Contribution of Atmospheric Rivers to Precipitation and Precipitation Extremes in East Asia: Diagnosis with Moisture Flux Convergence

东亚地区大气河对降水和极端降水的贡献:基于水汽通量散度的诊断分析

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  • Corresponding author: Xuejuan REN, renxuej@nju.edu.cn
  • Funds:

    Supported by the National Key Research and Development Program of China (2018YFC1505903) and National Natural Science Foundation of China (41621005)

  • doi: 10.1007/s13351-021-1066-2

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  • Atmospheric rivers (ARs), the long and narrow conveyors of intense moisture transport, have a non-negligible impact on hydrometeorological events over the extratropical regions. This study analyzes the climatology and interannual variability of ARs and their quantitative association with precipitation and precipitation extremes over East Asia (EA) during 1979–2019, based on calculations of not only moisture transport but also moisture flux convergence. It is found that the ARs over EA occur frequently in spring and summer, accounting for 25%–40% of seasonal precipitation and 60%–75% of extreme precipitation over EA. Increases in AR frequency are observed over EA during post-El Niño summers, meanwhile the AR-related anomalous moisture convergence is found leading to the increase of extreme precipitation. Specifically, increased ARs account for 70%–90% of total precipitation anomalies and up to 90% of extreme precipitation anomalies over the middle–lower reaches of the Yangtze River, and the anomalies of moisture flux convergence are caused mainly by changes in horizontal wind convergence rather than moisture advection during the post-El Niño summers.
    大气河是对流层中狭长的强水汽输送带,对热带外地区的水文气候事件有着重要的影响。基于水汽输送和水汽通量散度,本文分析了 1979–2019 年间东亚地区大气河的气候特征和年际变率及其对降水的影响。东亚地区的大气河主要发生在春夏季,大气河贡献了东亚地区春夏季25%–40%的总降水和 60%–75% 的极端降水。厄尔尼诺事件衰减年夏季东亚地区大气河明显增强。长江中下游以及中国北方70%–90%的降水异常和90%以上的极端降水异常与大气河的增强有关。大气河输送的水汽异常辐合导致了极端降水的增加,其中水汽通量的异常辐合主要由水平风场的异常辐合决定。
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  • Fig. 1.  Example of an AR affects the heavy rainfall in Beijing, China on 20 July 2016. Red and blue contours represent the AR boundary and 5880-gpm line at 500 hPa, respectively. Black and purple vectors indicate vertically integrated vapor transport (IVT; kg m−1 s−1) and horizontal wind (m s−1) at 200 hPa, respectively. Only values exceeding 200 kg m−1 s−1 are shown for IVT. Green shading represents precipitation (mm day−1). Orange diamond indicates a region of North China.

    Fig. 2.  Climatological AR frequency (%) during (a) spring (MAM), (b) summer (JJA), (c) autumn (SON), and (d) winter (DJF) for 1979–2019. The thin (thick) red contour in (a–d) indicates climatological seasonal AR frequency of 4% (8%) (the same below).

    Fig. 3.  Time–latitude diagram of seasonal variation of monthly-mean AR frequency averaged over 100°–130°E during 1979–2019.

    Fig. 4.  Climatological accumulated precipitation (mm season−1) during (a) spring, (b) summer, (c) autumn, and (d) winter for 1979–2019. (e)–(h) As in (a)–(d), but for AR-group. (i) Ratio of (e) to (a), (j) ratio of (f) to (b), (k) ratio of (g) to (c), and (l) ratio of (h) to (d).

    Fig. 5.  As in Fig. 4, but for climatological accumulated precipitation (mm season−1) of 2-day EPEs.

    Fig. 6.  As in Fig. 5, but for FIVT (vector; 105 kg m−1 season−1) and $\nabla \cdot {{\boldsymbol{F}}_{\rm IVT}}$ (shading; mm season−1) of 2-day EPEs during 1979–2019. Only values exceeding 5 × 106 kg m−1 season−1 are shown for FIVT. The core region (26°–38°N, 112°–121°E) is indicated by black boxes in (i–l).

    Fig. 7.  Bar charts denoting regional area-averaged seasonal accumulated terms of $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}}$ (term T; cyan bars), $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $_A (term A; red bars), $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}}$_B (term B; purple bars), and $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $_C (term C; orange bars) in AR-EPE days in the black boxes of Figs. 6il.

    Fig. 8.  Composite anomalies of AR frequency (%) during nine El Niño events in 1979–2019 for (a) autumn, (b) winter, (c) spring, and (d) summer. Symbols (0) and (1) stand for El Niño years and post-El Niño years, respectively. The thin (thick) blue contour in (a–d) indicates climatological AR frequency of 4% (8%). The left (/) and right (\) oblique lines indicate regions with anomalies statistically significant at the 95% and 90% levels of $t$ test, respectively.

