• Chen, M., W. Shi, P. Xie, V. B. S. Silva, V. E. Kousky, R.W. Higgins, J. E. Janowiak, 2008: Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res. 113, D04110, https://doi.org/10.1029/2007JD009132.

    • Search Google Scholar
    • Export Citation
  • Chen, Y., and P. Zhai, 2014: Two types of typical circulation patterns for the persistent extreme precipitation in central-eastern China. Quart. J. Roy. Meteor. Soc., 140, 14671478, https://doi.org/10.1002/qj.2231.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., D. Neelin, A. Chen, and Y. Tu, 2009: Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J. Climate, 22, 19822005, https://doi.org/10.1175/2008JCLI2471.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., H. Chiang, W. Lan, H. Chung, C. Liao, and J. Lee, 2013: Increase in the range between wet and dry season precipitation. Nat. Geosci., 6, 263267, https://doi.org/10.1038/ngeo1744.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Y., and J. Chan, 2005: The East Asian summer monsoon: An overview. Meteor. Atmos. Phys., 89, 117142, https://doi.org/10.1007/s00703-005-0125-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, W., L. Wang, Z.-Z. Hu, K. Hu, and Y. Li, 2018: Interannual variations of the first rainy season precipitation over South China. J. Climate, 31, 623640, https://doi.org/10.1175/JCLI-D-17-0284.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hitchens, N., H. Brooks, and R. Schumacher, 2013: Spatial and temporal characteristics of heavy hourly rainfall in the United States. Mon. Wea. Rev., 141, 45644575, https://doi.org/10.1175/MWR-D-12-00297.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, W., and Coauthors, 2019: A possible mechanism for the occurrence of wintertime extreme precipitation events over South China. Climate Dyn., 52, 23672384, https://doi.org/10.1007/s00382-018-4262-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jia, X., Y. You, R. Wu, and Y. Yang, 2019: Interdecadal changes in the dominant modes of the interannual variation of spring precipitation over China in the mid-1980s. J. Geophys. Res., 124, 10 67610 695, https://doi.org/10.1029/2019JD030901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuang, X., and Y. Zhang, 2005: Seasonal variation of the East Asian subtropical westerly jet and its association with the heating field over East Asia. Adv. Atmos. Sci., 22, 831840, https://doi.org/10.1007/BF02918683.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, C., J.-T. Wang, S.-Z. Lin, and H.-R. Cho, 2004: The relationship between East Asian summer monsoon activity and northward jump of the upper westerly jet location (in Chinese). Chin. J. Atmos. Sci., 28, 641658, https://doi.org/10.3878/j.issn.1006-9895.2004.05.01.

    • Search Google Scholar
    • Export Citation
  • Li, J., and L. Zhu, 2008: Climatological features of the western Pacific subtropical high southward retreat process in late-spring and early-summer (in Chinese). Acta Meteor. Sin., 66, 926939, https://doi.org/10.11676/qxxb2008.084.

    • Search Google Scholar
    • Export Citation
  • Li, J., and J. Mao, 2019: Coordinated influences of the tropical and extratropical intraseasonal oscillations on the 10–30-day variability of the summer rainfall over southeastern China. Climate Dyn., 53, 137153, https://doi.org/10.1007/s00382-018-4574-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, L., W. Li, and A. P. Barros, 2013: Atmospheric moisture budget and its regulation of the summer precipitation variability over the southeastern United States. Climate Dyn., 41, 613631, https://doi.org/10.1007/s00382-013-1697-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, S., C. Wang, J. Yan, and X. Liu, 2020: Variability of the event-based extreme precipitation in the south and north Qinling. Mountains (in Chinese). Acta Geogr. Sin., 75, 9891007, https://doi.org/10.11821/dlxb202005008.

    • Search Google Scholar
    • Export Citation
  • Liu, B., G. Wu, J. Mao, and J. He, 2013: Genesis of the South Asian high and its impact on the Asian summer monsoon onset. J. Climate, 26, 29762991, https://doi.org/10.1175/JCLI-D-12-00286.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, B., Y. Liu, G. Wu, J. Yan, J. He, and S. Ren, 2015: Asian summer monsoon onset barrier and its formation mechanism. Climate Dyn., 45, 711726, https://doi.org/10.1007/s00382-014-2296-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lu, R., Z. Lin, and Y. Zhang, 2013: Variability of the East Asian upper-tropospheric jet in summer and its impacts on the East Asian monsoon (in Chinese). Chin. J. Atmos. Sci., 37, 331340, https://doi.org/10.3878/j.issn.1006-9895.2012.

    • Search Google Scholar
    • Export Citation
  • Mao, J., and G. Wu, 2007: Interannual variability in the onset of summer monsoon over the eastern Bay of Bengal. Theor. Appl. Climatol., 89, 155170, https://doi.org/10.1007/s00704-006-0265-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pendergrass, A., 2018: What precipitation is extreme? Science, 6393, 10721073, https://doi.org/10.1126/science.aat1871.

  • Peng, D., and T. Zhou, 2017: Why was the arid and semiarid northwest China getting wetter in the recent decades? J. Geophys. Res. Atmos., 122, 90609075, https://doi.org/10.1002/2016JD026424.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, J.-H., W.-K. Tao, and K. Lau, 2004: Mechanisms for torrential rain associated with the mei-yu development during SCSMEX 1998. Mon. Wea. Rev., 132, 327, https://doi.org/10.1175/1520-0493(2004)132<0003:MFTRAW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., and N. Henderson, 2013: Diagnostic computation of moisture budgets in the ERA-Interim reanalysis with reference to analysis. J. Climate, 26, 78767901, https://doi.org/10.1175/JCLI-D-13-00018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., N. Naik, and G. Vecchi, 2010: Thermodynamic and dynamic mechanisms for large-scale changes in hydrological cycle in response to global warming. J. Climate, 23, 46514668, https://doi.org/10.1175/2010JCLI3655.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shang, W., S. Li, X. Ren, and K. Duan, 2020: Event-based extreme precipitation in central-eastern China: Large-scale anomalies and teleconnections. Climate Dyn., 54, 23472360, https://doi.org/10.1007/s00382-019-05116-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • She, D., Q. Shao, J. Xia, J. Taylor, Y. Zhang, L. Zhang, X. Zhang, and L. Zou, 2015: Investigating the variation and non-stationarity in precipitation extremes based on the concept of event-based extreme precipitation. J. Hydrol., 530, 785798, https://doi.org/10.1016/j.jhydrol.2015.10.029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, C., and S. Yang, 2012: Persistent severe drought in southern China during winter–spring 2011: Large-scale circulation patterns and possible impacting factors. J. Geophys. Res., 117, D10112, https://doi.org/10.1029/2012JD017500.

