Prediction Skill of North Pacific Variability in NCEP Climate Forecast System Version 2: Impact of ENSO and Beyond

Zeng-Zhen Hu Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland

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Arun Kumar Climate Prediction Center, NOAA/NWS/NCEP, College Park, Maryland

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Bohua Huang Department of Atmospheric, Oceanic, and Earth Sciences, College of Science, and Center for Ocean–Land–Atmosphere Studies, George Mason University, Fairfax, Virginia

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Jieshun Zhu Center for Ocean–Land–Atmosphere Studies, George Mason University, Fairfax, Virginia

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Yuanhong Guan School of Mathematics and Statistics, and Center for Data Assimilation Research and Application, Nanjing University of Information Science and Technology, Nanjing, China

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Abstract

This work examines the impact of El Niño–Southern Oscillation (ENSO) on the prediction skill of North Pacific variability (NPV) in retrospective predictions of the NCEP Climate Forecast System, version 2. It is noted that the phase relationship between ENSO and NPV at initial conditions (ICs) affects the prediction skill of NPV. For average lead times of 0–6 months, the prediction skills of sea surface temperature anomalies (SSTAs) in NPV (defined as the NPV index) increase from 0.42 to 0.63 from the cases of an out-of-phase relation between the Niño-3.4 and NPV indices in ICs to the cases of an in-phase relation. It is suggested that when ENSO and NPV are in phase in ICs, ENSO plays a constructive role in the NPV development and enhances its signals. Nevertheless, when ENSO and NPV are out of phase, some pronounced positive NPV events are still predictable. In these cases, the North Pacific is dominated by strong positive SSTAs, which may overcome the opposing influence from the tropical Pacific and display predictability.

Corresponding author address: Zeng-Zhen Hu, Climate Prediction Center, NOAA/NWS/NCEP, 5830 University Research Court, College Park, MD 20740. E-mail: zeng-zhen.hu@noaa.gov

Abstract

This work examines the impact of El Niño–Southern Oscillation (ENSO) on the prediction skill of North Pacific variability (NPV) in retrospective predictions of the NCEP Climate Forecast System, version 2. It is noted that the phase relationship between ENSO and NPV at initial conditions (ICs) affects the prediction skill of NPV. For average lead times of 0–6 months, the prediction skills of sea surface temperature anomalies (SSTAs) in NPV (defined as the NPV index) increase from 0.42 to 0.63 from the cases of an out-of-phase relation between the Niño-3.4 and NPV indices in ICs to the cases of an in-phase relation. It is suggested that when ENSO and NPV are in phase in ICs, ENSO plays a constructive role in the NPV development and enhances its signals. Nevertheless, when ENSO and NPV are out of phase, some pronounced positive NPV events are still predictable. In these cases, the North Pacific is dominated by strong positive SSTAs, which may overcome the opposing influence from the tropical Pacific and display predictability.

Corresponding author address: Zeng-Zhen Hu, Climate Prediction Center, NOAA/NWS/NCEP, 5830 University Research Court, College Park, MD 20740. E-mail: zeng-zhen.hu@noaa.gov
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  • Gershunov, A., and T. Barnett, 1998: Interdecadal modulation of ENSO teleconnections. Bull. Amer. Meteor. Soc., 79, 27152725, doi:10.1175/1520-0477(1998)079<2715:IMOET>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Guan, Y., J. Zhu, B. Huang, Z.-Z. Hu, and J. L. Kinter III, 2014: South Pacific Ocean dipole: A predictable mode on multi-seasonal time scales. J. Climate, 27, 1648–1658, doi:10.1175/JCLI-D-13-00293.1.

    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., and B. Huang, 2007: The predictive skill and the most predictable pattern in the tropical Atlantic: The effect of ENSO. Mon. Wea. Rev., 135, 17861806, doi:10.1175/MWR3393.1.

    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., and B. Huang, 2009: Interferential impact of ENSO and PDO on dry and wet conditions in the U.S. Great Plains. J. Climate, 22, 60476065, doi:10.1175/2009JCLI2798.1.

    • Search Google Scholar
    • Export Citation
  • Hu, Z.-Z., A. Kumar, B. Huang, W. Wang, J. Zhu, and C. Wen, 2013: Prediction skill of monthly SST in the North Atlantic Ocean in NCEP Climate Forecast System version 2. Climate Dyn., 40, 27452756, doi:10.1007/s00382-012-1431-z.

    • Search Google Scholar
    • Export Citation
  • Huang, B., P. S. Schopf, and Z. Pan, 2002: The ENSO effect on the tropical Atlantic variability: A regionally coupled model study. Geophys. Res. Lett., 29, 2039, doi:10.1029/2002GL014872.

    • Search Google Scholar
    • Export Citation
  • Kim, H.-M., P. J. Webster, and J. A. Curry, 2012: Seasonal prediction skill of ECMWF System 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere winter. Climate Dyn., 39, 29572973, doi:10.1007/s00382-012-1364-6.

