Subseasonal Prediction of Extreme Precipitation over Asia: Boreal Summer Intraseasonal Oscillation Perspective

Sun-Seon Lee Department of Atmospheric Sciences, International Pacific Research Center, and Atmosphere–Ocean Research Center, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Ja-Yeon Moon Department of Atmospheric Sciences, International Pacific Research Center, and Atmosphere–Ocean Research Center, University of Hawai‘i at Mānoa, Honolulu, Hawaii

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Bin Wang Department of Atmospheric Sciences, and International Pacific Research Center, and Atmosphere–Ocean Research Center, University of Hawai‘i at Mānoa, Honolulu, Hawaii, and Earth System Modeling Center, Nanjing University of Information Science and Technology, Nanjing, China

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Hae-Jeong Kim Asia–Pacific Economic Cooperation (APEC) Climate Center (APCC), Busan, South Korea

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Abstract

The boreal summer intraseasonal oscillation (BSISO) is one of the most prominent modes in the tropical climate system. For better subseasonal prediction of extreme precipitation the relationship between BSISO activity and extreme precipitation events (days with daily precipitation exceeding the local 90th percentile) over Asia is investigated, especially the dependence of extreme precipitation occurrence on BSISO precipitation anomaly pattern (phase) and intensity (amplitude) in each month. At a given area and month, the probability of extreme precipitation changes from less than 10% to over 40%–50% according to BSISO phases, and it tends to be high when BSISO amplitude is large. The extreme precipitation probability estimated by BSISO activity is generally higher over ocean than over land. Over some land regions, however, occurrence of extreme precipitation is notably modulated by BSISO activity. In May, the extreme precipitation probability over southeastern China can reach about 30%–40% when BSISO precipitation anomaly arrives over the region. Similarly, in September the extreme precipitation probability over western China can reach 40%–50% when BSISO precipitation anomaly arrives there. The BSISO activity provides useful information in narrowing down the area and timing of high probability of extreme precipitation occurrence. Using real-time BSISO monitoring and forecast data provided by the Asia–Pacific Economic Cooperation (APEC) Climate Center, it is shown that 1) the best model (ECMWF) can predict the leading BSISO modes about 20 days ahead with bivariate correlation skills higher than 0.5 except in May, and 2) the empirical probability distributions of extreme precipitation that are based on BSISO activity can be captured by the BSISO forecasts for lead times longer than 2 weeks.

School of Ocean and Earth Science and Technology Publication Number 9889, International Pacific Research Center Publication Number 1232, and Earth System Modeling Center Publication Number 143.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Prof. Bin Wang, wangbin@hawaii.edu

Abstract

The boreal summer intraseasonal oscillation (BSISO) is one of the most prominent modes in the tropical climate system. For better subseasonal prediction of extreme precipitation the relationship between BSISO activity and extreme precipitation events (days with daily precipitation exceeding the local 90th percentile) over Asia is investigated, especially the dependence of extreme precipitation occurrence on BSISO precipitation anomaly pattern (phase) and intensity (amplitude) in each month. At a given area and month, the probability of extreme precipitation changes from less than 10% to over 40%–50% according to BSISO phases, and it tends to be high when BSISO amplitude is large. The extreme precipitation probability estimated by BSISO activity is generally higher over ocean than over land. Over some land regions, however, occurrence of extreme precipitation is notably modulated by BSISO activity. In May, the extreme precipitation probability over southeastern China can reach about 30%–40% when BSISO precipitation anomaly arrives over the region. Similarly, in September the extreme precipitation probability over western China can reach 40%–50% when BSISO precipitation anomaly arrives there. The BSISO activity provides useful information in narrowing down the area and timing of high probability of extreme precipitation occurrence. Using real-time BSISO monitoring and forecast data provided by the Asia–Pacific Economic Cooperation (APEC) Climate Center, it is shown that 1) the best model (ECMWF) can predict the leading BSISO modes about 20 days ahead with bivariate correlation skills higher than 0.5 except in May, and 2) the empirical probability distributions of extreme precipitation that are based on BSISO activity can be captured by the BSISO forecasts for lead times longer than 2 weeks.

School of Ocean and Earth Science and Technology Publication Number 9889, International Pacific Research Center Publication Number 1232, and Earth System Modeling Center Publication Number 143.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author e-mail: Prof. Bin Wang, wangbin@hawaii.edu
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  • Adhikari, P., Y. Hong, K. R. Douglas, D. B. Kirschbaum, J. Gourley, R. Adler, and G. R. Brakenridge, 2010: A digitized global flood inventory (1998–2008): Compilation and preliminary results. Nat. Hazards, 55, 405422, doi:10.1007/s11069-010-9537-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Alessandri, A., A. Borrelli, A. Cherchi, S. Materia, A. Navarra, J.-Y. Lee, and B. Wang, 2015: Prediction of Indian summer monsoon onset using dynamical subseasonal forecasts: Effects of realistic initialization of the atmosphere. Mon. Wea. Rev., 143, 778793, doi:10.1175/MWR-D-14-00187.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Buizza, R., P. L. Houtekamer, Z. Toth, G. Pellerin, M. Wei, and Y. Zhu, 2005: A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems. Mon. Wea. Rev., 133, 10761097, doi:10.1175/MWR2905.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Chen, T.-C., and J.-H. Yoon, 2000: Interannual variation in Indochina summer monsoon rainfall: Possible mechanism. J. Climate, 13, 19791986, doi:10.1175/1520-0442(2000)013<1979:IVIISM>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dewan, T. H., 2015: Societal impacts and vulnerability to floods in Bangladesh and Nepal. Wea. Climate Extremes, 7, 3642, doi:10.1016/j.wace.2014.11.001.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ding, Q., and B. Wang, 2009: Predicting extreme phases of the Indian summer monsoon. J. Climate, 22, 346363, doi:10.1175/2008JCLI2449.1.