    Fig. 9.  (a) Composite anomalies in summer accumulated precipitation (mm summer−1) during the nine post-El Niño summers. (b) As in (a), but for AR-group. (c) Ratio of (b) to (a). The blue contour in (b–c) indicates climatological AR frequency of 8%. The left (/) and right (\) oblique lines indicate regions with anomalies statically significant at the 95% and 90% levels of $t$ test, respectively.

    Fig. 10.  As in Figs. 9a and 9b, but for FIVT (vector; 105 kg m−1 summer−1) and $ \nabla \cdot {{\boldsymbol{F}}_{\rm IVT}}$ (shading; mm summer−1). The right oblique lines and vectors indicate anomalies statistically significant at the 90% level of t test.

    Fig. 11.  As in Fig. 9, but for accumulated precipitation (mm summer−1) of 2-day EPEs.

    Fig. 12.  As in Fig. 10, but for FIVT (vector; 105 kg m−1 summer−1) and $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $ (shading; mm summer−1) of 2-day EPEs. The red boxes in (b) denote two core regions, which are located over the lower reaches of the Yangtze River basin (26°–34°N, 114°–121°E; region 1) and northern China (36°–44°N, 110°–130°E; region 2), respectively.

    Fig. 13.  As in Fig. 7, but for anomalous values over two regions during post-El Niño summers.

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Contribution of Atmospheric Rivers to Precipitation and Precipitation Extremes in East Asia: Diagnosis with Moisture Flux Convergence

    Corresponding author: Xuejuan REN, renxuej@nju.edu.cn
  • CMA–NJU Joint Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing 210023
Funds: Supported by the National Key Research and Development Program of China (2018YFC1505903) and National Natural Science Foundation of China (41621005)

Abstract: Atmospheric rivers (ARs), the long and narrow conveyors of intense moisture transport, have a non-negligible impact on hydrometeorological events over the extratropical regions. This study analyzes the climatology and interannual variability of ARs and their quantitative association with precipitation and precipitation extremes over East Asia (EA) during 1979–2019, based on calculations of not only moisture transport but also moisture flux convergence. It is found that the ARs over EA occur frequently in spring and summer, accounting for 25%–40% of seasonal precipitation and 60%–75% of extreme precipitation over EA. Increases in AR frequency are observed over EA during post-El Niño summers, meanwhile the AR-related anomalous moisture convergence is found leading to the increase of extreme precipitation. Specifically, increased ARs account for 70%–90% of total precipitation anomalies and up to 90% of extreme precipitation anomalies over the middle–lower reaches of the Yangtze River, and the anomalies of moisture flux convergence are caused mainly by changes in horizontal wind convergence rather than moisture advection during the post-El Niño summers.

东亚地区大气河对降水和极端降水的贡献:基于水汽通量散度的诊断分析

大气河是对流层中狭长的强水汽输送带,对热带外地区的水文气候事件有着重要的影响。基于水汽输送和水汽通量散度,本文分析了 1979–2019 年间东亚地区大气河的气候特征和年际变率及其对降水的影响。东亚地区的大气河主要发生在春夏季,大气河贡献了东亚地区春夏季25%–40%的总降水和 60%–75% 的极端降水。厄尔尼诺事件衰减年夏季东亚地区大气河明显增强。长江中下游以及中国北方70%–90%的降水异常和90%以上的极端降水异常与大气河的增强有关。大气河输送的水汽异常辐合导致了极端降水的增加,其中水汽通量的异常辐合主要由水平风场的异常辐合决定。
1.   Introduction
  • Atmospheric rivers (ARs) are unique filaments of intense moisture transport. They carry abundant water vapor from the low latitudes to mid–high latitudes (Zhu and Newell, 1998; Dettinger et al., 2011; Guan and Waliser, 2015; Liu et al., 2016; Ralph et al., 2020). Because of their copious moisture fluxes, ARs have substantial impacts on surface hydrology including changes of precipitation and runoff over the extratropical regions (Ralph et al., 2006; Neiman et al., 2008; Paltan et al., 2017; Ramos et al., 2018). In recent years, a series of studies have investigated the unique features of ARs and their roles in hydrology (Neiman et al., 2008; Lavers and Villarini, 2015; Waliser and Guan, 2017; Ridder et al., 2018; Xiong et al., 2019). ARs over the midlatitude ocean basins and coastal regions have received much attention. Previous studies reported that ARs appear most frequently over North Pacific and along the US west coast in winter (Guan and Waliser, 2015; Zavadoff and Kirtman, 2020). ARs are found responsible for 30%–50% of total precipitation as well as the majority of precipitation extremes along the US west coast during winters (Lavers and Villarini, 2015; Slinskey et al., 2020; Xiong and Ren, 2021).

