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淮河流域夏季极端降水频次空间分布的客观分类及其形成机理

卢睿 朱志伟 李天明 潘晓 江叶艳 陆雅君

卢睿, 朱志伟, 李天明, 等. 2021. 淮河流域夏季极端降水频次空间分布的客观分类及其形成机理[J]. 大气科学, 45(6): 1−18 doi: 10.3878/j.issn.1006-9895.2105.20223
引用本文: 卢睿, 朱志伟, 李天明, 等. 2021. 淮河流域夏季极端降水频次空间分布的客观分类及其形成机理[J]. 大气科学, 45(6): 1−18 doi: 10.3878/j.issn.1006-9895.2105.20223
LU Rui, ZHU Zhiwei, LI Tim, et al. 2021. Objective Clustering of Spatial Patterns of Summer Extreme Precipitation Frequency over the Huaihe River Basin and Their Formation Mechanisms [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(6): 1−18 doi: 10.3878/j.issn.1006-9895.2105.20223
Citation: LU Rui, ZHU Zhiwei, LI Tim, et al. 2021. Objective Clustering of Spatial Patterns of Summer Extreme Precipitation Frequency over the Huaihe River Basin and Their Formation Mechanisms [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 45(6): 1−18 doi: 10.3878/j.issn.1006-9895.2105.20223

淮河流域夏季极端降水频次空间分布的客观分类及其形成机理

doi: 10.3878/j.issn.1006-9895.2105.20223
基金项目: 国家自然科学基金项目42088101,淮河流域气象开放研究基金项目HRM201801,江苏省研究生科研与实践创新计划项目KYCX20_0947
详细信息
    作者简介:

    卢睿,男,1994年生,硕士研究生,主要从事极端天气事件和海气相互作用研究。E-mail:ruilu@nuist.edu.cn

    通讯作者:

    朱志伟,E-mail: zwz@nuist.edu.cn

  • 中图分类号: P461

Objective Clustering of Spatial Patterns of Summer Extreme Precipitation Frequency over the Huaihe River Basin and Their Formation Mechanisms

Funds: National Natural Science Foundation of China (Grant 42088101), Huai-River Meteorological Founding (Grant HRM201801), Postgraduate Research & Practice Innovation Program of Jiangsu Province (Grant KYCX20_0947)
  • 摘要: 本文基于1961~2016年淮河流域四省(江苏、安徽、河南、山东)逐日降水观测资料及全球大气再分析资料,利用K均值聚类、旋转经验正交函数分解对淮河流域夏季极端降水频次分布进行了客观分类,利用统计诊断和数值模拟的手段讨论了其相关环流异常和形成机理。结果表明:(1)淮河流域夏季极端降水频次的空间分布可客观分为以极端降水主要发生在淮河流域33°N以南地区的南部型,主要发生在32°~36°N之间的中部型,和主要发生在34°N以北的北部型这三种分布类型;(2)南部型极端降水频次分布与西北太平洋副热带高压异常偏西偏南有关,西北太平洋异常反气旋北侧的异常气旋性环流使得水汽输送停留在淮河流域南部,导致南部极端降水频次偏多。中部型对应淮河流域受鞍型场环流结构控制,导致中部极端降水频次偏多。北部型极端降水频次分布时,淮河流域处于反气旋性环流异常西南侧,偏南风将水汽输送至淮河流域北部,导致北部极端降水频次偏多;(3)南部型和北部型的极端降水频次分布相关环流异常分别受厄尔尼诺和拉尼娜相关海表温度异常所影响,而中部型极端降水频次分布的相关环流异常是巴伦支海/喀拉海海冰异常在欧亚大陆上空激发的自西北向东南传播的准定常罗斯贝波所导致的。
  • 图  1  1961~2016年淮河流域夏季(a)降水气候态(单位:mm d−1)、(b)降水标准差(单位:mm d−1)、(c)90百分位的极端降水阈值(单位:mm d−1)、(d)极端降水量占总降水量的比值、(e)累计极端降水日数气候态(单位:d a−1)的空间分布,(f)区域平均的气候态旬累计极端降水日数(单位:d)。图a–e中绿色实线为河流分布,下同

    Figure  1.  Spatial distributions of (a) climatology (units: mm d−1), (b) standard deviation (units: mm d−1), (c) 90 percentile extreme precipitation threshold (units: mm d−1), (d) ratio of the extreme to the total precipitation, (e) climatological cumulative extreme precipitation days (units: d a−1), and (f) climatological area-mean dekadly cumulative extreme precipitation days (units: d) for the summer precipitation over the Huaihe River basin from 1961 to 2016. In Figs. a–e, the green solid lines represent the main river, the same below

