Contribution of Water Vapor to the Record-breaking Extreme Meiyu Rainfall along the Yangtze River Valley in 2020

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  • Corresponding author: Xuguang SUN, xgsun@nju.edu.cn
  • Funds:

    Supported by the National Key R&D Program of China (2018YFC1505803), the National Natural Science Foundation of China (41775074), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (41621005)

  • doi: 10.1007/s13351-021-1030-1

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  • A record-breaking extreme Meiyu rainfall occurs along the Yangtze River valley (YRV) in 2020 since 1961, which persists from June 11 to July 31 with the largest amount and the highest intensity. From the aspect of water vapor, the causes of its formation are revealed in this study. The 2020 Meiyu rainfall amount is directly attributed to the greatly enhanced vertically integrated water vapor transport (IVT) convergence, which is in turn primarily determined by the mean circulation dynamic (MCD) contribution associated with anomalous East Asian summer monsoon and the thermodynamic (TH) contribution due to water vapor anomaly. The MCD contribution is mainly responsible for the extreme Meiyu rainfall amount and abundant water vapor convergence in the YRV, whereas the TH contribution tends to shift Meiyu rain belt northward to the Yangtze-Huaihe River valley, extending the Meiyu rainfall coverage area. Furthermore, the excessive moist static energy (MSE) associated with the largest water vapor anomaly could substantially increase the atmospheric instability, favoring the extreme 2020 Meiyu rainfall intensity. In terms of the tremendous IVT to the YRV from both South China Sea and Bay of Bengal during 2020 Meiyu period, the low-level anticyclone anomalies over the western North Pacific (WNP) and Bay of Bengal provide appropriate atmospheric circulation conditions, and they are generated by the super suppressed WNP convective activities as a Matsuno-Gill type response, which are further attributed to the combined warm SST anomalies in both the tropical western Indian Ocean and the tropical Atlantic Ocean eventually.
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  • Fig. 1.  Time-Latitude cross-section of rainfall amount anomalies (mm) averaged between 107°E and 122°E for the (a) composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b) the specific year 2020. The red vertical dashed lines indicate the start (June 11) and end (July 31) date of Meiyu rainfall period, and the crossed lines in (a) denote the 95% confidence level of Student’s t-test.

    Fig. 2.  Spatial distributions of anomalous Meiyu rainfall amount (mm) in (a) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016, (b) 2020, (c) 2017 and (d) 2010. The YRV region bounded by 27°N−34°N, 107°E−122°E is marked by a red rectangle, and the crossed lines in (a) denote the 95% confidence level of Student’s t-test.

    Fig. 3.  Time series of YRV area-averaged standardized anomalies of (a) Meiyu rainfall amount (blue) together with IVT convergence (red) and (b) Meiyu rainfall intensity (blue) accompanied by MSE (red) and specific humidity (green).

    Fig. 4.  Scatter distribution of standardized Meiyu rainfall amount versus standardized IVT convergence. Blue line is the corresponding linear regression line without considering the year 2020.

    Fig. 5.  (a, b) Vertically integrated IVT anomaly (vector, kg m−1 s−1) and its associated divergence anomaly (shaded, 10−5kg m−2 s−1), (c, d) wind vector anomaly (vector, m s−1) and specific humidity anomaly (shaded, g kg−1) at 850 hPa in (a, c) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b, d) 2020. The red rectangle and cross lines in (a) are the same as those in Fig. 2.

    Fig. 6.  Spatial distributions of (a, b) MCD (10−5kg m−2 s−1) and (c, d) TH (10−5kg m−2 s−1) in (a, c) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b, d) 2020. The red rectangle and cross lines in (a) are the same as those in Fig. 2.

    Fig. 7.  (a) IVT anomaly with its major components of MCD (10−5kg m−2 s−1) and TH (10−5kg m−2 s−1) and (b) vertically integrated MSE anomaly with its two control factors of latent energy (Lv*q, 105J kg−1) and internal energy (Cp*T, 105J kg−1) area-averaged over the YRV for the selected individual years and their composite (with 2020 excluded).

    Fig. 8.  Spatial distribution of (a, b) OLR anomaly (W m−2), (c, d) velocity potential (shaded, m2 s−1) and its associated divergent wind anomaly (vector, m s−1) at 200 hPa, and (e, f) SST anomaly (degC) in (a, c, e) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b, d, f) 2020. The red rectangles indicate the three key regions in TWIO (50°E–80°E, 20°S–20°N), WNP (120°E–160°E, 0°N–20°N) and TAO (60°W–10°W, 5°S–20°N), and the cross lines in (a, c, e) are the same as those in Fig. 2.

    Fig. 9.  Time series of WNP area-averaged OLR index (red) and combined index with SST anomalies in both TWIO and TAO (blue).

    Fig. 10.  Same as Fig. 2, but for zonal wind anomaly (shaded, m s−1) and its climatology (contour, m s−1) at 200 hPa.

