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Inconsistencies in ocean temperature monitoring for coral reefs

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posted on 2022-11-18, 00:41 authored by Hui Fen Neo

Coral reefs are extremely vulnerable to climate-driven warming of the ocean, which threatens their existence. Multiple sea surface temperature (SST) data sources are currently used to study and predict coral responses to rising temperatures. Understanding the differences between the different SST data sources applied to coral reefs may facilitate monitoring and understanding global warming's impact on coral reefs. Four types of SST data across North-Western and South-Western Australia are compared to assess their differences and ability to predict historical coral bleaching events. Four decades of coral bleaching indicators, Degree Heating Week (DHW) and Degree Heating Month (DHM) were calculated based on satellite-derived SST, global climate models (GCM), and coral core derived proxies. Both DHW and DHM were inconsistent among datasets and did not accurately predict moderate and severe bleaching events. Despite high DHW and DHM values, some reefs did not experience bleaching, suggesting site-specific coral adaptation. The SST data from different sources had better consistency for frequency, which highlights the utility of coral cores as proxies to predict temperature frequencies. By exploring the differences and similarities among data sources, this study highlights the need to compare thermal stress indicators from different datasets for a more robust prediction of coral bleaching.


Table of Contents

Introduction -- Materials and methods -- Results -- Discussion -- Conclusion -- References -- Supplementary data


A thesis submitted in partial fulfillment of the requirements for the degree of Master of Research

Awarding Institution

Macquarie University

Degree Type

Thesis MRes


Thesis (MRes), Macquarie University, Faculty of Science of Engineering, 2022

Department, Centre or School

Department of Earth and Environmental Sciences

Year of Award


Principal Supervisor

Joseph Maina Mbui

Additional Supervisor 1

Thomas Fung


Copyright: Hui Fen Neo Copyright disclaimer:






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