Editorial Type:
Article
Article Type:
Research Article

Long-Term Changes, Synoptic Behaviors, and Future Projections of Large-Scale Anomalous Precipitation Events in China Detected by a Deep Learning Autoencoder

Zeqin Huang aCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China

Search for other papers by Zeqin Huang in
Current site
Google Scholar
PubMed Close
,
Xuezhi Tan aCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China
bSouthern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China

Search for other papers by Xuezhi Tan in
Current site
Google Scholar
PubMed Close
https://orcid.org/0000-0001-5682-3477
,
Xinxin Wu aCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China

Search for other papers by Xinxin Wu in
Current site
Google Scholar
PubMed Close
,
Xuejin Tan aCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China

Search for other papers by Xuejin Tan in
Current site
Google Scholar
PubMed Close
,
Jianyu Fu aCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China

Search for other papers by Jianyu Fu in
Current site
Google Scholar
PubMed Close
, and
Bingjun Liu aCenter of Water Resources and Environment, School of Civil Engineering, Sun Yat-sen University, Guangzhou, China

Search for other papers by Bingjun Liu in
Current site
Google Scholar
PubMed Close
Online Publication:
23 May 2023
Print Publication:
15 Jun 2023
DOI:
https://doi.org/10.1175/JCLI-D-22-0737.1
Page(s):
4133–4149
Restricted access

Abstract

The frequency of large-scale anomalous precipitation events over China has increased during 1961–2018. However, it remains challenging to understand the mechanisms associated with these anomalous events showing different spatial patterns. Here, we applied an autoencoder technique to identify large-scale anomalous precipitation events for both observations and model simulations, which were then classified into several patterns through a self-organizing map method. The synoptic behavior and atmospheric circulation background of different anomalous patterns were also analyzed using simultaneous composite analyses. Results show that occurrences of different anomalous precipitation patterns have increased significantly, except those centered in North China, Northeast China, and the Yangtze River basin. The anomalous precipitation patterns manifest various intraseasonal distributions, which are linked to zonal oscillations of the western North Pacific subtropical high (WNPSH) and meridional displacements of East Asia westerly jet (EAJ). Accompanied by the westward movement of WNPSH, anticyclonic systems transport warm moist air from the Indian Ocean and the South China Sea to converge with the cold air caused by anomalous cyclones over the northwest flank of the WNPSH, leading to large-scale anomalous precipitation in these regions. Besides WNPSH, the northward and southward displacements of EAJ also favor the occurrence of anomalous precipitation events in northern and southern China, respectively. Our study also illustrates that the occurrence frequency of anomalous precipitation events is projected to increase remarkably under the Shared Socioeconomic Pathway 5–8.5 (SSP585) scenario by rates of twofold to fourfold.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding authors: Xuezhi Tan, tanxuezhi@mail.sysu.edu.cn; Bingjun Liu, liubj@mail.sysu.edu.cn

Abstract

The frequency of large-scale anomalous precipitation events over China has increased during 1961–2018. However, it remains challenging to understand the mechanisms associated with these anomalous events showing different spatial patterns. Here, we applied an autoencoder technique to identify large-scale anomalous precipitation events for both observations and model simulations, which were then classified into several patterns through a self-organizing map method. The synoptic behavior and atmospheric circulation background of different anomalous patterns were also analyzed using simultaneous composite analyses. Results show that occurrences of different anomalous precipitation patterns have increased significantly, except those centered in North China, Northeast China, and the Yangtze River basin. The anomalous precipitation patterns manifest various intraseasonal distributions, which are linked to zonal oscillations of the western North Pacific subtropical high (WNPSH) and meridional displacements of East Asia westerly jet (EAJ). Accompanied by the westward movement of WNPSH, anticyclonic systems transport warm moist air from the Indian Ocean and the South China Sea to converge with the cold air caused by anomalous cyclones over the northwest flank of the WNPSH, leading to large-scale anomalous precipitation in these regions. Besides WNPSH, the northward and southward displacements of EAJ also favor the occurrence of anomalous precipitation events in northern and southern China, respectively. Our study also illustrates that the occurrence frequency of anomalous precipitation events is projected to increase remarkably under the Shared Socioeconomic Pathway 5–8.5 (SSP585) scenario by rates of twofold to fourfold.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding authors: Xuezhi Tan, tanxuezhi@mail.sysu.edu.cn; Bingjun Liu, liubj@mail.sysu.edu.cn

Supplementary Materials

    • Supplemental Materials (PDF 4.62 MB)
Save
Cover Journal of Climate
Journal of Climate

  • Allen, M. R., and W. J. Ingram, 2002: Constraints on future changes in climate and the hydrologic cycle. Nature, 419, 224–232, https://doi.org/10.1038/nature01092.

