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Global warming phenomena have started to gain public attention as the associated impacts are starting to affect human livelihoods. In the marine environment, an increasing ocean temperature is threatening coral reef ecosystems. However, ocean warming across the globe is not uniform. The spatial and temporal trends of ocean temperature need to be characterised. Little is known about the past and future trends in local ocean temperatures, which may be especially important in coral rich areas like the Coral Triangle and the South China Sea. This thesis uses a combination of monthly 10 spatial resolution NOAA Optimum Interpolation (OI) Sea Surface Temperature (SST) V2 dataset (OISSTv2) and the Representative Concentration Pathways (RCP2.6) mitigation scenario of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to characterise Sea Surface Temperature (SST) trends in the Indo-Pacific region. This research revealed warming trends detected for three SST variables. In the Coral Triangle warming trends with a rate of 0.013 °C yr-1 , 0.017 °C yr-1 , and 0.019 °C yr-1 were detected over 29 years for MaxSST, MeanSST and MinSST, respectively. In the SCS, the warming rates were 0.011 °C yr-1 , (MaxSST), 0.012 °C yr-1 (MeanSST) and 0.015 °C yr-1 (MinSST) over 29 years. The CMIP5 RCP2.6 forecast suggested a future warming rate to 2100 of 0.004°C yr-1 for both areas. Using MaxSST as a proxy for coral bleaching, this thesis attempted to model their relationship using logistic regression. Coral bleaching probability maps for the past and the future were produced. Widespread coral bleaching was predicted within a few decades. Further analysis was undertaken to explore the most appropriate spatial resolution of SST data for modelling coral bleaching. This thesis demonstrated that 4 km spatial resolution MaxSST is the best resolution to model coral bleaching events in the region.