高级检索

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

海表温度的增暖趋势和自然变率对长江中下游夏季极端降水强度的影响

欧立健 余锦华 钟校尧 张旭煜 王璐 罗京佳

欧立健, 余锦华, 钟校尧, 等. 2022. 海表温度的增暖趋势和自然变率对长江中下游夏季极端降水强度的影响[J]. 大气科学, 46(6): 1595−1606 doi: 10.3878/j.issn.1006-9895.2202.21221
引用本文: 欧立健, 余锦华, 钟校尧, 等. 2022. 海表温度的增暖趋势和自然变率对长江中下游夏季极端降水强度的影响[J]. 大气科学, 46(6): 1595−1606 doi: 10.3878/j.issn.1006-9895.2202.21221
OU Lijian, YU Jinhua, ZHONG Xiaoyao, et al. 2022. Impacts of the SST Warming Trend and Natural Variability on the Summer Extreme Precipitation Intensity of the Middle and Lower Reaches of the Yangtze River [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(6): 1595−1606 doi: 10.3878/j.issn.1006-9895.2202.21221
Citation: OU Lijian, YU Jinhua, ZHONG Xiaoyao, et al. 2022. Impacts of the SST Warming Trend and Natural Variability on the Summer Extreme Precipitation Intensity of the Middle and Lower Reaches of the Yangtze River [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(6): 1595−1606 doi: 10.3878/j.issn.1006-9895.2202.21221

海表温度的增暖趋势和自然变率对长江中下游夏季极端降水强度的影响

doi: 10.3878/j.issn.1006-9895.2202.21221
基金项目: 国家重点研发计划项目2020YFA0608901、2018YFC1507700,国家自然科学基金项目41730961、41575083
详细信息
    作者简介:

    欧立健,男,1996年出生,硕士研究生,主要从事极端天气气候的研究。E-mail: atom_olj@163.com

    通讯作者:

    余锦华,E-mail: jhyu@nuist.edu.cn

  • 中图分类号: P467

Impacts of the SST Warming Trend and Natural Variability on the Summer Extreme Precipitation Intensity of the Middle and Lower Reaches of the Yangtze River

Funds: National Key Research and Development Program of China (Grants 2020YFA0608901, 2018YFC1507700), National Natural Science Foundation of China (Grants 41730961, 41575083)
  • 摘要: 极端降水引起的洪、涝等灾害每年给我国带来极大的人员伤亡和经济损失。全球增暖使极端降水事件发生的频率增加,强度增强。但是针对不同区域极端降水事件,其贡献究竟如何还有待于进一步认识。本文以我国长江中下游地区的极端降水事件为研究对象,通过典型年份夏季区域极端降水过程的水汽收支特征,探讨海表温度(SST)的增暖趋势和自然变率强迫对该区域典型极端降水强度的影响效应。结果表明:(1)极端降水过程及其夏季都伴随着区域整层大气的水汽辐合,且水汽辐合发生在经向方向。西北太平洋异常反气旋式环流,在区域南边界形成了稳定的西南风异常的水汽输送。(2)典型极端降水过程发生的夏季,SST在赤道印度洋和热带大西洋为强正异常,主要为增暖趋势的贡献,赤道中东太平洋SST异常表现为La Niña型。(3)SST增暖趋势和自然变率的数值敏感性试验表明,1998、2017和2020年的SST增暖趋势强迫的区域水汽辐合分别是其自然变率强迫的83%、210%和107%,SST增暖趋势比自然变率的影响更为重要。(4)SST增暖趋势和自然变率都是通过强迫西北太平洋异常反气旋式环流,引起长江中下游区域南边界异常的西南水汽输送,是导致极端降水发生的主要过程。
  • 图  1  (a)时空聚集性强度(TSG)方法识别的中国夏季极端降水过程的降水量(填色)空间分布,图中红色框为本文研究的长江中下游地区(27°~34°N,108°~122°E), (b)长江中下游夏季极端降水量(黑线)和夏季区域平均降水量(蓝线)的时间序列,单位:mm,其相关系数R=0.534显著性达到99%信度水平