    • Search Google Scholar
    • Export Citation

  • Bonsal, B. R., C. Cuell, E. Wheaton, D. J. Sauchyn, and E. Barrow, 2017: An assessment of historical and projected future hydro-climatic variability and extremes over southern watersheds in the Canadian prairies. Int. J. Climatol., 37, 3934–3948, https://doi.org/10.1002/joc.4967.

    • Search Google Scholar
    • Export Citation

  • Chen, G., J. Norris, J. D. Neelin, J. Lu, L. R. Leung, and K. Sakaguchi, 2019: Thermodynamic and dynamic mechanisms for hydrological cycle intensification over the full probability distribution of precipitation events. J. Atmos. Sci., 76, 497–516, https://doi.org/10.1175/JAS-D-18-0067.1.

    • Search Google Scholar
    • Export Citation

  • Chen, J., and Coauthors, 2021: Changing impacts of tropical cyclones on East and Southeast Asian inland regions in the past and a globally warmed future climate. Front. Earth Sci., 9, 769005, https://doi.org/10.3389/feart.2021.769005.

    • Search Google Scholar
    • Export Citation

  • Chen, S., B. Liu, X. Tan, and Z. Huang, 2019: Characteristics and circulation background of extreme precipitation over East China. Nat. Hazards, 99, 537–552, https://doi.org/10.1007/s11069-019-03758-2.

    • Search Google Scholar
    • Export Citation

  • Cheng, T. F., M. Lu, and L. Dai, 2019: The zonal oscillation and the driving mechanisms of the extreme western North Pacific subtropical high and its impacts on East Asian summer precipitation. J. Climate, 32, 3025–3050, https://doi.org/10.1175/JCLI-D-18-0076.1.

    • Search Google Scholar
    • Export Citation

  • Chiang, J. C. H., W. Kong, C. H. Wu, and D. S. Battisti, 2020: Origins of East Asian summer monsoon seasonality. J. Climate, 33, 7945–7965, https://doi.org/10.1175/JCLI-D-19-0888.1.

    • Search Google Scholar
    • Export Citation

  • Chong, Y. S., and Y. H. Tay, 2017: Abnormal event detection in videos using spatiotemporal autoencoder. Advances in Neural Networks—ISNN 2017, F. Cong, A. Leung, and Q. Wei, Eds., Springer International Publishing, 189–196.

  • Chow, J. K., 2020: Anomaly detection of defects on concrete structures with the convolutional autoencoder. Adv. Eng. Inf., 45, 101105, https://doi.org/10.1016/j.aei.2020.101105.

    • Search Google Scholar
    • Export Citation

  • Chu, J.-E., S. N. Hameed, and K.-J. Ha, 2012: Nonlinear, intraseasonal phases of the East Asian summer monsoon: Extraction and analysis using self-organizing maps. J. Climate, 25, 6975–6988, https://doi.org/10.1175/JCLI-D-11-00512.1.

    • Search Google Scholar
    • Export Citation

  • Davenport, F. V., and N. S. Diffenbaugh, 2021: Using machine learning to analyze physical causes of climate change: A case study of U.S. Midwest extreme precipitation. Geophys. Res. Lett., 48, e2021GL093787, https://doi.org/10.1029/2021GL093787.

    • Search Google Scholar
    • Export Citation

  • Ding, Y., and J. C. L. Chan, 2005: The East Asian summer monsoon: An overview. Meteor. Atmos. Phys., 89, 117–142, https://doi.org/10.1007/s00703-005-0125-z.

    • Search Google Scholar
    • Export Citation

  • Donat, M. G., A. L. Lowry, L. V. Alexander, P. A. O’Gorman, and N. Maher, 2016: More extreme precipitation in the world’s dry and wet regions. Nat. Climate Change, 6, 508–513, https://doi.org/10.1038/nclimate2941.

