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

珊瑚礁非常容易受到气候驱动的海洋变暖的影响，这威胁到它们的生存。目前正在利用卫星产品、温度记录仪、全球环流模型和珊瑚芯得出的海表温度等多种来源的海表温度来研究和预测珊瑚对温度上升的反应。尽管统一不同来源的互补数据很重要，但对所使用的主要数据集之间的一致性以及利用这些数据集所作的预测了解不够。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。将比较印度太平洋地区四种类型的SST数据，以评估它们的差异和预测历史珊瑚漂白事件的能力。将开发新的方法，用于从卫星出现前的珊瑚芯代用数据中提取SST值。校准珊瑚核心代理温度值涉及不确定性，本研究的目的是尽量减少使用统计方法，这将允许测试模型，优化校准珊瑚核心代理到绝对温度值。由于珊瑚核心代理是唯一需要校准成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以创建珊瑚漂白指数，本研究减少了不确定性，并更好地理解和更可靠地预测珊瑚及其周围生态系统对热应力的反应。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从四个数据集的协调中创建的模型进行比较。随后，

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