Anomalous Java cooling at the initiation of positive Indian Ocean Dipole events

Citation:
Delman, AS, Sprintall J, McClean JL, Talley LD.  2016.  Anomalous Java cooling at the initiation of positive Indian Ocean Dipole events. Journal of Geophysical Research: Oceans.

Date Published:

2016/08

Keywords:

1616 Climate variability, 1640 Remote sensing, 4504 Air/sea interactions, 4554 Planetary waves, 4572 Upper ocean and mixed layer processes, climate variability, Indian Ocean Dipole, interannual variability, java, kelvin waves, upwelling

Abstract:

Anomalous sea surface temperature (SST) cooling south of Java, initiated during May–July, is an important precursor to positive Indian Ocean Dipole (pIOD) events. As shown previously, the Java SST anomalies are spatially and temporally coincident with seasonal upwelling induced locally by southeasterly trade winds. However, we confirm earlier findings that interannual variability of the Java cooling is primarily driven by remote wind forcing from coastal Sumatra and the equatorial Indian Ocean (EqIO); we also find an influence from winds along the Indonesian Throughflow. The wind forcing in the EqIO and along coastal Sumatra does not initiate SST cooling locally due to a deep thermocline and thick barrier layer, but can force upwelling Kelvin waves that induce substantial surface cooling once they reach the seasonally shallower thermocline near the coast of Java. Satellite altimetry is used to obtain a Kelvin wave coefficient that approximates Kelvin wave amplitude variations along the equator. All pIOD years in the satellite record have anomalous levels of upwelling Kelvin wave activity along the equator during April–June, suggesting that upwelling waves during this season are necessary for pIOD event development. However, a change to wind-forced downwelling Kelvin waves during July–August can abruptly terminate cool Java SST anomalies and weaken the pIOD event. Upwelling Kelvin wave activity along the equator and wind stress anomalies west of Sumatra are both robust predictors of the IOD index later in the calendar year, while values of the Kelvin wave coefficient are the most reliable predictor of pIOD events specifically.

Notes:

n/a

Website

DOI:

10.1002/2016JC011635