    Table 1.  Correlation coefficients of amount and intensity of Meiyu rainfall with area-averaged indices of OLR and SST in WNP, TWIO and TAO respectively, as well as IAOSST index. IAOSST index combines area averages of SST anomalies in the TWIO and TAO. *(#) indicates significant correlation at the 99% (95%) confidence level

    Rainfall amountRainfall intensity
    OLR in the WNP0.57*0.54*
    OLR in the TWIO−0.33#−0.34#
    OLR in the TAO−0.020.04
    SST in the TWIO0.57*0.64*
    SST in the TAO0.39#0.49*
    IAOSST index0.59*0.68*
    Download: Download as CSV
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Contribution of Water Vapor to the Record-breaking Extreme Meiyu Rainfall along the Yangtze River Valley in 2020

    Corresponding author: Xuguang SUN, xgsun@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 R&D Program of China (2018YFC1505803), the National Natural Science Foundation of China (41775074), and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (41621005)

Abstract: A record-breaking extreme Meiyu rainfall occurs along the Yangtze River valley (YRV) in 2020 since 1961, which persists from June 11 to July 31 with the largest amount and the highest intensity. From the aspect of water vapor, the causes of its formation are revealed in this study. The 2020 Meiyu rainfall amount is directly attributed to the greatly enhanced vertically integrated water vapor transport (IVT) convergence, which is in turn primarily determined by the mean circulation dynamic (MCD) contribution associated with anomalous East Asian summer monsoon and the thermodynamic (TH) contribution due to water vapor anomaly. The MCD contribution is mainly responsible for the extreme Meiyu rainfall amount and abundant water vapor convergence in the YRV, whereas the TH contribution tends to shift Meiyu rain belt northward to the Yangtze-Huaihe River valley, extending the Meiyu rainfall coverage area. Furthermore, the excessive moist static energy (MSE) associated with the largest water vapor anomaly could substantially increase the atmospheric instability, favoring the extreme 2020 Meiyu rainfall intensity. In terms of the tremendous IVT to the YRV from both South China Sea and Bay of Bengal during 2020 Meiyu period, the low-level anticyclone anomalies over the western North Pacific (WNP) and Bay of Bengal provide appropriate atmospheric circulation conditions, and they are generated by the super suppressed WNP convective activities as a Matsuno-Gill type response, which are further attributed to the combined warm SST anomalies in both the tropical western Indian Ocean and the tropical Atlantic Ocean eventually.

1.   Introduction
  • Meiyu (also called Baiu in Japan and Changma in Korea) is a zonally elongated quasi-stationary rain belt along the Yangtze River valley (YRV) (Ninomiya and Muraki, 1986; Tao and Chen, 1987; Ding and Chan, 2005 本条文献在文后文献中未体现; Ding et al., 2008), and its rainfall amount generally accounts for 30%–40% of the annual total rainfall and sometimes more than 50% in this region (Li and Mao, 2019; Wang et al., 2021). The mean length of Meiyu period is approximately one month from mid-June to mid-July, which is a major rainy season for the Yangtze River Economic belt that owns more than 40% of the Chinese population and GDP (Ding and Wang, 2008 本条文献在文后文献中未体现; Ding et al., 2008; Li and Mao, 2019; Guan et al., 2020). Therefore, severe floods during Meiyu period could exert a deleterious effect on the local socio-economic development. In 2020, a record-breaking extreme Meiyu rainfall occurred in the middle-lower reaches of the YRV in China since 1961, which has killed 219 people and caused economic losses of at least 178 billion yuan. At the same time, more than 50 counties witnessed historical extreme rainfall. Some recent studies have investigated causes of the extreme 2020 Meiyu in terms of tropical Arabian Sea surface sea temperature (SST) warming in June (Wang et al., 2021), subseasonal phase transition of North Atlantic Oscillation (NAO) (Liu et al., 2020 本条文献指代信息不明确) and activities of Tibetan Plateau vortices (Li et al., 2020). However, the reasons why both rainfall amount and intensity in 2020 Meiyu reach up to a record-breaking level are still unclear.

    The formation of Meiyu is complicated, and it is affected by multiple factors among tropical, subtropical, and mid-high latitude’s systems (Ninomiya, 1999; Ninomiya and Kobayashi, 1999; Simmonds et al., 1999; Zhou and Yu, 2005; Ding et al., 2008; Sun et al., 2010, 2019; Liu et al., 2020 本条文献指代信息不明确). Generally speaking, Meiyu rain belt is mainly determined by the dynamic processes in the atmosphere (i.e. atmospheric circulations), and previous studies mostly highlighted the role of East Asian summer monsoon (EASM) members like the western Pacific subtropical high (WPSH), the East Asian westerly jet (EAWJ), and the mid-level warm advection (Zhou and Yu, 2005; Wang et al., 2008 本条文献在文后文献中未体现; Sun et al., 2010; Li et al., 2019 本条文献在文后文献中未体现). However, Meiyu rainfall is directly related to the water vapor supply that involves thermodynamical processes, and convergence of water vapor transport from both tropical and midlatitude regions is essential for the rainfall amount and intensity (Simmonds et al., 1999; Zhang, 2001; Zhou and Yu, 2005; Gao and Sun, 2016; Sun et al., 2019). For example, Zhou and Yu (2005) showed the southeastern Asian and Indian monsoon circulation can bring abundant water vapor from the South China Sea and the Bay of Bengal to southeast China, respectively, which induces much more rainfall amount over there. In turn, the water vapor transport is greatly affected by the monsoon circulation (Ninomiya and Kobayashi, 1999; Simmonds et al., 1999; Zhang, 2001; Xu et al., 2004; Zhou and Yu, 2005; Gao and Sun, 2016; Sun et al., 2019). So Meiyu is the combination of both dynamical and thermodynamical processes, and water vapor budget is a useful method to diagnose and separate their relative contributions to the formation of Meiyu rainfall, caused thermodynamically by changes in specific humidity, dynamically by changes in circulation (Trenberth and Guillemot, 1995; Seager et al., 2010).

