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中国西南地区5月降水与阿拉伯海季风关系的年代际变化

经皓童 孙建奇 于水 华维

经皓童, 孙建奇, 于水, 等. 2021. 中国西南地区5月降水与阿拉伯海季风关系的年代际变化[J]. 大气科学, 45(5): 1087−1098 doi: 10.3878/j.issn.1006-9895.2012.20195
引用本文: 经皓童, 孙建奇, 于水, 等. 2021. 中国西南地区5月降水与阿拉伯海季风关系的年代际变化[J]. 大气科学, 45(5): 1087−1098 doi: 10.3878/j.issn.1006-9895.2012.20195
JING Haotong, SUN Jianqi, YU Shui, et al. 2021. Decadal Variability in the Relationship between May Rainfall over Southwest China and the Arabian Sea Monsoon [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(5): 1087−1098 doi: 10.3878/j.issn.1006-9895.2012.20195
Citation: JING Haotong, SUN Jianqi, YU Shui, et al. 2021. Decadal Variability in the Relationship between May Rainfall over Southwest China and the Arabian Sea Monsoon [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(5): 1087−1098 doi: 10.3878/j.issn.1006-9895.2012.20195

中国西南地区5月降水与阿拉伯海季风关系的年代际变化

doi: 10.3878/j.issn.1006-9895.2012.20195
基金项目: 国家自然科学基金项目41825010,中国科学院战略性先导科技专项(A类)XDA23090102
详细信息
    作者简介:

    经皓童,女,1997年出生,硕士研究生,主要从事气候变化方面的研究。E-mail: jinghaotong@mail.iap.ac.cn

    通讯作者:

    孙建奇,E-mail: sunjq@mail.iap.ac.cn

  • 中图分类号: P461

Decadal Variability in the Relationship between May Rainfall over Southwest China and the Arabian Sea Monsoon

Funds: National Natural Science Foundation of China (Grant 41825010), Strategic Priority Research Program of Chinese Academy of Sciences (Grant XDA23090102)
  • 摘要: 本文利用1960~2017年中国西南地区115个台站观测降水资料和日本气象厅发布的55年再分析资料集,研究了中国西南地区5月降水变异的主导模态及其与阿拉伯海季风的关系。结果显示,中国西南地区5月降水的第一主导模态主要表现为全区一致的变异特征;该模态与同期5月阿拉伯海季风强度异常关系密切,但两者的关系在20世纪70年代后期发生了显著的年代际变化。在1960~1976年,阿拉伯海季风异常所引起的低层大气环流和水汽输送异常主要集中在阿拉伯海到孟加拉湾一带;阿拉伯海季风异常所引起的大气环流不能到达中国西南地区,因此它对中国西南地区5月降水的影响偏弱。但在1981~2017年,阿拉伯海季风异常可以导致整个北印度洋到南海地区的大气环流异常,进而引起中国西南地区水汽和垂直运动的变化,最终对该地区5月降水产生显著的影响。进一步的研究显示,阿拉伯海季风与中国西南地区5月降水关系的变化可能与季风自身的年代际变率有关。阿拉伯海季风在20世纪70年代末之前变率偏弱,其引起的环流异常也偏弱;相反在20世纪70年代末之后,其变率增强,它引起的大气环流异常也偏强,可以延伸到中国西南地区,进而影响到西南地区的5月降水。因此,季风变率的强弱可能在季风对西南地区5月降水的影响中起着非常重要的作用。
  • 图  1  中国西南地区115个站点分布

    Figure  1.  Locations of the 115 observation stations across Southwest China

    图  2  1960~2017年西南地区5月降水的(a)EOF1模态及其对应的(b)PC1时间序列(柱状)和RPI时间序列(折线)

    Figure  2.  (a) The first mode of EOF (Empirical Orthogonal Function) and (b) the time series of corresponding principal component (PC1, bars) and RPI (Regional Precipitation Index, curve) of precipitation in May over Southwest China during 1960–2017

    图  3  1960~2017年ASMI和RPI的(a)21年、(b)23年、(c)19年滑动相关系数。黑色虚线表示99%信度水平线

    Figure  3.  Sliding correlation coefficients between ASMI and RPI with windows of (a) 21, (b) 23, (c) 19 years. The dashed lines indicate 99% confidence level

    图  4  标准化的ASMI回归的(a)1960~1976和(b)1981~2017西南地区5月降水异常场(单位:mm d−1)。打点区域表示降水异常场通过95%信度水平的显著性检验

    Figure  4.  Precipitation anomalies (units: mm d−1) in May over Southwest China regressed onto standardized ASMI during (a) 1960–1976 and (b) 1981–2017. The dotted areas indicate anomalies passing test at the 95% confidence level

    图  5  标准化的ASMI回归的1960~1976年5月(a)500 hPa和(b)700 hPa位势高度异常(彩色阴影,单位:gpm)和风场异常(绿色矢量,单位:m s−1)。(c–d)同(a–b),但为1981~2017年的回归结果。打点区域(绿色矢量)表示位势高度(风场)异常通过95%信度水平的显著性检验