    • Search Google Scholar
    • Export Citation

  • Dong, S., Y. Sun, and C. Li, 2020: Detection of human influence on precipitation extremes in Asia. J. Climate, 33, 5293–5304, https://doi.org/10.1175/JCLI-D-19-0371.1.

    • Search Google Scholar
    • Export Citation

  • Du, Y., Z. Q. Xie, and Q. Miao, 2020: Spatial scales of heavy meiyu precipitation events in eastern China and associated atmospheric processes. Geophys. Res. Lett., 47, e2020GL087086, https://doi.org/10.1029/2020GL087086.

    • Search Google Scholar
    • Export Citation

  • Gao, T., H. J. Wang, and T. Zhou, 2017: Changes of extreme precipitation and nonlinear influence of climate variables over monsoon region in China. Atmos. Res., 197, 379–389, https://doi.org/10.1016/j.atmosres.2017.07.017.

    • Search Google Scholar
    • Export Citation

  • Gao, T., Q. Zhang, and M. Luo, 2020: Intensifying effects of El Niño events on winter precipitation extremes in southeastern China. Climate Dyn., 54, 631–648, https://doi.org/10.1007/s00382-019-05022-6.

    • Search Google Scholar
    • Export Citation

  • Grose, M. R., and Coauthors, 2020: Insights from CMIP6 for Australia’s future climate. Earth’s Future, 8, e2019EF001469, https://doi.org/10.1029/2019EF001469.

    • Search Google Scholar
    • Export Citation

  • Guan, W., H. Hu, X. Ren, and X.-Q. Yang, 2019: Subseasonal zonal variability of the western Pacific subtropical high in summer: Climate impacts and underlying mechanisms. Climate Dyn., 53, 3325–3344, https://doi.org/10.1007/s00382-019-04705-4.

    • Search Google Scholar
    • Export Citation

  • Halton, J. H., 1970: A retrospective and prospective survey of the Monte Carlo method. SIAM Rev., 12 (1), 1–63, https://doi.org/10.1137/1012001.

    • Search Google Scholar
    • Export Citation

  • He, L., X. Hao, H. Li, and T. Han, 2021: How do extreme summer precipitation events over eastern China subregions change? Geophys. Res. Lett., 48, e2020GL091849, https://doi.org/10.1029/2020GL091849.

    • Search Google Scholar
    • Export Citation

  • Horton, D. E., N. C. Johnson, D. Singh, D. L. Swain, B. Rajaratnam, and N. S. Diffenbaugh, 2015: Contribution of changes in atmospheric circulation patterns to extreme temperature trends. Nature, 522, 465–469, https://doi.org/10.1038/nature14550.

    • Search Google Scholar
    • Export Citation

  • Huang, X., and D. L. Swain, 2022: Climate change is increasing the risk of a California megaflood. Sci. Adv., 8, eabq0995, https://doi.org/10.1126/sciadv.abq0995.

    • Search Google Scholar
    • Export Citation

  • Huang, X., D. Wang, A. D. Ziegler, X. Liu, H. Zeng, Z. Xu, and Z. Zeng, 2022: Influence of urbanization on hourly extreme precipitation over China. Environ. Res. Lett., 17, 044010, https://doi.org/10.1088/1748-9326/ac59a6.

    • Search Google Scholar
    • Export Citation

  • Kosaka, Y., S.-P. Xie, and H. Nakamura, 2011: Dynamics of interannual variability in summer precipitation over East Asia. J. Climate, 24, 5435–5453, https://doi.org/10.1175/2011JCLI4099.1.

    • Search Google Scholar
    • Export Citation

  • Lee, M., T. Kim, D. Cha, S. Min, D. R. Park, S. Yeh, and J. C. L. Chan, 2021: How does Pacific decadal oscillation affect tropical cyclone activity over far East Asia? Geophys. Res. Lett., 48, e2021GL096267, https://doi.org/10.1029/2021GL096267.

    • Search Google Scholar
    • Export Citation

  • Lee, S., and S. B. Feldstein, 2013: Detecting ozone- and greenhouse gas–driven wind trends with observational data. Science, 339, 563–567, https://doi.org/10.1126/science.1225154.