    图  2  1961~2016年淮河流域夏季极端降水日数(a)在不同K值时进行K均值聚类的轮廓系数S,(b、c、d)K=3时聚类分析对应的极端降水频次异常的空间分布(单位:d a−1),(e)EOF分析的前10个EOF模态的解释方差,(f、g、h)旋转EOF分析的前三个模态。图b–d(f–h)中的红、蓝色方框表示绝对值大于1.5(1.0)的格点

    Figure  2.  (a) Silhouette coefficient for K-means cluster analysis with different K values, (b, c, d) spatial patterns of anomalous extreme precipitation days (units: d a−1) of the K-means cluster procedure with K=3, (e) variances of the top 10 empirical orthogonal function (EOF) modes, (f, g, h) the first three modes of rotated empirical orthogonal function analysis (REOF) of summer extreme precipitation days over the Huaihe River basin from 1961 to 2016. The red, blue boxes in Figs. b–d (f–h) represent the grids in which the absolute value exceeds 1.5 (1.0)

    图  3  计算(a)南部型、(b)中部型、(c)北部型极端降水频次指数时使用到的格点(红、蓝色方框,图2b–d分别与图2f–h中的同号格点合并后的区域),(d)各类型对应的极端降水频次指数

    Figure  3.  Grids [red (blue) boxes, the meaning of the boxes is the grids that merging the same sign grids in Figs. 2b–d and Figs. 2f–h, respectively] for calculating the extreme precipitation frequency index for (a) S-Type (rainfall extremes mainly appear southern region, south of 33°N), (b) C-Type (rainfall extremes mainly appear central region, between 32°–36°N), (c) N-Type (rainfall extremes mainly appear northern region, north of 34°N), (d) extreme precipitation frequency index for each type

    图  4  1961~2016年(a)500 hPa位势高度异常(红色实线、蓝色虚线表示正、负异常,单位:gpm)、风场异常(黑色矢量,单位:m s−1)、降水异常(填色,单位:mm d−1)回归至标准化的极端降水频次南部型指数,500 hPa位势高度气候态场(黑色粗实线,单位:gpm)。(b、c)同(a),但分别为中部型、北部型。打点区域为降水场回归系数通过90%信度水平的显著性检验的区域。字母A(C)代表反气旋(气旋)性环流中心,深绿色粗实线表示淮河流域,下同

    Figure  4.  (a) Regressed 500-hPa geopotential height anomalies (red solid lines and blue dashed lines represent positive and negative anomalies, respectively, units: gpm), wind anomalies (black vectors, units: m s−1), and precipitation anomalies (shadings, units: mm d−1) onto the standardized S-Type extreme precipitation frequency index from 1961 to 2016, the 500-hPa geopotential height climatology (black bold solid lines, units: gpm). (b, c) As in (a), but for the C-Type and N-Type, respectively. The dotted areas indicate the precipitation field passing significant test at the 90% confidence level. The letters “A” and “C” indicate the centers of anticyclonic and cyclonic anomalies, respectively, the bold green solid lines represent the Huaihe River basin, the same below

    图  5  1961~2016年各要素场回归至标准化的极端降水频次南部型指数:(a)200 hPa位势高度(单位:gpm)、风场(黑色矢量,单位:m s−1)、降水(填色,单位:mm d−1);(b)500 hPa位势高度(单位:gpm)、风场(黑色矢量,单位:m s−1)、波活动通量(橙色矢量,单位:m2 s−2);(c)850 hPa位势高度(单位:gpm)、风场(黑色矢量,单位:m s−1)、海表面温度(填色,单位:°C)。红色实线、蓝色虚线和黑色实线表示位势高度回归系数正、负值和零线,图a(c)中打点区域为降水场(海温场)回归系数通过90%信度水平的显著性检验的区域。图c中灰色阴影区域为青藏高原地区,红色粗虚线区域为海温关键区

    Figure  5.  Regressed onto the standardized S-Type extreme precipitation frequency index from 1961 to 2016: (a) 200-hPa geopotential height (units: gpm), wind (black vectors, units: m s−1), and precipitation (shadings, units: mm d−1); (b) 500-hPa geopotential height (units: gpm), wind (black vectors, units: m s−1), and wave activity fluxes (orange vectors, units: m2 s−2); (c) 850-hPa geopotential height (units: gpm), wind (black vectors, units: m s−1), and SST (shadings, units: °C). The red solid lines, blue dashed lines, and black lines represent positive, negative regression coefficients for geopotential height, and zero lines, respectively. In Fig. a (c), the dotted areas are the precipitation (SST) passing significant test at 90% confidence level. In Fig. c, the gray shading indicates the Qinghai Tibet Plateau, the areas enclosed by red bold dashed lines represent the key region of the SST

