Why Is the East Asian Summer Monsoon Extremely Strong in 2018?—Collaborative Effects of SST and Snow Cover Anomalies

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  • Corresponding author: Wei GU, guwei@cma.gov.cn
  • Funds:

    Supported by the National Key Research and Development Program of China (2018YFC1506006), National Science and Technology Support Program of China (2015BAC03B04), and National Natural Science Foundation of China (41805067 and 41275073)

  • doi: 10.1007/s13351-019-8200-4

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  • In 2018, summer precipitation was above normal in North and Northwest China and below normal around the Yangtze River valley, due to an extremely strong East Asian summer monsoon (EASM). The atmospheric circulation anomalies in East Asia and key external forcing factors that influence the EASM in 2018 are explored in this paper. The results show that there existed an anomalous cyclonic circulation near the Philippines, while the western Pacific subtropical high was located more northward than its normal position. In the mid–high latitudes, a negative geopotential height anomaly center was found near the Ural Mountains, suppressing the blocking activity. Under such a circulation pattern, precipitation near the Yangtze River valley decreased because local divergence and subsidence intensified, whereas precipitation in northern China increased due to large amounts of water vapor transport by anomalously strong southerly winds. Further analyses reveal that the strong EASM circulation in 2018 might result from the joint influences of several external forcing factors. The weak La Niña event that started from October 2017, the positive North Atlantic Tripolar mode (NAT) in spring 2018, and the reduced snow cover over the Tibetan Plateau in winter 2017/18 all collaboratively contributed to formation of the cyclonic circulation anomaly near the Philippines, leading to the extremely strong EASM. Especially, the positive NAT and the reduced Tibetan snow cover may have caused the negative geopotential height anomaly near the Ural Mountains, in favor of a strong EASM. The above external factors and their reinforcing impacts on the EASM are further verified by two groups of similar historical cases.
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  • Fig. 1.  Temporal evolutions of the (a) Shi, (b) Zhang, and (c) Zhu EASM indices during 1981–2018.

    Fig. 2.  (a) Difference in summer precipitation (mm) between strong and weak EASM years (thick dashed line indicates the area where the difference exceeds the significance level of 0.1). (b) Percentage precipitation anomaly (%) and (c) the anomaly of rainy days for summer 2018.

    Fig. 3.  Average summer precipitation (mm) in Northwest China (blue line), North China (red line), and the middle–lower reaches of Yangtze River (black line) for 1981–2018.

    Fig. 4.  Summertime geopotential height difference between 200 and 500 hPa: (a) climatological mean and (b) 2018 anomaly field (gpm).

    Fig. 5.  Anomalous (a) geopotential height (gpm) and wind (m s−1) at 200 hPa, (b) 500-hPa geopotential height (gpm) and 850-hPa wind (m s−1), (c) column-integrated water vapor flux (kg m−1 s−1) and its divergence (10−7 kg m−2 s−1), and (d) 500-hPa vertical velocity (−300 Pa s−1) in summer 2018. The red line in (b) represents the climatology mean 5880-gpm contour.

    Fig. 6.  North–south position index of the ridge line of the western Pacific subtropical high (WPSH) in the summers of 1981–2018.

    Fig. 7.  (a) Evolution of the Niño3.4 index (°C) and SOI index from September 2016 to August 2018 and (b) global SST anomaly (SSTA) in the 2017/18 winter. In (b), shadings in yellow (blue) with solid (dashed) contours denote positive (negative) SSTA, and contour interval (CI) is 0.3°C.

    Fig. 8.  Composite precipitation (mm) over eight summers that followed a La Niña event from 1981 to 2017 (no area in the figure exceeding the 0.1 significance level).

    Fig. 9.  Lead–lag correlation coefficients of the Niño3.4 index, IOBW index, NAT index, and Tibetan snow cover index with the EASM index (three-month sliding average is performed prior to the calculation of correlation).

    Fig. 10.  Temporal evolutions of (a) the Niño3.4 index in winter, (b) the IOBW index in summer, (c) the NAT index in spring, and (d) the Tibetan snow cover index in winter during 1982–2018.

    Fig. 11.  Composite 500-hPa geopotential height (gpm) and 850-hPa wind (m s−1) anomalies in the summers (a) following the La Niña occurrence winters with negative Niño3.4 index, (b) with negative summer IOBW index, (c) following the springs with positive NAT index, and (d) following the winters with negative winter plateau snow cover index. Dark, medium, and light shadings indicate the areas with values above the significance level of 0.01, 0.05, and 0.1, respectively; red solid lines represent the climatological mean 5870-gpm contour. Only wind vectors exceeding the 0.2 significance level are shown.

    Fig. 12.  Sum of the regressed values of 500-hPa geopotential height and 850-hPa wind in summer 2018 calculated according to the linear regression equations using the Niño3.4 index, the NAT index, and the Tibetan snow cover area index from 1982 to 2017, respectively. Black contours represent the 500-hPa geopotential height anomaly (gpm); vectors represent 850-hPa wind anomaly (m s−1); and shadings, red thick lines, and blue thick lines indicate the areas where the correlations of the Niño3.4 index, the NAT index, and the Tibetan snow cover index with the geopotential height anomaly exceeding the significant level of 0.1. Letters A and C denote anomalous anticyclone and cyclone, respectively.

    Fig. 13.  500-hPa geopotential height (gpm) and 850-hPa wind (m s−1) anomalies in the summers of (a) 1985, (b) 1983, and (c) 1998. The red lines represent the climatology mean 5880-gpm contour.

    Fig. 14.  Percentage precipitation anomalies (%) in the summers of (a) 1985, (b) 1983, and (c) 1998. Contour interval is 50% in each plot.

  • [1]

    Chen, L. J., Y. Yuan, M. Z. Yang, et al., 2013: A review of physi-cal mechanisms of the global SSTA impact on the EASM. J. Appl. Meteor. Sci., 24, 521–532. (in Chinese) doi: 10.3969/j.issn.1001-7313.2013.05.002.
    [2]

    Chen, L. J., W. Gu, T. Ding, et al., 2016: Overview of the precursory signals of seasonal climate prediction in summer 2015. Meteor. Mon., 42, 496–506. (in Chinese).
    [3]

    Chen, L. J., W. Gu, Z. X. Gong, et al., 2019: Precursory signals of the 2018 summer climate in China and evaluation of the real-time prediction. Meteor. Mon., 45, 553–564. (in Chinese).
    [4]

    Chen, Q. J., B. Gao, W. J. Li, et al., 2000: Studies on relationships among abnormal winter snow cover over the Tibetan Plateau, Meiyu season droughts/floods in the middle–lower reaches of the Yangtze River, and atmospheric circulation patterns. Acta Meteor. Sinica, 58, 582–595. (in Chinese) doi: 10.11676/qxxb2000.060.
    [5]

    Chen, X. F., and Z. G. Zhao, 2000: Study on Precipitation Forecast in China During Flood Season and Associated Application. China Meteorological Press, Beijing, 241 pp. (in Chinese).
    [6]

    Feng, J., L. Wang, and W. Chen, 2014: How does the East Asian summer monsoon behave in the decaying phase of El Niño during different PDO phases? J. Climate, 27, 2682–2698. doi: 10.1175/JCLI-D-13-00015.1.
    [7]

    Feng, M., B. J. Wang, and S. Q. Xiong, 2000: Analysis on the abnormality of general circulation and sea temperature in relation to the flood water of Yangtze river in 1998. Resour. Environ. Yangtze Basin, 9, 112–117. (in Chinese) doi: 10.3969/j.issn.1004-8227.2000.01.017.
    [8]

    Gao, H., and Y. G. Wang, 2007: On the weakening relationship between summer precipitation in China and ENSO. Acta Meteor. Sinica, 65, 131–137. (in Chinese) doi: 10.11676/qxxb2007.013.
    [9]

    Gu, W., and L. J. Chen, 2019: Characteristics of atmospheric and oceanic conditions and their influence on summer climate of China in 2018. Meteor. Mon., 45, 126–134. (in Chinese).
    [10]

