Evidence map›Paper›PMID 33041465›Full record

ReviewPhysics reports2021

Statistical physics approaches to the complex Earth system.

Jingfang Fan, Jun Meng, Josef Ludescher, Xiaosong Chen, Yosef Ashkenazy, Jürgen Kurths, Shlomo Havlin, Hans Joachim Schellnhuber

Abstract readReview
In one paragraph

Review in Physics reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed.

  1. Article
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  4. Review
  5. Article
  6. Article
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  8. Article
  9. TsallisEntropy (Basel, Switzerland) · 2024
    Article
  10. Lunar Lithium-7 Sensing (Sensors (Basel, Switzerland) · 2024
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. A Digital Template for the Generic Multi-Risk (GenMR) Framework: A Virtual Natural Environment.International journal of environmental research and public health · 2022
    Article
  17. Article
  18. Article
  19. Article
  20. Detecting Metabolic Thresholds from Nonlinear Analysis of Heart Rate Time Series: A Review.International journal of environmental research and public health · 2022
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Jingfang FanPotsdam Institute for Climate Impact Research, Potsdam 14412, Germany.
Jun MengSchool of Science, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Josef LudescherPotsdam Institute for Climate Impact Research, Potsdam 14412, Germany.
Xiaosong ChenSchool of Systems Science, Beijing Normal University, Beijing 100875, China.
Yosef AshkenazyDepartment of Solar Energy and Environmental Physics, The Jacob Blaustein Institutes for Desert Research, Ben-Gurion University of the Negev, Midreshet Ben-Gurion 84990, Israel.
Jürgen KurthsPotsdam Institute for Climate Impact Research, Potsdam 14412, Germany.
Shlomo HavlinDepartment of Physics, Bar Ilan University, Ramat Gan 52900, Israel.
Hans Joachim SchellnhuberPotsdam Institute for Climate Impact Research, Potsdam 14412, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Climate changeComplex Earth systemsComplex networkEarthquakeStatistical physics

Identifiers

PMID33041465
PMCPMC7532523

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.