    East Asia (EA) is one of the regions with fairly high population density in the world, where human life and social development are affected by water vapor transport and associated hydrological extremes. Several studies on the climatological characteristics of ARs and their hydrological influences over EA have been conducted (Mundhenk et al., 2016; Pan and Lu, 2019; Chen et al., 2020; Liang et al., 2020; Wu et al., 2020). ARs exhibit obvious seasonal variations over EA (Kamae et al., 2017b). They appear mostly over eastern China, the Korean Peninsula, and Japan in spring and summer, with less occurrence in autumn and winter. It has been revealed that ARs have non-negligible influences on precipitation, especially the extreme precipitation over EA (Guan and Waliser, 2015; Kamae et al., 2017a; Park et al., 2021). About 30%–60% of the annual-mean precipitation over EA is related to ARs (Kim et al., 2020). ARs contribute up to 30%–45% of precipitation over eastern China, the Korean Peninsula, and Japan in spring and summer, while their contributions are smaller in autumn and winter (Liang and Yong, 2021). Previous studies have pointed out that ARs have a larger impact on extreme precipitation than total precipitation (Kamae et al., 2017a; Pan and Lu, 2020). For instance, ARs account for up to 60% of extreme precipitation in summer over EA (Liang and Yong, 2021).

    Figure 1 displays an example of AR causing heavy rainfall on 20 July 2016. This event lasted for a long time and many stations in Beijing received record-breaking daily precipitation. In this heavy rainfall event, the westward stretch of the western North Pacific subtropical high (WNPSH) and the topographic obstruction of the Tibetan Plateau are conducive to forming enhanced southwesterly moisture transport, which is detected as an AR. The convergence of copious water vapor transported by the AR is a vital factor in forming the heavy rainfall. In fact, precipitation is directly decided by the convergence/divergence of moisture, not by the transport/flux of moisture, as indicated by the atmospheric water vapor budget equation. Hence, the moisture flux convergence/divergence is an important variable that can be used to demonstrate ARs’ association to precipitation and extreme precipitation. It is meaningful to identify ARs’ quantitative contribution from the perspective of both moisture transport and moisture flux convergence during extreme precipitation events.

    Figure 1.  Example of an AR affects the heavy rainfall in Beijing, China on 20 July 2016. Red and blue contours represent the AR boundary and 5880-gpm line at 500 hPa, respectively. Black and purple vectors indicate vertically integrated vapor transport (IVT; kg m−1 s−1) and horizontal wind (m s−1) at 200 hPa, respectively. Only values exceeding 200 kg m−1 s−1 are shown for IVT. Green shading represents precipitation (mm day−1). Orange diamond indicates a region of North China.

    ARs over EA show significant variability on the interannual timescale, of which the El Niño–Southern Oscillation (ENSO) may be an important cause (Mundhenk et al., 2016; Kamae et al., 2017b; Naoi et al., 2020; Wu et al., 2020). Previous studies reveal that above-normal rainfall takes place over south of the Yangtze River valley and north of the Yellow River during post-El Niño summers (Huang and Wu, 1989; Xie et al., 2009; Zhang et al., 2016; Yu and Zhai, 2018). There is a low-level anticyclonic anomaly over the western North Pacific. Enhanced northeastward water vapor transport occurs over the northwestern flank of the anticyclonic circulation (Zhang et al., 1996; Chang et al., 2000; Kosaka et al., 2011; Zhou et al., 2014). As a result, copious water vapor is transported to EA and related anomalous convergence is favorable to occurrence of rainfall. In fact, the enhanced northeastward water vapor transport leads to increases in ARs over EA (Kamae et al., 2017b; Naoi et al., 2020). Our study focuses on examining the role of ARs in precipitation anomaly via analyzing anomalies of moisture flux convergence/divergence in addition to water vapor transport for AR-related seasonal precipitation and extreme precipitation events. Moreover, the relative importance of wind divergence and moisture advection, which are the two components of moisture flux convergence, is also evaluated.

    The rest of the paper is structured as follows. Section 2 describes the data and methods. Section 3 shows the climatology of ARs in association with precipitation over EA. The related moisture transport and convergence/divergence are also analyzed. Section 4 evaluates interannual variations of ARs and their impact on precipitation anomalies. Relative importance of wind divergence and moisture advection in extreme precipitation events is discussed in Sections 3 and 4. A summary is provided in Section 5.

2.   Data and methods
  • The datasets used include the following: (1) daily gridded precipitation on 0.5° × 0.5° horizontal resolution from 1 January 1979 to 31 December 2019, obtained from the U.S. Climate Prediction Center (CPC) unified precipitation project (Chen et al., 2008); (2) daily speci-fic humidity, zonal and meridional winds on 0.75° × 0.75° horizontal resolution from 1 January 1979 to 31 August 2019, from the ECMWF interim reanalysis (ERA-Interim; Dee et al., 2011); and (3) monthly Niño3.4 index from CPC. El Niño events are identified when the Niño3.4 index is no less than 1°C and persists for three months. Based on the above criteria, we selected nine El Niño events (1982/1983, 1986/1987, 1987/1988, 1991/1992, 1994/1995, 1997/1998, 2002/2003, 2009/2010, and 2015/2016) from 1979 to 2019. In this study, the spring (March–May, MAM), summer (June–August, JJA), autumn (September–November, SON), and winter (December–February, DJF) seasons are considered separately.