    • Search Google Scholar
    • Export Citation
  • Kim, S. T., J.-Y. Yu, A. Kumar, and H. Wang, 2012: Examination of the two types of ENSO in the NCEP CFS model and its extratropical associations. Mon. Wea. Rev., 140, 19081923, doi:10.1175/MWR-D-11-00300.1.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and Z.-Z. Hu, 2014a: How variable is the uncertainty in ENSO sea surface temperature prediction? J. Climate, 27, 27792788, doi:10.1175/JCLI-D-13-00576.1.

    • Search Google Scholar
    • Export Citation
  • Kumar, A., and Z.-Z. Hu, 2014b: Interannual and interdecadal variability of ocean temperature along the equatorial Pacific in conjunction with ENSO. Climate Dyn.,42, 1243–1258, doi:10.1007/s00382-013-1721-0.

  • Kumar, A., and Coauthors, 2012: An analysis of the nonstationarity in the bias of sea surface temperature forecasts for the NCEP Climate Forecast System (CFS) version 2. Mon. Wea. Rev.,140, 3003–3016, doi:10.1175/MWR-D-11-00335.1.

  • Kumar, A., B. Jha, and H. Wang, 2014: Attribution of SST variability in global oceans and the role of ENSO. Climate Dyn., doi:10.1007/s00382-013-1865-y, in press.

  • Latif, M., and T. P. Barnett, 1994: Causes of decadal climate variability over the North Pacific and North America. Science, 266, 634637, doi:10.1126/science.266.5185.634.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., and T. Yamagata, 2002: Four decadal ocean–atmosphere modes in the North Pacific revealed by various analysis methods. J. Oceanogr., 58, 861876, doi:10.1023/A:1022831431602.

    • Search Google Scholar
    • Export Citation
  • Luo, J.-J., R. Zhang, S. Behera, Y. Masumoto, F.-F. Jin, R. Lukas, and T. Yamagata, 2010: Interaction between El Niño and extreme Indian Ocean dipole. J. Climate, 23, 726742, doi:10.1175/2009JCLI3104.1.

    • Search Google Scholar
    • Export Citation
  • Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis, 1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Amer. Meteor. Soc., 78, 10691079, doi:10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • National Research Council, 2010: Assessment of Intraseasonal to Interannual Climate Prediction and Predictability. National Academies Press, 192 pp.

    • Search Google Scholar
    • Export Citation
  • Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15, 16091625, doi:10.1175/1520-0442(2002)015<1609:AIISAS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2010: The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc., 91, 10151057, doi:10.1175/2010BAMS3001.1.

    • Search Google Scholar
    • Export Citation
  • Saha, S., and Coauthors, 2014: The NCEP Climate Forecast System version 2. J. Climate,27, 2185–2208, doi:10.1175/JCLI-D-12-00823.1.

  • Wen, C., Y. Xue, and A. Kumar, 2012: Seasonal prediction of North Pacific SSTs and PDO in the NCEP CFS hindcasts. J. Climate,25, 5689–5710, doi:10.1175/JCLI-D-11-00556.1.

  • Xue, Y., B. Huang, Z.-Z. Hu, A. Kumar, C. Wen, D. Behringer, and S. Nadiga, 2011: An assessment of oceanic variability in the NCEP Climate Forecast System Reanalysis. Climate Dyn., 37, 25112539, doi:10.1007/s00382-010-0954-4.

    • Search Google Scholar
    • Export Citation
  • Xue, Y., M. Chen, A. Kumar, Z.-Z. Hu, and W. Wang, 2013: Prediction skill and bias of tropical Pacific sea surface temperatures in the NCEP Climate Forecast System version 2. J. Climate,26, 5358–5378, doi:10.1175/JCLI-D-12-00600.1.

  • Zhu, J., B. Huang, L. Marx, J. L. Kinter III, M. A. Balmaseda, R.-H. Zhang, and Z.-Z. Hu, 2012: Ensemble ENSO hindcasts initialized from multiple ocean analyses. Geophys. Res. Lett., 39, L09602, doi:10.1029/2012GL051503.

    • Search Google Scholar
    • Export Citation
  • Zhu, J., B. Huang, Z.-Z. Hu, J. L. Kinter III, and L. Marx, 2013: Predicting U.S. summer precipitation using NCEP Climate Forecast System version 2 initialized by multiple ocean analyses. Climate Dyn., 41, 19411954, doi:10.1007/s00382-013-1785-x.

    • Search Google Scholar
    • Export Citation
  • Zuo, Z., S. Yang, Z.-Z. Hu, R. Zhang, W. Wang, B. Huang, and F. Wang, 2013: Predictable patterns and predictive skills of monsoon precipitation in Northern Hemisphere summer in NCEP CFSv2 reforecasts. Climate Dyn., 40, 30713088, doi:10.1007/s00382-013-1772-2.

    • Search Google Scholar
    • Export Citation
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