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Regimes of seasonal air–sea interaction and implications for performance of forced simulations

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Abstract

Sea surface temperature (SST) anomalies can induce anomalous convection through surface evaporation and low-level moisture convergence. This SST forcing of the atmosphere is indicated in a positive local rainfall–SST correlation. Anomalous convection can feedback on SST through cloud-radiation and wind-evaporation effects and wind-induced oceanic mixing and upwelling. These atmospheric feedbacks are reflected in a negative local rainfall–SST tendency correlation. As such, the simultaneous rainfall–SST and rainfall–SST tendency correlations can indicate the nature of local air–sea interactions. Based on the magnitude of simultaneous rainfall–SST and rainfall–SST tendency correlations, the present study identifies three distinct regimes of local air–sea interactions. The relative importance of SST forcing and atmospheric forcing differs in these regimes. In the equatorial central-eastern Pacific and, to a smaller degree, in the western equatorial Indian Ocean, SST forcing dominates throughout the year and the surface heat flux acts mainly as a damping term. In the tropical Indo-western Pacific Ocean regions, SST forcing and atmospheric forcing dominate alternatively in different seasons. Atmospheric forcing dominates in the local warm/rainy season. SST forcing dominates with a positive wind-evaporation feedback during the transition to the cold/dry season. SST forcing also dominates during the transition to the warm/rainy season but with a negative cloud-radiation feedback. The performance of atmospheric general circulation model simulations forced by observed SST is closely linked to the regime of air–sea interaction. The forced simulations have good performance when SST forcing dominates. The performance is low or poor when atmospheric forcing dominates.

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Acknowledgments

The authors appreciate insightful comments of Dr Harry Hendon and an anonymous reviewer. This research was supported by grants from the National Science Foundation ATM-0332910, the National Ocean and Atmospheric Administration NA04OAR4310034 and NA05OAR4311135, and the National Aeronautics and Space Administration NNG04GG46G.

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  1. Center for Ocean–Land–Atmosphere Studies, 4041 Powder Mill Road, Suite 302, Calverton, MD, 20705, USA

    Renguang Wu & Ben P. Kirtman

  2. School of Computational Sciences, George Mason University, Fairfax, VA, USA

    Ben P. Kirtman

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  1. Renguang Wu
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Wu, R., Kirtman, B.P. Regimes of seasonal air–sea interaction and implications for performance of forced simulations. Clim Dyn 29, 393–410 (2007). https://doi.org/10.1007/s00382-007-0246-9

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