    Furthermore, many studies have revealed contributions of ENSO, SST anomalies in the Indian and Atlantic Ocean to the year-to-year variations of Meiyu rainfall (Ding et al., 2008; Jiang et al., 2008; Xie et al., 2009; Feng et al., 2011; Kosaka et al., 2011; Yuan and Yang, 2012; Zuo et al., 2013; Oh and Ha, 2015; Li et al., 2016; Xie et al., 2016; Takaya et al., 2020; Wang et al., 2021). Meiyu rainfall amount anomaly is attributed to the changes in location and intensity of anomalous convection associated with local anticyclone anomaly over the western North Pacific (WNP), which is closely related to ENSO (Ding et al., 2008; Sun et al., 2010, 2019; Wang et al., 2021). In the following year of an El Niño event, Meiyu rainfall in the YRV is found to be significantly above-normal, and it is much stronger for the Eastern-Pacific El Niño than the Central-Pacific El Niño (Ding et al., 2008; Feng et al., 2011; Yuan and Yang, 2012; Zhu et al., 2013). However, only a weak warm condition occurs as a Central-Pacific El Niño event in 2019/2020 winter, which should not be responsible for the record-breaking extreme 2020 Meiyu rainfall along the YRV according to the previous El Niño-based studies. Some studies suggested that Indian Ocean warming can partly account for the enhanced Meiyu rainfall by stretching the WNP subtropical high southwestward and intensifying moisture advection to the YRV (Wu et al., 2009; Kosaka et al., 2011; Xie et al., 2016; Takaya et al., 2020; Wang et al., 2021). The extreme Meiyu rainfall in 1998 is corresponding to a typical case of the warm Indian Ocean (Jiang et al., 2008). Wang et al. (2021) identified that the later-than-normal Meiyu withdrawal is preceded by the significant tropical Arabian SST warm in June, which could be an important factor for the extreme 2020 Meiyu rainfall. They also noted that the basin-wide warm condition in Indian Ocean in early 2020 is similar to that in early 2019, but Meiyu rainfall amount in 2020 is more than that in 2019, and even larger than the 1998 Meiyu, so Indian Ocean itself is not the whole story of the causes of the extreme 2020 Meiyu rainfall, either. The impact of the Atlantic Ocean on 2020 Meiyu rainfall is also worth considering since obvious SST warming concurrently shows up in the tropical Atlantic Ocean (Fig. 8f). Previous studies have pointed out that Atlantic Ocean warming can drive easterly wind anomalies over the Indo-western Pacific as Kelvin waves through the wind-evaporation-SST effect, inducing an Indo-western Pacific warming that is the major cause of the anomalous anticyclone over the WNP (Rong et al., 2010; Wu et al., 2010 此处为Wu et al., 2010?/Wu et al., 2011?; Li et al., 2016; Xie et al., 2016). Moreover, Pacific, Indian and Atlantic Oceans can interact with each other through air-sea coupling and influence the climate variabilities over East Asia together (Wang, 2019), so their combined effect on the water vapor transport and Meiyu rainfall in 2020 should be considered.

    From the aspect of water vapor, this study is aimed to explore the reason why 2020 Meiyu rainfall has the record-breaking extreme in both amount and intensity, and furthermore, the potential forcing signals from the global oceans for the source of water vapor in YRV are discussed. The rest of the paper is organized as follows. Section 2 describes the data and analysis methods used in this study. Section 3 illustrates the role of water vapor in amount and intensity of the extreme 2020 Meiyu rainfall as well as the source of water vapor in YRV. Finally, the main conclusions are summarized in the last section together with some discussions.

2.   Data and methods
  • In this study, the daily precipitation data used to demonstrate the Meiyu rainfall is from NOAA Climate Prediction Center (CPC) with 0.5° × 0.5° spatial resolution (https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html). The daily data of meridional and zonal wind components, relative humidity, and air temperature at 17 vertical levels are from NCEP/DOE Reanalysis II (https://psl.noaa.gov/data/gridded/data.ncep.reanalysis.html), which have a spatial resolution of 2.5° × 2.5°, and the daily NOAA interpolated Outgoing Longwave Radiation (OLR) at the same spatial resolution (https://psl.noaa.gov/data/gridded/data.interp_OLR.html) is used to indicate the convective activities in the tropical region. All the above daily data are collected during the period from 1979 to 2020. Besides, daily SST data at a spatial resolution of 0.25° × 0.25° is obtained from NOAA Optimum Interpolation SST V2 High Resolution Dataset from 1982 to 2020 (https://psl.noaa.gov/data/gridded/data.noaa.oisst.v2.highres.html)

    According to the monitoring and analysis of the Meiyu period by the China Meteorological Administration (CMA), the period from 11 June to 31 July is selected as the 2020 Meiyu period in this study, when it demonstrates significantly concentrated rainfall amount in YRV (Fig. 1b). Based on the spatial distribution of total rainfall amount averaged for 2020 Meiyu period, area covering 27°N−34°N, 107°E −122°E is selected as the key study region of Meiyu in YRV (rectangle in Fig. 2). Then the time series of area-averaged values are used to select the abnormal years of Meiyu rainfall amount and intensity in YRV (Fig. 3), in which the values exceed their mean by one standard deviation. Specifically, they are 1980, 1983, 1998, 1999, 2010, 2016, and 2020 for Meiyu rainfall amount, and 1983, 1998, 2007, 2016, and 2020 for Meiyu rainfall intensity, among which there are 4 years (1983, 1998, 2016 and 2020) overlapped with each other, and the former 3 years are the decaying years of the 3 super El Niño events. Wherein, Meiyu rainfall intensity is defined as the ratio of Meiyu rainfall amount to days of rainfall more than 1 mm/day during Meiyu period in each year. To highlight the special features of 2020 Meiyu, except for explicit declaration, composites are made based on the abnormal years of Meiyu rainfall amount with 2020 excluded for comparisons, which actually have no obvious differences with those including 2020 (Figure not shown).