    Figure  1.  (a) Spatial patterns of the extreme precipitation (shaded) over the East China during summer identified by the Time-Spatial-Gather (TSG) method, the red box in the figure shows the middle and lower reaches of the Yangtze River (MLYR) region (27°–34°N,108°–122°E) studied in this paper. (b) Temporal series of the summer extreme precipitation (black line) and the averaged summer precipitation (mm) (blue line) over MLYR region. The correlation coefficient between both series is 0.534, which is significant at the 99% confidence level

    图  2  (a、d)1998年、(b、e)2017年、(c、f)2020年夏季长江中下游区域四个边界整层积分水汽通量(单位:1012 kg d−1)和区域水汽通量辐合(方框内数值,单位:kg m−2 d−1):(a–c)夏季相对于气候态的异常;(d–f)极端降水过程相对于夏季平均的偏差。图中红色框为本文研究的长江中下游,图中四个箭头分别为长江中下游区域各边界的水汽通量,数值代表其大小

    Figure  2.  Water vapor flux of four boundaries (units: 1012 kg d−1) during summer in (a, d) 1998, (b, e) 2017, and (c, f) 2020; the convergence of the water vapor flux (the value in the box, units: kg m−2 d−1): (a–c) Anomalous values corresponding to summer climatology , (d–f) departure in extreme events from the summer average. The red box in the figure shows the MLYR region, the four arrows in the figure are the direction of water vapor flux at each boundary of the MLYR, and the numerical value represents its magnitude

    图  3  (a)1998年、(b)2017年和(c)2020 年夏季长江中下游南边界水汽通量垂直廓线:实线为夏季相对于气候态的异常,虚线为极端降水过程相对于夏季平均的偏差,单位:108 kg hPa−1 d−1

    Figure  3.  Vertical profile of the water vapor flux (units: 108 kg hPa−1 d−1) in MLYR’ s south boundary during summer of (a) 1998, (b) 2017, and (c) 2020; the solid lines are anomalies during Summer from their respective climatology; the dotted lines indicate the departure during extreme precipitation events from respective summer average

    图  4  (a、d)1998年、(b、e)2017年和(c、f)2020年夏季850 hPa的水汽通量(矢量,单位:105 kg hPa−1 m−1 d−1):夏季相对于气候态的异常(左列);极端降水过程相对于夏季平均的偏差(右列)。图中蓝色框为本文研究的长江中下游地区

    Figure  4.  Spatial distribution of the water vapor flux (vectors, units: 105 kg hPa−1 m−1 d−1) at 850 hPa during summer of (a, d) 1998, (b, e) 2017, and (c, f) 2020: Anomalies during Summer from their respective climatology (left column); departures during extreme precipitation events from the respective summer average (right column). The blue box in the figure stands for the middle and lower reaches of the Yangtze River

    图  5  1900~2020年的全球海表温度异常进行EOF分解得到的(a、b)第一、(c、d)第二和(e、f)第三模态空间分布(左列),及其时间系数序列(右列)。(b)中红色竖线分别为1998年、2017年和2020年对应的时间系数

    Figure  5.  The lead (a, b) first, (c, d) second, and (e, f) third EOF (empirical orthogonal function) modes (left column) and corresponding time coefficients (right column) of sea surface temperature anomaly (SSTA) during 1900–2020 . The red vertical lines in (b) are the temporal values for the year of 1998, 2017, and 2020

    图  6  1998年(第一行)、2017年(第二行)和2020年(第三行)夏季(6~8月)总的海表温度异常场(左列)、增暖趋势模态(中间列,图5的EOF分解第一模态乘以对应年份的时间系数得到的空间分布)以及对应年份海温的自然变率(右列;总的海温场减去增暖趋势模态的得到的结果),单位:°C

    Figure  6.  Total SSTA (left column), spatial patterns of the warming trends in SSTA (middle column; result from the lead first EOFs of SSTA in Fig. 5), of the natural variability in SSTA (right column; result from the difference between the total SSTA and the warming trend) during the summer in 1998 (a-c), 2017 (d-f), and 2020 (g-i), units: °C

