Editorial Type:
Article
Article Type:
Research Article

The Global Influence of the Madden–Julian Oscillation on Extreme Temperature Events

Satoko Matsueda Climate Prediction Division, Japan Meteorological Agency, Tokyo, and Climate Research Department, Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan

Search for other papers by Satoko Matsueda in
Current site
Google Scholar
PubMed Close
and
Yuhei Takaya Climate Prediction Division, Japan Meteorological Agency, Tokyo, and Climate Research Department, Meteorological Research Institute, Japan Meteorological Agency, Tsukuba, Japan

Search for other papers by Yuhei Takaya in
Current site
Google Scholar
PubMed Close
Print Publication:
15 May 2015
DOI:
https://doi.org/10.1175/JCLI-D-14-00625.1
Page(s):
4141–4151
Restricted access

Abstract

The authors investigated the influence of the Madden–Julian oscillation (MJO) on extreme warm and cold events, which may have large social and economic impacts. The frequencies of extreme temperature events were analyzed and compared between active and inactive MJO periods by using the 7-day running average of the 850-hPa temperature during the extended boreal winter (November–April). The results show that the frequency of extreme events is significantly modulated (i.e., increased by a factor of more than 2) by the MJO with a time lag over some areas in the extratropics as well as in the tropics. In the extratropics, the modulation of the frequency of the extreme events is roughly associated with midlatitude wave responses to tropical forcing and anomalous lower-level circulation due to the MJO.

The relationship between the MJO and forecast skill of extreme temperature events was also investigated by using a suite of hindcasts made with the operational one-month ensemble prediction system of the Japan Meteorological Agency. Forecast skill of extreme events occurring after active MJO periods tend to be better over some areas, compared with after inactive MJO periods. These results suggest that a realistic representation of the MJO and of the atmospheric response to the MJO in forecast models is important for providing reliable early warning information about extreme events.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-14-00625.s1.

Corresponding author address: Satoko Matsueda, Climate Prediction Division, Japan Meteorological Agency, 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japan. E-mail: matsueda@met.kishou.go.jp

Abstract

The authors investigated the influence of the Madden–Julian oscillation (MJO) on extreme warm and cold events, which may have large social and economic impacts. The frequencies of extreme temperature events were analyzed and compared between active and inactive MJO periods by using the 7-day running average of the 850-hPa temperature during the extended boreal winter (November–April). The results show that the frequency of extreme events is significantly modulated (i.e., increased by a factor of more than 2) by the MJO with a time lag over some areas in the extratropics as well as in the tropics. In the extratropics, the modulation of the frequency of the extreme events is roughly associated with midlatitude wave responses to tropical forcing and anomalous lower-level circulation due to the MJO.

The relationship between the MJO and forecast skill of extreme temperature events was also investigated by using a suite of hindcasts made with the operational one-month ensemble prediction system of the Japan Meteorological Agency. Forecast skill of extreme events occurring after active MJO periods tend to be better over some areas, compared with after inactive MJO periods. These results suggest that a realistic representation of the MJO and of the atmospheric response to the MJO in forecast models is important for providing reliable early warning information about extreme events.

Supplemental information related to this paper is available at the Journals Online website: http://dx.doi.org/10.1175/JCLI-D-14-00625.s1.

Corresponding author address: Satoko Matsueda, Climate Prediction Division, Japan Meteorological Agency, 1-3-4 Otemachi, Chiyoda-ku, Tokyo 100-8122, Japan. E-mail: matsueda@met.kishou.go.jp

Supplementary Materials

    • Supplemental Materials (PDF 796.40 KB)
Save
Cover Journal of Climate
Journal of Climate

  • Alaka, G. J., Jr., and E. D. Maloney, 2012: The influence of the MJO on upstream precursors to African easterly waves. J. Climate, 25, 3219–3236, doi:10.1175/JCLI-D-11-00232.1.

    • Search Google Scholar
    • Export Citation

  • Bechtold, P., P. Bauer, J.-R. Bidlot, C. Cardinali, L. Magnusson, F. Prates, and M. Rodwell, 2013: Uncertainty in tropical winds. ECMWF Newsletter, No. 134, ECMWF, Reading, United Kingdom, 33–37.

  • Carvalho, L. M. V., C. Jones, and B. Liebmann, 2004: The South Atlantic convergence zone: Intensity, form, persistence, and relationships with intraseasonal to interannual activity and extreme rainfall. J. Climate, 17, 88–108, doi:10.1175/1520-0442(2004)017<0088:TSACZI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Cassou, C., 2008: Intraseasonal interaction between the Madden–Julian Oscillation and the North Atlantic Oscillation. Nature, 455, 523–527, doi:10.1038/nature07286.

    • Search Google Scholar
    • Export Citation

  • 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, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation

  • Ding, R., J. Li, and K.-H. Seo, 2010: Predictability of the Madden–Julian oscillation estimated using observational data. Mon. Wea. Rev., 138, 1004–1013, doi:10.1175/2009MWR3082.1.