    • Search Google Scholar
    • Export Citation

  • Li, C., W. Chen, X. Hong, and R. Lu, 2017: Why was the strengthening of rainfall in summer over the Yangtze River valley in 2016 less pronounced than that in 1998 under similar preceding El Niño events?—Role of midlatitude circulation in August. Adv. Atmos. Sci., 34, 1290–1300, https://doi.org/10.1007/s00376-017-7003-8.

    • Search Google Scholar
    • Export Citation

  • Li, C., and Coauthors, 2019: Larger increases in more extreme local precipitation events as climate warms. Geophys. Res. Lett., 46, 6885–6891, https://doi.org/10.1029/2019GL082908.

    • Search Google Scholar
    • Export Citation

  • Li, J., X. Hao, H. Liao, X. Yue, H. Li, X. Long, and N. Li, 2022: Predominant type of dust storms that influences air quality over northern China and future projections. Earth’s Future, 10, e2022EF002649, https://doi.org/10.1029/2022EF002649.

    • Search Google Scholar
    • Export Citation

  • Li, M., Z. Jiang, P. Zhou, H. Le Treut, and L. Li, 2020: Projection and possible causes of summer precipitation in eastern China using self-organizing map. Climate Dyn., 54, 2815–2830, https://doi.org/10.1007/s00382-020-05150-4.

    • Search Google Scholar
    • Export Citation

  • Li, X., and R. Lu, 2018: Subseasonal change in the seesaw pattern of precipitation between the Yangtze River basin and the tropical western North Pacific during summer. Adv. Atmos. Sci., 35, 1231–1242, https://doi.org/10.1007/s00376-018-7304-6.

    • Search Google Scholar
    • Export Citation

  • Li, X., R. Lu, and G. Li, 2021: Different configurations of interannual variability of the western North Pacific subtropical high and East Asian westerly jet in summer. Adv. Atmos. Sci., 38, 931–942, https://doi.org/10.1007/s00376-021-0339-0.

    • Search Google Scholar
    • Export Citation

  • Li, X., K. Zhang, H. Bao, and H. Zhang, 2022: Climatology and changes in hourly precipitation extremes over China during 1970–2018. Sci. Total Environ., 839, 156297, https://doi.org/10.1016/j.scitotenv.2022.156297.

    • Search Google Scholar
    • Export Citation

  • Liu, B., X. Tan, T. Y. Gan, X. Chen, K. Lin, M. Lu, and Z. Liu, 2020: Global atmospheric moisture transport associated with precipitation extremes: Mechanisms and climate change impacts. Wiley Interdiscip. Rev.: Water, 7, e1412, https://doi.org/10.1002/wat2.1412.

    • Search Google Scholar
    • Export Citation

  • Liu, L., Y. Wang, R. Zhan, J. Xu, and Y. Duan, 2020: Increasing destructive potential of landfalling tropical cyclones over China. J. Climate, 33, 3731–3743, https://doi.org/10.1175/JCLI-D-19-0451.1.

    • Search Google Scholar
    • Export Citation

  • Liu, Y., and Coauthors, 2022: Associated summer rainfall changes over the Three Rivers source region in China with the East Asian westerly jet from 1979 to 2015. J. Appl. Meteor. Climatol., 61, 1385–1397, https://doi.org/10.1175/JAMC-D-21-0127.1.

    • Search Google Scholar
    • Export Citation

  • Lu, R., 2004: Associations among the components of the East Asian summer monsoon system in the meridional direction. J. Meteor. Soc. Japan, 82, 155–165, https://doi.org/10.2151/jmsj.82.155.

    • Search Google Scholar
    • Export Citation

  • Min, S.-K., X. Zhang, F. W. Zwiers, and G. C. Hegerl, 2011: Human contribution to more-intense precipitation extremes. Nature, 470, 378–381, https://doi.org/10.1038/nature09763.

    • Search Google Scholar
    • Export Citation

  • Monerie, P.-A., L. J. Wilcox, and A. G. Turner, 2022: Effects of anthropogenic aerosol and greenhouse gas emissions on Northern Hemisphere monsoon precipitation: Mechanisms and uncertainty. J. Climate, 35, 2305–2326, https://doi.org/10.1175/JCLI-D-21-0412.1.