    Gu, W., C. Y. Li, X. Wang, et al., 2009: Linkage between Mei-yu precipitation and North Atlantic SST on the decadal timescale. Adv. Atmos. Sci., 26, 101–108. doi: 10.1007/s00376-009-0101-5.
    [11]

    Guo, Y. J., W. Li, and Q. J. Chen, 2004: An operational monitoring and diagnosing system for snow cover in the Northern Hemisphere. Meteor. Mon., 30, 24–27. (in Chinese) doi: 10.3969/j.issn.1000-0526.2004.11.005.
    [12]

    He, J. H., X. F. Zhi, and T. Nakazawa, 1995: Seasonal interlock of the intraseasonal variations of rainfall in East China. J. Trop. Meteor., 11, 370–374. (in Chinese) doi: 10.16032/j.issn.1004-4965.1995.04.010.
    [13]

    Huang, R. H., 1992: The East Asia/Pacific pattern teleconnection of summer circulation and climate anomaly in East Asia. Acta Meteor. Sinica, 6, 25–37.
    [14]

    Huang, R. H., and W. J. Li, 1987: Influence of the heat source anomaly over the western tropical Pacific on the subtropical high over East Asia. Proc. International Conference on the General Circulation of East Asia, Chengdu, China, 40–51.
    [15]

    Huang, R. H., and Y. F. Wu, 1989: The influence of ENSO on the summer climate change in China and its mechanism. Adv. Atmos. Sci., 6, 21–32. doi: 10.1007/BF02656915.
    [16]

    Huang, R. H., W. Chen, Y. H. Ding, et al., 2003: Studies on the monsoon dynamics and the interaction between monsoon and ENSO cycle. Chinese J. Atmos. Sci., 27, 484–502. (in Chinese) doi: 10.3878/j.issn.1006-9895.2003.04.05.
    [17]

    Huang, R. H., J. L. Chen, L. Wang, et al., 2012: Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system. Adv. Atmos. Sci., 29, 910–942. doi: 10.1007/s00376-012-2015-x.
    [18]

    Kalnay, E., M. Kanamitsu, R. Kistler, et al., 1996: The NCEP/NCAR 40-year reanalysis project. Bull. Amer. Meteor. Soc., 77, 437–472. doi: 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.
    [19]

    Kistler, R., E. Kalnay, W. Collins, et al., 2001: The NCEP–NCAR 50-year reanalysis: Monthly means CD-ROM and documentation. Bull. Amer. Meteor. Soc., 82, 247–268. doi: 10.1175/1520-0477(2001)082<0247:TNNYRM>2.3.CO;2.
    [20]

    Li, C. Y., R. H. Huang, J. F. Chou, et al., 2009: The Study of Meteorological Disasters and Chinese Response. China Meteorological Press, Beijing, 187 pp. (in Chinese).
    [21]

    Li, T., B. Wang, B. Wu, et al., 2017: Theories on formation of an anomalous anticyclone in western North Pacific during El Niño: A review. J. Meteor. Res., 31, 987–1006. doi: 10.1007/s13351-017-7147-6.
    [22]

    Li, W. J., 1999: General atmospheric circulation anomaly in 1998 and their impact on climate anomaly in China. Meteor. Mon., 25, 20–25. (in Chinese) doi: 10.3969/j.issn.1000-0526.1999.04.004.
    [23]

    Liu, Y. M., G. X. Wu, H. Liu, et al., 1999: The effect of spatially nonuniform heating on the formation and variation of subtropical high. Part Ⅲ: Condensation heating and South Asian high and western Pacific subtropical high. Acta Meteor. Sinica, 57, 525–538. (in Chinese) doi: 10.11676/qxxb1999.051.
    [24]

    Liu, Y. Y., W. J. Li, W. X. Ai, et al., 2012: Reconstruction and application of the monthly western North Pacific subtropical high indices. J. Appl. Meteor. Sci., 23, 414–423. (in Chinese).
    [25]

    Ma, Y., W. Chen, and L. Wang, 2011: A comparative study of the interannual variation of summer rainfall anomalies between the Huaihe Meiyu season and the Jiangnan Meiyu season and their climate background. Acta Meteor. Sinica, 69, 334–343. (in Chinese) doi: 10.11676/qxxb2011.028.
    [26]

    Marshall, J., Y. Kushnir, D. Battisti, et al., 2001: North Atlantic climate variability: Phenomena, impacts and mechanisms. Int. J. Climatol., 21, 1863–1898. doi: 10.1002/joc.693.
    [27]

    Nitta, T., 1987: Convective activities in the tropical western Pacific and their impact on the Northern Hemisphere summer circulation. J. Meteor. Soc. Japan, 65, 373–390. doi: 10.2151/jmsj1965.65.3_373.
    [28]

    Peng, J. B., L. T. Chen, and Q. Y. Zhang, 2005: Multi-scale variations of snow cover over QXP and tropical Pacific SST and their influences on summer rainfall in China. Plateau Meteor., 24, 366–377. (in Chinese) doi: 10.3321/j.issn:1000-0534.2005.03.013.
    [29]

    Qian, Y. F., Y. Q. Zheng, Y. Zhang, et al., 2003: Responses of China’s summer monsoon climate to snow anomaly over the Tibetan Plateau. Int. J. Climatol., 23, 593–613. doi: 10.1002/joc.901.
    [30]

    Ren, H.-C., W. J. Li, H.-L. Ren, et al., 2016: Distinct linkage between winter Tibetan Plateau snow depth and early summer Philippine Sea anomalous anticyclone. Atmos. Sci. Lett., 17, 223–229. doi: 10.1002/asl.646.
    [31]

    Ren, H.-L., B. Lu, J. H. Wan, et al., 2018: Identification standard for ENSO events and its application to climate monitoring and prediction in China. J. Meteor. Res., 32, 923–936. doi: 10.1007/s13351-018-8078-6.
    [32]

    Ren, Z. H., Y. Yu, F. L. Zou, et al., 2012: Quality detection of surface historical basic meteorological data. J. Appl. Meteor. Sci., 23, 739–747. (in Chinese) doi: 10.3969/j.issn.1001-7313.2012.06.011.
    [33]

    Reynolds, R. W., N. A. Rayner, T. M. Smith, et al., 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 1609–1625. doi: 10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2.
    [34]

    Shi, N., Q. G. Zhu, and B. G. Wu, 1996: The East Asian summer monsoon in relation to summer large scale weather–climate anomaly in China for last 40 years. Chinese J. Atmos. Sci., 20, 575–583. (in Chinese) doi: 10.3878/j.issn.1006-9895.1996.05.08.
    [35]

    Sun, S., D. Li, Z. Y. Wang, et al., 2019: Global major weather and climate events in 2018 and the possible causes. Meteor. Mon., 45, 533–542. (in Chinese).
    [36]

    Sung, M.-K., W.-T. Kwon, H.-J. Baek, et al., 2009: A possible impact of the North Atlantic Oscillation on the East Asian summer monsoon precipitation. Geophys. Res. Lett., 33, L21713. doi: 10.1029/2006GL027253.
    [37]

    Tao, S. Y., and Q. Y. Zhang, 1998: Response of the Asian winter and summer monsoon to ENSO events. Chinese J. Atmos. Sci., 22, 399–407. (in Chinese) doi: 10.3878/j.issn.1006-9895.1998.04.02.
    [38]

    Wang, B., R. G. Wu, and X. H. Fu, 2000: Pacific–East Asian teleconnection: How does ENSO affect East Asian climate? J. Climate, 13, 1517–1536. doi: 10.1175/1520-0442(2000)013<1517:PEATHD>2.0.CO;2.
    [39]

    Wang, L., and W. Gu, 2016: The eastern China flood of June 2015 and its causes. Sci. Bull., 61, 178–184. doi: 10.1007/s11434-015-0967-9.
    [40]