    Figure 1.  Time-Latitude cross-section of rainfall amount anomalies (mm) averaged between 107°E and 122°E for the (a) composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b) the specific year 2020. The red vertical dashed lines indicate the start (June 11) and end (July 31) date of Meiyu rainfall period, and the crossed lines in (a) denote the 95% confidence level of Student’s t-test.

    Figure 2.  Spatial distributions of anomalous Meiyu rainfall amount (mm) in (a) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016, (b) 2020, (c) 2017 and (d) 2010. The YRV region bounded by 27°N−34°N, 107°E−122°E is marked by a red rectangle, and the crossed lines in (a) denote the 95% confidence level of Student’s t-test.

    Figure 3.  Time series of YRV area-averaged standardized anomalies of (a) Meiyu rainfall amount (blue) together with IVT convergence (red) and (b) Meiyu rainfall intensity (blue) accompanied by MSE (red) and specific humidity (green).

  • To reveal the relative contributions of dynamic and thermodynamic processes to the Meiyu rainfall amount, water vapor budget equation (Trenberth and Guillemot, 1995; Seager et al., 2010; Chou et al., 2013) is diagnosed as follows:

    $$ {\rho }_{w}g\left(P-E\right)=-{\int }_{300}^{{p}_{s}}\nabla \bullet \left(\mathop v\limits^{\rightharpoonup}q\right)dp+\delta . $$ (1)

    Where, $ P $ is precipitation, $ E $ is evaporation, $ \rho $ is pressure, $ q $ is specific humidity, $ \mathop v\limits^{\rightharpoonup} $ is wind vector, $ {\rho }_{w} $ is the density of water, and the subscript$ s $ denotes surface values. The first term on the right-hand side of Eq. (1) is the vertically integrated convergence of moisture flux or vertically integrated water vapor transport (IVT) convergence, and the second term $ \delta $ contains transient eddies and surface quantities. Based on previous studies (Seager et al., 2010 Wu et al., 2010 此处为Wu et al., 2010?/Wu et al., 2011?), $ \delta $ is proved to be negligible, so it’s not considered in this study, either. Suppose that a variable can be divided into a basic state (denoted by an overbar) and a perturbation (denoted by a prime), thus the perturbed water vapor budget equation can be written as:

    $$ {\rho }_{w}g\left(P'-E'\right)\approx -{\int }_{300}^{{p}_{s}}\left(\nabla \bullet \left(\bar{\mathop v\limits^{\rightharpoonup}}q'\right)+\nabla \bullet \left(\mathop {v'}\limits^{\rightharpoonup}\bar{q}\right)+\nabla \bullet \left(\mathop {v'}\limits^{\rightharpoonup}q'\right)\right)dp. $$ (2)

    Here, overbar means the climatological mean during Meiyu period from 1979 to 2020, and prime indicates the interannual departure from the climatology. The first term on the right-hand side of Eq. (2) involves the anomalous specific humidity $ q' $ and the climatological wind vector $ \bar{\mathop v\limits^{\rightharpoonup}} $, which is the thermodynamic component (TH) contribution to $ P'-E' $. Correspondingly, the second term is the mean circulation dynamic (MCD) contribution, which is comprised of anomalous wind vector $ \mathop {v'}\limits^{\rightharpoonup} $ and climatological specific humidity $ \bar{q} $. The last term is the nonlinear (NL) contribution that is the product of both anomalous specific humidity $ q' $ and anomalous wind vector $ \mathop {v'}\limits^{\rightharpoonup} $. Considering the evaporation is much less than the precipitation along the YRV (Wei et al., 2012), $ P'-E' $ is dominated by $ P' $, so Meiyu rainfall anomaly can be further approximated as the sum of contributions of TH, MCD, and NL:

    $$ \hspace{30pt} {\rho }_{w}gP'\approx TH+MCD+NL. $$ (3)

    Wherein,

    $$\hspace{30pt} TH=-{\int }_{300}^{{p}_{s}}\nabla \bullet \left(\bar{\mathop v\limits^{\rightharpoonup}}q'\right)dp, $$
    $$ MCD=-{\int }_{300}^{{p}_{s}}\nabla \bullet \left(\mathop {v'}\limits^{\rightharpoonup}\bar{q}\right)dp, $$
    $$ NL=-{\int }_{300}^{{p}_{s}}\nabla \bullet \left(\mathop {v'}\limits^{\rightharpoonup}q'\right)dp, $$

    The column-integrated moist static energy (MSE) represents a thermodynamic state of the column atmosphere, and it can be used to indicate the instability of troposphere caused by the heating and moistening processes, which is further closely related to the amount and intensity of rainfall due to its induced convective activities (Srinivasan and Smith, 1996; Back and Bretherton, 2006; Sooraj et al., 2015; Zheng et al., 2020; Wang et al., 2021). MSE is the sum of internal energy, latent energy, and potential energy:

    $$ MSE={C}_{p}T+{L}_{v}q+gz. $$ (4)

    Where, $ T $ is temperature, $ q $ is specific humidity, $ z $ is geopotential height, $ {C}_{p} $ is dry air heat capacity at constant pressure (1004 J K kg−1), $ {L}_{v} $ is the latent heat of condensation (taken constant at 2.5*106 J kg−1), and $ g $ is gravity acceleration (9.8 m s−2). So the vertically integrated MSE is calculated to show the role of thermodynamic process in 2020 Meiyu rainfall, so are its components of column-integrated temperature and specific humidity.