    • Search Google Scholar
    • Export Citation
  • Takaya, K., and H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608627, https://doi.org/10.1175/1520-0469(2001)058,0608:AFOAPI.2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Z., A. Duan, S. Yang, and K. Ullah, 2017: Atmospheric moisture budget and its regulation on the variability of summer precipitation over the Tibetan Plateau. J. Geophys. Res. Atmos., 122, 614630, https://doi.org/10.1002/2016JD025515.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, T., and K. Yamazaki, 2014: The upper-level circulation anomaly over central Asia and its relationship to the Asian monsoon and mid-latitude wave train in early summer. Climate Dyn., 42, 24772489, https://doi.org/10.1007/s00382-013-1888-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, X., S. Guo, J. Yin, G. Yang, Y. Zhong, and D. Liu, 2018: On the event-based extreme precipitation across China: Time distribution, trends and return levels. J. Hydrol., 562, 305417, https://doi.org/10.1016/j.jhydrol.2018.05.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., A. Yatagai, M. Chen, T. Hayasaka, Y. Fukushima, C. Liu, and S. Yang, 2007: A gauge-based analysis of daily precipitation over East Asia. J. Hydrometeor., 8, 607627, https://doi.org/10.1175/JHM583.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xing, N., J. Li, and L. Wang, 2016: Effect of the early and late onset of summer monsoon over the Bay of Bengal on Asian precipitation in May. Climate Dyn., 47, 19611970, https://doi.org/10.1007/s00382-015-2944-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiong, Y., and X. Ren, 2021: Influence of atmospheric rivers on North Pacific winter precipitation: Climatology and dependence on ENSO condition. J. Climate, 34, 277292, https://doi.org/10.1175/JCLI-D-20-0301.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, C., Y. Qian, and M. Jian, 2019: Interdecadal change in the intensity of interannual variation of spring precipitation over southern China and possible reasons. J. Climate, 32, 58655881, https://doi.org/10.1175/JCLI-D-18-0351.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, J., Q. Bao, B. Wang, Z. He, M. Gao, and D. Gong, 2017: Characterizing two types of transient intraseasonal oscillations in the eastern Tibetan Plateau summer rainfall. Climate Dyn., 48, 17491768, https://doi.org/10.1007/s00382-016-3170-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, S., and T. Li, 2017: The role of intraseasonal variability at mid-high latitudes in regulating Pacific blockings during boreal winter. Int. J. Climatol., 37, 12481256, https://doi.org/10.1002/joc.5080.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, M., and J. Sun, 2017: Enhancement of the spring East China precipitation response to tropical sea surface temperature variability. Climate Dyn., 51, 30093021, https://doi.org/10.1007/s00382-017-4061-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, W., T. Zhou, and L. Zhang, 2017: Wetting and greening Tibetan Plateau in early summer in recent decades. J. Geophys. Res. Atmos., 122, 58085822, https://doi.org/10.1002/2017JD026468.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, B., and P. Zhao, 2010: Influence of the Asian-Pacific oscillation on spring precipitation over central eastern China. Adv. Atmos. Sci., 27, 575582, https://doi.org/10.1007/s00376-009-9058-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, T.-J., and R.-C. Yu, 2005: Atmospheric water vapor transport associated with typical anomalous summer rainfall patterns in China. J. Geophys. Res., 110, D08104, https://doi.org/10.1029/2004JD005413.

    • Search Google Scholar
    • Export Citation
  • Zhu, C., T. Nakazawa, and L. Chen, 2003: The 30–60 day intraseasonal oscillation over the western North Pacific Ocean and its impacts on summer flooding in China during 1998. Geophys. Res. Lett., 30, 1952, https://doi.org/10.1029/2003GL017817.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zuluaga, M., and J. Houze, 2015: Extreme convection of the near-equatorial Americas, Africa, and adjoining oceans as seen by TRMM. Mon. Wea. Rev., 143, 298316, https://doi.org/10.1175/MWR-D-14-00109.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • View in gallery

    (a) Maps of the rain gauge stations in central-eastern China and schematic diagram anomalous signals from the midlatitudes and subtropics (green arrows). (b) The concept of the EEP events is defined as the continuity of a precipitation event characterized by at least one daily precipitation that exceeds the 90th percentile. The EEP events in this study are extreme precipitation (blue bar) occurring in the first half of the event duration.

  • View in gallery

    (a) The total days of the regional EEP events (extreme precipitation occurring in the first half of the event) in central-eastern China during 1961–2014 from January to December. (b) As in (a), but for the gauge station numbers.

  • View in gallery

    Composite of precipitation (shaded; mm day−1) for spring EEP events of (a) observations during 1961–2014 and (b) NOAA/CPC during 1979–2014. The red box in (a) indicates the region of central-eastern China.

  • View in gallery

    Lead–lag composites of 200-hPa horizontal wind anomalies (vectors; m s−1) and meridional wind anomalies (contours; m s−1) for the spring EEP events at (a) day −9, (b) day −7, (c) day −5, (d) day −3, (e) day −1, (f) day 0, (g) day +3, and (h) day +5. The contour intervals are 1.0 m s−1 with negative contours dashed. Only anomalies statistically significant at the 95% level are plotted. The red box marks central-eastern China.

  • View in gallery

    As in Fig. 4, but for 500-hPa geopotential height anomalies (shaded; gpm), and wave activity flux (vectors; m−2 s−2). Only anomalies statistically significant at the 95% confidence level are plotted. The black box indicates the key domain.

  • View in gallery

    Composite of integrated moisture flux (vectors; kg m−1 s−1) and its divergence (shaded; 10−4 kg m−2 s−1) for spring EEP events at (a) day −7, (b) day −5, (c) day −3, and (d) day 0. (e)–(h) As in (a)–(d), but for integrated moisture flux anomalies. The dotted fields and plotted vectors exceed the 95% significance confidence level.

  • View in gallery

    (a) Latitude–time section of composites anomalies of zonal wind (contours with interval of 3 m s−1) and zonal wind anomalies (shaded; m s−1) for spring EEP events at 200 hPa averaged along 70°–120°E. (b) As in (a), but for the longitude–time section averaged along 40°–45°N.

  • View in gallery

    Scatter diagram plotting the relationship between the normalized onset dates of BOBSM (x axis) and start dates of EEP events (y axis). The linear fit is shown by the blue solid line.

  • View in gallery

    Composite anomalies of nine terms of Vhq in Eq. (3) denoted H1–H9 (green bars; mm day−1) and ωpq in Eq. (4) denoted Z1–Z9 (yellow bars, mm day−1) for the spring EEP events at (a) day −7, (b) day −5, (c) day −3, and (d) day 0 averaged over 27°–37°N, 100°–120°E.

  • View in gallery

    (a) Latitude–time section (averaged over 100°–120°E) of composite anomalies in moisture convergence of uq¯/x (DX; shaded; mm day−1). (b) Longitude–time section (averaged over 27°–37°N) of DX (shaded; mm day−1) for spring EEP events. (c),(d) As in (a) and (b), respectively, but for υq¯/y (DY; shaded; mm day−1). The black line denotes the statistically significant 95% confidence level.

  • View in gallery

    Composite anomalies in moisture convergence of uq¯/x (DX; red line; mm day−1), υq¯/y (DY; dark blue line; mm day−1), u¯q/x (TX; green line; mm day−1), υ¯q/y (TY; light blue line; mm day−1), ωpq¯ (DZ; purple line; mm day−1), and ω¯pq (TZ; yellow line; mm day−1) averaged over 27°–37°N, 100°–120°E.

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Precursors and Formation Mechanisms of Event-Based Extreme Precipitation during Springtime in Central-Eastern China

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  • 1 a School of Geography and Tourism, Shaanxi Normal University, Xi’an, China
  • | 2 b China Meteorological Administration–Nanjing University Joint Laboratory for Climate Prediction Studies, School of Atmospheric Sciences, Nanjing University, Nanjing, China
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Abstract

This study investigates the precursors and formation mechanisms of spring (April–May) event-based extreme precipitation (EEP) during 1961–2014 in central-eastern China. The EEP events during springtime are primarily characterized by extreme precipitation that occurs at the first half of an event. During early stages of spring EEP events, a Rossby wave grows over western Europe and the North Atlantic Ocean. The wave propagates eastward toward East Asia, exhibiting a circumglobal teleconnection (CGT) pattern. A strong anticyclone related to the CGT pattern is formed over the islands of Japan in the upper troposphere, enhancing the divergence anomalies and bringing more water vapor anomalies from the Sea of Japan into central-eastern China. Meanwhile, the westerly jet jumps northward and anomalous southwesterly water vapor flux is significantly prevalent, both associated with the onset of the Bay of Bengal summer monsoon (BOBSM). When the anomalous southwesterly and northeasterly moisture fluxes into central-eastern China combine, strong convergence is formed, providing abundant water vapor for extreme precipitation. The moisture budget analysis further suggests that the dynamic processes associated with horizontal wind anomalies play a crucial role in the moisture convergence for the spring EEP events. The advection of zonal and meridional moisture is strongly related to the anomalous winds of the CGT waves and BOBSM, respectively; the horizontal thermodynamic processes related to specific humidity and vertical advection contribute much less. The results indicate the preceding signals in the midlatitudes and subtropics for the spring EEP events, enabling extreme precipitation forecasting and hydrological prediction.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Wei Shang, shangwei@snnu.edu.cn

