Abstract
To understand the diversity of the El Niño-Southern Oscillation (ENSO) under the background of Pacific decadal oscillation (PDO) during recent decades, characteristics of westerly wind bursts (WWBs) during positive and negative phases of the PDO were analyzed. It is shown that, during the ENSO developing period, the El Niño evolution may be affected by stronger or more frequent WWBs in the positive PDO phase than in the negative PDO phase. The sustained effects of atmospheric dynamics on the equatorial ocean can be indicated by the accumulated WWB strength, which contains most WWB characteristics, including the accumulated days, occurrence frequency, strength, and spatial range of WWBs. The synoptic/climate systems that are directly related to WWBs show a wider spatial distribution in the positive PDO phase than in the negative PDO phase.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Ashok, K., S. K. Behera, S. A. Rao, et al., 2007: El Niño Modoki and its possible teleconnection. J. Geophys. Res. Oceans, 112, C11007, doi: https://doi.org/10.1029/2006JC003798.
Balmaseda, M. A., K. Mogensen, and A. T. Weaver, 2013: Evaluation of the ECMWF ocean reanalysis system ORAS4. Quart. J. Roy. Meteor. Soc., 139, 1132–1161, doi: https://doi.org/10.1002/qj.2063.
Barnston, A. G., M. K. Tippett, M. L. L’Heureux, et al., 2012: Skill of real-time seasonal ENSO model predictions during 2002–11: Is our capability increasing. Bull. Amer. Meteor. Soc., 93, 631–651, doi: https://doi.org/10.1175/BAMS-D-11-00111.1.
Barnston, A. G., M. K. Tippett, M. Ranganathan, et al., 2019: Deterministic skill of ENSO predictions from the North American Multimodel Ensemble. Climate Dyn., 53, 7215–7234, doi: https://doi.org/10.1007/s00382-017-3603-3.
Chen, D. K., T. Lian, C. B. Fu, et al., 2015: Strong influence of westerly wind bursts on El Niño diversity. Nat. Geosci., 8, 339–345, doi: https://doi.org/10.1038/ngeo2399.
Chen, L., Y. Q. Yu, and W. P. Zheng, 2016: Improved ENSO simulation from climate system model FGOALS-g1.0 to FGOALS-g2. Climate Dyn., 47, 2617–2634, doi: https://doi.org/10.1007/s00382-016-2988-8.
Chen, L., T. Li, B. Wang, et al., 2017: Formation mechanism for 2015/16 super El Niño. Sci. Rep., 7, 2975, doi: https://doi.org/10.1038/s41598-017-02926-3.
Dee, D. P., S. M. Uppala, A. J. Simmons, et al., 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553–597, doi: https://doi.org/10.1002/qj.828.
Grassi, B., G. Redaelli, P. O. Canziani, et al., 2012: Effects of the PDO phase on the tropical belt width. J. Climate, 25, 3282–3290, doi: https://doi.org/10.1175/JCLI-D-11-00244.1.
Harrison, D. E., and B. S. Giese, 1991: Episodes of surface westerly winds as observed from islands in the western tropical Pacific. J. Geophys. Res. Oceans, 96, 3221–3237, doi: https://doi.org/10.1029/90JC01775.
Harrison, D. E., and G. A. Vecchi, 1997: Westerly wind events in the tropical Pacific, 1986–95. J. Climate, 10, 3131–3156, doi: https://doi.org/10.1175/1520-0442(1997)010<3131:WWEITT>2.0.CO;2.
Hu, Z.-Z., A. Kumar, H.-L. Ren, et al., 2013: Weakened interannual variability in the tropical Pacific Ocean since 2000. J. Climate, 26, 2601–2613, doi: https://doi.org/10.1175/JCLI-D-12-00265.1.
Huang, B. Y., P. W. Thorne, V. F. Banzon, et al., 2017: Extended Reconstructed Sea Surface Temperature, version 5 (ERSSTv5): Upgrades, validations, and intercomparisons. J. Climate, 30, 8179–8205, doi: https://doi.org/10.1175/JCLI-D-16-0836.1.
Jin, F.-F., 1997: An equatorial ocean recharge paradigm for ENSO. Part I: Conceptual model. J. Atmos. Sci., 54, 811–829, doi: https://doi.org/10.1175/1520-0469(1997)054<0811:AEORPF>2.0.CO;2.
Keen, R. A., 1982: The role of cross-equatorial tropical cyclone pairs in the Southern Oscillation. Mon. Wea. Rev., 110, 1405–1416, doi: https://doi.org/10.1175/1520-0493(1822)110<1405:TROCET>2.0.CO;2.
Kiladis, G. N., G. A. Meehl, and K. M. Weickmann, 1994: Large-scale circulation associated with westerly wind bursts and deep convection over the western equatorial Pacific. J. Geophys. Res. Atmos., 99, 18527–18544, doi: https://doi.org/10.1029/94JD01486.
