Advances in Atmospheric Sciences

, Volume 35, Issue 8, pp 1021–1034 | Cite as

On Northern Hemisphere Wave Patterns Associated with Winter Rainfall Events in China

  • Claudia Christine StephanEmail author
  • Yan Ho Ng
  • Nicholas P. Klingaman
Open Access
Original Paper
Part of the following topical collections:
  1. Climate and Weather Extremes


During extended winter (November–April), 43% of the intraseasonal rainfall variability in China is explained by three spatial patterns of temporally coherent rainfall. These patterns were identified with empirical orthogonal teleconnection (EOT) analysis of observed 1982–2007 pentad rainfall anomalies and connected to midlatitude disturbances. However, examination of individual strong EOT events shows that there is substantial inter-event variability in their dynamical evolution, which implies that precursor patterns found in regressions cannot serve as useful predictors. To understand the physical nature and origins of the extratropical precursors, the EOT technique is applied to six simulations of the Met Office Unified Model at horizontal resolutions of 200–40 km, with and without air–sea coupling. All simulations reproduce the observed precursor patterns in regressions, indicating robust underlying dynamical processes. Further investigation into the dynamics associated with observed patterns shows that Rossby wave dynamics can explain the large inter-event variability. The results suggest that the apparently slowly evolving or quasi-stationary waves in regression analysis are a statistical amalgamation of more rapidly propagating waves with a variety of origins and properties.

Key words

rainfall in China spring flooding Rossby wave dynamics EOT analysis predictability teleconnections 


本文通过对1982-2007年冬季(11月–4月)逐候降水异常开展经验正交遥相关(EOT)分解, 发现中国冬季降水季节内变化的三个主导型态, 可以解释其季节内变率的43%, 且与中纬度扰动有关. 然而, 对强EOT事件的分析发现, 不同EOT事件对应的波动动力演变过程存在较大差异, 说明回归分析得到的前期信号不能作为有用的预测因子. 为了理解热带外预测因子的物理本质, 该文进一步对比分析了英国气象局一体化模式(MetUM)不同分辨率的大气环流模式和耦合模式模拟结果. 所有模拟均能模拟出观测中基于回归方法得到的前期预报因子, 说明了相应动力机制的可靠性. 对观测中降水型动力过程的进一步诊断指出, Rossby波可以解释不同EOT事件间动力过程差异的产生原因. 该文研究表明, 回归分析得到的是明显的演变缓慢的波动或准静止波, 这是统计合并多种起源、多种特性的快速传播的波动的结果.


中国降水 春季洪涝 罗斯贝动力学 EOT分析 可预报性 遥相关 



Claudia C. STEPHAN was supported by the UK–China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China, as part of the Newton Fund. Nicholas P. KLINGAMAN was supported by an Independent Research Fellowship from the UK Natural Environment Research Council (NE/L010976/1). APHRODITE data are available from The RWS function was computed using code from the python package windspharm v1.5.0, available at We thank Matthias RÖTHLISBERGER for providing the Rossby wave initialization segment data and helpful discussions.


