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Adopting robust decision-making to forest management under climate change
2017
Annals of Forest Science
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Finally, robust decision-making applications to forest management under climate change uncertainty were evaluated and recommendations drawn. & Results Deep uncertainty is not adequately considered in the ...
& Key message Multi-objective robust decision making is a promising decision-making method in forest management under climate change as it adequately considers deep uncertainties and handles the long-term ...
Quantitative overview Scenario analysis was the most applied method to find so-called robust solutions under deep uncertainty (Online Resource, Fig. 1 ). ...
doi:10.1007/s13595-017-0641-2
fatcat:sf5pl7j6bvcxdnpbwg3ovkd3l4
Climate policy decision making in contexts of deep uncertainty - from optimisation to robustness
2021
Environmental Science and Policy
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Scenarios-Focused Decision Analysis (SFDA) describes a family of methods that aim to explicitly characterise (deep) uncertainties within scenarios, and then undertake decision analysis within and across ...
Scenario Focused Decision Analysis and Robust Decision Making We now introduce Robust Decision Making (RDM) as an exemplar of a group of tools we define as "Scenarios-Focused Decision Analysis", and outline ...
doi:10.1016/j.envsci.2021.03.002
fatcat:gtg25eevknbzhausao2p6dxsye
Scenario driven optimal sequencing under deep uncertainty
2015
Environmental Modelling & Software
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Scenario driven optimal sequencing under deep uncertainty Environmental Modelling and Software, 2015; 68:181-195 ...
In contrast, optimisation methods for dealing with optimal sequencing under global / deep uncertainty are much less developed. ...
Next, global sensitivity analysis is performed on the selected sequences to assess the variation (robustness) of system performance under a wide range of plausible future conditions and to determine the ...
doi:10.1016/j.envsoft.2015.02.006
fatcat:gfquk6uq5vcedno2bgabgljgou
Climate Change and Decision-Making Under Uncertainty
2016
Current Forestry Reports
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Robust decision-making is a unique approach to deal with the deep uncertainty in general, but has rarely been applied to forest management. ...
., scenarios to meet the climate target would stay deeply uncertain for long. ...
the sensitivity of decision outcomes to deep uncertainty about scenarios (e.g., climate change). ...
doi:10.1007/s40725-016-0035-y
fatcat:h3xdkp5harb3tmt6iozdksyeua
Exploring national decarbonization pathways and global energy trade flows: a multi-scale analysis
2016
Climate Policy
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Policy relevance statement In recent years, how global fossil fuel markets evolve under different climate regimes has been subject to much debate and analysis. ...
We find that global scale models provide critical insights that complement the more detailed national analyses, and should play a stronger role in informing deep decarbonization pathways (DDPs). ...
/K039326/1], and by the Agence Nationale de la Recherche under the Investissements d'avenir programme [ANR-10-LABX-14-01]. ...
doi:10.1080/14693062.2016.1179619
fatcat:c2et767xzrfpticvz4hjgksydy
A safety factor approach to designing urban infrastructure for dynamic conditions
[article]
2021
arXiv
pre-print
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Depending on the location, we find that adding safety factors of 1.4 to 1.7 to the standard stormwater pipe design guidance produces robust performance to the considered deep uncertainties. ...
We quantify the upfront costs needed to achieve higher hydraulic reliability and robustness against the deep uncertainties surrounding projections of rainfall, surface runoff characteristics, and infrastructure ...
Acknowledgements This work was co-supported by the National Oceanic and Atmospheric Administration (NOAA) through the Mid-Atlantic Regional Integrated Sciences and Assessments (MARISA) program under NOAA ...
arXiv:2102.04496v4
fatcat:3nbcp5pr55hvnnkmaqt4n6hgty
Ensemble climate predictions using climate models and observational constraints
2007
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
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The consistency of these results, when obtained using independent techniques, demonstrates that past observed climate changes provide robust constraints on probable future climate changes. ...
P.A.S. funded by the UK Department of the Environment, Food and Rural Affairs under contract PECD 7/12/37. C.E.F. was funded partially by US NSF and thanks to A. Sokolov and M. ...
The TCR is the global-mean surface temperature change that is realized at the time of CO 2 doubling under an idealized scenario in which CO 2 concentrations increase at 1% per year. ...
doi:10.1098/rsta.2007.2075
pmid:17569655
fatcat:ah5argllrzaeph2c3apzadpuv4
An open source framework for many-objective robust decision making
2015
Environmental Modelling & Software
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discovery and trade-off analysis; and computing uncertainty/robustness metrics. ...