  • The integrated water vapor transport ($ \mathrm{I}\mathrm{V}\mathrm{T} $) is defined and calculated as below:

    $$ {\boldsymbol{F}}_{\rm{IVT}} = \frac{1}{g}\int _{{p_{\rm{t}}}}^{{p_{\rm{s}}}}q{\boldsymbol{V}}{\rm{d}}p, $$ (1)

    where $ g $ is the acceleration due to gravity, $ q $ is the speci-fic humidity, $ {p}_{\rm{s}} $ is the surface pressure, $ {p}_{\rm{t}} $ is set to be 300 hPa, and $ \boldsymbol{V} $ is the horizontal wind vector $ (u,v) $.

    We perform AR detections based on Guan and Waliser (2015). The first step is to compute the threshold of IVT at each grid. For each month, the 85th percentile threshold of IVT is calculated within five-continuous months centered on that month. The greater value of the 85th threshold and 100 kg m−1 s−1 are used to obtain contiguous regions. The second step is to consider the requirements on IVT direction. The purpose is to make sure that most of the AR grids’ IVT has similar direction. The third step is to ascertain the geometry of the regions. Those regions with a length > 2000 km or a large ratio of length to width > 2 are retained as AR regions. More details of the detection method can be found in Guan and Waliser (2015). If a grid point is in the detected AR region, this grid is defined as an AR grid, and the corresponding day is recorded as an AR day for this grid. The frequency of AR occurrence for a grid in each season is calculated as the ratio of the number of AR days to the number of total days in each season. The variables [precipitation, IVT, and divergence of IVT (i.e., $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}}) $] at the AR grids in the AR days belong to an AR-group. In each season, all variables (precipitation, IVT, and $\nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $) for the AR-group are individually summed up, in order to obtain the corresponding seasonal cumulation.

  • The moisture flux divergence $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $ can be decomposed as follows:

    $$\begin{aligned} \underbrace {\nabla \cdot \frac{1}{g}\int_{{p_{\rm{t}}}}^{{p_{\rm{s}}}} q{\boldsymbol{V}}{\rm{d}}p{\rm{}}}_{\rm{T}} = & \underbrace {\frac{1}{g}\int_{{p_{\rm{t}}}}^{{p_{\rm{s}}}} q ({\frac{{\partial u}}{{\partial x}} + \frac{{\partial v}}{{\partial y}}} ){\rm{d}}p}_{\rm{A}} + \underbrace {\frac{1}{g}\int_{{p_{\rm{t}}}}^{{p_{\rm{s}}}} u\frac{{\partial q}}{{\partial x}}{\rm{d}}p}_{\rm{B}} \\ & + \underbrace {\frac{1}{g}\int_{{p_{\rm{t}}}}^{{p_{\rm{s}}}} v\frac{{\partial q}}{{\partial y}}{\rm{d}}p}_{\rm{C}},\\[-15pt] \end{aligned}$$ (2)

    where the term A (horizontal wind divergence), term B (zonal moisture advection), and term C (meridional moisture advection) contribute to the term T ($ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $).

  • At each grid, we rank the daily precipitation of wet day (daily precipitation > 1 mm) from small to large for each season during 1979–2019. The statistical 95th percentile is used as the threshold for extreme precipitation (Hagos et al., 2016; Dong et al., 2018). The definition of a 2-day extreme precipitation event (2-day EPE) is as follows. First, the days with daily precipitation amount exceeding the 95th threshold are marked as extreme days. Then, we compare precipitation amounts on the day before and after the marked day, and the day with larger precipitation amount is selected. A 2-day EPE covers the marked day and the day with a larger precipitation amount. The days of all 2-day EPE are identified as 2-day EPE days (Shang et al., 2020; Xiong and Ren, 2021). If a 2-day EPE is accompanied with an AR (at least one day is an AR day), it is defined as an AR-EPE and the days for this EPE are AR-EPE days. We also sum up all variables (precipitation, IVT, and $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $) on 2-day EPE days and AR-EPE days for each season, respectively.

3.   Climatology of ARs in association with precipitation
  • Figure 2 shows climatological AR frequency over EA in four seasons during 1979–2019. ARs occur more frequently in spring and summer than in autumn and winter, which are broadly consistent with previous works (Guan and Waliser, 2015; Kim et al., 2020; Pan and Lu, 2020; Liang and Yong, 2021). In spring, the large value of AR frequency of 8%–12% (equal to 7–11 days) is observed over southeastern China, while the band with AR frequency of 4%–8% (3–7 days) appears over the lower reaches of the Yellow River basin and the Korean Peninsula (Fig. 2a). In summer, ARs’ main body with frequency of 8%–13% extends northward to northern China and northeastern China (Fig. 2b). In autumn, the AR band retreats eastward to the western Pacific, and AR frequency is about 4% (3–4 days) over southwestern China and Japan (Fig. 2c). AR frequency of 8% or above is seen over the western Pacific during winter (Fig. 2d). An AR band with frequency of 4%–7% in winter shifts westward and resides over southeastern China and Japan.

