The Implications of Nonlinear, Complex System Behaviour for Managing Changing Climate Risk

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Climatology".

Deadline for manuscript submissions: closed (30 June 2018) | Viewed by 3350

Special Issue Editor

Institute of Sustainable Industries and Liveable Cities, Victoria University, Melbourne 8001, Australia
Interests: disasters; climate change adaptation; environmental justice; sustainability; green social work; social protection; social work; field education; immigrant settlement; social development; international social work
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Special Issue Information

Dear Colleagues,

There are two schools of thought about how the climate changes under increasing greenhouse gases. One school considers that the forced component and internal variability are independent, with externally-forced atmospheric warming being gradual, surrounded by the uncertainty of (nonlinear) climate variability.

The other school of thought considers that added warming enhances climate variability, which, over decadal time scales, is fundamentally nonlinear. These nonlinearities are associated with step-like changes in steady state climate regimes. Under increased forcing, the nonlinear behaviour associated with climate variability would be enhanced, leading to more frequent regime changes. These would likely manifest on regional scales, even though, under sustained forcing, global warming is expected to follow a complex trend.

With the IPCC Sixth Assessment Report in its early stages, there is a very limited literature on managing the risk of nonlinear climate change on decadal timescales, yet nonlinear change poses a much greater risk than gradual change. If climate change on decision-making timescales proves to be fundamentally nonlinear, there will be a substantial gap in the assessment. This special issue invites submissions on all aspects of the implications of nonlinear climate change for risk management, from theory through to practice.

Prof. Dr. Roger Jones
Guest Editor

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Keywords

  • climate risk assessment
  • decadal climate variability
  • climate change
  • regime change
  • complex system behaviour

Published Papers (1 paper)

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Research

22 pages, 4039 KiB  
Article
Analysis of Drought Vulnerability Characteristics and Risk Assessment Based on Information Distribution and Diffusion in Southwest China
by Shouzheng Jiang, Ruixiang Yang, Ningbo Cui, Lu Zhao and Chuan Liang
Atmosphere 2018, 9(7), 239; https://doi.org/10.3390/atmos9070239 - 22 Jun 2018
Cited by 12 | Viewed by 2941
Abstract
Drought vulnerability characteristics and risk assessment form the basis of drought risk management. In this study, the standardized precipitation index (SPI) and drought damage rates (DDR) were combined to analyze drought vulnerability characteristics and drought risk in Southwest China (SC). The information distribution [...] Read more.
Drought vulnerability characteristics and risk assessment form the basis of drought risk management. In this study, the standardized precipitation index (SPI) and drought damage rates (DDR) were combined to analyze drought vulnerability characteristics and drought risk in Southwest China (SC). The information distribution method was applied to estimate the probability density of the drought strength (DS) and the two-dimensional normal information diffusion method was used to construct the vulnerability relationships between DS and drought damage (DD). The risk was then evaluated by combining the probability function of the DS and the DD vulnerability curve. The results showed that the relationship between the DS and the DD was nonlinear in SC and its provinces. With the increase in DS, the degree of DD increased gradually, stabilized, or decreased toward the end. However, the vulnerability characteristics of the different provinces varied widely due to multiple risk-bearing bodies and abilities to resist disasters. The risk values obtained across the range of time scales of the SPI were not significantly different. The yielding probabilities will be reduced for the crop area by 10%, 30%, and 70% due to drought. Compared to a normal year in SC, the probability values were 16.04%, 10.29%, and 2.70%, respectively. These results have the potential to provide a reference for agricultural production and drought risk management. Full article
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