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Session Proposal: MultiSector Dynamics: Uncertainty Characterization for Coupled Natural-Human Systems (AGU25)

GC081
MultiSector Dynamics: Uncertainty Characterization for Coupled Natural-Human Systems

Session ID#: 250235

Session Description:
Multi-sector and coupled natural-human systems often feature complex adaptive dynamics, including feedbacks and tipping points, and involve many uncertainties. However, models of coupled natural-human systems often fail to characterize uncertainty and its propagation across systems. Uncertainty characterization plays an important role in understanding and projecting dynamics in these systems under future socioeconomic and environmental conditions. It is therefore an essential component of MultiSector Dynamics (MSD) research, which aims to advance our understanding of the co-evolution of human and natural systems over time. This session invites contributions addressing the challenge of uncertainty characterization for systems that bridge sectors (e.g., energy, water, transportation) and scales (spatial, temporal, and institutional) to understand their dynamics and improve decision-making. We welcome contributions focusing on the probabilistic quantification of uncertainty in coupled natural-human systems, the development of outcome-oriented scenarios, or hybrid approaches, as well as uncertainty propagation through coupled systems to decision-relevant outcomes and metrics.
Index Terms:

1630 Impacts of global change [GLOBAL CHANGE]
1699 General or miscellaneous [GLOBAL CHANGE]
1990 Uncertainty [INFORMATICS]
4328 Risk [NATURAL HAZARDS]
Primary Convener:  Vivek Srikrishnan, Cornell University, Biological & Environmental Engineering, Ithaca, NY, United States
Conveners:  Jonathan Lamontagne, Tufts University, Civil and Environmental Engineering, Medford, United States and James Doss-Gollin, Rice University, Department of Civil and Environmental Engineering, Houston, TX, United States
Student/Early Career Convener:  Abigail Nora Birnbaum, Pacific Northwest National Laboratory, Richland, WA, United States
 
Leveraging Information Theoretic Sensitivity Analysis to Navigate Information-Action Feedbacks in Dynamic and Adaptive Infrastructure Investment Pathways (Invited) (1853725)
Lillian Lau, Cornell University, Ithaca, NY, United States and Patrick M Reed, Cornell University, School of Civil and Environmental Engineering, Ithaca, NY, United States
 
A Machine-Learning based Framework for Evaluating Energy and Environmental Outcomes of Bioenergy Technology Uncertainties (1881056)
Abigail Nora Birnbaum1, Maridee Weber2, Taryn Waite3, Yuan Jiang4, Kanishka Narayan4 and Marshall A Wise5, (1)Pacific Northwest National Laboratory, Richland, WA, United States, (2)Pacific Northwest National Laboratory, Joint Global Change Research Institute, Richland, WA, United States, (3)Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park, United States, (4)Pacific Northwest National Laboratory, Richland, United States, (5)Pacific Northwest National Laboratory, College Park, United States
 
Neglecting Initial Population Uncertainty Leads to Biased Assessments of Flood Risk Outcomes (1898615)
Parin Bhaduri1, Adam Pollack2, James Yoon3, Heng Wan4, Pranab Roy Chowdhury3, Brent Daniel3 and Vivek Srikrishnan5, (1)Cornell University, Biological & Environmental Engineering, Ithaca, NY, United States, (2)Dartmouth College, Thayer School of Engineering, Hanover, United States, (3)Pacific Northwest National Laboratory, Richland, United States, (4)Pacific Northwest National Laboratory, Richland, WA, United States, (5)Cornell University, Ithaca, NY, United States
 
Identifying Key Global and Domestic Uncertainties Affecting the Future U.S. Liquefied Natural Gas Export Market (1911079)
Hanwoong Kim, Princeton University, School of Public and International Affairs, Princeton, NJ, United States and Wei Peng, Princeton University, School of Public and International Affairs, Princeton, United States
 
Advancing characterization of and decision-making under uncertainty when adapting power systems to climate change (Invited) (1957103)
Michael Craig, University of Michigan, School for Environment and Sustainability, Ann Arbor, United States
 
Nature-Related Financial Risks for Global Systemically Important Banks (G-SIBs) (1982503)
Juan Sabuco, University of Oxford, Oxford, United Kingdom and Nicola Ranger, London School of Economics, London, United Kingdom
 
Studying Deep Meteorological Uncertainty in the Context of Energy System Planning (1987069)
Srihari Sundar1, Vincent Carag2, Stuart Cohen1, Grant Buster2 and Vincent cargo, (1)National Renewable Energy Laboratory Golden, Golden, CO, United States, (2)National Renewable Energy Laboratory Golden, Golden, United States
 
Adaptive Stratospheric Aerosol Injection Strategies under Uncertainty (1989906)
Adam Bauer1, David Keith2 and B. B. Cael2,3, (1)University of Chicago, Chicago, United States, (2)University of Chicago, Department of the Geophysical Sciences, Chicago, United States, (3)University of Chicago, Climate Systems Engineering initiative, Chicago, United States