Li, T. M., 1997: Phase transition of the El Niño-Southern Oscillation: A stationary SST mode. J. Atmos. Sci., 54, 2872–2887, doi: https://doi.org/10.1175/1520-0469(1997)054<2872:PTOTEN>2.0.CO;2.
McPhaden, M. J., 2012: A 21st century shift in the relationship between ENSO SST and warm water volume anomalies. Geophys. Res. Lett., 39, L09706, doi: https://doi.org/10.1029/2012GL051826.
Min, Q. Y., J. Z. Su, R. H. Zhang, et al., 2015: What hindered the El Niño pattern in 2014. Geophys. Res. Lett., 42, 6762–6770, doi: https://doi.org/10.1002/2015GL064899.
Philander, S. G., 1990: El Niño, La Niña, and the Southern Oscillation. Academic Press, London, 1–289.
Saha, S. K., S. Pokhrel, H. S. Chaudhari, et al., 2014: Improved simulation of Indian summer monsoon in latest NCEP climate forecast system free run. Int. J. Climatol., 34, 1628–1641, doi: https://doi.org/10.1002/joc.3791.
Schmid, C., R. L. Molinari, R. Sabina, et al., 2007: The real-time data management system for Argo profiling float observations. J. Atmos. Ocean. Technol., 24, 1608–1628, doi: https://doi.org/10.1175/JTECH2070.1.
Su, J. Z., B. Q. Xiang, B. Wang, et al., 2014: Abrupt termination of the 2012 Pacific warming and its implication on ENSO prediction. Geophys. Res. Lett., 41, 9058–9064, doi: https://doi.org/10.1002/2014GL062380.
Su, J. Z., R. H. Zhang, X. Y. Rong, et al., 2018: Sea surface temperature in the subtropical Pacific boosted the 2015 El Niño and hindered the 2016 La Niña. J. Climate, 31, 877–893, doi: https://doi.org/10.1175/JCLI-D-17-0379.1.
Timmermann, A., S.-I. An, J.-S. Kug, et al., 2018: El Niño-Southern Oscillation complexity. Nature, 559, 535–545, doi: https://doi.org/10.1038/s41586-018-0252-6.
Vecchi, G. A., and D. E. Harrison, 2000: Tropical Pacific sea surface temperature anomalies, El Niño, and equatorial westerly wind events. J. Climate, 13, 1814–1830, doi: https://doi.org/10.1175/1520-0442(2000)013<1814:TPSSTA>2.0.CO;2.
Yang, S., Z. N. Li, J.-Y. Yu, et al., 2018: El Niño-Southern Oscillation and its impact in the changing climate. Natl. Sci. Rev., 5, 840–857, doi: https://doi.org/10.1093/nsr/nwy046.
Zhao, M., H. H. Hendon, O. Alves, et al., 2013: Impact of salinity constraints on the simulated mean state and variability in a coupled seasonal forecast model. Mon. Wea. Rev., 141, 388–402, doi: https://doi.org/10.1175/MWR-D-11-00341.1.
Zhao, M., H. H. Hendon, O. Alves, et al., 2014: Impact of improved assimilation of temperature and salinity for coupled model seasonal forecasts. Climate Dyn., 42, 2565–2583, doi: https://doi.org/10.1007/s00382-014-2081-0.
Zhao, M., H. H. Hendon, O. Alves, et al., 2016: Weakened eastern Pacific El Niño predictability in the early twenty-first century. J. Climate, 29, 6805–6822, doi: https://doi.org/10.1175/JCLI-D-15-0876.1.
Author information
Authors and Affiliations
Corresponding author
Additional information
Supported by the National Key Research and Development Program of China (2016YFA0600602) and National Natural Science Foundation of China (41776039).
Acknowledgments
NOAA ERSSTv5 data were provided by the NOAA/Oceanic and Atmospheric Research (OAR)/Earth System Research Laboratory (ESRL) Physical Sciences Division (PSD), Boulder, Colorado, USA and accessed at their website at https://www.esrl.noaa.gov/psd/. The surface wind stress and 10-m wind data were obtained from the ECMWF interim reanalysis (ERA-Interim) at pttp://ppps.ecmwn.int/datasets/data/interim-full-daily/. The authors wish to thank Dr. Tao Lian who supplied the calculation method of WWA/EWA cumulant.
Rights and permissions
About this article
Cite this article
Shi, Y., Su, J. A Statistical Comparison of the Westerly Wind Bursts between the Positive and Negative Phases of the PDO. J Meteorol Res 34, 315–324 (2020). https://doi.org/10.1007/s13351-020-9115-9
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13351-020-9115-9