    Wu, G. X., Y. M. Liu, B. He, et al., 2018: Review of the impact of the Tibetan Plateau sensible heat driven air-pump on the Asian summer monsoon. Chinese J. Atmos. Sci., 42, 488–504. (in Chinese) doi: 10.3878/j.issn.1006-9895.1801.17279.
    [41]

    Xie, S.-P., K. M. Hu, J. Hafner, et al., 2009: Indian Ocean capaci-tor effect on Indo–western Pacific climate during the summer following El Niño. J. Climate, 22, 730–747. doi: 10.1175/2008JCLI2544.1.
    [42]

    Xie, S.-P., Y. Kosaka, Y. Du, et al., 2016: Indo–western Pacific Ocean capacitor and coherent climate anomalies in post-ENSO summer: A review. Adv. Atmos. Sci., 33, 411–432. doi: 10.1007/s00376-015-5192-6.
    [43]

    Xu, P. Q., L. Wang, W. Chen, et al., 2019a: Structural changes in the Pacific–Japan pattern in the late 1990s. J. Climate, 32, 607–621. doi: 10.1175/JCLI-D-18-0123.1.
    [44]

    Xu, P. Q., L. Wang, and W. Chen, 2019b: The British–Baikal corridor: A teleconnection pattern along the summertime polar front jet over Eurasia. J. Climate, 32, 877–896. doi: 10.1175/JCLI-D-18-0343.1.
    [45]

    Ye, D. Z., S. W. Luo, and B. Z. Zhu, 1957: Wind structure and heat balance in the lower troposphere over the Tibetan Plateau and its surrounding. Acta Meteor. Sinica, 28, 108–121. (in Chinese) doi: 10.11676/qxxb1957.010.
    [46]

    Yuan, Y., H. Gao, and Y. J. Liu, 2017: Analysis of the characteristics and causes of precipitation anomalies over eastern China in the summer of 2016. Meteor. Mon., 43, 115–121. (in Chinese).
    [47]

    Zhan, R. F., G. W. Sun, B. K. Zhao, et al., 2008: Quasi-biweekly oscillation of the subtropical summer monsoon rainfall over East China and its possible maintaining mechanism. Plateau Meteor., 27, 98–108. (in Chinese).
    [48]

    Zhang, H. X., W. P. Li, and W. J. Li, 2018: Influence of late springtime surface sensible heat flux anomalies over the Tibetan and Iranian Plateaus on the location of the South Asian high in early summer. Adv. Atmos. Sci., 36, 93–103. doi: 10.1007/s00376-018-7296-2.
    [49]

    Zhang, Q. Y., and S. Y. Tao, 2003: The anomalous subtropical anticyclone in western Pacific and their association with circu-lation over East Asia during summer. Chinese J. Atmos. Sci., 27, 369–380. (in Chinese) doi: 10.3878/j.issn.1006-9895.2003.03.07.
    [50]

    Zhang, Q. Y., S. Y. Tao, and L. T. Chen, 2003: The interannual variability of East Asian summer monsoon indices and its association with the pattern of general circulation over East Asia. Acta Meteor. Sinica, 61, 559–568. (in Chinese) doi: 10.11676/qxxb2003.056.
    [51]

    Zhang, R. H., A. Sumi, and M. Kimoto, 1996: Impact of El Niño on the East Asian monsoon: A diagnostic study of the ’86/87 and ’91/92 events. J. Meteor. Soc. Japan, 74, 49–62. doi: 10.2151/jmsj1965.74.1_49.
    [52]

    Zhang, R. H., Q. Y. Min, and J. Z. Su, 2017: Impact of El Niño on atmospheric circulations over East Asia and rainfall in China: Role of the anomalous western North Pacific anticyclone. Sci. China Earth Sci., 60, 1124–1132. doi: 10.1007/s11430-016-9026-x.
    [53]

    Zhang, S. L., and S. Y. Tao, 2001: Influences of snow cover over the Tibetan Plateau on Asian summer monsoon. Chinese J. Atmos. Sci., 25, 372–390. (in Chinese) doi: 10.3878/j.issn.1006-9895.2001.03.07.
    [54]

    Zhang, Y., 2004: Research on the characteristics of the thermal parameters of the Tibetan Plateau and its climate effects. Ph.D. dissertation, Nanjing University, China, 18 pp. (in Chinese).
    [55]

    Zhao, C. B., T. J. Zhou, B. Li, et al., 2011: Intraseasonal oscillation of summer rainfall over eastern China simulated with a regional climate model. Chinese J. Atmos. Sci., 35, 1033–1045. (in Chinese) doi: 10.3878/j.issn.1006-9895.2011.06.04.
    [56]

    Zhao, J. H., R. Zhi, Q. Shen, et al., 2014: Prediction of the distribution of the 2012 summer rainfall in China and analysis of the cause for anomaly. Chinese J. Atmos. Sci., 38, 237–250. (in Chinese) doi: 10.3878/j.issn.1006-9895.2013.12215.
    [57]

    Zhu, C. W., J. H. He, and G. X. Wu, 2000: East Asian monsoon index and its interannual relationship with large scale thermal dynamic circulation. Acta Meteor. Sinica, 58, 391–402. (in Chinese) doi: 10.11676/qxxb2000.042.
    [58]

    Zhu, Y. X., Y. H. Ding, and H. G. Xu, 2007: The decadal relationship between atmospheric heat source of winter and spring snow over Tibetan Plateau and rainfall in East China. Acta Meteor. Sinica, 65, 946–958. (in Chinese) doi: 10.11676/qxxb2007.089.
    [59]

    Zuo, J. Q., W. J. Li, H.-L. Ren, et al., 2012: Change of the relationship between spring NAO and East Asian summer monsoon and its possible mechanism. Chinese J. Geophys., 55, 384–395. (in Chinese).
    [60]

    Zuo, J. Q., W. J. Li, C. H. Sun, et al., 2013: Impact of the North Atlantic sea surface temperature tripole on the East Asian summer monsoon. Adv. Atmos. Sci., 30, 1173–1186. doi: 10.1007/s00376-012-2125-5.
    [61]

    Zuo, J. Q., W. J. Li, C. H. Sun, et al., 2018: Remote forcing of the northern tropical Atlantic SST anomalies on the western North Pacific anomalous anticyclone. Climate Dyn., 52, 2837–2853. doi: 10.1007/s00382-018-4298-9.
    [62]

    Zwiers, F. W., 1993: Simulation of the Asian summer monsoon with the CCC GCM-1. J. Climate, 6, 470–486. doi: 10.1175/1520-0442(1993)006<0469:SOTASM>2.0.CO;2.
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    [16] ZHU Yuxiang, DING Yihui, XU Huaigang. Decadal Relationship Between Atmospheric Heat Source and Winter-Spring Snow Cover over the Tibetan Plateau and Rainfall in East ChinaJournal of Meteorological Research, 2008, 22(3): 303-316.
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    [20] LI Xiaodong, WANG Zaiwen, HOU Zhangshuan. SIGNAL DETECTION OF GLOBAL CLIMATE CHANGE AND EXTERNAL FORCING FACTORSJournal of Meteorological Research, 2001, 15(4): 397-406.
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Why Is the East Asian Summer Monsoon Extremely Strong in 2018?—Collaborative Effects of SST and Snow Cover Anomalies

    Corresponding author: Wei GU, guwei@cma.gov.cn
  • 1. Laboratory for Climate Studies, National Climate Center, China Meteorological Administration, Beijing 100081
  • 2. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044
Funds: Supported by the National Key Research and Development Program of China (2018YFC1506006), National Science and Technology Support Program of China (2015BAC03B04), and National Natural Science Foundation of China (41805067 and 41275073)

Abstract: In 2018, summer precipitation was above normal in North and Northwest China and below normal around the Yangtze River valley, due to an extremely strong East Asian summer monsoon (EASM). The atmospheric circulation anomalies in East Asia and key external forcing factors that influence the EASM in 2018 are explored in this paper. The results show that there existed an anomalous cyclonic circulation near the Philippines, while the western Pacific subtropical high was located more northward than its normal position. In the mid–high latitudes, a negative geopotential height anomaly center was found near the Ural Mountains, suppressing the blocking activity. Under such a circulation pattern, precipitation near the Yangtze River valley decreased because local divergence and subsidence intensified, whereas precipitation in northern China increased due to large amounts of water vapor transport by anomalously strong southerly winds. Further analyses reveal that the strong EASM circulation in 2018 might result from the joint influences of several external forcing factors. The weak La Niña event that started from October 2017, the positive North Atlantic Tripolar mode (NAT) in spring 2018, and the reduced snow cover over the Tibetan Plateau in winter 2017/18 all collaboratively contributed to formation of the cyclonic circulation anomaly near the Philippines, leading to the extremely strong EASM. Especially, the positive NAT and the reduced Tibetan snow cover may have caused the negative geopotential height anomaly near the Ural Mountains, in favor of a strong EASM. The above external factors and their reinforcing impacts on the EASM are further verified by two groups of similar historical cases.

