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Statistical physics approaches to the complex Earth system
Global warming, extreme climate events, earthquakes and their accompanying socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, multiple interactions and complex structures of the Earth system, the understanding and, in particular, the prediction of such di...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Author(s). Published by Elsevier B.V.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532523/ https://www.ncbi.nlm.nih.gov/pubmed/33041465 http://dx.doi.org/10.1016/j.physrep.2020.09.005 |
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author | Fan, Jingfang Meng, Jun Ludescher, Josef Chen, Xiaosong Ashkenazy, Yosef Kurths, Jürgen Havlin, Shlomo Schellnhuber, Hans Joachim |
author_facet | Fan, Jingfang Meng, Jun Ludescher, Josef Chen, Xiaosong Ashkenazy, Yosef Kurths, Jürgen Havlin, Shlomo Schellnhuber, Hans Joachim |
author_sort | Fan, Jingfang |
collection | PubMed |
description | Global warming, extreme climate events, earthquakes and their accompanying socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, multiple interactions and complex structures of the Earth system, the understanding and, in particular, the prediction of such disruptive events represent formidable challenges to both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge of the Earth system, including climate extreme events, earthquakes and geological relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as critical phenomena, network theory, percolation, tipping points analysis, and entropy can be applied to complex Earth systems. Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics concepts and theories can be useful in the field of Earth system science. |
format | Online Article Text |
id | pubmed-7532523 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | The Author(s). Published by Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-75325232020-10-05 Statistical physics approaches to the complex Earth system Fan, Jingfang Meng, Jun Ludescher, Josef Chen, Xiaosong Ashkenazy, Yosef Kurths, Jürgen Havlin, Shlomo Schellnhuber, Hans Joachim Phys Rep Article Global warming, extreme climate events, earthquakes and their accompanying socioeconomic disasters pose significant risks to humanity. Yet due to the nonlinear feedbacks, multiple interactions and complex structures of the Earth system, the understanding and, in particular, the prediction of such disruptive events represent formidable challenges to both scientific and policy communities. During the past years, the emergence and evolution of Earth system science has attracted much attention and produced new concepts and frameworks. Especially, novel statistical physics and complex networks-based techniques have been developed and implemented to substantially advance our knowledge of the Earth system, including climate extreme events, earthquakes and geological relief features, leading to substantially improved predictive performances. We present here a comprehensive review on the recent scientific progress in the development and application of how combined statistical physics and complex systems science approaches such as critical phenomena, network theory, percolation, tipping points analysis, and entropy can be applied to complex Earth systems. Notably, these integrating tools and approaches provide new insights and perspectives for understanding the dynamics of the Earth systems. The overall aim of this review is to offer readers the knowledge on how statistical physics concepts and theories can be useful in the field of Earth system science. The Author(s). Published by Elsevier B.V. 2021-02-18 2020-10-03 /pmc/articles/PMC7532523/ /pubmed/33041465 http://dx.doi.org/10.1016/j.physrep.2020.09.005 Text en © 2020 The Author(s) Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Fan, Jingfang Meng, Jun Ludescher, Josef Chen, Xiaosong Ashkenazy, Yosef Kurths, Jürgen Havlin, Shlomo Schellnhuber, Hans Joachim Statistical physics approaches to the complex Earth system |
title | Statistical physics approaches to the complex Earth system |
title_full | Statistical physics approaches to the complex Earth system |
title_fullStr | Statistical physics approaches to the complex Earth system |
title_full_unstemmed | Statistical physics approaches to the complex Earth system |
title_short | Statistical physics approaches to the complex Earth system |
title_sort | statistical physics approaches to the complex earth system |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532523/ https://www.ncbi.nlm.nih.gov/pubmed/33041465 http://dx.doi.org/10.1016/j.physrep.2020.09.005 |
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