#C03 Sea surface temperature and salinity south of Java as predictors of Indonesian precipitation

1.Poster Title	Sea surface temperature and salinity south of Java as predictors of Indonesian precipitation
2.Authors	Sophia Chen (Unlicensed); Julie McClean; Janet Sprintall; Mark Taylor; David C. Bader; Mathew Maltrud; Milena Veneziani; Kate Evans (Unlicensed); Marcia Branstetter (Unlicensed); Salil Mahajan
3.Group	Coupled
4.Experiment
5.Poster Category	Early result
6.Submission Type	poster
7.Poster Link	Chen_McClean_etal_rainfall.pdf
8.Lightning Talk Slide

Abstract

Rainfall in the Indonesian Throughflow region is greatly influenced by coupled air-sea processes on a range of temporal scales: the Madden-Julian Oscillation on intraseasonal scales, the seasonal monsoon, and the interannual Indian Ocean Dipole (IOD) and ENSO climate modes.Using the 90-year monthly output from the ACME v0.1 enhanced resolution fully coupled model, we explore the predictability of Indonesian rainfall variability. Model-data comparisons indicate that ACME v0.1 is a useful tool for this study: the time-mean and standard deviation of the monthly averaged sea surface temperature (SST), sea surface salinity (SSS) and precipitation from the model qualitatively agree with observations in both their spatial patterns and magnitudes. The spectra of SST and SSS south of Java from the model and observations also match. Both model and observations reveal that the SST south of Java in the austral summer is positively correlated with precipitation in the subsequent fall, whereas SSS south of Java in the austral summer is negatively correlated with the subsequent fall precipitation. We further assess whether SST and SSS south of Java can be useful predictor of the Indonesian rainfall variability. Their skillfulness in the rainfall prediction is also compared with those of the standard climate indices (e.g. IOD and ENSO). We are exploring the underlying dynamics in our on-going work.