Abstract
Spatial and temporal variations of the sea surface temperature (SST) over the Indian Ocean are examined by using empirical orthogonal function (EOF) analysis. The first EOF mode explains 20.54% of the total variance indicating positive values which reveal coherent interannual variations over the study area. Time coefficients of the first EOF mode show a strong relationship with the Pacific SST anomalies. Therefore, the El Nino/Southern Oscillation (ENSO) events are observed in the time coefficients of the first EOF mode almost simultaneously. Power spectrum analysis reveals a dominant peak ranging from 18 to 48 months which covers the quasi-biennial oscillation (QBO) and the dominant cycle in the Southern Oscillation phenomenon (30 to 40 months). The second and third EOF modes explain relatively less contributions, 5.6% and 5.1% of the total variance.
A weak positive correlation coefficient is observed between the time coefficients of the first EOF mode of SST anomalies and the time coefficients of the first EOF mode of the rainfall over Sri Lanka when all months are considered, but strong relationships are noticed for the months of October, November and December which coincide with the mature and decay stages of ENSO events. The positive relationships between SST anomalies of the Pacific and Indian Oceans and rainfall anomalies of the above mentioned months first appear in March and April, and then gradually build up towards the significant level in the concurrent months. In the case of the summer monsoon season, Arabian Sea SSTs, where strong seasonal and regional variations are found, strongly influence the rainfall of Sri Lanka, particularly striking in the southwestern quadrant of the island. Rainfall of this season has a significant positive correlation with the SST over the Arabian Sea during the concurrent period, but significant negative correlation with the previous months, before six months. The changes in the sign of the correlation coefficients occur in the months of November-December of the year before the summer monsoon, thus it may be useful to foreshadow the excess and deficit rainfall over Sri Lanka few months in advance.