  • Endo, N., J. Matsumoto, and T. Lwin, 2009: Trends in precipitation extremes over Southeast Asia. Sci. Online Lett. Atmos., 5, 168171, doi:10.2151/sola.2009-043

    • Search Google Scholar
    • Export Citation
  • Goswami, B. N., 2011: South Asian monsoon. Intraseasonal Variability of the Atmosphere–Ocean Climate System, 2nd ed. W. K.-M. Lau and D. E. Waliser, Eds., Springer, 21–72.

    • Crossref
    • Export Citation
  • Goswami, B. N., R. S. Ajayamohan, P. K. Xavier, and D. Sengupta, 2003: Clustering of synoptic activity by Indian summer monsoon intraseasonal oscillations. Geophys. Res. Lett., 30, 1431, doi:10.1029/2002GL016734.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Goswami, B. N., V. Venugopal, D. Sengupta, M. S. Madhusoodanan, and P. K. Xavier, 2006: Increasing trend of extreme rain events over India in a warming environment. Science, 314, 14421445, doi:10.1126/science.1132027.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gottschalck, J., and Coauthors, 2010: A framework for assessing operational Madden–Julian oscillation forecasts: A CLIVAR MJO working group project. Bull. Amer. Meteor. Soc., 91, 12471258, doi:10.1175/2010BAMS2816.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hsu, P.-C., J.-Y. Lee, and K.-J. Ha, 2016: Influence of boreal summer intraseasonal oscillation on rainfall extremes in southeast China. Int. J. Climatol., 36, 14031412, doi:10.1002/joc.4433.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hudson, D., A. G. Marshall, Y. Yin, O. Alves, and H. H. Hendon, 2013: Improving intraseasonal prediction with a new ensemble generation strategy. Mon. Wea. Rev., 141, 44294449, doi:10.1175/MWR-D-13-00059.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and D. T. Bolvin, 2013: Version 1.2 GPCP one-degree daily precipitation data set documentation. Goddard Space Flight Center, 27 pp. [Available online at ftp://precip.gsfc.nasa.gov/pub/1dd-v1.2/1DD_v1.2_doc.pdf.]

  • Jones, C., and L. M. V. Carvalho, 2012: Spatial–intensity variations in extreme precipitation in the contiguous United States and the Madden–Julian oscillation. J. Climate, 25, 49894913, doi:10.1175/JCLI-D-11-00278.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jones, C., D. E. Waliser, K. M. Lau, and W. Stern, 2004: Global occurrences of extreme precipitation events and the Madden–Julian oscillation: Observations and predictability. J. Climate, 17, 45754589, doi:10.1175/3238.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jonkman, S. N., 2005: Global perspectives on loss of human life caused by floods. Nat. Hazards, 34, 151175, doi:10.1007/s11069-004-8891-3.