Abstract

This study investigates the precursors and formation mechanisms of spring (April–May) event-based extreme precipitation (EEP) during 1961–2014 in central-eastern China. The EEP events during springtime are primarily characterized by extreme precipitation that occurs at the first half of an event. During early stages of spring EEP events, a Rossby wave grows over western Europe and the North Atlantic Ocean. The wave propagates eastward toward East Asia, exhibiting a circumglobal teleconnection (CGT) pattern. A strong anticyclone related to the CGT pattern is formed over the islands of Japan in the upper troposphere, enhancing the divergence anomalies and bringing more water vapor anomalies from the Sea of Japan into central-eastern China. Meanwhile, the westerly jet jumps northward and anomalous southwesterly water vapor flux is significantly prevalent, both associated with the onset of the Bay of Bengal summer monsoon (BOBSM). When the anomalous southwesterly and northeasterly moisture fluxes into central-eastern China combine, strong convergence is formed, providing abundant water vapor for extreme precipitation. The moisture budget analysis further suggests that the dynamic processes associated with horizontal wind anomalies play a crucial role in the moisture convergence for the spring EEP events. The advection of zonal and meridional moisture is strongly related to the anomalous winds of the CGT waves and BOBSM, respectively; the horizontal thermodynamic processes related to specific humidity and vertical advection contribute much less. The results indicate the preceding signals in the midlatitudes and subtropics for the spring EEP events, enabling extreme precipitation forecasting and hydrological prediction.

© 2021 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Wei Shang, shangwei@snnu.edu.cn

1. Introduction

Spring precipitation has a substantial impact on agricultural investment and water resource management. Central-eastern China is located along the Yellow River and Yangtze River Valley, and severe floods or droughts can greatly affect social economic and water systems in this region (Zhou and Zhao 2010; Zhang and Sun 2017). Even though it is known that in the main belt in South China the first rainy season runs from approximately 6 April to 4 June (Ding and Chan 2005; Gu et al. 2018), an investigation into the extreme precipitation observed in central-eastern China during springtime remains necessary. Furthermore, the current understanding of forecasting regional extreme precipitation is not comprehensive, owing to not only the quantitative definition of the regional extreme precipitation events, but also the physical mechanisms and preceding signals of correlative atmospheric anomalies.

The methods employed to identify extreme precipitation events significantly influence our understanding of their seasonal features, as well as the prediction of associated flooding and hydrological parameters (She et al. 2015; Pendergrass 2018). Thus, the concept of event-based extreme precipitation (EEP), which is defined as a continuous precipitation event characterized by at least one daily precipitation event that exceeds the 90th percentile, has been proposed. Unlike when extreme precipitation intensities or durations in days are the sole focus, the EEP emphasizes the time distribution of extreme precipitation throughout an event (Wu et al. 2018; Li et al. 2020). The trends and interannual variations of EEP events over China have been illustrated in hydrological and geographical horizons (Hitchens et al. 2013; Zuluaga and Houze 2015). Recently, Shang et al. (2020) revealed that the different types of EEP events show season-related characteristics; for example, EEP events that develop in spring are primarily characterized by extreme precipitation occurring in the first half part of the event. The definition of EEP events highlights the different temporal distribution patterns of extreme precipitation. This provides new and important insights into accurately forecasting extreme precipitation and managing hydrological resources and conditions, which is crucial for preventing flooding disasters and reducing associated damages. Thus, we aim to demonstrate the possibly predictive signals and favorable conditions of the spring EEP events in this study.

Previous studies have been focused on the interannual and decadal variations of spring precipitation in East Asia, which have suggested that the western Pacific subtropical high (WPSH), Eurasian snow, and sea surface temperature anomalies in the western tropical Pacific Ocean may be impact factors (Zhou and Zhao 2010; Sun and Yang 2012; Gu et al. 2018; Jia et al. 2019; Xu et al. 2019). At the subseasonal time scale, it has been illustrated that the persistent extreme precipitation over East Asia is associated with mid-high-latitude anomalies of atmospheric circulation anomalies and intraseasonal oscillation from the tropics (Zhu et al. 2003; Chen and Zhai 2014; Watanabe and Yamazaki 2014; Yang et al. 2017; Yang and Li 2017). Li and Mao (2019) reported that the persistent precipitation over southeastern China is anchored by strong ascents, mainly caused by eastward-propagating Rossby waves and 10–30-day atmosphere oscillations. Huang et al. (2019) revealed that the Rossby waves from European continents, which are related to circumglobal teleconnection (CGT) with blocking highs, result in extreme precipitation in southern China. Nevertheless, most of these studies have focused on the mechanisms or conditions necessary for extreme precipitation in South China. The early stage of the signals and the lead–lag favorable conditions of atmospheric circulations, especially for the springtime extreme precipitation in central-eastern China at synoptic to subseasonal time scales, remain far from conclusive.

During the late April to May period, the Bay of Bengal summer monsoon (BOBSM) primarily originates in the subtropical regions, which can drive changes in the atmospheric circulations and enhance the moisture transport over the Asian monsoon regions (Mao and Wu 2007; Liu et al. 2013, 2015). Previous studies have shown that the transportation of the water vapor flux for extreme precipitation events observed in East Asia is dominantly related to the WPSH or the southwesterly winds from the BOBSM regions (Qian et al. 2004; Zhou and Yu 2005; Xing et al. 2016). Furthermore, the anomalous moisture transport convergence could be affected by both the dynamic components and thermodynamic components. The former is primarily related to atmospheric circulation anomalies. The latter is mainly linked to changes in specific humidity, which are in turn closely tied to temperature changes through the Clausius–Clapeyron relationship (Seager et al. 2010; Chou et al. 2013; Zhang et al. 2017, Xiong and Ren 2021). Extreme precipitation events in different regions may be impacted by distinct factors of moisture transport. For instance, precipitation anomalies over the Tibetan regions are dominantly influenced by the anomalous wind convergence, whereas for northwestern China anomalous circulations and increased specific humidity both play a role (Peng and Zhou 2017; Wang et al. 2017; Zhang et al. 2017). In our previous work (Shang et al. 2020) instances of springtime EEP events over central-eastern China were selected for examination. However, the physical mechanisms associated with the moisture flux convergence behind the spring EEP events have not yet been clarified. Here, we analyze the possible relationship between the spring EEP events and the onset of the BOBSM, and the dynamic and thermodynamic processes of water vapor convergence are identified to reveal the different roles of atmospheric circulation and specific humidity anomalies responsible for the spring EEP events.

In this study, we attempt to investigate the early stage of atmospheric signals and physical mechanisms that favor the occurrence of spring EEP events. The paper is structured as follows: the data and methods are described in section 2. The lead–lag atmospheric circulation anomalies of spring EEP events and their relationship to the onset of BOBSM are discussed in section 3. The moisture budget analysis associated with spring EEP events is demonstrated in section 4. Finally, section 5 has a summary and discussion. The objective of this study is to identify the precursors and conditions in formation of the spring EEP events in order to enhance spring extreme precipitation prediction over central-eastern China on an extended-range time scale.

