Uncertainties arising from future decisions driving the makeup of the energy system globally affect multiple sectors in the human-Earth system on diverse spatiotemporal scales. The complex interplay between sectors requires a thorough examination of these uncertainties, usually conducted through large scenario ensembles encompassing a wide range of potential futures. However, previous efforts have overlooked the methodological choice of aggregation measures across the ensemble, despite potential consequences. In this study, we leverage a large ensemble dataset that captures the uncertainties associated with the energy system generated using the Global Change Analysis Model. Using the ensemble, we first explore how energy-related uncertainties are propagated to both the global and regional water-energy-food sectors. We then conduct a rank correlation analysis across diverse cross-ensemble aggregation measures that are used to aggregate ensemble members for further analysis and highlight the potential downsides arising from relying on a single measure. Our results highlight that the influences that arise from low-carbon transitions can increase the uncertainties of all sectors at the end of the century, each with its unique dynamic. Moreover, the most severe outcomes in the majority of regions take place under scenarios with extreme socioeconomic assumptions in combination with low-carbon transitions. Our findings emphasize that threshold-based classification measures that have been frequently adopted to identify critical outcomes in multisectoral systems may overlook the dynamics embedded in the scenario ensemble. As an alternative, using appropriate cross-ensemble aggregation measures in order to derive robust insights from the outcomes holds promise.

Simulation models of multi-sector systems are increasingly used to understand societal resilience to climate and economic shocks and change. However, multi-sector systems are also subject to numerous uncertainties that prevent the direct application of simulation models for prediction and planning, particularly when extrapolating past behavior to a nonstationary future. Recent studies have developed a combination of methods to characterize, attribute, and quantify these uncertainties for both single- and multi-sector systems. Here we review challenges and complications to the idealized goal of fully quantifying all uncertainties in a multi-sector model and their interactions with policy design as they emerge at different stages of analysis: (1) inference and model calibration; (2) projecting future outcomes; and (3) scenario discovery and identification of risk regimes. We also identify potential methods and research opportunities to help navigate the tradeoffs inherent in uncertainty analyses for complex systems. During this discussion, we provide a classification of uncertainty types and discuss model coupling frameworks to support interdisciplinary collaboration on multi-sector dynamics (MSD) research. Finally, we conclude with recommendations for best practices to ensure that MSD research can be properly contextualized with respect to the underlying uncertainties.

The field of MultiSector Dynamics (MSD) explores the dynamics and co-evolutionary pathways of human and Earth systems with a focus on critical goods, services, and amenities delivered to people through interdependent sectors. This commentary lays out core definitions and concepts, identifies MSD science questions in the context of the current state of knowledge, and describes ongoing activities to expand capacities for open science, leverage revolutions in data and computing, and grow and diversify the MSD workforce. Central to our vision is the ambition of advancing the next generation of complex adaptive human-Earth systems science to better address interconnected risks, increase resilience, and improve sustainability. This will require convergent research and the integration of ideas and methods from multiple disciplines. Understanding the tradeoffs, synergies, and complexities that exist in coupled human-Earth systems is particularly important in the context of energy transitions and increased future shocks.