    Figure 2.  Climatological AR frequency (%) during (a) spring (MAM), (b) summer (JJA), (c) autumn (SON), and (d) winter (DJF) for 1979–2019. The thin (thick) red contour in (a–d) indicates climatological seasonal AR frequency of 4% (8%) (the same below).

    Next, seasonal variations of AR frequency over EA are examined. The region of 20°–50°N, 100°–150°E is often selected in studies of ARs over EA (Kamae et al., 2017a; Kim et al., 2020; Liang and Yong, 2021). Monthly-mean AR frequency is averaged over 100°–130°E in Fig. 3. AR frequency of 10%–11% (about 2–3 days) per month occurs over 23°–28°N during March–May. In June, AR frequency increases to 14%–16% (3–4 days) per month. From June to August, the AR band jumps northward to 32°–40°N. Extensive weakening of ARs starts in September, and the ARs enter their yearly weakest stage (September–October) with frequency of 1–2 days per month over 23°–28°N. A modest increase of ARs occurs in November, and then AR frequency is stable at 4%–9% (1–3 days) per month from December to February.

    Figure 3.  Time–latitude diagram of seasonal variation of monthly-mean AR frequency averaged over 100°–130°E during 1979–2019.

    Distributions of seasonal precipitation and the corresponding precipitation for AR-group over EA in four seasons are shown in the first and second rows of panels in Fig. 4. The third row of panels in Fig. 4 displays the ratio of precipitation for AR-group to the total precipitation, indicating the contribution of ARs. Climatological spring precipitation and the spring precipitation for AR-group are both large in southeastern China and southern Japan, which are more than 300 and 100 mm spring−1, respectively (Figs. 4a, e). ARs contribute 20%–35% of spring precipitation over the Yangtze–Huaihe River basin (Fig. 4i), where AR frequency is 5%–10% (Fig. 2a). During summer, the total precipitation and that for AR-group are enhanced over the Yangtze River basin, northern China, the Korean Peninsula, and Japan (Figs. 4b, f). A large fraction (30% or above) of summer precipitation for AR-group is observed over these regions (Fig. 4j). In this study, 20%–40% of seasonal accumulated precipitation over EA in spring and summer is related to ARs, which is close to the result obtained by Liang and Yong (2021).

    Figure 4.  Climatological accumulated precipitation (mm season−1) during (a) spring, (b) summer, (c) autumn, and (d) winter for 1979–2019. (e)–(h) As in (a)–(d), but for AR-group. (i) Ratio of (e) to (a), (j) ratio of (f) to (b), (k) ratio of (g) to (c), and (l) ratio of (h) to (d).

    During autumn, the total precipitation and the precipitation for AR-group decrease (Figs. 4c, g). AR frequency is 2%–3% over the Yangtze–Huaihe River basin, where 20%–25% of accumulated precipitation is attributed to ARs (25% of autumn precipitation is attributed to ARs (Fig. 4k). In winter, the total precipitation and the precipitation for AR-group are large in southeastern China and Japan, which are more than 200 and 50 mm winter−1, respectively (Figs. 4d, h). ARs determine nearly 20%–35% of winter precipitation over southern China and the middle and lower reaches of the Yangtze River basin, where AR frequency is 4%–7% (Fig. 2d). However, ARs only lead to up to 4%–12% (less than 4%) of the total precipitation over southeastern China in autumn (winter) in Liang and Yong (2021).

    The impact of ARs on extreme precipitation is shown in Fig. 5. The upper and second row of panels in Fig. 5 depict seasonal precipitation of 2-day EPEs and the corresponding extreme precipitation for AR-group, respectively. The third row of panels is the fraction for AR-group. The patterns of seasonal accumulated extreme precipitation (Figs. 5ad) coincide well with those of total precipitation (Figs. 4ad). The patterns of precipitation for AR-group (Figs. 5eh) closely resemble those in Figs. 4eh. The AR fractions of seasonal extreme precipitation (Figs. 5il) are larger than those of total precipitation (Figs. 4il). ARs’ contribution (60%–75% of extreme precipitation during spring and summer) is robust over eastern China, northern China, the Korean Peninsula, and southern Japan. The AR fraction of 50%–60% is seen over the lower reaches of the Yellow River in autumn. During winter, about 60%–75% of extreme precipitation is related to ARs over southern China, the Korean Peninsula, and southern Japan. The above results indicate that ARs have a larger impact on extreme precipitation than on total precipitation over EA, which is consistent with the result in Liang and Yong (2021). The contribution of ARs to extreme precipitation during autumn and winter in this study is also larger than that in Liang and Yong (2021). The discrepancy may arise from different AR detection procedure and different definition of AR-related precipitation used in their study.