2. Data and methods

a. Datasets

The datasets used include the following: 1) a dataset of daily precipitation at 765 rain gauge stations during the period of 1961–2014 from the Climate Data Center, China Meteorological Administration (CMA), and 196 stations distributed across central-eastern China (Fig. 1a); 2) daily global precipitation of 0.5° × 0.5° provided by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) for 1979–2014 (Xie et al. 2007; Chen et al. 2008); and 3) daily reanalysis data for geopotential height, surface pressure, horizontal wind, vertical velocity, and specific humidity on a 2.5° × 2.5° horizontal resolution for 1961–2014 period, obtained from the National Centers for Environmental Predication and National Center for Atmospheric Research (NCEP–NCAR) (Kalnay et al. 1996). The onset date of the BOBSM is identified based on the reversal of meridional air temperature gradient in the mid- to upper troposphere as reported by Mao and Wu (2007) and Liu et al. (2015).

Fig. 1.
Fig. 1.

(a) Maps of the rain gauge stations in central-eastern China and schematic diagram anomalous signals from the midlatitudes and subtropics (green arrows). (b) The concept of the EEP events is defined as the continuity of a precipitation event characterized by at least one daily precipitation that exceeds the 90th percentile. The EEP events in this study are extreme precipitation (blue bar) occurring in the first half of the event duration.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

b. Methods

In this study, the EEP events are selected according to the method proposed by Shang et al. (2020). For each station point, daily extreme precipitation is defined as daily precipitation exceeding the 90th percentile of all wet days (wet days mean daily precipitation exceeding 0.1 mm) during 1961–2014. A single-station EEP event is identified as a precipitation event characterized by daily precipitation that exceeds 0.1 mm for more than three consecutive days, with at least one daily precipitation exceeding the statistical 90th percentile. The EEP events could be classified into several categories based on their time distribution patterns of extreme precipitation (Shang et al. 2020).

If a given EEP event is recorded by at least 30% of the gauge stations, it is considered as a regional EEP event. As reported by Shang et al. (2020), the springtime EEP events are characterized by the extreme precipitation occurring at the first part of the event, which is displayed in Fig. 1b for the schematic diagram. Figure 2a gives the total days of these regional EEP events during the period from 1961 to 2014. It can be seen that they dominantly occurred in April and May and also have more extensive coverage, with more gauge stations recording them than in other months (Fig. 2b). Thus, we focus on the EEP events in April and May, which are characterized by extreme precipitation occurring at the first part of the event duration in this study. There are 23 events selected between April and May during 1961–2014 to use the time-lead composite analysis. Detailed information about start dates and end dates of the 23 events is summarized in Table S1 in the online supplemental material. Day 0 is defined as the precipitation dates of the simultaneous composite. Day −n represents the number of days before the occurrence of the events.

Fig. 2.
Fig. 2.

(a) The total days of the regional EEP events (extreme precipitation occurring in the first half of the event) in central-eastern China during 1961–2014 from January to December. (b) As in (a), but for the gauge station numbers.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

To demonstrate the characteristics and energy dispersion of the Rossby waves, a wave-activity flux for stationary Rossby waves (W) proposed by Takaya and Nakamura (2001) is adopted in this work, defined as
W=12|U¯|[u¯(ψx2ψxψxx)+υ¯(ψxψyψψxy)u¯(ψxψyψψxy)+υ¯(ψy2ψψyy)],
where is ψ the streamfunction and U¯ is the climatology of the horizontal vector wind (u, υ). An overbar in a variable is its long-term mean in the corresponding season. Subscript and prime notations in a variable represent the partial differential and daily anomalies, respectively.

c. Atmospheric moisture budget

The procedure of extracting synoptic to subseasonal variations has two steps. First, the daily anomalies are computed by removing the daily climatology of the corresponding days from the raw data. Second, the interannual and decadal signals are deducted through the elimination of seasonal anomalies. The daily anomalies of atmospheric variables are extracted by the two steps before composite and diagnostic analysis in this study.

Regional precipitation is governed by local evaporation and remote moisture transport. To understand the physical mechanisms underlying the moisture transport anomalies for extreme precipitation, we perform a moisture budget diagnostic analysis. The anomalous moisture budget derivation is similar to the equations in Chou et al. (2009, 2013) and Seager and Henderson (2013) (shown in the online supplemental material). The anomalous variables of the moisture budget in this study are extracted by synoptic-to-subseasonal time scale. Moreover, the dynamic and thermodynamic processes of the moisture convergence anomalies are also diagnosed to evaluate the contributions of atmospheric circulations and specific humidity anomalies.

When a variable (e.g., X) is decomposed, we distinguish its climatological mean (overbar, X¯) and synoptic-to-subseasonal anomalies (single prime, X′) and non-synoptic-to-subseasonal component (double prime, X″, including the time scales except for synoptic to subseasonal, such as interannual and decadal time scales). The synoptic to subseasonal anomalies are extracted by the method at begin of section 2c. The non-synoptic-to-subseasonal component is calculated as the raw daily data minus the daily climatology and the synoptic to subseasonal anomalies (X=XX¯X).

The integrated moisture budget at synoptic-to-subseasonal time scale is expressed as follows:
P=EtqVhqωpq,
where q is the specific humidity, E is the evapotranspiration rate, P is the precipitation rate, V is the horizontal wind vector (u, υ), and ω is the vertical pressure velocity. The angle brackets (⟨⋅⟩) denote a vertical integration from surface pressure to 300 hPa [X=(1/g)300PsXdp]. The unit in Eq. (2) is mm day−1. The ∂tq⟩′ term represents the tendency term of specific humidity, which are small compared with other terms and can be ignored. The evaporation anomalies are also much smaller in this study.
The term −⟨V ⋅ ∇h q⟩′ and term −⟨ωp q⟩′ represent the anomalous horizontal and vertical moisture advection at synoptic-to-subseasonal time scale. They can be further decomposed as shown below:
Vhq=V¯hq¯H1V¯hqH2V¯hqH3Vhq¯H4VhqH5VhqH6Vhq¯H7VhqH8VhqH9,
ωpq=ω¯pq¯Z1ω¯pqZ2ω¯pqZ3ωpq¯Z4ωpqZ5ωpqZ6ωpq¯Z7ωpqZ8ωpqZ9.

The diagnostic analysis of all the terms in Eqs. (3) and (4) is provided in section 4.

All the values included in the moisture budget and geopotential height are extracted by the synoptic to subseasonal anomalies. Before the preprocessing, the raw precipitation observation data are also used in order to get the start dates, end dates, and station numbers of the EEP events. Student’s t test with a confidence level of 95% is performed to examine the statistical significance of the composite fields. Effective sample lengths are also used to estimate the temporal persistence in composite anomalies.

3. Lead–lag circulation patterns for the spring EEP events

a. The evolution of circulation anomalies

Figure 3a depicts the composite of precipitation for the spring EEP events. It can be seen that when the EEP events occur, rainfall is dominant over central-eastern China. There are two rainfall centers located over the middle and lower reaches of the Yangtze River. The rainfall mean intensity for the EEP events is about 16–18 mm day−1 over the Yangtze River valley. The precipitation distribution in NOAA/CPC has a pattern similar to the observation data (Fig. 3b). However, it is shown as a rainfall band along the Yangtze River with a slightly higher intensity, which may be related to a shorter period of the NOAA/CPC dataset.

Fig. 3.
Fig. 3.