3.   Results
  • As shown in Fig. 1b, in 2020, the rain belt jumps from South China to the YRV along 30°N on June 11, and then persists and maintains its position albeit with some perturbations till the end of July (July 31), after which it quickly shifts to North China. In comparison, the composite rain belt based on the selected years in terms of YRV Meiyu rainfall amount displays similar characteristics at the beginning of Meiyu, however, its rainfall amount is obviously smaller than that in 2020 Meiyu, and furthermore, it mainly lasts from June 11 to July 21 that is pretty shorter by 10 days than the 2020 Meiyu period (Fig. 1a). When it is averaged from June 11 to July 31, the spatial pattern of rainfall shows a remarkable rain belt along the YRV in both 2020 (Fig. 2b) and composite (Fig. 2a), and the former has much larger spatial scale and amplitude than the latter, especially in the mid-lower reaches of YRV, with the maximum rainfall amount anomaly more than 600 mm (Fig. 2).

    From the standardized evolvements of both amount and intensity of YRV Meiyu rainfall, it can be seen that the 2020 Meiyu rainfall is dramatically outstanding in history during the period from 1979 to 2020 (Fig. 3). Its amount anomaly is record-breaking with more than 4 standard deviations, followed by Meiyu rainfall amount anomalies in 2016 and 1998 with less than 2 standard deviations. The same situation can also be found in 2020 Meiyu rainfall intensity, which is larger than 3 standard deviations. The amount and intensity of Meiyu rainfall are closely correlated with each other (0.87), and their abnormal large years are almost the same. As one of the major components involved in both amount and intensity of Meiyu rainfall, water vapor is the starting point and the aspect deserved to examining for the formation mechanism of the extreme 2020 Meiyu.

  • According to the composite anomalies of IVT and its divergence associated with above-normal Meiyu rainfall amount (Fig. 5a), there is a much stronger southwest IVT mainly initiated from South China Sea (SCS) to the YRV and the south of Japan, which is the northwestern part of a large anticyclonic IVT anomaly over the WNP. Accordingly, significant IVT divergence anomaly is located from the subtropical WNP to the Indo-China peninsula with the large center over the Indo-China peninsula and the SCS, whereas the prominent IVT convergence anomaly dominates the YRV, which is responsible for increased specific humidity along the YRV (Fig. 5c) and consistent with much more Meiyu rainfall amount over there according to Eq. (3) (Fig. 2a). As shown in the scatter plot of standardized Meiyu rainfall amount versus standardized IVT convergence (Fig. 4), the 2020 Meiyu rainfall is dramatically outstanding with the largest anomalous values of both rainfall amount and IVT convergence in history during the period from 1979 to 2020, and with 2020 excluded, the IVT convergence anomaly is significantly correlated with the Meiyu rainfall amount (0.38), demonstrating close relationship between them. Besides, the similarity of IVT anomaly and anomalous wind vector at 850 hPa (Figs. 5a, b) implies that anomalous monsoon circulation has a great impact on the IVT anomaly (Zhou and Yu, 2005; Gao and Sun, 2016; Sun et al., 2019).

    Figure 4.  Scatter distribution of standardized Meiyu rainfall amount versus standardized IVT convergence. Blue line is the corresponding linear regression line without considering the year 2020.

    Figure 5.  (a, b) Vertically integrated IVT anomaly (vector, kg m−1 s−1) and its associated divergence anomaly (shaded, 10−5kg m−2 s−1), (c, d) wind vector anomaly (vector, m s−1) and specific humidity anomaly (shaded, g kg−1) at 850 hPa in (a, c) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b, d) 2020. The red rectangle and cross lines in (a) are the same as those in Fig. 2.

    In 2020, the water vapor anomaly and its associated IVT convergence anomaly over YRV are both much larger than the composite (Fig. 4), and it is subjected to the much stronger IVT anomaly and 850 hPa wind anomaly (Figs. 5b, d). Specifically, compared to the composite, the anomalous WNP anticyclone and its related WNP IVT anomaly in 2020 are more significant, so is the northeastward transported water vapor to the YRV accompanied with the enhanced East Asian summer monsoon. Moreover, the remarkable anticyclonic IVT anomaly and low-level wind vector anomaly over the Bay of Bengal provides another source for the increased IVT from the tropical regions during Meiyu period in 2020, which is met with the cold and dry IVT anomaly from mid-high latitudes at the YRV (Fig. 5b), causing more significant IVT convergence anomaly and increased moisture over there (Figs. 5b, d). Wherein, the distinct anticyclone and cyclone anomalies on both sides of YRV provide a beneficial background of water vapor supply and eventually result in the dramatic Meiyu rainfall over the YRV in 2020 (Fig. 5d, Fig. 2b).