    图  6  图5,但为中部型

    Figure  6.  As in Fig.5, but for the C-Type

    图  7  1979~2016年海冰密集度(填色)回归至标准化的极端降水频次中部型指数。打点区域为通过90%信度水平的显著性检验的区域,红色粗虚线区域为海冰关键区

    Figure  7.  Regressed sea ice area fraction (shadings) onto the standardized C-Type extreme precipitation frequency index from 1979 to 2016. Dotted areas pass significant test at the 90% confidence level. The areas enclosed by the red bold dashed lines represent the key region of the sea ice area fraction

    图  8  同图5,但为北部型

    Figure  8.  As in Fig.5, but for the N-Type

    图  9  1961~2016年(a)标准化的极端降水频次南部型指数与IOSI、EPSI的散点图;(b)标准化的极端降水频次中部型指数与ARSI散点图;(c)标准化的极端降水频次北部型指数与IOSI、EPSI的散点图。图例括号内数字为相关系数,“*”/“**”表示相关系数通过90%/95%信度水平的显著性检验

    Figure  9.  Scatter diagrams for (a) the standardized S-Type extreme precipitation frequency index (SSEPFI) and IOSI (Indian Ocean Sea surface temperature Index), EPSI (East Pacific Sea surface temperature Index), (b) the standardized C-Type extreme precipitation frequency index (SCEPFI) and ARSI (Arctic Sea ice Index), (c) the standardized N-Type extreme precipitation frequency index (SNEPFI) and IOSI, EPSI from 1961 to 2016. The correlation coefficients are shown in brackets. The symbols “*”/“**” indicate that the correlation coefficients are statistically significant at the 90%/95% confidence level

    图  10  各要素场对数值模式外强迫场的响应:(a)200 hPa位势高度异常(单位:gpm)、风场异常(黑色矢量,单位:m s−1)、降水异常(填色,单位:mm d−1);(b)500 hPa位势高度异常(单位:gpm)、风场异常(黑色矢量,单位:m s−1)、波活动通量异常(橙色矢量,单位:m2 s−2);(c)850 hPa位势高度异常(单位:gpm)、风场异常(黑色矢量,单位:m s−1)。红色实线、蓝色虚线、黑色实线表示位势高度正、负异常和零线,图c中填色场为数值模式中给定的海表面温度异常场(单位:°C)

    Figure  10.  Each meteorological element fields response to the forcing in the model: (a) 200-hPa geopotential height anomalies (units: gpm), wind anomalies (black vectors, units: m s−1), and precipitation anomalies (shadings, units: mm d−1); (b) 500-hPa geopotential height anomalies (units: gpm), wind anomalies (black vectors, units: m s−1), and wave activity fluxes anomalies (orange vectors, units: m2 s−2); (c) 850-hPa geopotential height anomalies (units: gpm) and wind anomalies (black vectors, units: m s−1). The red solid lines, blue dashed lines, and black lines represent positive and negative geopotential height anomalies, zero lines, respectively. In Fig. c, shadings represent SST anomalies (units: °C) adding in the model

    图  11  图10,但为数值模式对图11c中大气冷源(70°~85°N,0°~80°E)异常场(填色,单位:K d−1)的响应

    Figure  11.  As in Fig. 10, but for the response for the diabatic cooling source (70°–85°N,0°–80°E) anomalies (shadings, units: K d−1) in the atmosphere in Fig. 11c

    图  12  同图10,但为数值模式对图12c中海表面温度异常场(填色,单位:°C)的响应

    Figure  12.  As in Fig. 10, but for the response for the SST anomalies (shadings, units: °C) forcing in Fig. 12c

    图  13  极端降水频次(a)南部型、(b)中部型和(c)北部型空间分布的物理机制示意图。蓝色/红色阴影区域的海冰/海温异常(颜色深浅代表相对强度的强弱)代表与该类型相关的外强迫因子的分布

    Figure  13.  Schematic of the physical processes associated with the (a) S-Type, (b) C-Type, and (c) N-Type. The sea ice/sea surface temperature anomalies [dark (light) shadings represent strong (weak) relative intensity] over blue/red shading area indicates the external forcing for each type

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    doi: 10.14188/j.1671-8836.2016.04.013
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  • 收稿日期:  2020-11-04
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