Composite of precipitation (shaded; mm day−1) for spring EEP events of (a) observations during 1961–2014 and (b) NOAA/CPC during 1979–2014. The red box in (a) indicates the region of central-eastern China.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

To explore the preceding signals from midlatitudes, the lead–lag composite anomalies of horizontal and meridional winds at 200 hPa are investigated (Fig. 4). On day −9, the anomalous winds are rather weak and slightly positive and negative over the Eurasian continent, far away from central-eastern China. During day −7 to day −5, there is an increase in the intensity of these anomalous winds and they propagate eastward, initiating an anticyclone disturbance that is observed over western Europe. The following centers of this disturbance are positioned over the eastern European plain, western Siberia, and central Asia, showing a wave train. On day −5, an anomalous anticyclone associated with this wave train propagates to northern China, partially splitting toward the Arabian Sea and fading away gradually. Meanwhile, a weak wave train grows over western North America, and thereafter its center is positioned over the San Francisco Bay area of California, the North Pacific, and the Sea of Japan, propagating slightly westward. On day −3, these two wave trains merge, resulting in strong northerly wind anomalies over the islands of Japan and a strong anomalous anticyclone that prevails over northeastern China and the Korean Peninsula. During day −3 to day 0, the waves become more intense and exhibit a GCT-like pattern. The anticyclone anomalies enhance the upper-level divergence and convey relatively cold air southward into central-eastern China, which provides conditions for spring EEP events. Between day +3 and day +5, the CGT-like pattern remains clear; however, the northerly wind anomalies over the East Asia are reduced and weakened. The cyclone and anticyclone anomalies over the Eurasian continent also declined slowly.

Fig. 4.
Fig. 4.

Lead–lag composites of 200-hPa horizontal wind anomalies (vectors; m s−1) and meridional wind anomalies (contours; m s−1) for the spring EEP events at (a) day −9, (b) day −7, (c) day −5, (d) day −3, (e) day −1, (f) day 0, (g) day +3, and (h) day +5. The contour intervals are 1.0 m s−1 with negative contours dashed. Only anomalies statistically significant at the 95% level are plotted. The red box marks central-eastern China.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

The CGT-like pattern observed could also be seen clearly in the geopotential height anomalies at 500 hPa (Fig. 5). During day −9 to day −7, weakly positive and negative geopotential height anomalies are present over the Eurasian and western North American continents. At the same time, the horizontal wave-active flux (WAF) anomalies emerge from North Atlantic and propagate eastward. During day −5 to day −3, the Rossby wave propagates eastward along the westerly jet and the WAF energy subsequently arrive in East Asia. After then, the eastward-propagating waves, together with the alternative positive and negative anomalies over the North Pacific, display a CGT-like pattern. The CGT wave trains show an equivalent barotropic structure in the midlatitudes. This CGT-like anomalous pattern become more intensive and stable during day −3 to day 0. After day 0, the CGT-like pattern becomes weakened and dissipates locally and the WAF energy propagates eastward to the North Pacific regions. The above analysis indicates that the precursory CGT Rossby waves significantly contribute to the spring EEP events over central-eastern China. The prediction of the EEP events could be associated with forecast of the midlatitude signals. However, detailed study about the prediction skills oversteps the aim of the present study and further research may be carried out in the future.

Fig. 5.
Fig. 5.

As in Fig. 4, but for 500-hPa geopotential height anomalies (shaded; gpm), and wave activity flux (vectors; m−2 s−2). Only anomalies statistically significant at the 95% confidence level are plotted. The black box indicates the key domain.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

b. Influence of the Bay of Bengal summer monsoon

To demonstrate the water vapor transport associated with the spring EEP events, the composite of integrated moisture fluxes and their anomalies with divergence are shown in Fig. 6. On day −7, the moisture fluxes are rather weak with transporting from the western Pacific to the Indochina Peninsula and southern China. After that, the cross-equatorial flow strongly enhances during day −3 to day 0, with southwesterly moisture transport from the Bay of Bengal to central-eastern China. The southwesterly moisture flux is decreased in northward propagation over northern China, and thus, the convergence is increased over central-eastern China, providing favorable conditions for the EEP events.

Fig. 6.
Fig. 6.

Composite of integrated moisture flux (vectors; kg m−1 s−1) and its divergence (shaded; 10−4 kg m−2 s−1) for spring EEP events at (a) day −7, (b) day −5, (c) day −3, and (d) day 0. (e)–(h) As in (a)–(d), but for integrated moisture flux anomalies. The dotted fields and plotted vectors exceed the 95% significance confidence level.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

With respect to the moisture flux anomalies, weak anomalous southerly and anomalous northerly winds characterized by few moisture anomalies prevail in central-eastern China during day −7. During day −5 to day −3, owing to the enhanced cross-equatorial flow, the southwesterly water vapor anomalies prevail from the Bay of Bengal to the Indochina Peninsula. During day −3 to day 0, the intensity of the anomalous southwesterly moisture flux transport further enhances with more water vapor being carried to central-eastern China. Meanwhile, the anomalous northeasterly moisture flux also increases substantially. The anomalous southwesterly and northeasterly moisture flux into central-eastern China strongly converge, provided abundant water vapor for extreme precipitation. After day 0, the southwesterly water vapor flux retreats to South China Sea, and the anomalous northerly moisture flux again dominates with anomalous divergence over central-eastern China. Hence, the spring EEP events in central-eastern China are greatly affected by the anomalous water vapor transport from subtropical regions.

Figures 7a and 7b display the evolution of the zonal winds and their anomalies averaged over 40°–45°N, 70°–120°E at 200 hPa for the spring EEP events. The positive zonal wind anomalies related to the Rossby wave propagate southward and eastward from the Eurasian continent from day −9 to day −5. During day −4 to day 0, the westerly jet strengthens and jumps northward to 30°N, representing the waveguide for the Rossby wave propagating eastward to East Asia. The enhancement processes of the southwesterly moisture transportation and northward jumping of the westerly jet indicate that there is an abrupt seasonal transition in atmospheric circulations at the onset of the Asian summer monsoon (Li et al. 2004; Kuang and Zhang 2005; Lu et al. 2013). During springtime, the BOBSM has a first general onset during late April to early May (Mao and Wu 2007; Liu et al. 2015), indicating that there is a connection between the occurrence of the spring EEP events over central-eastern China and the onset of the BOBSM.

Fig. 7.
Fig. 7.

(a) Latitude–time section of composites anomalies of zonal wind (contours with interval of 3 m s−1) and zonal wind anomalies (shaded; m s−1) for spring EEP events at 200 hPa averaged along 70°–120°E. (b) As in (a), but for the longitude–time section averaged along 40°–45°N.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

To further check the relationship between the spring EEP events and BOBSM onset, Fig. 8 plots a scatter diagram between starting dates of each spring EEP events and the onset dates of BOBSM. It can be seen that about 73% of the EEP cases fall into the top-right or bottom-left quadrants. The blue solid line in Fig. 8 demonstrates the linear fit between the spring EEP events and the BOBSM onset with the correlation coefficient (r = 0.52) being statistically significant at the 95% confidence level. This indicates that a quasi-linear relationship is shown between the spring EEP events and the BOBSM. Earlier (later) onsets of the BOBSM are generally associated with advanced (delayed) spring EEP events. In addition, we also analyzed the lead composite of the stream fields at 200 hPa and 5860-gpm line of the WPSH at 500 hPa from day −9 to day 0 (figures not shown). The South Asian high migrates northwestward from the South China Sea during day −9 to day −5 and establishes at the Indochina Peninsula on day −3, which is conductive to trigger the onset of the BOBSM (Liu et al. 2013). Influenced by the seasonal transition and Asian summer monsoon onset, the 5860-gpm line of the WPSH retreats eastward and becomes slightly weakened (Li and Zhu 2008). Therefore, the occurrence of the spring EEP events over central-eastern China has a close relationship with the onset of the BOBSM. This further suggests that the onset dates of the BOBSM may be a possible precursor for the spring EEP events at synoptic to subseasonal time scales.