    • Under the influence of the East Asian monsoon, the climate in China exhibits large interannual variability, and associated meteorological disasters occur frequently. Based on statistical analysis, the economic loss caused by various meteorological disasters accounts for about 71% of the total losses from various natural disasters in China. Among all the meteorological disasters, 80% are caused by drought and flood (Li et al., 2009; Huang et al., 2012). Since summer is the rainy season in most parts of China, it is also the season when drought and flood occur most frequently. These disasters often cause large direct or indirect damages to people’s lives and economic infrastructure. For example, severe flooding disasters happened in the Yangtze River valley in summer 1998 and 2016 (Feng et al., 2000; Yuan et al., 2017), while serious meteorological drought occurred in Jianghuai and Jianghan areas in summer 2012 (Zhao et al., 2014), and a severe flooding disaster occurred over the Huaihe River basin in 2003 (Ma et al., 2011). Since the spatial variation of summer precipitation in China is mainly affected by the East Asian summer monsoon (EASM), it is of great scientific significance to probe the internal dynamics and external forcing factors leading to the interannual variability of the EASM, which has an important implication for disaster prevention and mitigation.

      The summertime weather and climate in China are significantly affected by the EASM system, which is under the control of some external forcing factors such as sea surface temperature (SST) and land surface thermal conditions (Huang et al., 2012). Complicated interaction and combination of multiple influencing factors make the EASM and summer precipitation in China vary significantly on the interannual timescale (Chen and Zhao, 2000; Chen et al., 2013; Wang and Gu, 2016). Among all the external factors affecting summer precipitation in China, El Nino–Southern Oscillation (ENSO) is the most important one. The ENSO events also exhibit significant interannual variability, closely associated with the summer precipitation variability in China (Huang and Wu, 1989). The SST anomaly during an ENSO event may trigger an abnormal anticyclone/cyclone near the Philippines in the lower troposphere (Zhang et al., 1996; Li et al., 2017; Zhang et al., 2017). The northward propagation of the anomalous anticyclone/cyclone leads to the formation of East Asia–Pacific (EAP) teleconnection pattern and/or the Pacific–Japan (PJ) type teleconnection pattern (Huang and Li, 1987; Nitta, 1987; Wang et al., 2000; Xu et al., 2019a), which subsequently affect the EASM and summer climate in China. During this process, the local air–sea coupling in the tropical Indian Ocean and the SST anomaly over Northwest Pacific also play an important role as “capacitor,” which stores and prolongs the ENSO effect into spring and summer (Xie et al., 2009, 2016). In addition, the interdecadal oscillation of the North Pacific SST, which behaves as an important interdecadal background, modulates the influence of ENSO on the EASM (Feng et al., 2014).

      In addition to the SSTs in the tropical Pacific and tropical Indian Ocean, the SST in North Atlantic and the snow cover over the Tibetan Plateau may also exert significant impacts on the EASM. The North Atlantic Tripolar mode (NAT) reflects the most important interan-nual variability of SST over the North Atlantic region. Studies have shown that the springtime NAT may have influenced the EASM in a great manner (Gu et al., 2009; Sung et al., 2009). On the one hand, the NAT affects the blocking activity near the Ural Mountains by activating a teleconnection wave train across the mid–high latitude region of Eurasia, and thus intensifies the Meiyu front and the EASM. On the other hand, the NAT affects convective activity in the tropical western Pacific through atmospheric teleconnection in the tropics, and thus contributes to the maintaining of the abnormal anticyclone/cyclone near the Philippines (Zuo et al., 2013, 2018).

      In addition to SST, some other surface thermal conditions may also influence the EASM and summer climate in China. In particular, the thermal condition over the Tibetan Plateau correlates well with the monsoon circulation over the plateau and East Asia (Ye et al., 1957; Zwiers, 1993). The extent of wintertime snow cover over the plateau and the snow melting in spring reflect the atmospheric thermal conditions over the plateau (Chen et al., 2000; Qian et al., 2003; Zhang, 2004; Zhu et al., 2007). Many previous studies have investigated the influence and mechanism of the Tibetan snow cover on the EASM. Zhang and Tao (2001) pointed out that the anomaly of wintertime snow cover over the Tibetan Plateau could maintain until spring or even summer. By changing surface albedo and soil moisture status, snow cover over large areas can greatly affect energy budget on local and regional scales, leading to significant variations of sea–land thermal difference in spring and summer, which subsequently influences the intensity of the EASM. A study by Ren et al. (2016) showed that snow cover anomalies over the Tibetan Plateau can also induce variation of the EASM intensity by triggering anticyclonic or cyclonic circulation anomalies near the Philippines. Note that such kinds of snow cover effects on atmospheric circulation are independent of ENSO effects. A recent study by Zhang et al. (2018) also pointed out that sensible heat anomalies over the Tibetan Plateau led to changes in latent heat transport to the northeast of India in summer, which may result in anomalies of the South Asian high and thus affect the intensity of the EASM.

      Preliminary analyses reveal that the Asian summer monsoon system in 2018 appeared abnormally strong (Gu and Chen, 2019; Sun et al., 2019). Specifically, the Indian summer monsoon was much stronger than normal at certain stages and heavy rainfall and flooding disasters occurred in India from May to August 2018 (Sun et al., 2019); and the South China Sea summer monsoon was stronger than normal and the EASM was particularly strong in 2018 (Gu and Chen, 2019). Based on station rainfall observations in China, it is found that summer (June–August) precipitation was higher than normal in the northern and southeastern coastal areas of China but much lower than normal in the Yangtze River valley. Although previous studies have revealed different circulation patterns and external forcing factors leading to strong/weak EASM and associated precipitation anomalies, specific mechanisms behind the EASM anomaly are usually different for individual years. For the EASM anomaly in a certain year, it is possible that a single factor plays a leading role, or it may be the result of the joint effects of multiple factors. What is the specific mechanism for the strong EASM in 2018? This is a question that needs to be explored in particular. All in all, the current paper intends to answer the following questions. (1) What are the main characteristics of the East Asian summer circulation in 2018? (2) What are the key exter-nal factors that have exerted significant impacts on the 2018 summer circulation? (3) How do all the external factors jointly affect the EASM? Answers to these questions will provide further understanding on the mechanisms for the strong EASM in 2018 and the interannual variability of the EASM. The present study can also provide reference for future application of the precursor signals in the external forcing to more accurate seasonal climate prediction.

    2.   Data and method
    • The precipitation data used in the present study are extracted from the Daily Data of Basic Meteorological Elements of China National Ground Weather Station (V3.0) issued by the National Meteorological Information Center of China (Ren et al., 2012). This dataset covers the period of January 1951–August 2018. The atmospheric circulation data such as geopotential height and horizon-tal wind fields are extracted from the NCEP/NCAR reanalysis monthly data on a horizontal resolution of 2.5° × 2.5° (Kalnay et al., 1996; Kistler et al., 2001). The NOAA SST data (OISSTv2) are employed in the present study, with a horizontal resolution of 1° × 1° and the dataset starts from December 1981 (Reynolds et al., 2002) and ends in November 2018. The original snow cover data are obtained from Rutgers University in the United States (http://climate.rutgers.edu/snowcover/). Following the approach of Guo et al. (2004), the original weekly snow cover data are converted into the number of snow/snow-free days through area weighted averaging over the Tibetan Plateau, and the snow cover index over the Tibetan Plateau is obtained. The averages from 1981 to 2010 for individual fields in each dataset are taken as the corresponding climatological means. In this paper, the winter, spring, and summer means are averages from December to February, March to May, and June to August, respectively.

