Journal of Climate, submitted April 2013.

The effect of greenhouse-gas-induced changes in SST on the seasonality of tropical precipitation

John Dwyer
Department of Applied Physics and Applied Mathematics, Columbia University, New York, NY

Michela Biasutti
Lamont-Doherty Earth Observatory of Columbia University, Palisades, NY

Adam Sobel
Department of Applied Physics and Applied Mathematics, Department of Earth and Environmental Sciences, and Lamont-Doherty Earth Observatory, Columbia University, New York, NY.


CMIP5 models project changes to the seasonality of both tropical sea surface temperature (SST) and precipitation when forced by an increase in greenhouse gases. Nearly all models project an amplification and a phase delay of the annual cycle for both quantities, indicating a greater annual range and extrema reached later in the year. We detail these changes and investigate the nature of the seasonal precipitation changes in an AGCM. In response to a prescribed SST with a uniformly higher annual mean temperature, we find a strengthened annual cycle of precipitation due to enhanced vertical moisture advection, and we find a delay to the timing of peak precipitation, consistent with a delay to the timing of the circulation. A budget analysis of this simulation indicates a large degree of similarity with the CMIP5 results. In the second experiment, we change only the seasonal characteristics of SST. For an amplified annual cycle of SST we find an amplified annual cycle of precipitation, while for a delayed SST we find a delayed annual cycle of precipitation. Additionally, there are cross effects: the phase of SST affects the amplitude of precipitation and the amplitude of SST affects the phase of precipitation. Assuming that the seasonal changes of precipitation in the CMIP5 models are entirely due to SST effects and that ocean feedbacks are not important, our AGCM simulations suggest that the annual mean SST warming can explain around 90% of the amplitude increase and 60% of the phase delay of precipitation in the CMIP5 models with the remainder due to seasonal changes in SST.