1Institute of Mathematics, University of the Philippines Diliman, 1101 Quezon City, Philippines
2Marine Science Institute, University of the Philippines Diliman, 1101 Quezon City, Philippines
3Departement de Géographie, Université de Montréal, C.P. 6128 succursale centre-ville, Montréal, QC H3C 3JY, Canada
*now at: Genome Institute of Singapore, 60 Biopolis Street, #02-01 Genome, Singapore
Abstract. A spatio-temporal complexity (STC) measure which has been previously used to analyze data from terrestrial ecosystems is employed to analyse 21 years of remotely sensed sea-surface temperature (SST) data from the Philippines. STC on the Philippine wide SST showed the monsoonal variability of the Philippine waters. STC is correlated with the SST mean (R2 ≈ 0.7), and inversely correlated with the SST standard deviation (R2 ≈ 0.9). Both STC and SST are highest during the middle of the year, which coincides with the Southwest Monsoon, but with the STC values being higher towards the end of the monsoon until the start of the inter-monsoon. In order to determine if STC has the potential to define limits of bio-regions, the spatial domain was subsequently divided into six thermal regions computed via clustering of temperature means. STC and EOF of the STC values were computed for each thermal region. Our STC analysis of the SST data, and comparisons with SST values suggest that the STC measure may be useful for characterising environmental heterogeneity over space and time for many long-term remotely sensed data.