    图  7  1998年(第一行)、2017年(第二行)和2020年(第三行)夏季敏感试验的长江中下游四个边界整层积分水汽通量异常(单位:1012 kg d−1)和区域水汽通量辐合异常(方框内数值,单位:kg m−2 d−1):典型年份SSTA试验结果(左列);SSTA增暖趋势试验结果(中间列);SSTA自然变率试验结果(右列);图中红色框为本文研究的长江中下游地区,图中四个箭头分别为长江中下游区域各边界的水汽通量,数值代表其大小

    Figure  7.  Anomalous of the water vapor flux in four boundaries (units: 1012 kg d−1) during summer of 1998 (top line), 2017 (second line), and 2020 (bottom line) and anomalous convergence of the water vapor flux (the value in the box, units: kg m−2 d−1) for numerical sensitivity experiments: (a, d, g) Results from total SSTA forcing; (b, e, h) forcing from warming trend in SSTA; (c, f, i) forcing from the natural variability in SSTA; the red box in the figure shows the MLYR region, the four arrows in the figure are anomalous direction of the water vapor flux at each boundary of the MLYR, and the numerical value represents respective magnitude

    图  8  图7,但为850 hPa的水汽通量异常场(矢量,单位:105 kg hPa−1 m−1 d−1

    Figure  8.  Same as Fig. 7, except for spatial distribution of the anomalous water vapor flux (vectors, units: 105 kg hPa−1 m−1 d−1) at 850 hPa

    表  1  本文使用CESM2.1.3(Community Earth System Model version 2.1.3)进行的数值试验列表

    Table  1.   List of numerical experiments conducted with CESM2.1.3 (Community Earth System Model version 2.1.3)

    试验类型外强迫条件描述
    控制试验全球SST气候态
    典型年份SST试验1998年夏季赤道附近SSTA+全球SST气候态
    2017年夏季赤道附近SSTA+全球SST气候态
    2020年夏季赤道附近SSTA+全球SST气候态
    SST增暖趋势试验1998年夏季赤道附近SST增暖趋势+
    全球SST气候态
    2017年夏季赤道附近SST增暖趋势+
    全球SST气候态
    2020年夏季赤道附近SST增暖趋势+
    全球SST气候态
    SST自然变率试验1998年夏季赤道附近SST自然变率+
    全球SST气候态
    2017年夏季赤道附近SST自然变率+
    全球SST气候态
    2020年夏季赤道附近SST自然变率+
    全球SST气候态
    下载: 导出CSV

    表  2  典型年份极端降水事件开始和结束时间

    Table  2.   Start and end time of extreme precipitation events in typical years

    1998年2017年2020年
    开始时间结束时间开始时间结束时间开始时间结束时间
    6月13日6月26日6月1日6月1日6月3日6月5日
    7月22日7月22日6月10日6月10日6月28日6月28日
    6月23日6月24日7月2日7月8日
    6月30日7月1日7月22日7月22日
    8月12日8月13日
    下载: 导出CSV
  • [1] Chen J M, Gu S X, Jiang R C, et al. 2018. The relationship between Pacific SSTA and autumn extreme precipitation events of China [J]. MATEC Web Conf., 246: 02056. doi: 10.1051/matecconf/201824602056
    [2] Chen Y, Li W, Jiang X L, et al. 2021. Detectable intensification of hourly and daily scale precipitation extremes across eastern China [J]. J. Climate, 34(3): 1185−1201. doi: 10.1175/JCLI-D-20-0462.1
    [3] Danabasoglu G, Lamarque J F, Bacmeister J, et al. 2020. The community earth system model version 2 (CESM2) [J]. Journal of Advances in Modeling Earth Systems, 12(2): e2019MS001916. doi: 10.1029/2019MS001916
    [4] 丁一汇, 胡国权. 2003. 1998年中国大洪水时期的水汽收支研究 [J]. 气象学报, 61(2): 129−145. doi: 10.3321/j.issn:0577-6619.2003.02.001

