Effects of different uncertainties on optimal policies

Decisions are usually taken sequentially in climate change policy: every certain amount of years, new agreements and promises are made about greenhouse gas emission reduction etc. In the intersection of decision theory and climate science, sequential decision problems can be formulated and solved, to find optimal sequences of policies and support policy makers with some advice.

There are, however, many uncertainties affecting the outcome of these optimisations. Since these decision problems tend to be very simple in comparison with the complexity of the real world, knowing how different uncertainties affect optimal policies might be more important than what the optimal policy comes out to be. In this work, we explore how some uncertainties affect optimal policies and the possible trajectories associated with those optimal policies. 
  
For this aim we formulate a sequential decision problem with a single "global" policy maker. The decision problem starts with the world state in 2020 and decisions are taken every 10 years till 2100. The policy maker has options regarding CO2 emissions reduction, geoengineering in the form of solar radiation modification and carbon dioxide removal.

We simulate the effects of the decisions on the world’s state with SURFER. SURFER is a simple and fast model featuring a carbon cycle responsive to positive and negative emissions, it allows for geoengineering and accounts for sea level rise from ice sheets (containing tipping points) and from ocean expansion and glacier melt. SURFER has been shown to reproduce the globally averaged behavior of earth system models and models of intermediate complexity from decades to millennia. As opposed to some optimal decision problems in the context of climate change which use integrated assessment models of the climate and the economy, here, with the aim of transparency and simplicity, we consider only a climate model. 

We define a modular and transparent cost function that contains what the policy maker cares about. This function is a linear sum of costs associated with: green transition, geoengineering use and risks, temperature and ocean acidification damages and long term sea level rise commitments.

Using this decision problem we investigate how different kinds of uncertainties affect the sequence of optimal policies obtained and the optimal trajectories associated with those optimal policies. We consider three different kinds of uncertainties: uncertainties in the priorities of the decision maker (i.e., in the reward, cost or utility function), uncertainties on some physical parameters (in particular, climate sensitivity and ice sheet tipping points) and political uncertainty (policymaker’s decisions may not be implemented).