-KMA1.875°×1.25°2015~2100
    15MIROC6日本  MIROC1.40625°×~1.4°2015~2100
    16MPI-ESM1-2-HR德国  MPI-M0.9375°×~0.9°2015~2100
    17MPI-ESM1-2-LR德国  MPI-M1.875°×~1.9°2015~2100
    18NESM3中国  NUIST1.875°×~1.9°2015~2100
    19NorESM2-LM挪威  NCC2.5°×~1.9°2015~2100
    20NorESM2-MM挪威  NCC1.25°×~0.9°2015~2100
    注:第5列“~”表示“约”
    下载: 导出CSV

    表  2  根据20个CMIP6模式中位数,相对于1995~2014年,在SSP1-2.6、SSP2-4.5和SSP5-8.5情景下,21世纪近期(2021~2040年)、中期(2041~2060年)和末期(2080~2099年),新疆的年和季节温度、降水变化的区域平均值及模式间预估结果的不确定性

    Table  2.   Regionally averaged annual and seasonal temperature and precipitation changes over Xinjiang projected by the median of 20 CMIP6 models under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios in the near (2021–2040)-, middle (2041–2060)-, and long (2080–2099)-terms of the 21st century relative to 1995–2014. The regionally averaged inter-model uncertainty of the projected temperature and precipitation changes among the models is listed in the brackets

    温度变化/°C(不确定性/°C)降水变化(不确定性)
    前期中期末期前期中期末期
    SSP1-2.6年平均0.9(1.1)1.3(1.1)1.3(1.1)4(107(115(12
    春季0.8(0.8)1.2(0.9)1.3(0.9)8(188(186(17
    夏季1.1(1.4)1.5(1.4)1.6(1.4)−1(22−1(221(25
    秋季1.0(1.3)1.4(1.4)1.3(1.4)1(196(212(20
    冬季0.9(1.3)1.3(1.2)1.3(1.2)12(2112(2111(20
    SSP2-4.5年平均1.0(1.1)1.8(1.1)2.6(1.2)4(109(1413(18
    春季0.8(0.9)1.4(1.0)2.2(1.0)4(1610(1817(24
    夏季1.1(1.3)2.0(1.5)3.0(1.5)2(302(301(29
    秋季0.9(1.4)1.8(1.4)2.6(1.5)4(187(2112(27
    冬季0.9(1.3)1.7(1.2)2.6(1.4)18(2318(2329(29
    SSP5-8.5年平均1.1(1.1)2.3(1.3)5.3(1.8)4(119(1525(27
    春季0.9(1.0)2.0(1.1)4.8(1.7)5(1611(2028(34
    夏季1.4(1.4)2.6(1.6)5.8(2.2)1(24−1(262(38
    秋季1.1(1.4)2.3(1.6)5.3(2.2)5(219(2522(38
    冬季1.0(1.2)2.1(1.3)5.1(1.9)10(2021(2659(54
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-09-20
  • 录用日期:  2022-01-18
  • 网络出版日期:  2022-01-21
  • 刊出日期:  2023-03-15

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