Climate Dynamics: Precursors of tipping points in a rapidly changing climate (Ref: 4342-6)

该项目旨在通过分析CMIP6模型数据找到引爆点的前兆。为了实现这一目标，首先要开发一种可靠的方法来检测CMIP6数据中的引爆事件。该项目的第一阶段将重点开发一种算法，通过机器学习技术检测数据的突变。然后，该算法可用于检测所选引爆元素的未来预测中的引爆事件。一旦确定了引爆事件，将进行统计分析，并用于在数据中找到引爆点的潜在前兆。确定的前体可以在多个模型中进行可靠性测试，并用于评估所选引爆元素未来发生引爆事件的风险。

This project will aim to find precursors to tipping points through analysis of CMIP6 model data. To achieve this, first a reliable method for detecting tipping events in the CMIP6 data would be developed. The first stage of this project will focus on developing an algorithm to detect abrupt shifts in data through machine learning techniques. This algorithm may then be used to detect tipping events in future projections for a chosen tipping element. Once tipping events have been identified, statistical analysis will be performed and used to find potential precursors to tipping points within the data. Identified precursors can then be tested for reliability across multiple models and used to assess the risk of future tipping events occurring for a chosen tipping element.