  • Kemball-Cook, S., and B. Wang, 2001: Equatorial waves and air–sea interaction in the boreal summer intraseasonal oscillation. J. Climate, 14, 29232942, doi:10.1175/1520-0442(2001)014<2923:EWAASI>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Krishnamurthy, C. K. B., U. Lall, and H.-H. Kwon, 2009: Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Climate, 22, 47374746, doi:10.1175/2009JCLI2896.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kundzewicz, Z., and Coauthors, 2014: Flood risk and climate change: Global and regional perspectives. Hydrol. Sci. J., 59, 128, doi:10.1080/02626667.2013.857411.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, J.-Y., B. Wang, M. Wheeler, X. Fu, D. Waliser, and I.-S. Kang, 2013: Real-time multivariate indices for the boreal summer intraseasonal oscillation over the Asian summer monsoon region. Climate Dyn., 40, 493509, doi:10.1007/s00382-012-1544-4.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, S.-S., and B. Wang, 2016: Regional boreal summer intraseasonal oscillation over Indian Ocean and western Pacific: Comparison and predictability study. Climate Dyn., 46, 22132229, doi:10.1007/s00382-015-2698-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lee, S.-S., B. Wang, D. E. Waliser, J. M. Neena, and J.-Y. Lee, 2015: Predictability and prediction skill of the boreal summer intraseasonal oscillation in the Intraseasonal Variability Hindcast Experiment. Climate Dyn., 45, 21232135, doi:10.1007/s00382-014-2461-5.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liebmann, B., H. Hendon, and J. Glick, 1994: The relationship between tropical cyclones of the western Pacific and Indian Oceans and the Madden–Julian oscillation. J. Meteor. Soc. Japan, 72, 401412.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lin, H., G. Brunet, and J. Derome, 2008: Forecast skill of the Madden–Julian oscillation in two Canadian atmospheric models. Mon. Wea. Rev., 136, 41304149, doi:10.1175/2008MWR2459.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Liu, F., and B. Wang, 2014: A mechanism for explaining the maximum intraseasonal oscillation center over the western North Pacific. J. Climate, 27, 958968, doi:10.1175/JCLI-D-12-00797.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maloney, E., and D. Hartmann, 2001: The Madden–Julian oscillation, barotropic dynamics, and North Pacific tropical cyclone formation. Part I: Observations. J. Atmos. Sci., 58, 25452558, doi:10.1175/1520-0469(2001)058<2545:TMJOBD>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Mirza, M. M. Q., 2011: Climate change, flooding in South Asia and implications. Reg. Environ. Change, 11 (Suppl. 1), 95107, doi:10.1007/s10113-010-0184-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moon, J.-Y., B. Wang, and K.-J. Ha, 2012: MJO modulation on 2009/10 winter snowstorms in the United States. J. Climate, 25, 978991, doi:10.1175/JCLI-D-11-00033.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Moon, J.-Y., B. Wang, K.-J. Ha, and J.-Y. Lee, 2013: Teleconnections associated with Northern Hemisphere summer monsoon intraseasonal oscillation. Climate Dyn., 40, 27612774, doi:10.1007/s00382-012-1394-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2014: The NCEP Climate Forecast System version 2. J. Climate, 27, 21852208, doi:10.1175/JCLI-D-12-00823.1.

  • Sen Roy, S., and R. C. Balling Jr., 2004: Trends in extreme daily precipitation indices in India. Int. J. Climatol., 24, 457466, doi:10.1002/joc.995.

  • Vitart, F., W. Robertson, and D. L. T. Anderson, 2012: Subseasonal to Seasonal Prediction Project: Bridging the gap between weather and climate. WMO Bull., 61, 2328.

    • Search Google Scholar
    • Export Citation
  • Waliser, D. E., 2006: Intraseasonal variability. The Asian Monsoon, B. Wang, Ed., Springer, 203–257.

    • Crossref
    • Export Citation
  • Wang, B., 1992: The vertical structure and development of the ENSO anomaly mode during 1979–1989. J. Atmos. Sci., 49, 698712, doi:10.1175/1520-0469(1992)049<0698:TVSADO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and X. Xie, 1997: A model for the boreal summer intraseasonal oscillation. J. Atmos. Sci., 54, 7286, doi:10.1175/1520-0469(1997)054<0072:AMFTBS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and X. Xu, 1997: Northern Hemisphere summer monsoon singularities and climatological intraseasonal oscillation. J. Climate, 10, 10711085, doi:10.1175/1520-0442(1997)010<1071:NHSMSA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wang, B., and J.-Y. Moon, 2017: Sub-seasonal prediction of extreme weather events. Bridging Science and Policy Implication for Managing Climate Extremes: Linking Science and Policy Implications, C.-S. Chung and B. Wang, Eds., World Scientific Series of Asia-Pacific Weather and Climate Press, in press.

    • Crossref
    • Export Citation
  • Wang, B., Q. Ding, and J.-G. Jhun, 2006: Trends in Seoul (1778–2004) summer precipitation. Geophys. Res. Lett., 33, L15803, doi:10.1029/2006GL026418.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wu, R., and B. Wang, 2000: Interannual variability of summer monsoon onset over the western North Pacific and the underlying processes. J. Climate, 13, 24832501, doi:10.1175/1520-0442(2000)013<2483:IVOSMO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xavier, P., R. Rahmat, W. K. Cheong, and E. Wallace, 2014: Influence of Madden–Julian oscillation on Southeast Asia rainfall extremes: Observations and predictability. Geophys. Res. Lett., 41, 44064412, doi:10.1002/2014GL060241.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yao, C., W. Qian, S. Yang, and Z. Lin, 2010: Regional features of precipitation over Asia and summer extreme precipitation over Southeast Asia and their associations with atmospheric–oceanic conditions. Meteor. Atmos. Phys., 106, 5773, doi:10.1007/s00703-009-0052-5.

    • Crossref
    • 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, 10961108, doi:10.1175/JCLI-3318.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhang, C., 2013: Madden–Julian oscillation: Bridging weather and climate. Bull. Amer. Meteor. Soc., 94, 18491870, doi:10.1175/BAMS-D-12-00026.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, S., M. L’Heureux, S. Weaver, and A. Kumar, 2012: A composite study of the MJO influence on the surface air temperature and precipitation over the continental United States. Climate Dyn., 38, 14591471, doi:10.1007/s00382-011-1001-9.

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

    • Crossref
    • Search Google Scholar
    • Export Citation
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