    • Search Google Scholar
    • Export Citation

  • Murakami, H., 2022: Replication data for: “Increasing frequency of extreme precipitation events in Japan detected by deep learning autoencoder.” Harvard Dataverse, accessed 10 July 2022, https://doi.org/10.7910/DVN/TWZR75.

    • Search Google Scholar
    • Export Citation

  • Murakami, H., T. L. Delworth, W. F. Cooke, S. B. Kapnick, and P.-C. Hsu, 2022: Increasing frequency of anomalous precipitation events in Japan detected by a deep learning autoencoder. Earth’s Future, 10, e2021EF002481, https://doi.org/10.1029/2021EF002481.

    • Search Google Scholar
    • Export Citation

  • Ning, G., M. Luo, Q. Zhang, S. Wang, Z. Liu, Y. Yang, S. Wu, and Z. Zeng, 2021: Understanding the mechanisms of summer extreme precipitation events in Xinjiang of arid northwest China. Geophys. Res. Atmos., 126, e2020JD034111, https://doi.org/10.1029/2020JD034111.

    • Search Google Scholar
    • Export Citation

  • Ning, L., J. Liu, and B. Wang, 2017: How does the South Asian High influence extreme precipitation over eastern China? J. Geophys. Res. Atmos., 122, 4281–4298, https://doi.org/10.1002/2016JD026075.

    • Search Google Scholar
    • Export Citation

  • O’Gorman, P. A., 2015: Precipitation extremes under climate change. Curr. Climate Change Rep., 1, 49–59, https://doi.org/10.1007/s40641-015-0009-3.

    • Search Google Scholar
    • Export Citation

  • Pendergrass, A. G., 2018: What precipitation is extreme? Science, 360, 1072–1073, https://doi.org/10.1126/science.aat1871.

  • Pfahl, S., P. A. O’Gorman, and E. M. Fischer, 2017: Understanding the regional pattern of projected future changes in extreme precipitation. Nat. Climate Change, 7, 423–427, https://doi.org/10.1038/nclimate3287.

    • Search Google Scholar
    • Export Citation

  • Ren, X., X.-Q. Yang, and X. Sun, 2013: Zonal oscillation of western Pacific subtropical high and subseasonal SST variations during Yangtze persistent heavy rainfall events. J. Climate, 26, 8929–8946, https://doi.org/10.1175/JCLI-D-12-00861.1.

    • Search Google Scholar
    • Export Citation

  • Sakurada, M., and T. Yairi, 2014: Anomaly detection using autoencoders with nonlinear dimensionality reduction. Proc. MLSDA 2014 2nd Workshop on Machine Learning for Sensory Data Analysis, Gold Coast, QLD, Australia, ACM, 4–11.

  • Sampe, T., and S.-P. Xie, 2010: Large-scale dynamics of the meiyu-baiu rainband: Environmental forcing by the westerly jet. J. Climate, 23, 113–134, https://doi.org/10.1175/2009JCLI3128.1.

    • Search Google Scholar
    • Export Citation

  • Sarojini, B. B., P. A. Stott, and E. Black, 2016: Detection and attribution of human influence on regional precipitation. Nat. Climate Change, 6, 669–675, https://doi.org/10.1038/nclimate2976.

    • Search Google Scholar
    • Export Citation

  • Seager, R., N. Naik, and G. A. Vecchi, 2010: Thermodynamic and dynamic mechanisms for large-scale changes in the hydrological cycle in response to global warming. J. Climate, 23, 4651–4668, https://doi.org/10.1175/2010JCLI3655.1.

    • Search Google Scholar
    • Export Citation

  • Shi, X., Y. Wang, and X. Xu, 2008: Effect of mesoscale topography over the Tibetan Plateau on summer precipitation in China: A regional model study. Geophys. Res. Lett., 35, L19707, https://doi.org/10.1029/2008GL034740.

    • Search Google Scholar
    • Export Citation

  • Sun, Q., X. Zhang, F. Zwiers, S. Westra, and L. V. Alexander, 2021: A global, continental, and regional analysis of changes in extreme precipitation. J. Climate, 34, 243–258, https://doi.org/10.1175/JCLI-D-19-0892.1.

    • Search Google Scholar
    • Export Citation

  • Tan, X., T. Y. Gan, and D. E. Horton, 2018: Projected timing of perceivable changes in climate extremes for terrestrial and marine ecosystems. Global Change Biol., 24, 4696–4708, https://doi.org/10.1111/gcb.14329.