    According to Eq. (3), precipitation anomaly approximately represented by the IVT convergence anomaly can be attributed to TH contribution, MCD contribution, and NL contribution. In Fig. 6, only contributions of TH and MCD are shown because the NL contribution is much smaller and negligible (Seager et al., 2010; Wu et al., 2010 此处为Wu et al., 2010?/Wu et al., 2011?). It is clear to see that distribution of MCD is highly consistent with the IVT anomaly including magnitude and spatial pattern, for both the common situation with above-normal Meiyu rainfall amount and the extreme 2020 Meiyu case (Fig. 5a, b and Fig. 6a, b), which indicates that MCD contribution associated with anomalous monsoon circulation dominates the IVT anomaly and the Meiyu rainfall amount along the YRV during Meiyu period (Fig. 6a), consistent with previous studies (Zhang, 2000本条文献在文后文献中未体现; Chen and Sun, 2013; Gao and Sun, 2016; Gao et al., 2016). In contrast, TH contribution has rather different spatial pattern from MCD contribution (Figs. 6c, 6d), and it shows a meridional dipole pattern with a relatively weaker amplitude in the southeastern China, inducing anomalous IVT convergence and divergence over north and south of the YRV, respectively (Figs. 6c, 6d), which means that the enhanced water vapor anomaly along the YRV (Fig. 5d) may mainly shift the position of Meiyu rain belt northward, favoring much more Meiyu rainfall amount (positive TH contribution for increased rainfall amount) in Yangtze-Huaihe River valley (YHRV) and suppressing precipitation (negative TH contribution for decreased rainfall) in South China (Fig. 2a, b). Particularly, in 2020, the IVT convergence anomaly is the largest among those with above-normal Meiyu rainfall amount, and it is more than twice of the composite (Fig. 3a, Fig. 7a). While the much larger amount of IVT convergence due to MCD contribution undoubtedly determines the extreme Meiyu rainfall amount along the YRV, it is the TH contribution related thermodynamic process that makes the Meiyu rain belt extend northward to the YHRV compared to the composite (Fig. 6 and Fig. 2). Therefore, the combinations of MCD and TH contributions are essential for the record-breaking YRV Meiyu rainfall since 1979.

    Figure 6.  Spatial distributions of (a, b) MCD (10−5kg m−2 s−1) and (c, d) TH (10−5kg m−2 s−1) in (a, c) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b, d) 2020. The red rectangle and cross lines in (a) are the same as those in Fig. 2.

    Figure 7.  (a) IVT anomaly with its major components of MCD (10−5kg m−2 s−1) and TH (10−5kg m−2 s−1) and (b) vertically integrated MSE anomaly with its two control factors of latent energy (Lv*q, 105J kg−1) and internal energy (Cp*T, 105J kg−1) area-averaged over the YRV for the selected individual years and their composite (with 2020 excluded).

    The frequent occurrence of extreme rainfall events is also another feature in 2020 Meiyu (Fig. 1b). As one of the indicators of atmospheric instability, vertically integrated MSE is used to represent the intensity of convective activity and rainfall intensity as well. And it is expected that the larger the MSE is, the stronger the Meiyu rainfall intensity will be, which is true for the relationship of vertically integrated MSE and YRV Meiyu rainfall intensity with significant correlation coefficient (0.39). As shown in Fig. 7b, the vertically integrated MSE anomaly in 2020 is also the largest among those with above-normal Meiyu rainfall intensity and more than two times as large as the composite, and it is quite in accordance with the extraordinary 2020 Meiyu rainfall intensity, too (Fig. 3b). According to the MSE expression, its vertical integral anomaly mainly depends on the vertically integrated anomalies of internal energy (CpT) and latent energy (Lvq), and both of them are the largest in 2020 among the selected years with above-normal Meiyu rainfall intensity and have consistent contributions to the vertically integrated MSE anomaly (Fig. 7b), so is the vertically integrated specific humidity (Fig. 3b) that has much high correlation with MSE (0.94). Furthermore, the latent energy anomaly due to water vapor is about three times larger than the internal energy anomaly due to temperature in 2020, highlighting the dominant role of water vapor anomaly in 2020 Meiyu rainfall intensity though the temperature anomaly also has some important contributions. However, we should also note that not all the years with above-normal YRV Meiyu rainfall intensity are primarily determined by the latent energy anomaly, on the contrary, internal energy anomaly due to temperature is much more significant in some years like 2016 and 2007, which implies that there may exist different thermodynamical processes for the top 3 of extreme YRV Meiyu rainfall intensity (1998, 2016 and 2020).

  • As we have found that, water vapor plays an essential role in the record-breaking amount and intensity of 2020 Meiyu rainfall through both dynamic and thermodynamic processes, and in turn, its tremendous anomaly and associated significant IVT convergence anomaly in YRV are primarily attributed to the anomalous atmospheric circulation related to EASM (Fig. 5) (Simmonds et al., 1999; Zhang, 2001; Xu et al., 2004; Zhou and Yu, 2005; Gao and Sun, 2016). Wherein, the strong low-level WNP anticyclone anomaly is directly induced by the suppressed convective activity in WNP through the Matsuno-Gill type response and the local air-sea interaction (Zhang et al., 2018; Hu et al., 2019; Li and Mao, 2019; Zhao and Wang, 2020), and it is clear to see that the suppressed WNP convective activity are well represented by the local positive OLR anomaly (Fig. 8a, b) as well as the anomalous convergence wind accompanied by positive velocity potential anomaly at 200 hPa (Figs. 8c, d). Compared with the composite based on the selected years of above-normal Meiyu rainfall amount, amplitude of positive OLR anomaly over the WNP in 2020 is much larger (Figs. 8a, b), and it is also the largest in history since 1979 (Fig. 9), which may be responsible for the massive warm water vapor transport to the YRV during 2020 Meiyu period.

    Figure 8.  Spatial distribution of (a, b) OLR anomaly (W m−2), (c, d) velocity potential (shaded, m2 s−1) and its associated divergent wind anomaly (vector, m s−1) at 200 hPa, and (e, f) SST anomaly (degC) in (a, c, e) the composite based on the years of 1980, 1983, 1998, 1999, 2010, and 2016 and (b, d, f) 2020. The red rectangles indicate the three key regions in TWIO (50°E–80°E, 20°S–20°N), WNP (120°E–160°E, 0°N–20°N) and TAO (60°W–10°W, 5°S–20°N), and the cross lines in (a, c, e) are the same as those in Fig. 2.