    Figure 5.  As in Fig. 4, but for climatological accumulated precipitation (mm season−1) of 2-day EPEs.

    The above results demonstrate that ARs have a large impact on extreme precipitation over EA. Thus, it is interesting to further analyze water vapor transports and their convergence when 2-day EPEs occur. Climatologi-cal seasonal accumulated IVT and $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ for 2-day EPEs during 1979–2019 are provided in the upper panels of Fig. 6. At each grid, IVT and $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ on 2-day EPE days are summed up for each season. Similarly, IVT and $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ on AR-EPE days are also summed up at each grid for each season (second row of panels in Fig. 6). The third row of panels shows the fraction of $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ for AR-group to total $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $. An enhanced northeastward IVT during 2-day EPEs appears over EA in spring and summer (Figs. 6a, b). The northeastward IVT in 2-day EPEs is weaker over southwestern China in autumn, while the IVT in 2-day EPEs only occurs over southern China in winter (Figs. 6c, d). It is noted that IVTs at each grid and adjacent grids are spatially discontinuous. Simi-lar direction of IVTs indicates that the direction of IVT is northeastward at each grid point over EA when 2-day EPE occurs. Seasonal variations of IVT in 2-day EPEs may be influenced by the WNPSH. The AR-related IVT is stronger over regions of high AR frequency than over other regions (Figs. 6eh) because ARs are intensive horizontal moisture conveyors. The northeastward IVT for AR-group is also strong over EA in spring and summer, while it becomes weaker in winter and the weakest in autumn. The above results indicate that the distribution of ARs’ moisture transport varies seasonally, in broad consistency with the seasonal variations of ARs.

    Figure 6.  As in Fig. 5, but for FIVT (vector; 105 kg m−1 season−1) and $\nabla \cdot {{\boldsymbol{F}}_{\rm IVT}}$ (shading; mm season−1) of 2-day EPEs during 1979–2019. Only values exceeding 5 × 106 kg m−1 season−1 are shown for FIVT. The core region (26°–38°N, 112°–121°E) is indicated by black boxes in (i–l).

    The related $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ for 2-day EPEs displays a large sink of moisture over EA, which is directly conducive to local extreme precipitation (Figs. 5ad). In spring, nearly 70%–80% of total moisture convergence for 2-day EPEs is related to ARs over the lower reaches of the Yellow River and the Korean Peninsula (Fig. 6i). ARs contribute 60%–80% of moisture convergence for 2-day EPEs over eastern China, northern China, the Korean Peninsula, and southern Japan during summer (Fig. 6j). In autumn, AR fraction of 60%–70% is seen over the lower reaches of the Yellow River and Japan (Fig. 6k). ARs account for 70%–80% of moisture convergence for 2-day EPEs over the lower reaches of the Yangtze River and southern Korea during winter. The patterns of ARs fraction for moisture convergence are almost the same as those for extreme precipitation. These results demonstrate that extreme precipitation is greatly affected by AR-generated in-situ moisture convergence.

    Above analysis indicates that AR-produced convergence is vital to formation of extreme precipitation over EA, especially over eastern China. Thus, we now examine the core region (black box in Figs. 6il) of the ARs’ influence. To compare the role of different processes responsible for $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $, terms A (horizontal wind divergence), B (zonal moisture advection), and C (meridional moisture advection) are calculated based on Eq. (2). The results over the core region are depicted in Fig. 7. $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ is large in spring and summer, which is consistent with the results in Fig. 6. It is noted that AR-produced convergence is mainly determined by horizontal wind convergence in Fig. 7. Because of the difference in water vapor distribution between land and sea in summer/winter, the zonal gradient of specific humidity is opposite, which results in the positive/negative contribution of term B in summer/winter. In addition, the contribution of term C is the largest in winter. The reason may be that the maximum region of southerly wind is exactly corresponding to that of meridional gradient of specific humidity for AR-group in winter (figure omitted).

    Figure 7.  Bar charts denoting regional area-averaged seasonal accumulated terms of $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}}$ (term T; cyan bars), $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $_A (term A; red bars), $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}}$_B (term B; purple bars), and $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $_C (term C; orange bars) in AR-EPE days in the black boxes of Figs. 6il.

4.   Interannual variations of ARs and impact on precipitation
  • Figure 8 depicts composite anomalies of AR frequency for the nine El Niño events identified in Section 2.1. ARs decrease over the Yellow River basin in El Niño autumns (Fig. 8a). ARs do not show any significant change over EA, but increase over the western Pacific during El Niño winters (Fig. 8b). The increases of ARs occur over northeastern China, Japan, and the South China Sea during post-El Niño springs (Fig. 8c). During post-El Niño summers, ARs obviously increase by 2%–3% over eastern China and northeastern China, and by 3%–4% over the western Pacific (Fig. 8d). Thus, we focus on examining the impact of ARs on accumulated and extreme precipitation over EA during post-El Niño summers in this section.