Fig. 8.
Fig. 8.

Scatter diagram plotting the relationship between the normalized onset dates of BOBSM (x axis) and start dates of EEP events (y axis). The linear fit is shown by the blue solid line.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

4. Atmospheric moisture budget analysis

As mentioned in Eqs. (3) and (4), the moisture convergence that drives variations in precipitation can be affected by several terms. Specially, the terms determined by atmospheric circulation anomalies are called dynamic processes and the ones related to specific humidity changes are called thermodynamic processes. However, it remains unclear how these two processes impact the spring EEP events and what terms are the most significant factors. To resolve these uncertainties, we perform moisture budget analysis to diagnose the physical mechanisms driving the spring EEP events.

Figure 9 shows the composite anomalies of all the terms in Eqs. (3) and (4) from day −7 to day 0 averaged over central-eastern China. It can be seen that the horizontal moisture advection terms V¯hq (H2) and Vhq¯ (H4) play the most significant role of all the terms. The vertical moisture advection terms ω¯pq (Z2) and ωpq¯ (Z4) are in the second place. They are much larger than other terms during day −7 to day 0. The terms Vhq¯ and ωpq¯ are the horizontal and vertical dynamic terms, which indicate the contribution of atmospheric circulation changes to moisture convergence anomalies. In these terms, q¯ is the climatology of the specific humidity, which is an invariant constant. The terms V′ and ω′ are the synoptic to subseasonal anomalies of horizontal winds and vertical velocity. Thus, the values of Vhq¯ and ωpq¯ depend on the anomalies of atmospheric circulations. The thermodynamic processes represent the contribution of specific humidity changes to the moisture convergence anomalies. For example, V¯hq is the horizontal thermodynamic term. In this term, V¯ is the climatology of the winds and ∇h q′ is the gradient of specific humidity anomalies. The term V¯hq depends on the changes of specific humidity, which is in turn closely linked to temperature changes via the Clausius-Clapeyron relationship (Seager and Henderson 2013; Li et al. 2013).

Fig. 9.
Fig. 9.

Composite anomalies of nine terms of Vhq in Eq. (3) denoted H1–H9 (green bars; mm day−1) and ωpq in Eq. (4) denoted Z1–Z9 (yellow bars, mm day−1) for the spring EEP events at (a) day −7, (b) day −5, (c) day −3, and (d) day 0 averaged over 27°–37°N, 100°–120°E.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

The values of other terms in Eqs. (3) and (4) present the non-synoptic-to-subseasonal component and nonlinear interaction between multiple time scales, which are much smaller and thus could be ignored in this study. The Vhq¯ and V¯hq terms are further decomposed as follows:
Vhq¯=uq¯xυq¯y,
V¯hq=u¯qxυ¯qy.

Therefore, the uq¯/x (DX), υq¯/y (DY), u¯q/x (TX), υ¯q/y (TY), ωpq¯ (DZ), and ω¯pq (TZ) terms are considered as the possible factors affecting the spring EEP events over central-eastern China.

Figure 10 illustrates the latitude–time and longitude–time sections of the anomalous horizontal dynamic moisture convergence uq¯/x term (DX) and υq¯/y term (DY) averaged over central-eastern China (27°–37°N, 100°–120°E). The anomalous DX term remains negative between day −9 and day −5, and becomes positive from the beginning at day −4 (Fig. 10a). The DX term indicates the influence of zonal gradients of climatological specific humidity and zonal wind anomalies. As shown in Figs. 4 and 5, the anomalous anticyclone related to the Rossby wave train arrives at northeastern China during day −5 to day −3. Thus, the easterly anomalies strengthen in the south of the anomalous anticyclone. Correspondingly, the DX anomalies give rise to the moisture convergence and contribute to the occurrence of EEP events during day −3 to day +3. Moreover, the DX anomalies dominantly have an influence on central China, as shown around 105°E in Fig. 10b. This is consistent with the anomalous northeasterly moisture flux that brings more water vapor from the Sea of Japan to central China in Fig. 6.

Fig. 10.
Fig. 10.

(a) Latitude–time section (averaged over 100°–120°E) of composite anomalies in moisture convergence of uq¯/x (DX; shaded; mm day−1). (b) Longitude–time section (averaged over 27°–37°N) of DX (shaded; mm day−1) for spring EEP events. (c),(d) As in (a) and (b), respectively, but for υq¯/y (DY; shaded; mm day−1). The black line denotes the statistically significant 95% confidence level.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

The DY anomalies show a similar evolution to the DX anomalies, and also influence the spring EEP events from day −4 (Fig. 10c). The DY term suggests the impact of meridional gradients of climatological specific humidity and meridional wind anomalies. As displayed in Fig. 6, the southwesterly moisture flux prevails from day −5 to day −3, which leads to the DY anomalies becoming evident. Note that the DY term mainly has an impact on the eastern China (110°–120°E; Fig. 10d), which is different from the DX term. This is mainly because the northerly wind anomalies in central China are stronger than those in eastern China, and offset the southerly wind anomalies. Although the DX and DY terms respectively contribute to central China and eastern China, they both affect the moisture convergence significantly during day −3 to day +3, resulting in the occurrence of the large-area regional EEP events. The significant anomalies of DX and DY also suggest that the moisture convergence for spring EEP events is attributable to the atmospheric circulation anomalies both from the midlatitude and subtropical regions.

To further demonstrate the horizontal thermodynamic and vertical components of moisture convergence anomalies related to the spring EEP events, Fig. 11 plots the lead–lag composite anomalies of dynamic and thermodynamic components of all the horizontal and vertical terms in the moisture budget for spring EEP events, averaged over central-eastern China. It can be seen that the DX and DY terms begin to contribute to the moisture convergence after day −4. They have the most notable impacts between day −1 and day +1. The anomalous meridional thermodynamic component υ¯q/y (TY) begins to exhibit a minor influence on the moisture convergence from day −5 to day −3, which may be linked to the increase of the meridional gradient specific humidity anomalies. However, it exhibits much smaller values than the dynamic terms and decreases sharply between day −1 and day +1. The zonal thermodynamic u¯q/x (TX) term also make small contributions. This indicates that for the water vapor convergence of the spring EEP events, the changes in specific humidity are less important than the anomalies in atmospheric circulations.

Fig. 11.
Fig. 11.

Composite anomalies in moisture convergence of uq¯/x (DX; red line; mm day−1), υq¯/y (DY; dark blue line; mm day−1), u¯q/x (TX; green line; mm day−1), υ¯q/y (TY; light blue line; mm day−1), ωpq¯ (DZ; purple line; mm day−1), and ω¯pq (TZ; yellow line; mm day−1) averaged over 27°–37°N, 100°–120°E.

Citation: Journal of Climate 35, 1; 10.1175/JCLI-D-20-0884.1

Furthermore, during day −3 to day +3, due to the anomalous vertical velocity with precipitation, the vertical term ωpq¯ (DZ) favors increased water vapor convergence. However, the ω¯pq term (TZ) shows negative contributions. The DZ and TZ terms are also much smaller than the horizontal terms, which implies that the local vertical anomalies also play minor roles. Therefore, the above analysis again verifies the key role of the horizontal circulation anomalies in formation of the moisture convergence responsible for the spring EEP events. The favorable signals from the midlatitude and subtropics have a coordinated influence on the extreme precipitation over central-eastern China.

