The parallel scenario process enables characterization of climate-related risks and response options to climate change under different socio-economic futures and development prospects. The process is based on representative concentration pathways, shared socio-economic pathways, and shared policy assumptions. Although this scenario architecture is a powerful tool for evaluating the intersection of climate and society at the regional and global level, more specific context is needed to explore and understand risks, drivers, and enablers of change at the national and local level. We discuss the need for a stronger recognition of such national-scale characteristics to make climate change scenarios more relevant at the national and local scale, and propose ways to enrich the scenario architecture with locally relevant details that enhance salience, legitimacy, and credibility for stakeholders. Dynamic adaptive pathways are introduced as useful tools to draw out which elements of a potentially infinite scenario space connect with decision-relevant aspects of particular climate-related and non-climate-related risks and response options. Reviewing adaptation pathways for New Zealand case studies, we demonstrate how this approach could bring the global-scale scenario architecture within reach of local-scale decision-making. Such a process would enhance the utility of scenarios for mapping climate-related risks and adaptation options at the local scale, involving appropriate stakeholder involvement.

Solar geoengineering, also known as Solar Radiation Modification (SRM), has been proposed to alter Earth’s radiative balance to reduce the effects of anthropogenic climate change. SRM has been identified as a research priority, as it has been shown to effectively reduce surface temperatures, while substantial uncertainties remain around side effects and impacts. Global modeling studies of SRM have often relied on idealized scenarios to understand the physical processes of interventions and their widespread impacts. These extreme or idealized scenarios are not directly policy-relevant and are often physically implausible (such as imposing global solar reduction to counter the warming of an instantaneous quadrupling of CO2). The climatic and ecological impacts of politically relevant and potentially plausible SRM approaches have rarely been modeled and assessed. Nevertheless, commentators and policymakers often falsely assume that idealized or extreme scenarios are proposed solutions to climate change. This paper proposes 18 scenarios that appear to be broadly plausible from political and Earth System perspectives and encompass futures that could be both warnings or perhaps desirable. We place these scenarios into four groups following broader strategic contexts: (1) Global Management; (2) Regional Emergencies; (3) Coordinated Regional Interventions; and (4) Reactive Global Interventions. For each scenario, relevant model experiments are proposed. Some may be performed with existing setups of global climate models, while others require further specification. Developing and performing these model experiments – and assessing likely resulting impacts on society and ecosystems – would be essential to inform public debate and policymakers on the real-world issues surrounding SRM.

The evolutionary paths of social-ecological systems comprise periods of structural continuity punctuated by moments of convulsive change. Various forms of systemic global shock could materialize in the coming decades, triggered by the climate crisis, social disruption, economic breakdown, financial collapse, nuclear conflict, or pandemics. The unfolding COVID-19 pandemic stands as a real-time example of an interruption of historic continuity. More hopefully, deep institutional and cultural shifts could rapidly usher in more resilient forms of global civilization. These plausible possibilities challenge scenario studies to spotlight discontinuous futures, an imperative that has not been adequately met. Several factors—for example, gradualist theories of change, scientific reticence, the lure of quantitative tractability, embeddedness in policymaking processes—have rendered mainstream scenario analysis ill-suited to the task. The emphasis on continuity fails to alert decision makers and the public to the risks and opportunities latent in our singular historical moment. A shift to a paradigm that foregrounds discontinuity is long overdue, calling for efforts to broaden the base of persons involved; devote more attention to balancing narrative storytelling and a broader range of quantitative methods; and apply and develop methods to explicitly consider discontinuities in global scenario development.

(2002). Editorial. Integrated Assessment: Vol. 3, No. 2-3, pp. 97-99. doi: 10.1076/iaij.3.2.97.13580

Basking sharks ( Cetorhinus maximus ) are largely solitary, following highly individualized migration routes, yet they exhibit poorly understood aggregation behaviors, ranging from pairs to groups of up to 1,000 individuals. These surface aggregations put sharks at risk of boat strikes and are thought to be driven in part by localized zooplankton availability, though observational evidence suggests that food alone may not fully explain this behavior. Previous modeling approaches have successfully identified long-range basking shark migration trends but have not accurately reproduced behavior at finer spatial scales, and commonly used chlorophyll a proxies for zooplankton have produced inconsistent results when compared with sightings data. This study presents the first individual-based model (IBM) of basking shark aggregation behavior, simulating shark movement around the Inishowen Peninsula, Ireland, from 1982 to 2018. Rather than relying on a phytoplankton proxy, zooplankton was simulated directly to capture fine-scale prey patchiness. Four behavioral submodels were tested and compared with three decades of sightings data from the Irish Basking Shark Group and Irish Whale and Dolphin Group: sharks seeking food only, sharks seeking other sharks only, sharks seeking both food and other sharks, and a random-movement control. The combined food-and-social submodel produced the most realistic results, with lower error and greater qualitative correspondence to observed sightings data than the food-only, social-only, or random submodels, which rarely generated aggregations larger than two individuals. These findings indicate that basking shark aggregations emerge from a combination of environmental and social drivers rather than food availability or chance alone. This model demonstrates the viability of IBMs for simulating basking shark behavior, offers a flexible framework that can incorporate improved environmental and behavioral data as they become available, and provides a foundation for future research into the drivers of basking shark aggregation.

The interconnected relationships among climate change, global economies, and mitigation policies will shape the future of anthropogenic greenhouse gas emissions. Understanding these dynamics is critical for designing optimal policy, but structural limitations in the benefit-cost integrated assessment models used to measure them could lead to underestimates of future temperature increases and their economic impacts. Often these models, including DICE 2023, represent ecological feedbacks through aggregated emulators that preclude mechanistic attribution to individual ecological pathways. We replaced DICE 2023's native DFAIR carbon module with a simple carbon cycle model (SCM), yielding extended configuration DICE-C. DICE-C results in a similar temperature trajectory to DICE 2023, suggesting that the SCM functions similarly to DFAIR. We then augmented this configuration with gradual and abrupt permafrost thaw dynamics, yielding another extended configuration: DICE-CP. DICE-CP results in higher temperatures than DICE 2023 or DICE-C due to permafrost carbon release, a lagged but persistent reinforcing feedback, with DICE-CP maintaining a mean global atmospheric temperature of 1.8°C above pre-industrial by 2300 compared to 0.57°C under DICE 2023. Permafrost carbon release depends on a temperature threshold and a 200-year lagged response to warming, so near-term emissions decisions determine whether this feedback engages decades before its economic consequences. Despite this physically meaningful divergence, cumulative discounted welfare changes under the standard DICE damage function remain small: +0.02 for DICE-C and -0.21 for DICE-CP relative to the DICE 2023 baseline. Replacing the standard quadratic damage coefficient with an updated empirical estimate raises welfare losses by 1.56% for DICE 2023 alone and 1.96% for DICE-CP, exceeding any ecological feedback-driven welfare loss under standard damage assumptions. These results demonstrate that the apparent insensitivity of DICE welfare projections to ecological feedback-driven temperature increases reflects structural choices in the damage function and discount convention.