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Investigation of past and present climate dynamics and impact of climate tipping elements by means of a spatio-temporal analysis of climate data using complex networks

利用复杂网络对气候数据进行时空分析，调查过去和现在的气候动态以及气候临界因素的影响

基本信息

批准号：
190717089
负责人：
Professor Dr. Jürgen Kurths
金额：
--
依托单位：
Potsdam-Institut für Klimafolgenforschung (PIK)
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2011
资助国家：
德国
起止时间：
2010-12-31 至 2013-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/190717089?language=en
关键词：
Investigation past present climate dynamics

项目摘要

The study of the stability of the climate system and the impacts of the changes it undergoes requires both data analysis and modelling approaches. Recent findings of particularly sensitive sub-systems in the climate system (tipping elements), have risen concerns that common climate models still underestimate climate change. Focusing on the data analysis part, this project aims to investigate the role and connectivity of tipping elements with respect to global and regional climate and environmental change, using ideas from complex network theory for a spatio-temporal, multi-variate analysis of climate data. This approach will be critically reviewed and tested. For this purpose, new methods for inferring coupling directions and indirect couplings will be developed and implemented. Tipping elements will be studied by their spatio-temporal interactions; this will help to understand the stability or multi-stability of the global climate network due to changes of tipping elements and the crossing of tipping points. This study is complemented by comparing modern spatio-temporal climate interactions with past changes of climate during the Holocene, including the development of an appropriate approach to compare sparsely distributed data (palaeo-data) with complex network data (recent climate interaction network). The project will, therefore, significantly contribute to the climate change studies (better understanding tipping elements) and the methodological development (new approaches for spatio-temporal analysis), which could eventually also be used to improve climate models.

研究气候系统的稳定性及其所经历的变化的影响，需要数据分析和建模方法。最近对气候系统中特别敏感的子系统（倾翻因素）的研究结果引起了人们的关注，即普通气候模型仍然低估了气候变化。该项目重点关注数据分析部分，旨在利用复杂网络理论的思想对气候数据进行时空、多变量分析，探讨临界要素在全球和区域气候和环境变化中的作用和连通性。这一办法将受到严格审查和检验。为此，将开发和实施推断耦合方向和间接耦合的新方法。通过对临界要素时空相互作用的研究，有助于理解由于临界要素的变化和临界点的跨越而导致的全球气候网络的稳定性或多稳定性。这项研究的补充，比较现代时空气候相互作用与过去的气候变化在全新世，包括一个适当的方法来比较稀疏分布的数据（古数据）与复杂的网络数据（最近的气候相互作用网络）的发展。因此，该项目将大大有助于气候变化研究（更好地了解临界要素）和方法学发展（时空分析的新方法），最终也可用于改进气候模型。