5. Summary and discussion

The spring EEP events observed in central-eastern China are characterized by the extreme precipitation exceeding the 90th percentile occurring at the first part of the event, which dominantly occurs between April and May. The present study investigates the early stage and favorable atmospheric anomalies of the spring EEP events and their relationship with the BOBSM onset. The physical mechanisms related to the moisture transport are also studied to reveal the formation conditions for spring EEP events. The major conclusions are summarized as follows:

  1. The precursory eastward CGT Rossby waves in the midlatitudes significantly contribute to spring EEP events over central-eastern China. During day −7 to day −5 prior to the EEP events, a Rossby wave emerges over the North Atlantic and western Europe regions with the horizontal WAF propagating eastward. The wave train could be seen at both 200 and 500 hPa with an equivalent barotropic structure in the midlatitudes. After that, the westerly jet jumps northward to 30°N, acting as the waveguide for the Rossby wave propagating to East Asia during day −5 to day −3. During day −3 to day 0, the wave train becomes more intense and exhibits a GCT-like pattern with the positive and negative geopotential height anomalies over the North Pacific. A strong anomalous anticyclone associated with this CGT pattern is present over northeast China and the Korean Peninsula, enhancing the divergence anomalies in the upper troposphere and bringing cold air masses southward into central-eastern China.

  2. The occurrence of spring EEP events has a close relationship to the onset of the BOBSM. On one hand, the BOBSM onset occurs about 5–7 days before the EEP events, and leads to the northward jumping of the westerly jet acting as the waveguide for the CGT Rossby wave propagating eastward. On the other hand, during day −5 to day −3, the onset of BOBSM enhances the cross-equatorial flow and strengthens the moisture flux transportation from the Bay of Bengal to Indochina Peninsula regions, providing favorable conditions for more precipitation. During day −3 to day 0, along with the CGT pattern, an anomalous northeasterly moisture flux transports more water vapor from the Sea of Japan to central China. The anomalous southwesterly and northeasterly moisture fluxes converge over central-eastern China, resulting in extreme precipitation. Thus, the BOBSM may be a possible preceding signal for the spring EEP events over central-eastern China.

  3. The dynamic and thermodynamic processes of moisture convergence responsible for the spring EEP events are investigated. The horizontal dynamic DX and DY terms explore the most significant contributions to the spring EEP event, which show a similar impact around 35°N from day −3 to day +3. The DX term indicates the easterly wind anomalies associated with the anomalous anticyclone in northeast China. The DY term indicates the southerly wind anomalies related to the BOBSM. The horizontal thermodynamic TX and TY terms begin to influence moisture transport from day −5 to day −3, owing to the horizontal gradient of anomalous specific humidity. However, the thermodynamic components have much smaller contributions than the dynamic components. In addition, the vertical terms also play a minor role in the moisture convergence anomalies. Namely, the moisture convergence anomalies of spring EEP events are primarily attributed to the remote atmospheric circulation anomalies from the midlatitudes and subtropics, rather than the specific humidity anomalies or local vertical circulations.

In this study, we have highlighted the time distribution pattern of extreme precipitation throughout a continuous precipitation event. The midlatitude and subtropical anomalous signals as well as the physical mechanisms have been emphasized as driving the spring EEP events at synoptic to subseasonal time scale. The results in the present study are beneficial with respect to the development of extended-range forecasting of spring precipitation and hydrological prediction over central-eastern China. Under global warming, regional extreme precipitation is complicated and difficult to forecast. The number of the EEP events is reduced from the late 1990s, showing a decreasing-trend transition (Li et al. 2020). Whether or not this change is due to sea surface temperature anomalies such as the Atlantic mode oscillation or Indian Ocean basin mode in response to global warming needs to be further studied. Furthermore, EEP events also occur in summer and autumn, showing different time distribution patterns of extreme precipitation in the events. The mechanism and evolution of different types of EEP events deserve more detailed studies in the future.

Acknowledgments

This work was jointly supported by the National Key R&D Program of China (Grant 2018YFC1505903), the National Natural Science Foundation of China (Grant 41701592), the Postdoctoral Science Foundation of China (Grants 2019M663616, 2021T140435), and the Fundamental Research Funds for the Central Universities (Grant GK202003061). The NCEP–NCAR daily reanalysis data were obtained from https://www.esrl.noaa.gov/psd/data/gridded/data.ncep.reanalysis.html. The daily precipitation data were provided for academic use from the website http://data.cma.cn/en/?r=data/index&cid=6d1b5efbdcbf9a58 by the CMA.

REFERENCES

  • Chen, M., W. Shi, P. Xie, V. B. S. Silva, V. E. Kousky, R.W. Higgins, J. E. Janowiak, 2008: Assessing objective techniques for gauge-based analyses of global daily precipitation. J. Geophys. Res. 113, D04110, https://doi.org/10.1029/2007JD009132.

    • Search Google Scholar
    • Export Citation
  • Chen, Y., and P. Zhai, 2014: Two types of typical circulation patterns for the persistent extreme precipitation in central-eastern China. Quart. J. Roy. Meteor. Soc., 140, 14671478, https://doi.org/10.1002/qj.2231.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., D. Neelin, A. Chen, and Y. Tu, 2009: Evaluating the “rich-get-richer” mechanism in tropical precipitation change under global warming. J. Climate, 22, 19822005, https://doi.org/10.1175/2008JCLI2471.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chou, C., H. Chiang, W. Lan, H. Chung, C. Liao, and J. Lee, 2013: Increase in the range between wet and dry season precipitation. Nat. Geosci., 6, 263267, https://doi.org/10.1038/ngeo1744.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Y., and J. Chan, 2005: The East Asian summer monsoon: An overview. Meteor. Atmos. Phys., 89, 117142, https://doi.org/10.1007/s00703-005-0125-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, W., L. Wang, Z.-Z. Hu, K. Hu, and Y. Li, 2018: Interannual variations of the first rainy season precipitation over South China. J. Climate, 31, 623640, https://doi.org/10.1175/JCLI-D-17-0284.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hitchens, N., H. Brooks, and R. Schumacher, 2013: Spatial and temporal characteristics of heavy hourly rainfall in the United States. Mon. Wea. Rev., 141, 45644575, https://doi.org/10.1175/MWR-D-12-00297.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huang, W., and Coauthors, 2019: A possible mechanism for the occurrence of wintertime extreme precipitation events over South China. Climate Dyn., 52, 23672384, https://doi.org/10.1007/s00382-018-4262-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jia, X., Y. You, R. Wu, and Y. Yang, 2019: Interdecadal changes in the dominant modes of the interannual variation of spring precipitation over China in the mid-1980s. J. Geophys. Res., 124, 10 67610 695, https://doi.org/10.1029/2019JD030901.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kuang, X., and Y. Zhang, 2005: Seasonal variation of the East Asian subtropical westerly jet and its association with the heating field over East Asia. Adv. Atmos. Sci., 22, 831840, https://doi.org/10.1007/BF02918683.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, C., J.-T. Wang, S.-Z. Lin, and H.-R. Cho, 2004: The relationship between East Asian summer monsoon activity and northward jump of the upper westerly jet location (in Chinese). Chin. J. Atmos. Sci., 28, 641658, https://doi.org/10.3878/j.issn.1006-9895.2004.05.01.

    • Search Google Scholar
    • Export Citation
  • Li, J., and L. Zhu, 2008: Climatological features of the western Pacific subtropical high southward retreat process in late-spring and early-summer (in Chinese). Acta Meteor. Sin., 66, 926939, https://doi.org/10.11676/qxxb2008.084.

