Abstract

A spectral cumulus parameterization (spectral scheme) is implemented in Scale Interaction Experiment Frontier version 2 (SINTEX-F2) seasonal prediction system, and the impact on the El Niño Southern Oscillation (ENSO) prediction is examined. By conducting hindcast experiments using the original convection scheme (Tiedtke scheme) and the spectral scheme, and comparing the ENSO prediction skill, the impact of the spectral scheme is analyzed in detail. It was found that prediction skill in terms of ENSO phase and the sea surface temperature (SST) persistence were improved by using the spectral scheme, but the root-mean-square error (RMSE) increased. The ENSO feedback was also changed by changing the convection scheme. The original scheme failed to predict the zonal wind stress anomaly toward the Niño 3.4 region, whereas the spectral scheme simulated it over the equatorial eastern Pacific with narrowing the meridional width, indicating that the spectral scheme strengthened the ENSO feedback. The spectral scheme also improved zonal-vertical atmospheric response to the Niño 3.4 index due to its advantageous features. Analysis of the ENSO feedback terms revealed that strengthened forcing in the eastern Pacific improved the thermocline feedback of ENSO, as its reversed timing of positive and negative tendencies for the mixed layer temperature matched that estimated from the reanalysis data. In conclusion, the spectral scheme can improve ENSO prediction through the atmospheric forcing and mean state in the eastern Pacific which impacted the ocean properties. It improved the phase error by improving thermocline feedback, but did not improve the RMSE. Tuning of the original scheme to obtain additional improvements to ENSO prediction would be difficult, since it requires modification of detailed convective cloud properties to correct the phase error. The spectral scheme tends to overestimate the ENSO amplitude, i.e., large RMSE, but this drawback can be mitigated by tuning the convection scheme so that it suppresses the warm SST climate drift, and this is considered the more promising method to further improve ENSO prediction.

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