    Figure 9.  Time series of WNP area-averaged OLR index (red) and combined index with SST anomalies in both TWIO and TAO (blue).

    In addition, enhanced convective activity also occurs in the tropical western Indian Ocean (TWIO), which is much significant in 2020 compared to the composite (Figs. 8a, b), and together with the suppressed WNP convection activity, it forms a dipole pattern of anomalous convections in the tropical Indian-western Pacific Ocean, corresponding to significant upper-level divergent and convergent wind anomalies in the TWIO and WNP, respectively (Figs. 8c, d), which tends to form a weakened Walker circulation, especially in 2020. Moreover, different from the composite that has nearly no convection anomaly in the tropical Atlantic Ocean (TAO), 2020 Meiyu witnesses an obvious enhanced convective activity over there, too (Figs. 8a, b). As a result, the enhanced convective activity in the TAO can induce upper-level convergent wind anomaly over the western North Pacific (WNP) directly via mass flow, suppressing the local convection (Fig. 8d). And on the other hand, it can trigger low-level Kelvin wave and cause easterly wind anomaly extending from the tropical Indian Ocean to the WNP, and then the anticyclonic shear associated with the easterly wind anomaly leads to the boundary layer divergence through Ekman pumping, which further generates weakened convective activities and an anomalous anticyclone over the WNP (Fig. 5d; Rong et al., 2010). Thus, the much warmer SST in the TAO acts as an additional forcing factor for the low-level WNP anticyclone anomaly and the record-breaking 2020 Meiyu rainfall besides the primary contribution of the tropical Indian Ocean warming.

    Therefore, as for the record-breaking 2020 Meiyu, the WNP (120°E−160°E, 0°N−20°N), the TWIO (50°E−80°E, 20°S−20°N) and the TAO (60°W−10°W, 5°S−20°N) are the three key regions of anomalous convective activities for the WNP anticyclone anomaly and for the Meiyu rainfall as well. The correlations of their area-averaged OLR anomalies with YRV Meiyu rainfall amount are 0.57, −0.33, and −0.02, respectively, and they are 0.54, −0.34, and 0.04 accordingly when correlated with YRV Meiyu rainfall intensity (Table 1), which further confirms the crucial influences of convective activities over the WNP followed by that in the TWIO (Sun et al., 2019; Wang et al., 2021). In the TAO, both convective activity and its association with Meiyu rainfall are generally weak in terms of significant correlation between SSTA and Meiyu rainfall, it is mainly due to the relatively weaker albeit warm SSTA over there, the convective activity induced by which is greatly suppressed by the enhanced convective activities over the tropical eastern Pacific, the western tropical Indian Ocean as well as the tropical North Africa through divergent wind anomalies (Fig. 8a, 8c, 8e). However, in 2020, SST in the TAO is much warmer, and it produces significantly enhanced convective activity above and overcomes the inhibition effects from the surrounding regions (Fig. 8b, 8d, 8f), which makes 2020 Meiyu most outstanding from others, together with the significant dipole convection anomalies in the tropical Indian-western Pacific Ocean.

    Rainfall amountRainfall intensity
    OLR in the WNP0.57*0.54*
    OLR in the TWIO−0.33#−0.34#
    OLR in the TAO−0.020.04
    SST in the TWIO0.57*0.64*
    SST in the TAO0.39#0.49*
    IAOSST index0.59*0.68*

    Table 1.  Correlation coefficients of amount and intensity of Meiyu rainfall with area-averaged indices of OLR and SST in WNP, TWIO and TAO respectively, as well as IAOSST index. IAOSST index combines area averages of SST anomalies in the TWIO and TAO. *(#) indicates significant correlation at the 99% (95%) confidence level

    Different from the TWIO and TAO where enhanced convective activities are greatly generated by the warm SST underneath, in the WNP, warm SST anomaly is corresponding to the suppressed convection activity during Meiyu period (Fig. 8a, b, e, f), which indicates that the atmosphere mainly drives the ocean in this region (Trenberth and Shea, 2005; Wang et al., 2005; Wu et al., 2009; Lu and Lu, 2014). In this case, both the suppressed WNP convective activity and the WNP anticyclone anomaly during Meiyu period are remotely controlled by the warm SST anomalies in both the TWIO and the TAO, so is the Meiyu rainfall in the YRV. The correlations of TWIO SST anomaly with both amount and intensity of Meiyu rainfall are much higher than those of TAO SST anomaly (Table 1), consistent with the larger convective activities represented by significant negative OLR anomalies over there (Fig. 8a, b), implying the leading role of TWIO SST anomaly (Wang et al., 2021). On the other hand, the TAO SST anomaly is also very important for the YRV Meiyu rainfall with significant correlation between them (Table 1), and during 2020 Meiyu period, its notable warming causes remarkable local convective activities and upper-level divergent wind anomaly (Figs. 8b, 8d).

    However, SST anomalies in both Indian and Atlantic Ocean are not the warmest in history since 1979, and they cannot be directly linked to the record-breaking YRV Meiyu rainfall individually. Therefore, considering the effects of SST anomalies in TWIO and TAO, a combined SST index is defined as follows,

    $$ IAOSSTI={SST}_{INO}+{SST}_{TAO}, $$

    Where, $ {SST}_{INO} $ and $ {SST}_{TAO} $ are the area averages of SST anomalies in the TWIO and TAO, respectively. As shown in Fig. 9, the IAOSSTI reaches the maximum in 2020 in accordance with the record-breaking YRV Meiyu rainfall during the study period, and furthermore, it has higher correlations with amount (0.59) and intensity (0.68) of Meiyu rainfall than the individual index of TWIO and TAO (Table 1). Therefore, IAOSSTI may be a good indicator of the potential sources of water vapor in the tropics for YRV Meiyu rainfall, and increases of its two components (TWIO and TAO) are both responsible for the significant increase of correlations with Meiyu rainfall, wherein contribution of TWIO is dominant.

