Investigation of past and present climate dynamics and its stability by means of a spatio-temporal analysis of climate data using complex networks

使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及其稳定性

• 批准号: 256063231
• 负责人: Privatdozent Dr. Norbert Marwan
• 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: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/256063231?language=en
• 关键词: Investigation; past; present; climate; dynamics

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 indirect couplings, extreme events, spatial predominant directions, and boundary effects will be developed and implemented as well as applied to the monsoon regions in South America and Asia. This includes a novel anisotropy measure which is able to quantify directions along which extreme events synchronize locally. Spatio-temporal interactions between and within these specific tipping elements will investigated in order to understand the stability or multi-stability of the considered monsoon regions due to environmental changes or crossing of tipping points. 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。最近关于气候系统中特别敏感的子系统（引爆要素）的发现，引起了人们的关注，即普通气候模式仍然低估了气候变化。本项目以数据分析部分为重点，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，探讨引爆要素在全球和区域气候与环境变化中的作用和连通性。这种方法将受到严格的审查和测试。为此，将开发和实施推断间接耦合、极端事件、空间主导方向和边界效应的新方法，并将其应用于南美洲和亚洲的季风区。这包括一种新的各向异性测量，它能够量化极端事件在局部同步的方向。为了了解由于环境变化或临界点的交叉所考虑的季风区的稳定性或多重稳定性，将研究这些特定临界点要素之间和内部的时空相互作用。因此，该项目将对气候变化研究（更好地理解引爆因素）和方法发展（时空分析的新方法）做出重大贡献，最终也可用于改进气候模型。

项目成果

Non-linear time series analysis of precipitation events using regional climate networks for Germany

• DOI: 10.1007/s00382-015-2632-z
• 发表时间: 2016-02
• 期刊: Climate Dynamics
• 影响因子: 4.6
• 作者: A. Rheinwalt;N. Boers;N. Marwan;J. Kurths;P. Hoffmann;F. Gerstengarbe;P. Werner

The South American rainfall dipole: A complex network analysis of extreme events

• DOI: 10.1002/2014gl061829
• 发表时间: 2014-10-28
• 期刊: GEOPHYSICAL RESEARCH LETTERS
• 影响因子: 5.2
• 作者: Boers, Niklas;Rheinwalt, Aljoscha;Kurths, Juergen
• 通讯作者: Kurths, Juergen

How complex climate networks complement eigen techniques for the statistical analysis of climatological data

• DOI: 10.1007/s00382-015-2479-3
• 发表时间: 2015-11-01
• 期刊: CLIMATE DYNAMICS
• 影响因子: 4.6
• 作者: Donges, Jonathan F.;Petrova, Irina;Kurths, Juergen
• 通讯作者: Kurths, Juergen

Complex network based techniques to identify extreme events and (sudden) transitions in spatio-temporal systems.

• DOI: 10.1063/1.4916924
• 发表时间: 2015-04
• 期刊: Chaos
• 影响因子: 2.9
• 作者: N. Marwan;J. Kurths

Analysing spatially extended high-dimensional dynamics by recurrence plots

• DOI: 10.1016/j.physleta.2015.01.013
• 发表时间: 2015-05-08
• 期刊: PHYSICS LETTERS A
• 影响因子: 2.6
• 作者: Marwan, Norbert;Kurths, Juergen;Foerster, Saskia
• 通讯作者: Foerster, Saskia