    • Search Google Scholar
    • Export Citation

  • Ebita, A., and Coauthors, 2011: The Japanese 55-year Reanalysis “JRA-55”: An interim report. SOLA, 7, 149–152, doi:10.2151/sola.2011-038.

    • Search Google Scholar
    • Export Citation

  • Efron, B., and R. J. Tibshirani, 1994: An Introduction to the Bootstrap. Chapman and Hall/CRC Press, 456 pp.

  • Ferranti, L., T. N. Palmer, F. Molteni, and E. Klinker, 1990: Tropical–extratropical interaction associated with the 30–60 day oscillation and its impact on medium and extended range prediction. J. Atmos. Sci., 47, 2177–2199, doi:10.1175/1520-0469(1990)047<2177:TEIAWT>2.0.CO;2.

    • 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, 1247–1258, doi:10.1175/2010BAMS2816.1.

    • Search Google Scholar
    • Export Citation

  • Grimm, A. M., and P. L. Silva Dias, 1995: Analysis of tropical–extratropical interactions with influence functions of a barotropic model. J. Atmos. Sci., 52, 3538–3555, doi:10.1175/1520-0469(1995)052<3538:AOTIWI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hendon, H. H., and B. Liebmann, 1990: The intraseasonal (30–50 day) oscillation of the Australian summer monsoon. J. Atmos. Sci., 47, 2909–2924, doi:10.1175/1520-0469(1990)047<2909:TIDOOT>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hirai, M., K. Miyaoka, H. Sato, H. Sugimoto, A. Minami, and C. Matsukawa, 2014: March 2014 upgrade of JMA’s one-month ensemble prediction system. CAS/JSC WGNE Research Activities in Atmospheric and Oceanic Modelling, Vol. 44, No. 6, 9–10. [Available online at http://www.wcrp-climate.org/WGNE/BlueBook/2014/individual-articles/06_Hirai_Masayuki_WGNE_bluebook2013_K1v1403.pdf.]

  • Hong, C. C., and T. Li, 2009: The extreme cold anomaly over Southeast Asia in February 2008: Roles of ISO and ENSO. J. Climate, 22, 3786–3801, doi:10.1175/2009JCLI2864.1.

    • Search Google Scholar
    • Export Citation

  • JMA, 2013: Outline of the operational numerical weather prediction at the Japan Meteorological Agency. Appendix to WMO Technical Progress Report on the Global Data-processing and Forecasting System (GDPFS) and Numerical Weather Prediction (NWP) Research, Japan Meteorological Agency, Tokyo, Japan, 138 pp. [Available online at http://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2013-nwp/index.htm.]

  • Jeong, J.-H., B.-M. Kim, C.-H. Ho, and Y.-H. Noh, 2008: Systematic variation in wintertime precipitation in East Asia by MJO-induced extratropical vertical motion. J. Climate, 21, 788–801, doi:10.1175/2007JCLI1801.1.

    • Search Google Scholar
    • Export Citation

  • Jin, F., and B. J. Hoskins, 1995: The direct response to tropical heating in a baroclinic atmosphere. J. Atmos. Sci., 52, 307–319, doi:10.1175/1520-0469(1995)052<0307:TDRTTH>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Jones, C., D. E. Waliser, K. M. Lau, and W. Stern, 2004: The Madden–Julian oscillation and its impact on Northern Hemisphere weather predictability. Mon. Wea. Rev., 132, 1462–1471, doi:10.1175/1520-0493(2004)132<1462:TMOAII>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Jones, C., J. Gottschalck, L. M. V. Carvalho, and W. Higgins, 2011: Influence of the Madden–Julian oscillation on forecasts of extreme precipitation in the contiguous United States. Mon. Wea. Rev., 139, 332–350, doi:10.1175/2010MWR3512.1.

    • Search Google Scholar
    • Export Citation

  • Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471, doi:10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Kiladis, G. N., J. Dias, K. H. Straub, M. C. Wheeler, S. N. Tulich, K. Kikuchi, K. M. Weickmann, and M. J. Ventrice, 2014: A comparison of OLR and circulation-based indices for tracking the MJO. Mon. Wea. Rev., 142, 1697–1715, doi:10.1175/MWR-D-13-00301.1.

    • Search Google Scholar
    • Export Citation

  • Kobayashi, S., and Coauthors, 2015: The JRA-55 reanalysis: General specifications and basic characteristics. J. Meteor. Soc. Japan, 93, 5–48, doi:10.2151/jmsj.2015-001.

    • Search Google Scholar
    • Export Citation

  • Liebmann, B., and C. A. Smith, 1996: Description of a complete (interpolated) outgoing longwave radiation dataset. Bull. Amer. Meteor. Soc., 77, 1275–1277.

    • Search Google Scholar
    • Export Citation

  • Lin, H., and G. Brunet, 2009: The influence of the Madden–Julian oscillation on Canadian wintertime surface air temperature. Mon. Wea. Rev., 137, 2250–2262, doi:10.1175/2009MWR2831.1.