      Three representative EASM indices defined by Shi et al. (1996), Zhang et al. (2003), and Zhu et al. (2000) are calculated in this study. The Shi index is defined as the difference of normalized sea level pressure between 110° and 160°E within the range of 20°–50°N. The Zhang index is defined as the difference in the average 850-hPa zonal wind between the eastern subtropical monsoon trough region (10°–20°N, 100°–150°E) and the East Asian subtropical region (25°–35°N, 100°–150°E). The Zhu index reflects the comprehensive east–west and north–south thermal differences over East Asia. The Niño3.4 index represents the mean SST anomaly over the Niño3.4 region (5°S–5°N, 170°–120°W). The NAT index (Marshall et al., 2001; Zuo et al., 2012) is defined as the time series corresponding to the first leading mode of the empirical orthogonal function analysis of the SST anomaly in the North Atlantic region (0°–60°N, 80°W–0°). A “negative–positive–negative” distribution of SSTA over North Atlantic from the tropics to the high latitude region reflects the feature of the NAT in its positive phase, and vice versa. In this paper, the relationship between external forcing factors and summer circulation is analyzed by composite analysis and linear regression analysis. Considering the maximum data overlapping and the interdecadal variation of the EASM, the composite/regression analyses are conducted over the period from 1982 to 2017.

    3.   Characteristics of the East Asian summer monsoon in 2018 and its influence on summer rainfall in China
    • The historical time series of the three EASM indices employed in this paper (Fig. 1) show that, for each index, the value in 2018 demonstrates an obvious positive anomaly (exceeding one standard deviation), indicating that the EASM in 2018 is much stronger than normal. Among the three indices, the index defined by Zhang et al. (2003) exceeds two standard deviations in 2018 and indicates that 2018 is the strongest EASM year since 1981 (Fig. 1b). Based on the indices defined by Shi et al. (1996) and Zhu et al. (2000), the EASM in 2018 is the 4th and 3rd strongest since 1981 (Figs. 1a, c), respectively. All the above three indices indicate that the overall intensity of the EASM is extremely large in 2018.

      Figure 1.  Temporal evolutions of the (a) Shi, (b) Zhang, and (c) Zhu EASM indices during 1981–2018.

      Summer rainfall in China shows different drought and flood distribution characteristics in various years, following different intensities of the EASM. Based on the threshold defined as 0.7 standard deviation of the EASM index proposed by Zhang et al. (2003), 11 strong EASM years (1981, 1984, 1985, 1986, 1990, 1994, 1997, 2001, 2002, 2004, and 2012) and 11 weak EASM years (1983, 1987, 1988, 1993, 1995, 1996, 1998, 2003, 2007, 2010, and 2013) are identified. Composite precipitation fields for the strong and weak EASM summers show that when the EASM is strong, precipitation in the middle and lower reaches of the Yangtze River is significantly lower than that in weak EASM summers, whereas precipitation in North, Northwest, Northeast, and South China is higher than that in weak EASM summers (Fig. 2a). Figure 2b shows the percentage precipitation anomaly (the percentage of precipitation anomaly relative to the climatology) in summer 2018. It can be seen that precipitation in most parts of North China, Northwest China, and South China is higher than normal while precipitation in the middle and lower reaches of the Yangtze River is obviously lower than normal (Fig. 2b). Such a distribution pattern indicates that the summer rainfall in 2018 is probably affected by the strong EASM in this year. Meanwhile, the anomalous distribution pattern of rainy days (daily precipitation ≥ 0.1 mm) also shows that the rainy days in most areas over the middle and lower reaches of the Yangtze River are 20%–40% less than the climatologi-cal value (Fig. 2c). In contrast, for most parts of North-west and South China, the rainy days are significantly more than normal in 2018. Such an anomalous feature of the rainy days indicates that the key circulation factors that have affected precipitation in 2018 are persistent and stable. However, for the eastern part of North China and eastern part of Huanghuai region, although the precipitation in most areas is more than normal, the rainy days are less than normal, implying that extreme precipitation may be prominent in these regions.

      Figure 2.  (a) Difference in summer precipitation (mm) between strong and weak EASM years (thick dashed line indicates the area where the difference exceeds the significance level of 0.1). (b) Percentage precipitation anomaly (%) and (c) the anomaly of rainy days for summer 2018.

      The historical time series of regional average summer precipitation show that summer precipitation in Northwest China (including Xinjiang and Ningxia regions, Qinghai, Gansu, and Shaanxi provinces) has reached 196 mm in 2018, which is 32% more than the climatological average over the same region and is the largest since 1981 (blue line in Fig. 3). The average precipitation in North China (including Beijing and Tianjin, and Hebei and Shanxi provinces) is 376 mm, 14% more than the climatological value (red line in Fig. 3). The average precipitation in the middle and lower reaches of the Yangtze River (including Shanghai and Hubei, Anhui, Jiangsu, Zhejiang, Jiangxi, and Hunan provinces) is 11% less than the climatological value and is also the least in the past five years (black line in Fig. 3).

      Figure 3.  Average summer precipitation (mm) in Northwest China (blue line), North China (red line), and the middle–lower reaches of Yangtze River (black line) for 1981–2018.

      The intraseasonal variation of summer precipitation in China is significant (He et al., 1995; Zhan et al., 2008; Zhao et al., 2011). The characteristics of precipitation anomaly in certain months in summer often exhibit large difference from overall characteristics of precipitation anomaly in the whole season (Chen et al., 2016; Yuan et al., 2017). However, in summer 2018, precipitation anomalies in June, July, and August consistently show the characteristic of “less precipitation in the middle and lower reaches of the Yangtze River and more precipitation in the northern region.” This pattern indicates that during the whole summer of 2018, the anomalous atmospheric circulations are relatively persistent and stable. The above result implies that the influence of external forcing factors may have played a dominant role compared with that of internal dynamic processes of the atmosphere.

    4.   Characteristics of the East Asian atmos-pheric circulation in summer 2018
    • The basic cause of the East Asian monsoon is the seasonal variation of the atmospheric thermal difference between ocean and land. In summer 2018, the atmospheric thermal state over the ocean and land shows a typical feature leading to strong EASM. The thickness of the atmosphere (the difference in geopotential height between 200 and 500 hPa) is used to represent the thermal state of the atmosphere. From the perspective of climatology, a warm center of the atmosphere is located near the Tibetan Plateau in summer, and hence there is an obvious thermal difference between East Asia and the North Pacific Ocean to its east and the tropical oceans to its south (Fig. 4a). Therefore, the thermal contrast between the land area in East Asia and the adjacent oceans may cause a continental thermal low over East Asia as well as the EASM. In summer 2018, there exists an anomalous warm center in the northern–central part of East Asia (Fig. 4b), implying that the atmospheric thermal difference between the ocean and land is enhanced and the EASM is intensified correspondingly.

      Figure 4.  Summertime geopotential height difference between 200 and 500 hPa: (a) climatological mean and (b) 2018 anomaly field (gpm).

