  Climate models are critical tools for developing strategies to manage the
risks posed by sea-level rise to coastal communities. While these models are
necessary for understanding climate risks, there is a level of uncertainty
inherent in each parameter in the models. This model parametric uncertainty
leads to uncertainty in future climate risks. Consequently, there is a need to
understand how those parameter uncertainties impact our assessment of future
climate risks and the efficacy of strategies to manage them. Here, we use
random forests to examine the parametric drivers of future climate risk and how
the relative importances of those drivers change over time. We find that the
equilibrium climate sensitivity and a factor that scales the effect of aerosols
on radiative forcing are consistently the most important climate model
parametric uncertainties throughout the 2020 to 2150 interval for both low and
high radiative forcing scenarios. The near-term hazards of high-end sea-level
rise are driven primarily by thermal expansion, while the longer-term hazards
are associated with mass loss from the Antarctic and Greenland ice sheets. Our
results highlight the practical importance of considering time-evolving
parametric uncertainties when developing strategies to manage future climate
risks.