  1. Boyle, J. S., and T. J. Chen, 1987: Synoptic aspects of the wintertime East Asian monsoon. Monsoon Meteorology, C. P. Chang, and T. N. Krishnamurti, Eds., Oxford University Press, 125–160.Google Scholar
  2. Chang, C. P, Y. H. Ding, N. C. Lau, R. H. Johnson, B, Wang, T. Yasunari, 2011: The Global Monsoon System: Research and Forecast. 2nd ed., World Scientific, 43–72.CrossRefGoogle Scholar
  3. Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, CrossRefGoogle Scholar
  4. Gao, H., and Coauthors, 2008: Analysis of the severe cold surge, ice-snow and frozen disasters in south China during January 2008: II. Possible climatic causes. Meteorological Monthly, 34, 101–106 (in Chinese)Google Scholar
  5. Gu, L., K. Wei, and R. H. Huang, 2008: Severe disaster of blizzard, freezing rain and low temperature in January 2008 in China and its association with the anomalies of East Asian monsoon system. Climatic and Environmental Research, 13, 405–418, (in Chinese)Google Scholar
  6. Hamada, A., O. Arakawa, and A. Yatagai, 2011: An automated quality control method for daily rain-gauge data. Global Environmental Research, 15, 183–192.Google Scholar
  7. Henderson, S. A., E. D. Maloney, and E. A. Barnes, 2016: The influence of the Madden-Julian Oscillation on northern hemisphere winter blocking. J. Climate, 29, 4597–4616, CrossRefGoogle Scholar
  8. Hoskins, B. J., and D. J. Karoly, 1981: The steady linear response of a spherical atmosphere to thermal and orographic forcing. J. Atmos. Sci., 38, 1179–1196,<1179:TSLROA>2.0.CO;2.CrossRefGoogle Scholar
  9. Hoskins, B. J., M. E. McIntyre, and A. W. Robertson, 1985: On the use and significance of isentropic potential vorticity maps. Quart. J. Roy. Meteor. Soc., 111, 877–946, CrossRefGoogle Scholar
  10. Hurrell, J.W., Y. Kushnir, G. Ottersen, and M. Visbeck, 2003: The North Atlantic oscillation: Climatic significance and environmental impact. Geophysical Monograph Series, 134, 279.Google Scholar
  11. Madden, R. A., and P. R. Julian, 1972: Description of globalscale circulation cells in the tropics with a 40–50 day period. J. Atmos. Sci., 29, 1109–1123,–0469(1972)029<1109:DOGSCC>2.0.CO;2.CrossRefGoogle Scholar
  12. Martius, O., C. Schwierz, and H. C. Davies, 2010: Tropopauselevel waveguides. J. Atmos. Sci., 67, 866–879, CrossRefGoogle Scholar
  13. Park, T. W., C.-H. Ho, and S. Yang, 2011: Relationship between the Arctic Oscillation and cold surges over East Asia. J. Climate, 24, 68–83, CrossRefGoogle Scholar
  14. Park, T. W., C. H. Ho, and Y. Deng, 2014: A synoptic and dynamical characterization of wave-train and blocking cold surge over East Asia. Climate Dyn., 43, 753–770, CrossRefGoogle Scholar
  15. Park, T. W., J.-H. Jeong, C.-H. Ho, and S. J. Kim, 2008: Characteristics of atmospheric circulation associated with cold surge occurrences in East Asia: A case study during 2005/06 winter. Adv. Atmos. Sci., 25, 791–804, CrossRefGoogle Scholar
  16. Petoukhov, V., S. Petri, S. Rahmstorf, D. Coumou, K. Kornhuber, and H. J. Schellnhuber, 2016: Role of quasiresonant planetary wave dynamics in recent boreal spring-to-autumn extreme events. Proceedings of the National Academy of Sciences of the United States of America, 113, 6862–6867, CrossRefGoogle Scholar
  17. Röthlisberger, M., O. Martius, and H. Wernli, 2016: An algorithm for identifying the initiation of synoptic-scale Rossby waves on potential vorticity waveguides. Quart. J. Roy. Meteor. Soc., 142, 889–900, CrossRefGoogle Scholar
  18. Sardeshmukh, P. D., and B. J. Hoskins, 1988: The generation of global rotational flow by steady idealized tropical divergence. J. Atmos. Sci., 45, 1228–1251,<1228:TGOGRF>2.0.CO;2.CrossRefGoogle Scholar
  19. Scaife, A. A., and Coauthors, 2017: Tropical rainfall, Rossby waves and regional winter climate predictions. Quart. J. Roy. Meteor. Soc., 143, 1–11, CrossRefGoogle Scholar
  20. Smith, I., 2004: An assessment of recent trends in Australian rainfall. Aust. Meteor. Mag., 53, 163–173.Google Scholar
  21. Stephan, C. C., N. P. Klingaman, P. L. Vidale, A. G. Turner, M.-E. Demory, and L. Guo, 2017a: A comprehensive analysis of coherent rainfall patterns in China and potential drivers. Part II: Intraseasonal variability. Climate Dyn., (in press)Google Scholar
  22. Stephan, C. C., N. P. Klingaman, P. L. Vidale, A. G. Turner, M.-E. Demory, and L. Guo, 2017b: Interannual rainfall variability over China in the MetUM GA6 and GC2 configurations. Geo scientific Model Development, (in press)Google Scholar
  23. Takaya, K., and H. Nakamura, 2005: Mechanisms of intraseasonal amplification of the cold Siberian high. J. Atmos. Sci., 62, 4423–4440, CrossRefGoogle Scholar
  24. Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic oscillation signature in the wintertime geopotential height and temperature fields. Geophys. Res. Lett., 25, 1297–1300, CrossRefGoogle Scholar
  25. Walters, D., and Coauthors, 2017: The met office unified model global atmosphere 6.0/6.1 and JULES global land 6.0/6.1 configurations. Geoscientific Model Development, 10, 1487–1520, CrossRefGoogle Scholar
  26. Wang, L., and Coauthors, 2008: Analysis of the severe cold surge, ice-snow and frozen disasters in south China during January 2008: I. Climatic features and its impact. Meteorological Monthly, 34, 95–100. (in Chinese)Google Scholar
  27. Williams, K. D., and Coauthors, 2015: The Met Office Global Coupled model 2.0 (GC2) configuration. Geoscientific Model Development, 8, 1509–1524, CrossRefGoogle Scholar
  28. Wu, P., 1993: Nonlinear resonance and instability of planetary waves and low-frequency variability in the atmosphere. J. Atmos. Sci., 50, 3590–3607,<3590:NRAIOP>2.0.CO;2.CrossRefGoogle Scholar
  29. Yao, Y. H., H. Lin, and Q. G. Wu, 2015: Subseasonal variability of precipitation in China during boreal winter. J. Climate, 28, 6548–6559, CrossRefGoogle Scholar
  30. 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, CrossRefGoogle Scholar

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© The Author(s) 2018

Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.

Authors and Affiliations

  • Claudia Christine Stephan
    • 1
    Email author
  • Yan Ho Ng
    • 2
  • Nicholas P. Klingaman
    • 1
  1. 1.National Centre for Atmospheric Science – Climate, Department of MeteorologyUniversity of ReadingReadingUK
  2. 2.Department of MeteorologyUniversity of ReadingReadingUK

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