      In summer 2018, all the key members of the East Asian atmospheric circulation system demonstrate features of a strong EASM. In the upper troposphere at 200 hPa, there exists an anomalous positive geopotential height center while an anticyclonic anomaly is located in northern East Asia (Fig. 5a). This pattern implies that the location of the East Asian subtropical upper jet stream is located further north than its normal position. A positive geopotential height center is also remarkably notified at 500 hPa (Fig. 5b), accompanied by two negative centers to the north and south of the positive center respectively, forming a “negative–positive–negative” anomalous pattern along the coast of East Asia. Such a feature of circulation anomaly resembles that in the positive EAP phase (Huang, 1992; Huang et al., 2003). Affected by the above circulation anomaly, the western Pacific subtropical high (WPSH) is located further north than normal. The position index of the WPSH ridge line in summer (as in Liu et al., 2012) indicates that 2018 is the year when the WPSH has reached its northernmost position since 1981 (Fig. 6). Correspondingly, anomalous wind fields at 850 hPa (Fig. 5b) show a cyclonic anomaly located from the Taiwan Strait to the northern Philippines, and an anticyclonic anomaly situated to its north. Under the influence of such a circulation anomaly pattern, most areas to the south of the middle and lower reaches of the Yangtze River are dominated by anomalous northerly winds, suppressing the transfer of water vapor to the middle and lower reaches of the Yangtze River. The divergence of horizontal wind and that of water vapor flux increase (Figs. 5b, c), which results in stronger than normal descending motion (Fig. 5d) and less precipitation in the middle and lower reaches of the Yangtze River. For most areas in the northern part of China, the lower troposphere is under the control of southerly wind anomalies (Fig. 5b), which are conducive to the transfer of water vapor (Fig. 5c) and the intensification of ascending motion (Fig. 5d), and thereby favoring more precipitation.

      Figure 5.  Anomalous (a) geopotential height (gpm) and wind (m s−1) at 200 hPa, (b) 500-hPa geopotential height (gpm) and 850-hPa wind (m s−1), (c) column-integrated water vapor flux (kg m−1 s−1) and its divergence (10−7 kg m−2 s−1), and (d) 500-hPa vertical velocity (−300 Pa s−1) in summer 2018. The red line in (b) represents the climatology mean 5880-gpm contour.

      Figure 6.  North–south position index of the ridge line of the western Pacific subtropical high (WPSH) in the summers of 1981–2018.

      In addition to the tropical and subtropical circulation systems, the atmospheric circulation in the middle and high latitudes also has important impacts on the EASM (Tao and Zhang, 1998; Wang and Gu, 2016; Xu et al., 2019b). For example, studies have pointed out that the Ural Mountains and the Okhotsk Sea are two key regions of summer atmospheric blocking activities, and establishment of the blocking situation in these two areas plays an important role in the maintenance and intensification of the Meiyu front (Tao and Zhang, 1998; Zhang and Tao, 2003). The 500-hPa geopotential height field in summer 2018 is displayed in Fig. 5b, which shows negative geopotential height centers over the regions in the vicinity of the Ural Mountains and the Okhotsk Sea, where no obvious blocking activity has occurred. Such a situation is disadvantageous for the establishment and maintenance of the Meiyu front. In contrast, it is helpful for the intensification of southerly winds over the northern part of China and thus promoting the enhancement of the EASM. To sum up, it is inferred that in addition to the East Asian subtropical jet stream and the WPSH circulation system, the atmospheric circulation anomaly over the mid–high latitudes of Eurasia also makes significant contributions to the abnormally strong EASM in 2018.

    5.   Collaborative impacts of external forcing factors on EASM in 2018
    • From autumn 2017 to spring 2018, the Niño3.4 index continued to be lower than −0.5°C, and the Southern Oscillation Index (SOI) maintained positive. A La Niña event occurred in the equatorial central eastern Pacific (Fig. 7a). According to the criterion defined by Ren et al. (2018), this is a weak La Niña event starting in October 2017 and ending in April 2018. In terms of spatial distribution of SSTA (Fig. 7b), this event is a distinct eastern type La Niña event with the cold center located near the equatorial eastern Pacific (Niño 3 region), while warm SST anomaly dominated the tropical western Pacific from winter 2017 until the subsequent summer.

      Figure 7.  (a) Evolution of the Niño3.4 index (°C) and SOI index from September 2016 to August 2018 and (b) global SST anomaly (SSTA) in the 2017/18 winter. In (b), shadings in yellow (blue) with solid (dashed) contours denote positive (negative) SSTA, and contour interval (CI) is 0.3°C.

      Previous studies have shown that in the summer following a La Niña event, an anomalous cyclonic circulation is likely to occur near the Philippines, which is favorable for a strong EASM (Wang et al., 2000). Correspondingly, the precipitation in the middle and lower reaches of the Yangtze River would be suppressed while the precipitation in North China and South China would be enhanced (Huang and Wu, 1989; Zhang et al., 1996; Wang et al., 2000). However, the impact of ENSO event on the EASM and summer precipitation in China is not the same due to interdecadal variations (Feng et al., 2014). Under the current interdecadal background (after the 1980s), the impact of La Niña on summer precipitation in China is weaker than that before the 1980s (Gao and Wang, 2007). The monsoon index in the eight summers (1985, 1989, 1996, 2000, 2001, 2008, 2011, and 2012) that followed a La Niña event since 1981 never showed any obvious feature of a strong EASM. The EASM in all five (1989, 1996, 2000, 2001, and 2008) out of the above eight years is close to normal or weak (Fig. 1). Composite precipitation in the above eight summers that followed a La Niña event never showed any significant anomalous feature either (Fig. 8). Note that the composite precipitation pattern discussed above is different from that of the summer precipitation anomaly in 2018 (Fig. 2a). This indicates that the effect of the La Niña event on the EASM and summer rainfall in China has been weakened since 1981. At the same time, under the current interdecadal background, the strong EASM in 2018 may not be the result of the single factor of La Niña event. Instead, it cloud be caused by the combined influences of several external forcing factors.

      Figure 8.  Composite precipitation (mm) over eight summers that followed a La Niña event from 1981 to 2017 (no area in the figure exceeding the 0.1 significance level).

      In addition to the ENSO event occurring in the tropi-cal Pacific, the tropical Indian SST, the North Atlantic SST, and the snow cover over the Tibetan Plateau are all key external forcing factors affecting the EASM (Chen Q. J. et al., 2000; Chen L. J. et al., 2013). The lead–lag correlations between the Niño3.4 index, the Indian Ocean basin wide mode (IOBW) index, the NAT index, the Tibetan Plateau snow area index, and the EASM index (Zhang et al., 2003) are calculated. The results are presented in Fig. 9. It is seen that all the above factors have significant correlation with the EASM index, although the correlation coefficient varies with different lead times. It is therefore concluded that each factor has significant influences on the EASM. However, there is a difference in the lead time of such an effect for each factor. It is worth noting that the snow cover index and the NAT index show similar relationships with the EASM index after removing the ENSO trend (figure omitted), which indicates that the impacts of the snow cover and the NAT on the EASM are independent of ENSO. Specifically, the relationship between the Niño3.4 index and the EASM index is most significant when the SST index leads about half a year, indicating the lagged effect of the wintertime ENSO mature phase on the EASM. For IOBW, it is found that the summertime SST is most significantly correlated with the EASM, indicating that the influence of the Indian Ocean on the EASM is almost instantaneous. Since the variability of summertime SST over the tropical Indian Ocean is largely attributed to its response to ENSO event, it has been revealed that the summer Indian Ocean SST mainly acts as a “capacitor” and exerts a delayed effect on the EASM, after the ENSO event (Xie et al., 2009, 2016). For the NAT, the most significantly correlated period with EASM is in spring, and the relationship between the Tibetan snow cover and the EASM is significant since winter and reaches its peak value in spring. The lead–lag correlation relationships of the above factors with the EASM are basically consistent with previous studies.

      Figure 9.  Lead–lag correlation coefficients of the Niño3.4 index, IOBW index, NAT index, and Tibetan snow cover index with the EASM index (three-month sliding average is performed prior to the calculation of correlation).