    However, we should note that following 2020, 2010, and 2017 have the second and the third largest amplitude of IAOSSTI, respectively (Fig. 9), which indicates that Meiyu rainfall in the two years could just follow that in 2020, too. However, according to the YRV area-averaged Meiyu rainfall, 2010 and 2017 are not the years with much larger Meiyu rainfall amount, even below-normal in 2017 (Fig. 3), which is mainly attributed to the southward shifted Meiyu rain belt in the two years, demonstrating a meridionally opposite rainfall anomalies on the two sides of YRV, especially in 2017 (Figs. 2c, 2d). Sun et al. (2019) pointed out, locations of summer rain belt anomaly around the YRV are closely related to the anomalous East Asian summer westerly jet (EASWJ), which are further determined by the meridional teleconnections over East Asia originated from tropical and extratropical regions. Therefore, while the IAOSSTI can be taken as a tropical signal for the Meiyu rainfall, mid-high latitude signals should also be considered. As shown in Fig. 10, both 2020 and the composite correspond to the enhanced EASWJ whereas both 2010 and 2017 are related to the weakened and southward shifted EASWJ, and the two situations are much similar to the tropical and extratropical-origin summer meridional teleconnection over East Asia, respectively (Sun et al., 2019), which confirms the necessity of considering both tropical and extratropical signals in understanding and predicting the YRV Meiyu rainfall, and on the other hand, addresses the significance of tropical signal in the record-breaking 2020 Meiyu rainfall.

    Figure 10.  Same as Fig. 2, but for zonal wind anomaly (shaded, m s−1) and its climatology (contour, m s−1) at 200 hPa.

4.   Conclusion and discussion
  • The YRV witnesses a record-breaking extreme Meiyu rainfall in 2020 since 1961, with the largest amount, the highest intensity, and the longest duration (from June 11 to July 31), which can be clearly demonstrated by the temporal-spatial distributions of YRV Meiyu rainfall in comparison with the corresponding above-normal composite over there. Since YRV Meiyu rainfall amount is directly caused by the IVT convergence according to the water vapor budget equation, formation of extreme 2020 Meiyu rainfall is investigated from the aspect of water vapor.

    It’s not surprising to see that anomalous IVT convergence reaches its positively maximum accompanying the Meiyu rainfall amount, which is further primarily determined by the MCD contribution due to anomalous EASM circulation and the TH contribution related to anomalous specific humidity, with the former much larger than the latter. Generally, MCD contribution mainly transports warm moisture to the YRV from the tropical region via a significant WNP anticyclone anomaly, and causing much more Meiyu rainfall amount along the YRV, whereas TH contribution tends to shift Meiyu rainfall northward to the YHRV instead, greatly extending the covering area of 2020 Meiyu rainfall. Furthermore, water vapor anomaly during 2020 Meiyu period is the largest in history since 1979, and its associated latent energy anomaly dominates the anomalous MSE, which is also the largest and favors the record-breaking 2020 Meiyu rainfall intensity by inducing the greatest atmospheric instability. Therefore, the distinctively strengthened water vapor supply for 2020 Meiyu leads to not only the record-breaking rainfall amount but also the strongest rainfall intensity.

    In terms of the tremendous IVT to the YRV from both SCS and Bay of Bengal during 2020 Meiyu period, the low-level anticyclone anomalies over the WNP and Bay of Bengal provide much more appropriate atmospheric circulation conditions compared with the other years, and they are further directly caused by the super suppressed WNP convective activity through Matsuno-Gill type response and the local air-sea interaction (Zhang et al., 2018; Hu et al., 2019; Li and Mao, 2019; Zhao and Wang, 2020). In turn, the weakened WNP convective activity is corresponding to the local upper-level convergence wind anomaly that is closely linked with upper-level divergent wind anomaly in the TWIO and TAO, respectively, forming a significantly reduced Walker circulation. The enhanced convective activities in both TWIO and TAO are generated by their locally warm SST anomalies underneath, whereas the negative relationship of warm SST anomaly and suppressed convective activity over the WNP implies a passive role of the local warm SST anomaly. Therefore, in 2020, instead of their individuals as well as the WNP warm SST anomaly, the combined warm SST anomalies in TWIO and TAO produce the weakest convective activity over the WNP and the largest IVT convergence anomaly in YRV, and finally cause the record-breaking Meiyu rainfall over there.

    However, we are aware that while the index of the combined SST anomalies in both TWIO and TAO could be used as a good indicator for Meiyu rainfall anomaly, forcing signals from mid-high latitudes should be also considered (Sun et al., 2019; Liu et al., 2020 本条文献指代信息不明确), and the proper configurations of forcing signals originated from both tropical and extratropical are essential for the formation of extreme Meiyu rainfall (Sun et al., 2019). On the other hand, under the background of global warming, rising surface temperature can help to significantly enlarge the water vapor content in the atmosphere and the atmospheric instability as well especially since the beginning of 21st century, which could provide much better thermal and dynamic conditions for more frequent extreme Meiyu rainfall events in future (Gao et al., 2016; Liu et al., 2020 本条文献指代信息不明确).

    Acknowledgements. This study was jointly supported by the National Key R&D Program of China (2018YFC1505803), the National Natural Science Foundation of China (Grant No. 41775074) and the Foundation for Innovative Research Groups of the National Natural Science Foundation of China (Grant No. 41621005).

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