Global climate goals require a transition to a deeply decarbonized
energy system. Meeting the objectives of the Paris Agreement through
countries’ Nationally Determined Contributions and Long-Term Strategies
represents a complex problem with consequences across multiple systems
shrouded by deep uncertainty. Robust, large-ensemble methods and
analyses mapping a wide range of possible future states of the world are
needed to help policymakers design effective strategies to meet
emissions reduction goals. This study contributes a scenario discovery
analysis applied to a large ensemble of 5,760 model realizations
generated using the Global Change Analysis Model. Eleven energy-related
uncertainties are systematically varied, representing national
mitigation pledges, institutional factors, and techno-economic
parameters, among others. The resulting ensemble maps how uncertainties
impact common energy system metrics used to characterize national and
global pathways toward deep decarbonization. Results show globally
consistent but regionally variable energy transitions as measured by
multiple metrics, including electricity costs and stranded assets.
Larger economies and developing regions experience more severe economic
outcomes across a broad sampling of uncertainty. The scale of
CO removal globally determines how much the energy
system can continue to emit, but the relative role of different
CO removal options in meeting decarbonization goals
varies across regions. Previous studies characterizing uncertainty have
typically focused on a few scenarios, and other large-ensemble work has
not (to our knowledge) combined this framework with national emissions
pledges or institutional factors. Our results underscore the value of
large-ensemble scenario discovery for decision support as countries
begin to design strategies to meet their goals.