Abstract
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.
Highlights
Temperature is a controlling factor in ocean systems
The use of non-overlapping time slices yielded plots qualitatively similar to those in Fig. 4 (Supplement Fig. 2), but since fewer spatiotemporal complexity (STC) values for each year were generated with this method, we used overlapping time slices for the rest of the paper
We have discussed the prevailing meteorology and oceanography system of the Philippines as it correlates with observations from the STC signals
Summary
Temperature is a controlling factor in ocean systems. Anomalies in sea surface temperature (SST) have a wide range of effects on marine ecosystems including the decline in reef fish populations (Pratchett et al, 2006) and coral dis-ease outbreaks (Bruno et al, 2007). We explore the hypothesis that the spatio-temporal complexity of the SST signal can be linked to physical processes such as prevailing winds and weather systems and our objective is to characterize these dynamics. We assess the ability of a recently developed measure of spatiotemporal complexity (STC) to provide additional information from the SST data. STC is a relatively new measure whose applications to remotely sensed data in the ocean sciences have yet to be demonstrated. If sufficiently sensitive, such a measure could serve as an indicator of impending change in the dynamics of SST, which might help to detect the onset of coral bleaching or other regime shifts in the marine ecosystem
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