    • Search Google Scholar
    • Export Citation
  • Li, J., and J. Mao, 2019: Coordinated influences of the tropical and extratropical intraseasonal oscillations on the 10–30-day variability of the summer rainfall over southeastern China. Climate Dyn., 53, 137153, https://doi.org/10.1007/s00382-018-4574-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, L., W. Li, and A. P. Barros, 2013: Atmospheric moisture budget and its regulation of the summer precipitation variability over the southeastern United States. Climate Dyn., 41, 613631, https://doi.org/10.1007/s00382-013-1697-9.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Li, S., C. Wang, J. Yan, and X. Liu, 2020: Variability of the event-based extreme precipitation in the south and north Qinling. Mountains (in Chinese). Acta Geogr. Sin., 75, 9891007, https://doi.org/10.11821/dlxb202005008.

    • Search Google Scholar
    • Export Citation
  • Liu, B., G. Wu, J. Mao, and J. He, 2013: Genesis of the South Asian high and its impact on the Asian summer monsoon onset. J. Climate, 26, 29762991, https://doi.org/10.1175/JCLI-D-12-00286.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, B., Y. Liu, G. Wu, J. Yan, J. He, and S. Ren, 2015: Asian summer monsoon onset barrier and its formation mechanism. Climate Dyn., 45, 711726, https://doi.org/10.1007/s00382-014-2296-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lu, R., Z. Lin, and Y. Zhang, 2013: Variability of the East Asian upper-tropospheric jet in summer and its impacts on the East Asian monsoon (in Chinese). Chin. J. Atmos. Sci., 37, 331340, https://doi.org/10.3878/j.issn.1006-9895.2012.

    • Search Google Scholar
    • Export Citation
  • Mao, J., and G. Wu, 2007: Interannual variability in the onset of summer monsoon over the eastern Bay of Bengal. Theor. Appl. Climatol., 89, 155170, https://doi.org/10.1007/s00704-006-0265-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pendergrass, A., 2018: What precipitation is extreme? Science, 6393, 10721073, https://doi.org/10.1126/science.aat1871.

  • Peng, D., and T. Zhou, 2017: Why was the arid and semiarid northwest China getting wetter in the recent decades? J. Geophys. Res. Atmos., 122, 90609075, https://doi.org/10.1002/2016JD026424.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Qian, J.-H., W.-K. Tao, and K. Lau, 2004: Mechanisms for torrential rain associated with the mei-yu development during SCSMEX 1998. Mon. Wea. Rev., 132, 327, https://doi.org/10.1175/1520-0493(2004)132<0003:MFTRAW>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., and N. Henderson, 2013: Diagnostic computation of moisture budgets in the ERA-Interim reanalysis with reference to analysis. J. Climate, 26, 78767901, https://doi.org/10.1175/JCLI-D-13-00018.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Seager, R., N. Naik, and G. Vecchi, 2010: Thermodynamic and dynamic mechanisms for large-scale changes in hydrological cycle in response to global warming. J. Climate, 23, 46514668, https://doi.org/10.1175/2010JCLI3655.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Shang, W., S. Li, X. Ren, and K. Duan, 2020: Event-based extreme precipitation in central-eastern China: Large-scale anomalies and teleconnections. Climate Dyn., 54, 23472360, https://doi.org/10.1007/s00382-019-05116-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • She, D., Q. Shao, J. Xia, J. Taylor, Y. Zhang, L. Zhang, X. Zhang, and L. Zou, 2015: Investigating the variation and non-stationarity in precipitation extremes based on the concept of event-based extreme precipitation. J. Hydrol., 530, 785798, https://doi.org/10.1016/j.jhydrol.2015.10.029.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, C., and S. Yang, 2012: Persistent severe drought in southern China during winter–spring 2011: Large-scale circulation patterns and possible impacting factors. J. Geophys. Res., 117, D10112, https://doi.org/10.1029/2012JD017500.

    • Search Google Scholar
    • Export Citation
  • Takaya, K., and H. Nakamura, 2001: A formulation of a phase-independent wave-activity flux for stationary and migratory quasigeostrophic eddies on a zonally varying basic flow. J. Atmos. Sci., 58, 608627, https://doi.org/10.1175/1520-0469(2001)058,0608:AFOAPI.2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, Z., A. Duan, S. Yang, and K. Ullah, 2017: Atmospheric moisture budget and its regulation on the variability of summer precipitation over the Tibetan Plateau. J. Geophys. Res. Atmos., 122, 614630, https://doi.org/10.1002/2016JD025515.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Watanabe, T., and K. Yamazaki, 2014: The upper-level circulation anomaly over central Asia and its relationship to the Asian monsoon and mid-latitude wave train in early summer. Climate Dyn., 42, 24772489, https://doi.org/10.1007/s00382-013-1888-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, X., S. Guo, J. Yin, G. Yang, Y. Zhong, and D. Liu, 2018: On the event-based extreme precipitation across China: Time distribution, trends and return levels. J. Hydrol., 562, 305417, https://doi.org/10.1016/j.jhydrol.2018.05.028.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., A. Yatagai, M. Chen, T. Hayasaka, Y. Fukushima, C. Liu, and S. Yang, 2007: A gauge-based analysis of daily precipitation over East Asia. J. Hydrometeor., 8, 607627, https://doi.org/10.1175/JHM583.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xing, N., J. Li, and L. Wang, 2016: Effect of the early and late onset of summer monsoon over the Bay of Bengal on Asian precipitation in May. Climate Dyn., 47, 19611970, https://doi.org/10.1007/s00382-015-2944-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xiong, Y., and X. Ren, 2021: Influence of atmospheric rivers on North Pacific winter precipitation: Climatology and dependence on ENSO condition. J. Climate, 34, 277292, https://doi.org/10.1175/JCLI-D-20-0301.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xu, C., Y. Qian, and M. Jian, 2019: Interdecadal change in the intensity of interannual variation of spring precipitation over southern China and possible reasons. J. Climate, 32, 58655881, https://doi.org/10.1175/JCLI-D-18-0351.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, J., Q. Bao, B. Wang, Z. He, M. Gao, and D. Gong, 2017: Characterizing two types of transient intraseasonal oscillations in the eastern Tibetan Plateau summer rainfall. Climate Dyn., 48, 17491768, https://doi.org/10.1007/s00382-016-3170-z.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yang, S., and T. Li, 2017: The role of intraseasonal variability at mid-high latitudes in regulating Pacific blockings during boreal winter. Int. J. Climatol., 37, 12481256, https://doi.org/10.1002/joc.5080.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, M., and J. Sun, 2017: Enhancement of the spring East China precipitation response to tropical sea surface temperature variability. Climate Dyn., 51, 30093021, https://doi.org/10.1007/s00382-017-4061-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, W., T. Zhou, and L. Zhang, 2017: Wetting and greening Tibetan Plateau in early summer in recent decades. J. Geophys. Res. Atmos., 122, 58085822, https://doi.org/10.1002/2017JD026468.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, B., and P. Zhao, 2010: Influence of the Asian-Pacific oscillation on spring precipitation over central eastern China. Adv. Atmos. Sci., 27, 575582, https://doi.org/10.1007/s00376-009-9058-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, T.-J., and R.-C. Yu, 2005: Atmospheric water vapor transport associated with typical anomalous summer rainfall patterns in China. J. Geophys. Res., 110, D08104, https://doi.org/10.1029/2004JD005413.

    • Search Google Scholar
    • Export Citation
  • Zhu, C., T. Nakazawa, and L. Chen, 2003: The 30–60 day intraseasonal oscillation over the western North Pacific Ocean and its impacts on summer flooding in China during 1998. Geophys. Res. Lett., 30, 1952, https://doi.org/10.1029/2003GL017817.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zuluaga, M., and J. Houze, 2015: Extreme convection of the near-equatorial Americas, Africa, and adjoining oceans as seen by TRMM. Mon. Wea. Rev., 143, 298316, https://doi.org/10.1175/MWR-D-14-00109.1.

    • Crossref
    • Search Google Scholar
    • Export Citation

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