      According to the period during which each factor is significantly correlated to the EASM, the wintertime Niño3.4 index, summertime IOBW index, springtime NAT index, and wintertime Tibetan snow cover index are used to further analyze the characteristics of external forcing factors and their influences on the EASM in 2018. The historical series of the above indices show clearly that these factors in 2018 demonstrate obvious anomalous characteristics (Fig. 10). In winter, the Niño3.4 SST is significantly colder (Fig. 10a) and the Tibetan snow cover is less than normal (Fig. 10d); in spring, the NAT remains in its positive phase (Fig. 10c); in summer, the SST in the tropical Indian Ocean is colder than normal (Fig. 10b). In order to further reveal the impact of each individual factor on the EASM in 2018, the atmospheric circulation is regressed onto each external factor and the results are discussed next.

      Figure 10.  Temporal evolutions of (a) the Niño3.4 index in winter, (b) the IOBW index in summer, (c) the NAT index in spring, and (d) the Tibetan snow cover index in winter during 1982–2018.

    • In the typical years with colder than normal Niño3.4 SST in winter, atmospheric circulation in the subtropical East Asia usually demonstrates significant signals of a positive EAP pattern (cyclone–anticyclone–cyclone) developing along the coastal region of East Asia at 500 hPa. The WPSH tends to be located further north and an anomalous cyclonic circulation appears near the Philippines (Fig. 11a). Such a circulation pattern reflects the main feature of a strong EASM, suggesting that the wintertime cold SST in the eastern tropical Pacific is favorable for a strong EASM. However, as shown in Fig. 11a, the significance level in the East Asian subtropical region is not very high and the corresponding geopotential height and wind anomalies are also relatively weak. The above result indicates that the influence of the La Niña event on the EASM is probably limited under the current interdecadal background.

      Figure 11.  Composite 500-hPa geopotential height (gpm) and 850-hPa wind (m s−1) anomalies in the summers (a) following the La Niña occurrence winters with negative Niño3.4 index, (b) with negative summer IOBW index, (c) following the springs with positive NAT index, and (d) following the winters with negative winter plateau snow cover index. Dark, medium, and light shadings indicate the areas with values above the significance level of 0.01, 0.05, and 0.1, respectively; red solid lines represent the climatological mean 5870-gpm contour. Only wind vectors exceeding the 0.2 significance level are shown.

      Generally, in the summer following an ENSO event, the equatorial eastern Pacific SST usually becomes close to normal, while the anomalous anticyclone/cyclone near the Philippines can still maintain. The maintenance of the anticyclone/cyclone anomaly near the Philippines can be attributed to the IOBW, which has a strong lagged response to the ENSO event and a positive feedback with the anomalous anticyclone/cyclone in the Philippines. That is to say, the Indian Ocean SST can preserve the wintertime ENSO signal and release it in the summer. According to the composite circulation pattern in the cold IOBW summers (Fig. 11b), a positive EAP phase along the coast of East Asia and an anomalous cyclone near the Philippines are promoted by the cold Indian Ocean SST. The above impacts of the Indian Ocean on the circulation are similar to and even more significant than that of the equatorial eastern Pacific (Fig. 11a), indicating that the Indian Ocean can store the La Niña signal and “relay” it in the summer. The close relationship between the Indian Ocean SST and the summer circulation in East Asia shows that the cold IOBW in summer plays an important role in maintaining the influence of the La Niña event until summer and promoting a strong EASM.

    • The NAT is the first leading mode of the North Atlantic SST and it is also the main source for the atmospheric interannual variability in North Atlantic. Previous studies have revealed that the springtime NAT can significantly influence the EASM. It affects the EASM through triggering atmospheric teleconnection wave trains over Eurasia, which subsequently lead to circulation anomaly in the mid–high latitude area. In addition, it is found that the anomalous convective activities in the tropical Atlantic corresponding to the NAT play an important role in the anomalous cyclone/anticyclone near the Philippines (Zuo et al., 2013, 2018). The composite circulation pattern at 500 hPa in the summer following a positive springtime NAT (Fig. 11c) shows that there is a significant positive geopotential height anomaly center near the Balkhash Lake and a negative center near the Ural Mountains. This suggests that the blocking activity near the Ural Mountains is suppressed, which is not favorable for the strengthening and maintenance of the Meiyu front but is helpful for the intensification of the EASM. Meanwhile, there is an obvious anomalous cyclone located to the east of the Philippines (Fig. 11c), which has beneficial effects on the northward shift of the WPSH and a strong EASM. The anomalous circulation in summer 2018 (Fig. 5b) has shown similar features to the composite circulation pattern in positive NAT years (Fig. 11c) in the mid–high latitude regions. It is therefore deduced that the positive phase NAT probably exerts a significant influence on the circulation over the mid–high latitudes in summer 2018. Moreover, the NAT might also contribute to the anomalous cyclonic circulation around the Philippines in summer 2018.

    • The Tibetan Plateau plays an important role in the formation and variation of the East Asian monsoon due to its special geographical location, topographical height, and remarkable seasonal to interannual variations of thermal condition (Liu et al., 1999; Wu et al., 2018). The area of snow cover is one of the most important variables used to reflect the thermal condition on the plateau, and it is also an important external forcing signal frequently used in the diagnosis and prediction of summertime climate in China in recent years (Chen et al., 2000; Peng et al., 2005). It has been revealed that the wintertime snow cover anomaly on the Tibetan Plateau can affect the EASM either by changing the thermal difference between the plateau and the surrounding oceans (Zhang and Tao, 2001) or by contributing to the formation of the cyclone/anticyclone anomaly near the Philippines in early summer (Ren et al., 2016). The composite circulation pattern during the summers that follow those winters with less snow cover on the plateau shows negative geopotential height anomalies in the subtropical region of East Asia and an anomalous cyclone near the Philippines (Fig. 11d). The above circulation pattern indicates a strong EASM, and such a snow–EASM relationship is consistent with the results found in previous studies (Zhang and Tao, 2001; Ren et al., 2016). In the 2017/18 winter, the snow cover area on the plateau was obviously smaller than normal (Fig. 10d) and the summer circulation in East Asia (Fig. 5b) also showed characteristics similar to the composite circulation pattern in less snow years (Fig. 11d). The above result indicates that the less than normal snow cover over the Tibetan Plateau in the winter of 2017/18 has also contributed to the strong EASM in the following summer of 2018.

    • The above analyses have revealed that the strong EASM in summer 2018 is a result of the combined impacts of the La Niña event, the cold IOBW, the positive NAT, and the less than normal snow cover over the Tibetan Plateau. Since the variability of IOBW mainly arises from ENSO events, the influence of the IOBW on the EASM is not independent of ENSO impact. Furthermore, the correlations of the NAT index and the plateau snow cover index with the EASM index are still significant after the ENSO signal is removed, which indicates that the influences of the NAT and the snow cover on the EASM are also independent of ENSO. Therefore, when the combined effects of external factors are examined, only the La Niña event, the NAT, and the Tibetan snow cover are considered as three independent factors.

      Linear regression equations for the summer circulation are established by using the Nino3.4 index, the NAT index, and the Tibetan snow cover index as predictors, respectively. The data from 1982 to 2017 are used to establish the equations. The circulation in summer 2018 is then forecasted by using the three equations and values of individual predictors in 2018, respectively. Finally, predictions of the circulation in summer 2018 based on the three equations are added to represent the combined impacts of the three predictors. The results are displayed in Fig. 12, which shows obvious negative geopotential height anomalies in the tropical western Pacific region. These negative anomalies apparently correspond to the cyclonic circulation anomaly near the Philippines. Along the coastal region of East Asia, the “cyclone–anticyclone–cyclone” distribution from south to north represents a positive phase of the EAP teleconnection pattern. In the mid–high latitude region of Eurasia, two negative geopotential height anomaly centers are located near the Ural Mountains and the Okhotsk Sea, respectively, while a positive center is found to the north of the Lake Baikal. The characteristics of the predicted circulation anomaly described above are similar to those in the observations (Fig. 5b), implying that the combined impacts of the three factors all play key roles in the East Asian circulation in summer 2018. In Fig. 12, the shadings, the red bold lines, and blue bold lines indicate the areas where the La Niña event, the NAT, and the Tibetan snow cover are significantly correlated with the 500-hPa geopotential height anomaly. It can be seen that all the three factors contribute significantly to the negative geopotential height center in the tropical western Pacific and the corresponding anomalous cyclone near the Philippines, while the anomalous geopotential height centers near the Ural Mountains and the Okhotsk Sea are largely related to variations of the NAT and snow cover over the Tibetan Plateau.

