Improving seasonal forecasting through tropical ocean bias corrections

Mulholland, D. P., Haines, K. ORCID: https://orcid.org/0000-0003-2768-2374 and Balmaseda, M. A. (2016) Improving seasonal forecasting through tropical ocean bias corrections. Quarterly Journal of the Royal Meteorological Society, 142 (700). pp. 2797-2807. ISSN 1477-870X doi: 10.1002/qj.2869

Abstract/Summary

Initialisation shock is often discussed in the context of coupled atmosphere-ocean forecasting, but its detection has remained elusive. In this paper, the presence of initialisation shock in seasonal forecasts is clearly identified in the variability of the tropical thermocline. The specific source of shock studied here is the use of a bias correction procedure to account for errors in equatorial wind stress forcing during ocean initialisation. It is shown that the abrupt removal of the bias correction at the beginning of the forecast leads to rapid adjustments in the upper ocean, creating a shock that remains in the system for at least three months. By contrast, gradual removal of the correction term, over 20 days, greatly reduces the initialisation shock. Evidence is presented of substantial increases in sea surface temperature (SST) seasonal forecast skill, at around 3–7 months’ lead time, when the gradual removal approach is used. Gains in skill of up to 0.05, as measured by the anomaly correlation coefficient for SST in the Nino4 region, are found, using a modest hindcast set covering four seasonal start dates. The results show that improvements in coupled initialisation aimed at reducing shocks may considerably benefit seasonal forecasting.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/65950
Identification Number/DOI	10.1002/qj.2869
Refereed	Yes
Divisions	Science > School of Mathematical, Physical and Computational Sciences > National Centre for Earth Observation (NCEO) Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
Publisher	Royal Meteorological Society
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