    Figure 8.  Composite anomalies of AR frequency (%) during nine El Niño events in 1979–2019 for (a) autumn, (b) winter, (c) spring, and (d) summer. Symbols (0) and (1) stand for El Niño years and post-El Niño years, respectively. The thin (thick) blue contour in (a–d) indicates climatological AR frequency of 4% (8%). The left (/) and right (\) oblique lines indicate regions with anomalies statistically significant at the 95% and 90% levels of $t$ test, respectively.

    Figure 9 shows the composite anomalies of precipitation in the nine after-El Niño summers. Total precipitation increases over the Yangtze River basin, northern China, and northeastern China (Fig. 9a). Figure 9b depicts the composite of precipitation anomalies for AR-group. There are two centers with positive anomalies in precipitation for AR-group over EA, with one over the lower reach of the Yangtze River valley and the other over northern China. The anomalies in precipitation of AR-group account for nearly 90% and 70% of the positive total precipitation anomalies over eastern China and northern China, respectively (Fig. 9c).

    Figure 9.  (a) Composite anomalies in summer accumulated precipitation (mm summer−1) during the nine post-El Niño summers. (b) As in (a), but for AR-group. (c) Ratio of (b) to (a). The blue contour in (b–c) indicates climatological AR frequency of 8%. The left (/) and right (\) oblique lines indicate regions with anomalies statically significant at the 95% and 90% levels of $t$ test, respectively.

    The composite anomalies of IVT and $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}}$ during the nine post-El Niño summers are shown in Fig. 10. Anomalous northeastward moisture transport is observed over EA, while anomalous moisture convergence occurs over the Yangtze River basin, northern China, and northeastern China (Fig. 10a). Above anomalous moisture convergence leads to the increase in precipitation (Fig. 9a). The increases of ARs over eastern China and northeastern China (Fig. 8d) lead to enhanced southwesterly moisture transport for AR-group over the two regions (Fig. 10b). Anomalous moisture transport converges over the south of the Yangtze River and northern China, contributing to the anomalies of local precipitation (Fig. 9b).

    Figure 10.  As in Figs. 9a and 9b, but for FIVT (vector; 105 kg m−1 summer−1) and $ \nabla \cdot {{\boldsymbol{F}}_{\rm IVT}}$ (shading; mm summer−1). The right oblique lines and vectors indicate anomalies statistically significant at the 90% level of t test.

    El Niño also affects extreme precipitation over EA. Composite anomalies in accumulated precipitation and precipitation for AR-EPEs are shown in Fig. 11. The pattern of extreme precipitation anomalies (Figs. 11a, b) resembles that of the accumulated precipitation anomalies (Figs. 9a, b). During post-El Niño summers, total precipitation and precipitation for AR-EPEs increase by 30–60 mm summer−1 over the middle and lower reaches of the Yangtze River basin and northern China. It is shown that up to 90% of the positive anomalies in extreme precipitation are attributable to AR-group over these two areas (Fig. 11c). Thus, it is suggested that ARs have a larger contribution to extreme precipitation than to accumulated precipitation during post-El Niño summers.

    Figure 11.  As in Fig. 9, but for accumulated precipitation (mm summer−1) of 2-day EPEs.

    Figure 12a depicts the composite anomalies in accumulated IVT and $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ for 2-day EPEs during post-El Niño summers. Anomalous northeastward IVT and anomalous water vapor convergence are seen over the middle and lower reaches of the Yangtze River basin and northern China (Fig. 12a). Those patterns are favorable to in-situ increases of extreme precipitation (Fig. 11a). In addition, enhanced northeastward water vapor transport results in positive anomalies of AR frequency over eastern China (Fig. 8d). It is noted that the above patterns of total IVT and $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}}$ for 2-day EPEs are largely contributed by AR-group (Fig. 12b). Positive anomalies of extreme precipitation for AR-group in Fig. 11b are attributed to anomalous water vapor convergence in Fig. 12b.

    Figure 12.  As in Fig. 10, but for FIVT (vector; 105 kg m−1 summer−1) and $ \nabla \cdot {\boldsymbol{F}}_{\rm{IVT}} $ (shading; mm summer−1) of 2-day EPEs. The red boxes in (b) denote two core regions, which are located over the lower reaches of the Yangtze River basin (26°–34°N, 114°–121°E; region 1) and northern China (36°–44°N, 110°–130°E; region 2), respectively.