    Ding Yihui, Hu Guoquan. 2003. A study on water vapor budget over China during the 1998 severe flood periods [J]. Acta Meteorologica Sinica (in Chinese), 61(2): 129−145. doi: 10.3321/j.issn:0577-6619.2003.02.001
    [5] Gill A E. 1980. Some simple solutions for heat-induced tropical circulation [J]. Quart. J. Roy. Meteor. Soc., 106(449): 447−462. doi: 10.1002/qj.49710644905
    [6] Hagos S M, Leung L R, Yoon J H, et al. 2016. A projection of changes in landfalling atmospheric river frequency and extreme precipitation over western North America from the large Eensemble CESM simulations [J]. Geophys. Res. Lett., 43(3): 1357−1363. doi: 10.1002/2015gl067392
    [7] 贺冰蕊, 翟盘茂. 2018. 中国1961-2016年夏季持续和非持续性极端降水的变化特征 [J]. 气候变化研究进展, 14(5): 437−444. doi: 10.12006/j.issn.1673-1719.2018.016

    He Bingrui, Zhai Panmao. 2018. Characteristics of the persistent and non-persistent extreme precipitation in China from 1961 to 2016 [J]. Climate Change Research (in Chinese), 14(5): 437−444. doi: 10.12006/j.issn.1673-1719.2018.016
    [8] Hersbach H, Bell B, Berrisford P, et al. 2019. Global reanalysis: Goodbye ERA-interim, hello ERA5 [J]. ECMWF Newsletter, 159: 17−24. doi: 10.21957/vf291hehd7
    [9] IPCC. 2021. Climate Change 2021: The Physical Science Basis [M]. Cambridge: Cambridge University Press.
    [10] Pan X, Li T M, Sun Y, et al. 2021. Cause of extreme heavy and persistent rainfall over Yangtze River in summer 2020 [J]. Adv. Atmos. Sci., 38(12): 1994−2009. doi: 10.1007/S00376-021-0433-3
    [11] Rayner N A, Parker D E, Horton E B, et al. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century [J]. J. Geophys. Res. Atmos., 108(D104): 4407. doi: 10.1029/2002JD002670
    [12] Schubert S, Gutzler D, Wang H L, et al. 2009. A U. S. CLIVAR project to assess and compare the responses of global climate models to drought-related SST forcing patterns: Overview and results [J]. J. Climate, 22(19): 5251−5272. doi: 10.1175/2009JCLI3060.1
    [13] Simpson I R, Bacmeister J, Neale R B, et al. 2020. An evaluation of the large-scale atmospheric circulation and its variability in CESM2 and other CMIP models [J]. J. Geophys. Res. Atmos., 125(13): e2020JD032835. doi: 10.1029/2020JD032835
    [14] Sun Q H, Zhang X B, Zwiers F, et al. 2020. A global, continental, and regional analysis of changes in extreme precipitation [J]. J. Climate, 34(1): 243−258. doi: 10.1175/jcli-d-19-0892.1
    [15] Trenberth K E, Fasullo J T, Shepherd T G. 2015. Attribution of climate extreme events [J]. Nature Climate Change, 5(8): 725−730. doi: 10.1038/nclimate2657
    [16] Wang B, Li J, He Q. 2017. Variable and robust East Asian monsoon rainfall response to El Niño over the past 60 years (1957-2016) [J]. Adv. Atmos. Sci., 34(10): 1235−1248. doi: 10.1007/s00376-017-7016-3
    [17] Wang B, Wu R G, Fu X H. 2000. Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? [J]. J. Climate, 13(9): 1517−1536. doi: 10.1175/1520-0442(2000)013<1517:PEATHD>2.0.CO;2
    [18] Wang X L, Hou X Y, Wang Y D. 2017. Spatiotemporal variations and regional differences of extreme precipitation events in the coastal area of China from 1961 to 2014 [J]. Atmos. Res., 197: 94−104. doi: 10.1016/j.atmosres.2017.06.022
    [19] 王志福, 钱永甫. 2009. 中国极端降水事件的频数和强度特征 [J]. 水科学进展, 20(1): 1−9. doi: 10.3321/j.issn:1001-6791.2009.01.001

