Sea surface temperature variations partitioned through multiple seasonal cycles
by Rameshan Kallummal
Low-frequency changes in the tropical Indian Ocean surface temperature have previously been investigated in the context of the Indian Ocean basin-wide (IOBM) and dipole (IOD) modes. The IOBM and IOD are the leading eigenmodes estimated from a traditional anomaly of SST. This approach ignores the possibility of multiple seasonal cycles (SCs) having different geographic patterns and interannually modulating amplitudes. The analyses presented here are anchored on the four sets of multivariate seasonal cycles independently extracted from the monthly observations of sea surface temperature (SST), surface wind, and surface pressure variations. We show that the secular warming, encapsulated by the monotonic variations of the first SC of SST (SST–SC1), differs from the previous linear trend patterns and has the most significant variance in the Indian Ocean Warm Pool (IOWP). Hence, these warming tendencies quantify the monotonic expansion rates of IOWP. The most significant interannual responses of Indian Ocean SST to remote forces (such as El Niño and La Niña) are also captured by SST–SC1. Unlike the traditional IOBM but similar to SST–SC1’s secular warming, these remotely forced interannual signals also have considerable variances in IOWP. The interannual variations in SST’s third seasonal cycle (i.e., SST–SC3) inherit SST–SC3’s dipole pattern but diverge from classical IOD in many aspects and are predominantly controlled by local processes. However, they are insufficient to account for the total interannual signals on their own. The collective interannual variations of four seasonal cycles—with significant variances off Africa’s eastern shores—demonstrate basin-wide unipolar patterns. Hence, SST interannual signals in the north-western Indian Ocean and the constantly growing warming in the IOWP influence climate and weather over countries surrounding the Indian Ocean. Thus, this study offers a simple way to separate three types of climate signals: secular, internal, and remotely induced climate fluctuations.