    The analysis so far indicates that anomalous moisture convergence results in the increases of extreme precipitation, especially over two regions: the lower reaches of the Yangtze River basin (26°–34°N, 114°–121°E; region 1) and northern China (36°–44°N, 110°–130°E; region 2). The relative changes in different processes of $ \nabla \cdot {\boldsymbol F}_{\rm{IVT}} $ in the two regions during post-El Niño summers are shown in Fig. 13. Indeed, moisture convergence anomalies are mainly contributed by anomalies of term A (horizontal wind convergence) in regions 1 and 2. The anomalies in terms B and C are relatively small in regions 1 and 2. In region 2, the anomaly of term C is larger than that of term B, which may be due to enhanced southerly wind (figure omitted).

    Figure 13.  As in Fig. 7, but for anomalous values over two regions during post-El Niño summers.

5.   Summary
  • Based on statistical analysis of daily data from CPC and ERA-Interim, the present study investigates the climatology and interannual variations of ARs and their impact on precipitation over EA during 1979–2019 from the perspective of water vapor transport and moisture flux convergence. By comparing the relative importance of wind divergence and moisture advection in extreme precipitation events, influences of ARs on extreme precipitation are discussed.

    Climatologically, ARs show a clear seasonality in spatiotemporal distribution. In spring, ARs with frequency of 8%–12% are seen over southern China and Japan. AR frequency is about 8%–13% over EA in summer. It decreases to 4%–7% over southern China and Japan in winter. ARs play an essential role in deciding the amount of precipitation. ARs are related to 25%–40% of total precipitation and 60%–75% of extreme precipitation over eastern China, the Korean Peninsula, and Japan in spring, summer, and winter. In autumn, ARs contribute 20%–25% of total precipitation and 50%–60% of extreme precipitation over the Yangtze–Huaihe River basin, Korea, and southern Japan. ARs’ contribution to precipitation in our study is larger than that in Liang and Yong (2021), especially in autumn and winter.

    As unique moisture plumes, ARs carry plenty of water vapor and produce a large moisture sink over the whole East Asian region, which are conducive to forming extreme precipitation. Previous studies mostly focus on the moisture transport by ARs and the fraction of precipitation for AR-group to total precipitation. Our study focuses on the moisture convergence induced by ARs and reveals that it contributes to a fairly high fraction of extreme precipitation. This indicates that extreme precipitation for the AR-group is largely caused by AR-generated water vapor convergence over EA. We find that AR-produced water vapor flux convergence is mainly decided by horizontal wind convergence instead of moisture advection over eastern China.

    During post-El Niño summers, AR frequency increases over EA. Meanwhile, increases in accumulated and extreme precipitation are observed over the middle and lower reaches of the Yangtze River basin and northern China. The increases of precipitation in the AR-group account for nearly 90% of the positive precipitation anomalies over the middle and lower reaches of the Yangtze River basin and 70% over northern China, respectively. As for extreme precipitation, its anomalous patterns are mostly related to the extreme anomalies of the AR-group over the above two regions.

    During post-El Niño summers, enhanced northeastward water vapor transport and anomalous water vapor convergence are observed over the middle and lower reaches of the Yangtze River basin and northern China, which are favorable to the increases of in-situ total precipitation and extreme precipitation. The above anomalies in moisture transport and moisture sink are largely associated with ARs. In addition, the anomalous moisture sink is largely contributed by the anomalies of wind convergence over the middle and lower reaches of the Yangtze River basin and northern China in the decaying summer of El Niño.

    This study reveals climatological spatiotemporal distributions of ARs and their impact on precipitation over EA in four seasons. Due to the complexity in the East Asian summer monsoon system, atmospheric circulation and rainfall over EA show different features before and after mid-July (Ding and Chan, 2005). ARs also show different features during early and late summers (Pan and Lu, 2020; Park et al., 2021). In the early summer, ARs are influenced by southwesterly monsoon along the northern flank of WNPSH. In the late summer, WNPSH shifts northward and ARs frequently occur over the storm track region. The underlying mechanisms of ARs over EA are still not clear and need further exploration.

    This study shows that the northeastward water vapor transport is enhanced over eastern China. The reasons for this enhancement are not analyzed in the current study. Previous works found that the westward expansion of WNPSH and the establishment of East Asia/Pacific teleconnection are conducive to the development of southwesterly winds that transport abundant moisture to the Yangtze River basin (Wang et al., 2000; Xie et al., 2016). The enhanced northeastward water vapor transport over northern China may also be attributed to the double-blocking in Eurasian mid–high latitudes (Wu et al., 2017). Further investigation along this line is needed.

    In this study, it is concluded that extreme precipitation associated with ARs is mainly caused by local convergence of AR-produced water vapor transport. Based on the decomposition of water vapor divergence, horizontal wind divergence is the dominant process. This may help us predict ARs and understand the physical mechanism of ARs affecting extreme precipitation.

    Acknowledgments. The authors would like to acknowledge the two anonymous reviewers and JMR Editorial Office for their constructive and thoughtful comments on the paper. We great appreciate Dr. Guan for sharing the AR detection code.

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