    • Search Google Scholar
    • Export Citation

  • Tan, X., T. Y. Gan, S. Chen, D. E. Horton, X. Chen, B. Liu, and K. Lin, 2019a: Trends in persistent seasonal-scale atmospheric circulation patterns responsible for seasonal precipitation totals and occurrences of precipitation extremes over Canada. J. Climate, 32, 7105–7126, https://doi.org/10.1175/JCLI-D-18-0408.1.

    • Search Google Scholar
    • Export Citation

  • Tan, X., T. Y. Gan, and Y. D. Chen, 2019b: Synoptic moisture pathways associated with mean and extreme precipitation over Canada for winter and spring. Climate Dyn., 53, 2663–2681, https://doi.org/10.1007/s00382-019-04649-9.

    • Search Google Scholar
    • Export Citation

  • Tan, X., X. Wu, and B. Liu, 2021: Global changes in the spatial extents of precipitation extremes. Environ. Res. Lett., 16, 054017, https://doi.org/10.1088/1748-9326/abf462.

    • Search Google Scholar
    • Export Citation

  • Tang, Y., A. Huang, P. Wu, D. Huang, D. Xue, and Y. Wu, 2021: Drivers of summer extreme precipitation events over East China. Geophys. Res. Lett., 48, e2021GL093670, https://doi.org/10.1029/2021GL093670.

    • Search Google Scholar
    • Export Citation

  • Thackeray, C. W., A. Hall, J. Norris, and D. Chen, 2022: Constraining the increased frequency of global precipitation extremes under warming. Nat. Climate Change, 12, 441–448, https://doi.org/10.1038/s41558-022-01329-1.

    • Search Google Scholar
    • Export Citation

  • Wang, L., and Coauthors, 2021: Multiple metrics informed projections of future precipitation in China. Geophys. Res. Lett., 48, e2021GL093810, https://doi.org/10.1029/2021GL093810.

    • Search Google Scholar
    • Export Citation

  • Wang, S., and H. Zuo, 2016: Effect of the East Asian westerly jet’s intensity on summer rainfall in the Yangtze River valley and its mechanism. J. Climate, 29, 2395–2406, https://doi.org/10.1175/JCLI-D-15-0259.1.

    • Search Google Scholar
    • Export Citation

  • Wang, X., and Coauthors, 2022: Spatiotemporal evolution patterns of contiguous extreme precipitation events across China from a 3D perspective. Geophys. Res. Lett., 49, e2022GL098840, https://doi.org/10.1029/2022GL098840.

    • Search Google Scholar
    • Export Citation

  • Wei, L., X. Gu, D. Kong, and J. Liu, 2021: A long-term perspective of hydroclimatological impacts of tropical cyclones on regional heavy precipitation over eastern monsoon China. Atmos. Res., 264, 105862, https://doi.org/10.1016/j.atmosres.2021.105862.

    • 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 patterns, trends, and return levels. J. Hydrol., 562, 305–317, https://doi.org/10.1016/j.jhydrol.2018.05.028.

    • Search Google Scholar
    • Export Citation

  • Wu, X., X. Tan, B. Liu, H. Chen, and X. Chen, 2022: Fronts and cyclones associated with changes in the total and extreme precipitation over China. J. Climate, 35, 4131–4146, https://doi.org/10.1175/JCLI-D-21-0467.1.

    • Search Google Scholar
    • Export Citation

  • Xiao, C., P. Wu, L. Zhang, and L. Song, 2016: Robust increase in extreme summer rainfall intensity during the past four decades observed in China. Sci. Rep., 6, 38506, https://doi.org/10.1038/srep38506.

    • Search Google Scholar
    • Export Citation

  • Yang, J., D. Gong, W. Wang, M. Hu, and R. Mao, 2012: Extreme drought event of 2009/2010 over southwestern China. Meteor. Atmos. Phys., 115, 173–184, https://doi.org/10.1007/s00703-011-0172-6.

    • Search Google Scholar
    • Export Citation

  • Yang, J., Q. Bao, B. Wang, D.-Y. Gong, H. He, and M.-N. Gao, 2014: Distinct quasi-biweekly features of the subtropical East Asian monsoon during early and late summers. Climate Dyn., 42, 1469–1486, https://doi.org/10.1007/s00382-013-1728-6.