    Figure  5.  Geopotential height anomalies (color shadings, units: gpm) and wind anomalies (green vectors, units: m s−1) regressed onto standardized ASMI at (a) 500 hPa and (b) 700 hPa in May during 1960–1976. (c–d) As in (a–b), but for 1981–2017. The dotted areas (green vectors) indicate geopotential height (wind) anomalies passing test at the 95% confidence level

    图  6  西南地区5月标准化的RPI回归的1981~2017年5月(a)500 hPa和(b)700 hPa位势高度异常(单位:gpm)。打点区域表示异常通过95%信度水平的显著性检验

    Figure  6.  Geopotential height anomalies (units: gpm) regressed onto standardized RPI at (a) 500 hPa and (b) 700 hPa over Southwest China in May during 1981–2017. The dotted areas indicate anomalies passing test at the 95% confidence level

    图  7  标准化的ASMI回归的(a)1960~1976年和(b)1981~2017年5月可降水量异常(阴影,单位:kg m−2)。(c–d)同(a–b),但为回归的整层积分水汽通量异常(蓝色矢量,单位:kg m−1 s−1)。(e–f)同(a–b),但为回归的整层积分水汽通量散度异常(阴影,单位:10−5 kg m−2 s−1)。图a、b、e、f中的打点区域和图c、d中的阴影区域代表异常通过95%信度水平的显著性检验

    Figure  7.  Precipitable water anomalies (shadings, units: kg m−2) regressed onto standardized ASMI during (a) 1960–1976 and (b) 1981–2017. (c–d) As in (a–b), but for regressed vertical integrated water vapor fluxes anomalies (blue vectors, units: kg m−1 s−1). (e–f) As in (a–b), but for regressed divergence anomalies (shadings, units: 10−5 kg m−2 s−1) of the vertical integrated water vapor fluxes. The dotted areas in Figs. a, b, e, f and shadings in Figs. c, d indicate anomalies passing test at the 95% confidence level

    图  8  标准化的ASMI回归的(a)1960~1976年和(b)1981~2017年5月沿95°~105°E平均的经圈环流异常(经向风单位:m s−1;垂直速度单位:Pa s−1;垂直速度乘以了−150)。阴影区域表示异常通过95%信度水平的显著性检验

    Figure  8.  Mean meridional circulation anomalies [meridional wind (units: m s−1), vertical velocity (units: Pa s−1), the vertical velocity is multiplied by −150] along 95°–105°E regressed onto standardized ASMI in May during (a) 1960–1976 and (b) 1981–2017. The shadings indicate anomalies passing test at the 95% confidence level

    图  9  (a)1960~1976和(b)1981~2017年ASM强、弱年合成的5月位势高度异常(单位:gpm)。(c–d)同(a–b),但为合成的整层积分水汽通量异常(单位:kg m−1 s−1)。(e–f)同(a–b),但为合成的沿95°~105°E平均的经圈环流异常(经向风单位:m s−1;垂直速度单位:Pa s−1;垂直速度乘以了−150)。图a、b中的打点区域和图c–f中的阴影区域代表异常通过95%信度水平的显著性检验

    Figure  9.  Composited geopotential height anomalies (units: gpm) between strong and weak ASM years in May during (a) 1960–1976 and (b) 1981–2017. (c–d) As in (a–b), but for composited vertical integrated water vapor fluxes anomalies (units: kg m−1 s−1). (e–f) As in (a–b), but for a composited latitude–pressure cross section of meridional circulation [meridional wind (units: m s−1), vertical velocity (units: Pa s−1), the vertical velocity is multiplied by −150] averaged between 95°E and 105°E. The dotted areas in Figs. a, b and shadings in Figs. c–f indicate anomalies passing test at the 95% confidence level

    图  10  ASMI的19年滑动标准差与ASMI–RPI(ASMI和中国西南地区5月RPI)的19年滑动相关系数的散点图。横虚线为95%信度水平对应的相关系数值,竖虚线为1.67。蓝色(黄色)圆点代表滑动窗口的中心年份位于1960–1976(1981–2017)年的时段

    Figure  10.  Scatter plot of 19-year sliding standard deviations of ASMI and 19-year sliding correlation coefficients between ASMI and RPI in May over Southwest China. The horizontal dotted line indicates a significant correlation at the 95% confidence level, and the vertical dotted line is at 1.67. The blue and yellow dots represent the periods with central years in 1960–1976 and 1981–2017, respectively

    表  1  RPI与ASMI在各时段的相关系数

    Table  1.   The correlation coefficients between RPI (Regional Precipitation Index) and ASMI (Arabian Sea Monsoon Index) in each period

    相关系数
    RPI(1960~2017)RPI(1960~1976)RPI(1981~2017)
    ASMI0.39*−0.390.55*
    注:*代表通过99%信度水平的显著性检验
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-08-25
  • 录用日期:  2020-12-31
  • 网络出版日期:  2021-03-02
  • 刊出日期:  2021-10-14

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