    Wang Zhifu, QIAN Yongfu. 2009. Frequency and intensity of extreme precipitation events in China [J]. Advances in Water Science (in Chinese), 20(1): 1−9. doi: 10.3321/j.issn:1001-6791.2009.01.001
    [20] Wu B, Li T M, Zhou T J. 2010. Relative contributions of the Indian Ocean and local SST anomalies to the maintenance of the western North Pacific anomalous anticyclone during the El Niño decaying summer [J]. J. Climate, 23(11): 2974−2986. doi: 10.1175/2010JCLI3300.1
    [21] Wu Y K, Huang A Y, Wu C K, et al. 2020. Effect of warm SST in the subtropical eastern North Pacific on triggering the abrupt change of the Mei–Yu rainfall over South China in the early 1990s [J]. J. Climate, 33(2): 657−673. doi: 10.1175/JCLI-D-18-0292.1
    [22] Xiao C, Wu P L, Zhang L X, et al. 2016. Robust increase in extreme summer rainfall intensity during the past four decades observed in China [J]. Sci. Rep., 6: 38506. doi: 10.1038/srep38506
    [23] Xie S P, Hu K M, Hafner J, et al. 2009. Indian Ocean capacitor effect on Indo–western Pacific climate during the summer following El Niño [J]. J. Climate, 22(3): 730−747. doi: 10.1175/2008JCLI2544.1
    [24] 叶梦茜. 2021. 中国东部区域极端降水事件监测及低频特征分析 [D]. 南京信息工程大学硕士学位论文. Ye Mengxi. 2021. Monitoring and low frequency characteristics of extreme precipitation events in eastern China [D]. M. S. thesis (in Chinese), Nanjing University of Information Science and Technology.
    [25] Yu J H, Li T M, Tan Z M, et al. 2016. Effects of tropical North Atlantic SST on tropical cyclone genesis in the western North Pacific [J]. Climate Dyn., 46(3): 865−877. doi: 10.1007/s00382-015-2618-x
    [26] Zhai P M, Zhang X B, Wan H, et al. 2005. Trends in total precipitation and frequency of daily precipitation extremes over China [J]. J. Climate, 18(7): 1096−1108. doi: 10.1175/JCLI-3318.1
    [27] 赵炜. 2018. 基于聚类分析和 REID 方法的降水极端事件识别方法及其应用 [D]. 南京信息工程大学博士学位论文. Zhao Wei. 2018. Precipitation extreme event recognition method based on cluster analysis and REID Method and its Application [D]. Ph. D. dissertation (in Chinese), Nanjing University of Information Science and Technology.
    [28] 赵永晶, 钱永甫. 2009. 全球海温异常对中国降水异常的影响 [J]. 热带气象学报, 25(5): 561−570. doi: 10.3969/j.issn.1004-4965.2009.05.006

    Zhao Yongjing, Qian Yongfu. 2009. Analyses of the impacts of global SSTA on precipitation anomaly in China [J]. Journal of Tropical Meteorology (in Chinese), 25(5): 561−570. doi: 10.3969/j.issn.1004-4965.2009.05.006
    [29] 赵煜飞, 朱江. 2015. 近50年中国降水格点日值数据集精度及评估 [J]. 高原气象, 34(1): 50−58. Zhao Yufei, Zhu Jiang. 2015. Assessing quality of grid daily precipitation datasets in China in recent 50 years [J]. Plateau Meteorology (in Chinese), 34(1): 50–58. doi:10.7522/j.issn.1000-0534.2013.00141
  • 加载中
图(8) / 表(2)
计量
  • 文章访问数:  99
  • HTML全文浏览量:  18
  • PDF下载量:  36
  • 被引次数: 0
出版历程
  • 收稿日期:  2021-11-25
  • 录用日期:  2022-08-01
  • 网络出版日期:  2022-08-02
  • 刊出日期:  2022-11-24

目录

    /

    返回文章
    返回