Improving thermal stress prediction for coral reefs from observational, modelled and proxy datasets across the Tropics

珊瑚礁极易受到气候驱动的海洋变暖的影响，这威胁到它们的生存。珊瑚对气温升高的反应目前是利用卫星产品、温度记录仪、全球环流模型和珊瑚核心得出的海面温度等多种来源的海洋表面温度(SST)进行研究和预测的。尽管协调来自不同来源的补充数据很重要，但对所使用的主要数据集和利用这些数据集进行的预测之间的一致性了解不足。了解适用于珊瑚礁的不同SST数据之间的一致性，可能有助于监测和了解全球变暖对珊瑚礁的影响。将对印度-太平洋地区的四种类型的SST数据进行比较，以评估它们的差异和预测历史珊瑚白化事件的能力。将开发新的方法从前卫星时代的珊瑚岩芯代理数据中提取SST值。珊瑚核心替代物对温度值的校准涉及不确定性，本研究的目的是利用统计方法尽量减少这种不确定性，这将允许对将珊瑚核心替代物校准为绝对温度值的优化模型进行测试。由于珊瑚核心指标是唯一需要校准到SST值的数据集，因此在协调四个数据集之前优化这一步骤至关重要。通过协调这四个数据源来创建珊瑚漂白指数，本研究减少了不确定性，并对珊瑚及其周围生态系统对热胁迫的反应进行了更好的理解和更稳健的预测。已知的历史珊瑚漂白事件和从现场观察到的当前事件可以与通过协调四个数据集创建的模型进行比较。随后，对每个珊瑚生态系统的影响

Coral reefs are extremely vulnerable to climate-driven warming of the ocean, which threatens their survival. Coral responses to rising temperatures are currently studied and predicted using sea surface temperature (SST) from multiple sources such as satellite products, temperature loggers, global circulation models and coral core derived SST. Despite the importance of harmonizing complementary data from different sources, there is inadequate understanding of the consistency among the main datasets used and the predictions made using them. Understanding the consistency among the different SST data applied to coral reefs may facilitate monitoring and understanding global warming's impact on coral reefs. Four types of SST data across the Indo-Pacific region will be compared to assess their differences and ability to predict historical coral bleaching events. Novel approaches will be developed for extracting SST values from coral core proxy data in pre-satellite era. The calibration of coral core proxies to temperature values involves uncertainties, in which this study aims to minimize with the use of statistical methods, which will allow testing of models that optimize the calibration of coral core proxy into absolute temperature values. As coral core proxies are the only datasets that require calibration into SST values, it is crucial to optimize this step prior to harmonizing the four datasets.By harmonizing these four data sources to create indices for coral bleaching, this study reduces uncertainties and creates a better understanding and a more robust prediction of coral and its surrounding ecosystem's response to thermal stress. Known historical coral bleaching events and current events observed from the field can be compared to the model created from harmonization of the four datasets. Subsequently, the impact to coral ecosystems in each