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Effects of ocean initial perturbation on developing phase of ENSO in a coupled seasonal prediction model

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Abstract

Coupled prediction systems for seasonal and inter-annual variability in the tropical Pacific are initialized from ocean analyses. In ocean initial states, small scale perturbations are inevitably smoothed or distorted by the observational limits and data assimilation procedures, which tends to induce potential ocean initial errors for the El Nino-Southern Oscillation (ENSO) prediction. Here, the evolution and effects of ocean initial errors from the small scale perturbation on the developing phase of ENSO are investigated by an ensemble of coupled model predictions. Results show that the ocean initial errors at the thermocline in the western tropical Pacific grow rapidly to project on the first mode of equatorial Kelvin wave and propagate to the east along the thermocline. In boreal spring when the surface buoyancy flux weakens in the eastern tropical Pacific, the subsurface errors influence sea surface temperature variability and would account for the seasonal dependence of prediction skill in the NINO3 region. It is concluded that the ENSO prediction in the eastern tropical Pacific after boreal spring can be improved by increasing the observational accuracy of subsurface ocean initial states in the western tropical Pacific.

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Acknowledgements

The support offered by the NOAA Climate Program Office for HC Lee is gratefully acknowledged. We thank Drs. Suranjana Saha and David Behringer for helpful comments and supports. Comments from the anonymous reviewer were very constructive for the final version of this manuscript and we appreciate for that.

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Authors and Affiliations

  1. Environmental Modeling Center, NCEP\NOAA, College Park, MD, USA

    Hyun-Chul Lee

  2. Climate Prediction Center, NCEP\NOAA, College Park, MD, USA

    Arun Kumar & Wanqiu Wang

  3. IMSG, Rockville, MD, USA

    Hyun-Chul Lee

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  1. Hyun-Chul Lee
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  2. Arun Kumar
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Correspondence to Hyun-Chul Lee.

Appendix: Model climatology

Appendix: Model climatology

In order to compare the model climatology of CFSv2L, the control runs of CFSv2 and CFSv2L are carried out for 33 years. The control run of CFSv2 starts from the initial conditions of January 1st 1979 with the same model configurations of the operational NCEP CFSv2 (Saha et al. 2014). At the sea surface boundary, temperature and salinity fields of CFSv2 are weakly relaxed to the climatology by the 1000 day e-folding time scale. In CFSv2L, the control run starts from January 1st 1980 initial conditions and has no relaxation at the sea surface. Figure 15 shows sea surface temperature (SST) and salinity (SSS) differences between CFSv2L and CFSv2 (CFSv2L-CFSv2). The lower panels of Fig. 15 show the differences of standard deviation for monthly anomaly of SST and SSS. The anomaly is calculated from the monthly annual mean for 33 year results of each run.

Fig. 15
figure 15

Differences (CFSv2L-CFSv2) of seasonal SST (left) and SSS (right) of the 33 years control run in winter (top), summer (middle), and differences of its standard deviation of monthly anomaly for 33 years (bottom)

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Figure 16 shows differences of annual mean temperature between CFSv2L and CFSv2 (upper panel), and difference of standard deviation of monthly temperature anomaly over 33 years. Along the equator, the vertical gradient of thermocline in CFSv2 is a slightly larger than the one of CFSv2L, even though the reduced vertical background diffusivity of CFSv2L could strengthen the thermocline. It is expected that the reduced horizontal resolution in CFSv2L would tend to weaken the vertical gradient of thermocline, especially in the east–west slope in thermocline with seasonal fluctuation. This difference of the thermocline can also affect patterns of ENSO variability (Meehl et al. 2001).

Fig. 16
figure 16

Differences (CFSv2L-CFSv2) of mean temperature (upper) and standard deviation of monthly anomaly (lower) for the 33 years along the equator with depth

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Lee, HC., Kumar, A. & Wang, W. Effects of ocean initial perturbation on developing phase of ENSO in a coupled seasonal prediction model. Clim Dyn 50, 1747–1767 (2018). https://doi.org/10.1007/s00382-017-3719-5

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