This study introduces a new open source software framework to support bottom-up environmental systems planning under deep uncertainty with a focus on many-objective robust decision making (MORDM), called ...
The authors gratefully acknowledge Riddhi Singh and Tori Ward for providing source code for the lake problem and Elmar Plischke for giving permission to translate his Matlab sensitivity analysis codes ...
doi:10.1016/j.envsoft.2015.07.014
fatcat:bafafuzhcbcbrc4siz4mlhx2ii
Trapped between two tails: trading off scientific uncertainties via climate targets
2013
Environmental Research Letters
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Policy evaluations are more sensitive to uncertainty about abatement technology and impacts than to uncertainty about warming. ...
We use the technology-rich GCAM integrated assessment model to assess the robustness of 450 and 500 ppm carbon targets to each uncertain factor. ...
scenario analysis. ...
doi:10.1088/1748-9326/8/3/034019
fatcat:yrf764md7zfohpi4ox7bpttyre
Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty
2016
Journal of water resources planning and management
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The methods have been selected primarily to investigate a contrasting local vs global method of assessing water system robustness to deep uncertainty but also to compare a robustness model approach (IG ...
The methods under assessment are Info-Gap decision theory (IG) and Robust Optimisation (RO). ...
" scenario starting point for the analysis despite the deep uncertainties. ...
doi:10.1061/(asce)wr.1943-5452.0000660
fatcat:yzqeeratpjhb5b5iw7sklegsdm
Characterizing Climate-Change Uncertainties for Decision-Makers. An Editorial Essay
2004
Climatic Change
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Several research groups have derived probability distributions for climate sensitivity via statistical comparisons of climate model results to recent climate records (Andronova and Schlesinger, 2001; ...
considered in the analysis. ...
doi:10.1023/b:clim.0000037561.75281.b3
fatcat:qsr737f6jbh35pwguxiyu7zmvi
Comparison of Info-gap and Robust Optimisation Methods for Integrated Water Resource Management under Severe Uncertainty
2015
Procedia Engineering
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The methods under comparison are Info-Gap decision theory (IG) and Robust Optimisation (RO), with particular regard to two key issues: (a) a local vs global measure of water supply robustness and (b) a ...
The results reveal the impact of using alternative methodologies and analysis parameters on the final intervention strategies selected. ...
IG can tailor local robustness around the most likely scenarios which offer an alternative assessment to otherwise global or linear forms of analysis. ...
doi:10.1016/j.proeng.2015.08.955
fatcat:4fjd3xlgxngkzml7lsfkzoi2va
Estimated PDFs of climate system properties including natural and anthropogenic forcings
2006
Geophysical Research Letters
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The MIT Joint Program on the Science and Policy of Global Change is an organization for research, independent policy analysis, and public education in global environmental change. ...
Further, assessments of possible societal and ecosystem impacts, and analysis of mitigation strategies, need to be based on realistic evaluation of the uncertainties of climate science. ...
We thank many scientists who have encouraged this work including Myles Allen and Jim Hansen (MIT) and the support of the Joint Program on the Science and Policy of Global Change at MIT. ...
doi:10.1029/2005gl023977
fatcat:kwviiltrajc43fqxmnrteij7uy
Including robustness considerations in the search phase of Many-Objective Robust Decision Making
2018
Environmental Modelling & Software
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In its original inception, the search phase identifies optimal strategies for a single reference scenario for deep uncertainties, which may result in missing locally near-optimal, but globally more robust ...
Abstract Many-Objective Robust Decision Making (MORDM) is a prominent model-based approach for dealing with deep uncertainty. ...
Step 4: Tradeoff analysis In Step 4, the candidate solutions generated under the reference scenario and the four selected scenarios are evaluated in terms of their robustness against deep uncertainties ...
doi:10.1016/j.envsoft.2018.03.029
fatcat:ufvm3j3nk5d2ljzrj4l7o5u4gy
Adaptive mitigation strategies hedge against extreme climate futures
2021
Climatic Change
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both well-characterized and deep climate uncertainties. ...
Furthermore, the coupled human-Earth systems are subject to deep and dynamic uncertainties. ...
of adaptive strategies over non-adaptive ones under consideration of key deep uncertainties. ...
doi:10.1007/s10584-021-03132-x
fatcat:ebrq7ao55rfr3afqwceeuvzyby
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