    • Search Google Scholar
    • Export Citation

  • Lin, H., G. Brunet, and J. Derome, 2009: An observed connection between the North Atlantic Oscillation and the Madden–Julian oscillation. J. Climate, 22, 364–380, doi:10.1175/2008JCLI2515.1.

    • Search Google Scholar
    • Export Citation

  • Lin, H., G. Brunet, and R. Mo, 2010: Impact of the Madden–Julian oscillation on wintertime precipitation in Canada. Mon. Wea. Rev., 138, 3822–3839, doi:10.1175/2010MWR3363.1.

    • Search Google Scholar
    • Export Citation

  • Madden, R. A., and P. R. Julian, 1994: Observations of the 40–50-day tropical oscillation—A review. Mon. Wea. Rev., 122, 814–837, doi:10.1175/1520-0493(1994)122<0814:OOTDTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Matthews, A. J., B. J. Hoskins, and M. Masutani, 2004: The global response to tropical heating in the Madden–Julian oscillation during the northern winter. Quart. J. Roy. Meteor. Soc., 130, 1991–2011, doi:10.1256/qj.02.123.

    • Search Google Scholar
    • Export Citation

  • Mori, M., and M. Watanabe, 2008: The growth and triggering mechanisms of the PNA: A MJO–PNA coherence. J. Meteor. Soc. Japan, 86, 213–236, doi:10.2151/jmsj.86.213.

    • Search Google Scholar
    • Export Citation

  • Paegle, J. N., L. A. Byerle, and K. C. Mo, 2000: Intraseasonal modulation of South American summer precipitation. Mon. Wea. Rev., 128, 837–850, doi:10.1175/1520-0493(2000)128<0837:IMOSAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Pohl, B., and P. Camberlin, 2006: Influence of the Madden–Julian Oscillation on East African rainfall. I: Intraseasonal variability and regional dependency. Quart. J. Roy. Meteor. Soc., 132, 2521–2539, doi:10.1256/qj.05.104.

    • Search Google Scholar
    • Export Citation

  • Reichler, T., and J. O. Roads, 2005: Long-range predictability in the tropics. Part II: 30–60-day variability. J. Climate, 18, 634–650, doi:10.1175/JCLI-3295.1.

    • Search Google Scholar
    • Export Citation

  • 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, doi:10.1175/1520-0469(1988)045<1228:TGOGRF>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sato, H., R. Nagasawa, K. Miyaoka, M. Hirai, Y. Takaya, S. Matsueda, A. Shimpo, and H. Sugimoto, 2014: Performance of JMA’s new one-month ensemble prediction system. CAS/JSC WGNE Research Activities in Atmospheric and Oceanic Modelling, Vol. 44, No. 6, 13–14. [Available online at http://www.wcrp-climate.org/WGNE/BlueBook/2014/individual-articles/06_Sato_Hitoshi_WGNE_bluebook2013_K1verif.pdf.]

  • Schreck, C. J., J. M. Cordeira, and D. Margolin, 2013: Which MJO events affect North American temperatures? Mon. Wea. Rev., 141, 3840–3850, doi:10.1175/MWR-D-13-00118.1.

    • Search Google Scholar
    • Export Citation

  • Seo, K.-H., and S.-W. Son, 2012: The global atmospheric circulation response to tropical diabatic heating associated with the Madden–Julian oscillation during northern winter. J. Atmos. Sci., 69, 79–96, doi:10.1175/2011JAS3686.1.

    • Search Google Scholar
    • Export Citation

  • Vitart, F., and F. Molteni, 2010: Simulation of the Madden–Julian Oscillation and its teleconnections in the ECMWF forecast system. Quart. J. Roy. Meteor. Soc., 136, 842–855, doi:10.1002/qj.623.

    • Search Google Scholar
    • Export Citation

  • Waliser, D. E., K. M. Lau, W. Stern, and C. Jones, 2003: Potential predictability of the Madden–Julian oscillation. Bull. Amer. Meteor. Soc., 84, 33–50, doi:10.1175/BAMS-84-1-33.

    • Search Google Scholar
    • Export Citation

  • Wheeler, M. C., and H. H. Hendon, 2004: An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Wea. Rev., 132, 1917–1932, doi:10.1175/1520-0493(2004)132<1917:AARMMI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Wheeler, M. C., H. H. Hendon, S. Cleland, H. Meinke, and A. Donald, 2009: Impacts of the Madden–Julian oscillation on Australian rainfall and circulation. J. Climate, 22, 1482–1498, doi:10.1175/2008JCLI2595.1.

    • Search Google Scholar
    • Export Citation

  • Zhang, C., 2005: Madden–Julian Oscillation. Rev. Geophys., 43, RG2003, doi:10.1029/2004RG000158.

  • 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, 1459–1471, doi:10.1007/s00382-011-1001-9.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 854 262 24
PDF Downloads 667 159 11