by Judith Curry
So, what do you think climate science and policy would look like if the IPCC worked for the World Bank, instead of the UNFCCC?
World Bank Report
The World Bank has a new white paper entitled: Investment decision making under deep uncertainty — application to climate change. From the Summary:
While agreeing on the choice of an optimal investment decision is already difficult for any diverse group of actors, priorities, and world views, the presence of deep uncertainties further challenges the decision-making framework by questioning the robustness of all purportedly optimal solutions. This paper summarizes the additional uncertainty that is created by climate change, and reviews the tools that are available to project climate change (including downscaling techniques) and to assess and quantify the corresponding uncertainty. Assuming that climate change and other deep uncertainties cannot be eliminated over the short term (and probably even over the longer term), it then summarizes existing decision-making methodologies that are able to deal with climate-related uncertainty, namely cost-benefit analysis under uncertainty, cost-benefit analysis with real options, robust decision making, and climate informed decision analysis. It also provides examples of applications of these methodologies, highlighting their pros and cons and their domain of applicability. The paper concludes that it is impossible to define the “best” solution or to prescribe any particular methodology in general. Instead, a menu of methodologies is required, together with some indications on which strategies are most appropriate in which contexts. This analysis is based on a set of interviews with decision-makers, in particular World Bank project leaders, and on a literature review on decision-making under uncertainty. It aims at helping decision-makers identify which method is more appropriate in a given context, as a function of the project’s lifetime, cost, and vulnerability.
Michael Levi
Michael Levi lays out the challenge at Energy, Security and Climate in a post entitled How can we cope with deep climate uncertainty?
The basic problem is that climate policy faces at least two sets of big unknowns. The first concerns the climate itself: How much damage will a given accumulation of greenhouse gases cause? Will damages rise steadily with increasing concentrations – or are there thresholds beyond which impacts will rapidly multiply? In the presence of such unknowns, a push for robustness tends to mean a push for deeper emissions cuts, even if those might turn out to cost more than actual climate sensitivity ultimately justifies.
The second set of unknowns surrounds the relationship between public policy and the energy system. We have little idea of which policies would actually succeed in delivering particular emissions reductions – and no, “capping” emissions doesn’t guarantee any particular outcome.
Combining this source of uncertainty with the first one can quickly run you into trouble. Unknowns at the extremely ugly end of possible climate outcomes tend to drive policy toward big bets on large emissions reductions. But these sorts of bets, which take us the furthest away from past experience, are vulnerable to the biggest unknowns on the policy side. It’s difficult to completely escape this bind.
Focusing on particularly disruptive policies because they’re the only ones that have a chance to be “strong enough” to deal with an unexpectedly sensitive climate also raises the odds of political failure, and hence also increases the chances of ultimately being stuck with the status quo. Both of these tendencies tend to shift the distribution of likely climate outcomes toward the extremes: either things end up a lot better than they’re currently on course to turn out, or our prospects don’ improve much at.
David Roberts
David Roberts at Grist has an excellent article on the World Bank Report: In a climate crazed world, how can we plan for the future? Excerpts:
The politicians and other leaders who make (or influence) such decisions do not like deep uncertainty. So they ask analysts for cost-benefit analysis (CBA). CBA is useful in some circumstances, particularly where there are bounded time spans and known risks. But remember, there’s a difference between risk (statistically quantifiable) and uncertainty (not). It is the difference, if you will, between Rumsfeld’s “known unknowns” and his “unknown unknowns.”
“Results from the CBA,” says the World Bank, are “extremely dependent on parameters on which there is no scientific agreement (e.g., the impact of climate change on hurricanes) or no consensus (e.g., the discount rate).” It’s still possible to construct models and get answers, but the danger becomes higher and higher of getting the wrong answer, i.e., optimizing for the wrong thing.
Lesson: If you spend a bunch of money optimizing for the wrong thing, it can be worse than doing nothing.
Now, whenever I criticize cost-benefit analysis, someone will ask, Well, what’s the alternative? What else can you do but weigh costs and benefits? How else would you make decisions?
Shift the focus from optimality to robustness.
The optimal decision is the one that achieves the best cost-benefit ratio in a given set of conditions. A robust decision can be expected to hold up, and perform reasonably well, under a wide variety of possible conditions. To make the optimal decision, you must be able to quantify risks. When there is uncertainty rather than risk — “multiple possible future worlds without known relative probabilities” — one is better off with robust decisions.
The optimal decision aims for efficiency; the robust decision aims for resilience. A resilient solution may not be — probably won’t be — the one best suited for whatever circumstances do end up coming to pass. But it is, from the present-day perspective, the one most broadly suited to the widest array of possible futures.
When it comes to climate change, most economic models are premised on CBA — the search for efficiency. The World Bankers suggest an alternative, based on robustness, and yes, it involves yet another acronym: CIDA, or Climate Informed Decision Analysis, also known as “decision scaling.”
“As a process committed to acceptance of deep uncertainties,” they say, “CIDA does not attempt to reduce uncertainties or make predictions, but rather determine which decision options are robust to a variety of plausible futures.”
The main thing to understand is that the first step is assembling stakeholders and mapping out their concerns — where they are vulnerable, what they can tolerate, what they want to avoid, what they aspire to. That’s your vulnerability analysis and it is entirely separate from the vagaries of climate models. It gives you a set of decisions to analyze.
Then you figure out which decisions are vulnerable to which climate outcomes. Once you have a “map of which decision options are optimal under which groups of climate conditions,” then, and only then, you use statistical techniques (and “expert judgment”) to try to figure out how likely those climate outcomes are. That last step is as much an art as a science.
This gives you, not a single, optimal decision, but a kind of decision matrix that reflects stakeholder concerns and reveals which specific dangers face which specific decisions. It avoids the hubris of pretending to know exactly what will happen in the future. And it’s more transparent and democratic.
JC comment: IMO the World Bank report is a breakthrough in climate policy, given their influence (and $$) in the policy world. Others (including myself) have been talking about and embracing these ideas in an academic context, e.g. see these two recent posts at Climate Etc.:
- Alternative approaches to assessing climate risks
- My recent presentation at the Royal Society (.ppt; audio recording)
It is particularly interesting to see David Roberts embrace these ideas; David is the founder of the ‘Climate Hawks’ movement.
So, back to my original question: What do you think climate science and policy would look like if the IPCC worked for the World Bank, instead of the UNFCCC? My RS presentation on climate models provides my thoughts on what this would look like, with a greater emphasis on the historical and paleo data record and climate models used to develop and assess likelihood of a much broader range of future climate scenarios.
Update: here is the latest from the UN climate deliberations