      Figure 12.  Sum of the regressed values of 500-hPa geopotential height and 850-hPa wind in summer 2018 calculated according to the linear regression equations using the Niño3.4 index, the NAT index, and the Tibetan snow cover area index from 1982 to 2017, respectively. Black contours represent the 500-hPa geopotential height anomaly (gpm); vectors represent 850-hPa wind anomaly (m s−1); and shadings, red thick lines, and blue thick lines indicate the areas where the correlations of the Niño3.4 index, the NAT index, and the Tibetan snow cover index with the geopotential height anomaly exceeding the significant level of 0.1. Letters A and C denote anomalous anticyclone and cyclone, respectively.

    6.   Comparative analysis of the EASM in typical years with combined influence of multiple factors
    • The key external forcing factors of the EASM, such as the tropical SST, the North Atlantic SST, and the Tibetan snow cover, have a complicated collaborative effect on summer climate in East Asia. Sometimes only one factor plays a dominant role, and sometimes multiple factors jointly contribute to the variation of the EASM. There are also cases in which different factors “cancel out” their impacts. The above analysis has shown clearly that in summer 2018, the tropical SST, the NAT, and the Tibetan snow cover all have reinforced their influences on the EASM circulation and these influences are consistent and collaborative; i.e., all of the three factors are favorable for a strong EASM, and they act together to have produced an extremely strong EASM in 2018.

      Historical data of the three external factors since 1981 have been examined, and the EASM in 1985 is found to have features similar to that in 2018. The summer of 1985 also followed a weak La Niña event, the spring NAT was in a strong positive phase, and the wintertime Tibetan snow cover was less than normal. Correspondingly, circulation in East Asia and precipitation in China in summer 1985 are similar to their counterparts in summer 2018. The EAP pattern in its positive phase along the coast of East Asia, an anomalous cyclone near the Philippines, and a negative geopotential height center near the Ural Mountains are obvious features shown in the 500-hPa geopotential height and 850-hPa wind fields (Fig. 13a). The EASM in 1985 was also stronger than normal (Fig. 1). The main feature of precipitation in 1985 also resembled that of 2018, with negative anomalies dominating the regions around the Yangtze River valley and positive anomalies distributed mainly in North China (Fig. 14a).

      Figure 13.  500-hPa geopotential height (gpm) and 850-hPa wind (m s−1) anomalies in the summers of (a) 1985, (b) 1983, and (c) 1998. The red lines represent the climatology mean 5880-gpm contour.

      Figure 14.  Percentage precipitation anomalies (%) in the summers of (a) 1985, (b) 1983, and (c) 1998. Contour interval is 50% in each plot.

      Different from the situation in 1985, there are two other years with features of the external factors opposite to the case of 2018. Both the summers of 1983 and 1998 followed an El Niño event, the spring NAT in the two years was in strong negative phase, and the Tibetan snow co-ver in the winter was larger than normal. Correspondingly, the East Asian summer circulation and precipitation generally exhibited features opposite to that in the summers of 2018 and 1985. An anticyclone–cyclone–anticyclone circulation pattern developed along the coastal region of East Asia, corresponding to the EAP pattern in negative phase. Meanwhile, an anomalous anticyclone occurred near the Philippines and a positive geopotential height center appeared near the Ural Mountains (Figs. 13b, c). Under such a circulation circumstance, the EASM in 1983 and 1998 was much weaker than normal. According to the index defined by Zhang et al. (2003), 1998 is the weakest EASM year since 1981 (Fig. 1). In the summers of 1983 and 1998, there was more precipitation near the Yangtze River valley (Figs. 14b, c) and severe flooding disasters occurred (Li, 1999).

      Comparative analysis of the EASM in typical anomalous years described above further demonstrates that ENSO event related SST anomaly, NAT, and the Tibetan snow cover all have significant influences on the EASM. Specifically, when the effects of the above factors are reinforced, their combined impact on the summer circulation and precipitation in East Asia could be highly significant.

    7.   Summary and discussion
    • According to the three representative EASM indices, the EASM in summer 2018 is found stronger than normal. Particularly, the index defined by Zhang et al. (2003) shows that 2018 is the strongest EASM year since 1981. The East Asian atmospheric circulation in summer 2018 also exhibits typical characteristics of a strong EASM. In the upper troposphere, the location of the East Asian subtropical jet is further north than normal in 2018. In the middle troposphere, the EAP in positive phase is obvious along the coastal region of East Asia and the ridge line of the WPSH is located more northward. In the lower troposphere, an anomalous cyclone occurs near the Philippines and an anomalous anticyclo-nic circulation appears to its north. Under the above circulation background, anomalous northerly winds occur to the south of the Yangtze River valley while southerly wind anomalies happen to the north. These circulation anomalies are favorable for the development of divergence and descending motion near the Yangtze River valley, and precipitation in this region is suppressed. For most of the northern areas of China, anomalous southerly winds are beneficial for the transfer of water vapor and more precipitation is thus induced. In addition, the features of mid–high latitude circulation also contribute to the strong EASM in 2018. Two negative geopotential height centers are located in the vicinity of the Ural Mountains and the Okhotsk Sea, respectively, and the blocking activities near the above two regions are suppressed, which weaken the Meiyu front, intensify the EASM, and promote more rainfall in the northern parts of China.

      From winter 2017/18 to summer 2018, several key external forcing factors of the EASM, such as the La Niña event, the cold IOBW, the positive NAT, and the less than normal snow cover over the Tibetan Plateau all exhibit obvious anomalous features. The impacts of individual factors mentioned above are consistently favorable for the development of a strong EASM. A weak La Niña event occurred from October 2017 to April 2018, which triggered an anomalous cyclonic circulation near the Philippines during winter 2017. In response to the La Niña event, the IOBW entered its cold phase in the subsequent spring and summer, conducive to maintenance of the anomalous cyclone in the Philippine until summer. Meanwhile, the NAT in its positive phase in spring has weakened the blocking activities by triggering wave trains over Eurasia, resulting in a negative geopotential height center near the Ural Mountains. As a result, the Meiyu front is attenuated. The NAT in its positive phase might also contribute to the development of the cyclonic anomaly in the Philippines through remote teleconnection of the tropical atmosphere. Besides, the less than normal Tibetan snow cover in winter of 2017/18 is favorable for the strengthening of the thermal effect of the plateau in the subsequent spring and summer and further enhancement of the cyclonic anomaly in the Philippines in early summer, which further intensifies the EASM. It is concluded that the strong EASM in 2018 is closely related to the combined, reinforced, and collaborative effects of the La Niña event, the tropical Indian Ocean SST, the North Atlantic SST, and the Tibetan snow cover.

      By examining the external factors that affect the EASM since 1981, it is found that the case in 1985 is similar to that in 2018, while the features in 1983 and 1998 are opposite to those in 2018. For the two groups of years with different characteristics, the East Asian summer circulation and precipitation in China exhibit opposite features. This result further demonstrates the importance of collaborative impacts of external forcing factors on the EASM, such as the tropical SST, the North Atlantic SST, and the Tibetan snow cover. With reinforced impacts of the above external factors, the anomalous feature of the EASM turns to be more remarkable. That is to say, the presence of such strong precursor signals is beneficial to improving the climate predictability and to more accurate climate prediction and better service for disaster prevention (Li, 1999; Chen et al., 2019). In the future, it is necessary to investigate the ability of dyna-mic climate models in simulating and predicting the combined effects of the multiple factors on the EASM and quantitatively analyze the contribution and the influencing mechanism of individual factors.

      Acknowledgments. We thank the four anonymous reviewers for their constructive comments that led to improvements to this paper.

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