    • Search Google Scholar
    • Export Citation

  • Yang, L., G. Villarini, J. A. Smith, F. Tian, and H. Hu, 2013: Changes in seasonal maximum daily precipitation in China over the period 1961–2006. Int. J. Climatol., 33, 1646–1657, https://doi.org/10.1002/joc.3539.

    • Search Google Scholar
    • Export Citation

  • Yatagai, A., K. Kamiguchi, O. Arakawa, A. Hamada, N. Yasutomi, and A. Kitoh, 2012: APHRODITE: Constructing a long-term daily gridded precipitation dataset for Asia based on a dense network of rain gauges. Bull. Amer. Meteor. Soc., 93, 1401–1415, https://doi.org/10.1175/BAMS-D-11-00122.1.

    • Search Google Scholar
    • Export Citation

  • Yu, J., H. Xue, and J. Song, 2017: Tropical cyclone potential hazard in Southeast China and its linkage with the East Asian westerly jet. Asia-Pac. J. Atmos. Sci., 53, 295–304, https://doi.org/10.1007/s13143-017-0028-1.

    • Search Google Scholar
    • Export Citation

  • Zhai, P., X. Zhang, H. Wan, and X. Pan, 2005: Trends in total precipitation and frequency of daily precipitation extremes over China. J. Climate, 18, 1096–1108, https://doi.org/10.1175/JCLI-3318.1.

    • Search Google Scholar
    • Export Citation

  • Zhang, K., W. J. Randel, and R. Fu, 2017: Relationships between outgoing longwave radiation and diabatic heating in reanalyses. Climate Dyn., 49, 2911–2929, https://doi.org/10.1007/s00382-016-3501-0.

    • Search Google Scholar
    • Export Citation

  • Zhang, Q., Y. Zheng, V. P. Singh, M. Luo, and Z. Xie, 2017: Summer extreme precipitation in eastern China: Mechanisms and impacts. J. Geophys. Res. Atmos., 122, 2766–2778, https://doi.org/10.1002/2016JD025913.

    • Search Google Scholar
    • Export Citation

  • Zhang, W., and T. Zhou, 2020: Increasing impacts from extreme precipitation on population over China with global warming. Sci. Bull., 65, 243–252, https://doi.org/10.1016/j.scib.2019.12.002.

    • Search Google Scholar
    • Export Citation

  • Zhang, X., F. W. Zwiers, G. C. Hegerl, F. H. Lambert, N. P. Gillett, S. Solomon, P. A. Stott, and T. Nozawa, 2007: Detection of human influence on twentieth-century precipitation trends. Nature, 448, 461–465, https://doi.org/10.1038/nature06025.

    • Search Google Scholar
    • Export Citation

  • Zhao, Y., J. Zhu, and Y. Xu, 2014: Establishment and assessment of the grid precipitation datasets in China for recent 50 years. J. Meteor. Sci., 34, 414–420, https://doi.org/10.3969/2013jms.0008.

    • Search Google Scholar
    • Export Citation

  • Zhou, B., P. Zhai, and Y. Chen, 2020: Contribution of changes in synoptic‐scale circulation patterns to the past summer precipitation regime shift in Eastern China. Geophys. Res. Lett., 47, e2020GL087728, https://doi.org/10.1029/2020GL087728.

    • Search Google Scholar
    • Export Citation

  • Zhou, T., W. Zhang, L. Zhang, X. Zhang, Y. Qian, D. Peng, S. Ma, and B. Dong, 2020: The dynamic and thermodynamic processes dominating the reduction of global land monsoon precipitation driven by anthropogenic aerosols emission. Sci. China Earth Sci., 63, 919–933, https://doi.org/10.1007/s11430-019-9613-9.

    • Search Google Scholar
    • Export Citation

  • Zhu, H., Z. Jiang, and L. Li, 2021: Projection of climate extremes in China, an incremental exercise from CMIP5 to CMIP6. Sci. Bull., 66, 2528–2537, https://doi.org/10.1016/j.scib.2021.07.026.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 583 583 20
Full Text Views 199 199 2
PDF Downloads 244 244 2