To confront the climate crisis, we need to hedge our bets against the risk of climate change. We must be willing to spend some money now in order reap a larger benefit that will take many decades to deliver. This is similar to the philosophical concept of Pascal’s Wager, where one bets a finite resource for a potentially infinite reward. But estimating how much we should spend now is not easy; attempts to estimate this amount – the “social cost of carbon” – produce a wide range of numbers. We may need to accept that there is going to be radical uncertainty in any numerical estimate. Nevertheless, we can use climate models to quantify the risk of climate change as best we can, while taking into account the different types of uncertainties. Often, risk assessment requires numerical probabilities, but these are not always available for uncertainties associated with climate prediction.

Future projections are uncertain, for multiple reasons. Limits to scientific understanding of natural variability, structural and parametric uncertainty in scientific modeling, climate sensitivity, bias correction and downscaling all play a role. The uncertainty due to human choices that will determine emissions of heat-trapping gases becomes increasingly important over time, to the point where it dominates the uncertainty in many aspects of global and regional change by the end of century. Quantifying how a given system will respond to a changing climate adds yet another layer of uncertainty that can be prohibitively large in systems that are complex and/or not well understood. Understanding the source of these uncertainties and how they can be addressed when applying downscaled climate projections to assess future impacts is essential to quantifying the range of future change and resulting impacts on human and natural systems