Climate War Game – A Free Lunch

I’m at CNAS’ climate war game listening to Diana Farrell from the McKinsey Global Institute. So far my takeaway from the exercise has been rather gloomy; Farrell presented a more hopeful view, informed by McKinsey’s construction of supply curves for carbon emissions reductions. I found her opening point particulaly critical: don’t wait for energy supply-side silver bullets to save us, when there are demand-side opportunities now.

McKinsey supply curve for global emissions reductions
Per-Anders Enkvist, Tomas Nauclér, and Jens Riese, What Countries Can Do About Cutting Carbn Emissions, McKinsey Quarterly, April 2008

McKinsey’s supply curves (and others from bottom-up modeling efforts) indicate large reductions available at low or negative cost. The idea of cheap negawatts has been around for a long time. Hard line economists have also been declaring the idea dead for a long time (see my old bibliography of the top-down/bottom-up debate).

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Climate War Game – First Salvo

Sunday evening I attended the kickoff of a CNAS war game, Clout & Climate Change, examining the intersection of climate policy and national security. I’m on the science advisory team, along with Drew Jones and Lori Siegel from the Sustainability Institute. We hope to provide real-time, model-based decision support. The exercise brings together a rather extraordinary talent pool, so it’s a daunting task.

Peter Schwartz delivered an opening talk on scenario planning; he made a compelling case for robust thinking. He also set a tone that has haunted much of the subsequent proceedings: there are striking technological options for dealing with climate, but progress is difficult because people are caught up in their individual worlds (they want more stuff). As a result, he expects that lots of adaptation will be needed. Negotiations since have borne out his framing: aggressive targets (-80% by 2050) appear elusive in the face of the perceived need for continued economic growth to keep US and EU workers happy, avoid regime change in China, and provide for development in the poorest regions.

Paty Romero-Lankao asked the key question of the evening. To paraphrase crudely, she wondered whether a focus on technology and adaptation missed the point; that one must also address the lifestyle issues that are the underlying driver of growth. Amen. Lifestyle is a tougher nut to crack than technology, but to borrow Peter’s phrase guiding scenario planning, it’s important to avoid thinking, “that can’t happen.”

US Regional Climate Initiatives – Model Roll Call

The Pew Climate Center has a roster of international, US federal, and US state & regional climate initiatives. Wikipedia has a list of climate initiatives. The EPA maintains a database of state and regional initiatives, which they’ve summarized on cool maps. The Center for Climate Strategies also has a map of links. All of these give some idea as to what regions are doing, but not always why. I’m more interested in the why, so this post takes a look at the models used in the analyses that back up various proposals.

EPA State Climate Initiatives Map

In a perfect world, the why would start with analysis targeted at identifying options and tradeoffs for society. That analysis would inevitably involve models, due to the complexity of the problem. Then it would fall to politics to determine the what, by choosing among conflicting stakeholder values and benefits, subject to constraints identified by analysis. In practice, the process seems to run backwards: some idea about what to do bubbles up in the political sphere, which then mandates that various agencies implement something, subject to constraints from enabling legislation and other legacies that do not necessarily facilitate the best outcome. As a result, analysis and modeling jumps right to a detailed design phase, without pausing to consider the big picture from the top down. This tendency is somewhat reinforced by the fact that most models available to support analysis are fairly detailed and tactical; that makes them too narrow or too cumbersome to redirect at the broadest questions facing society. There isn’t necessarily anything wrong with the models; they just aren’t suited to the task at hand.

My fear is that the analysis of GHG initiatives will ultimately prove overconstrained and underpowered, and that as a result implementation will ultimately crumble when called upon to make real changes (like California’s ambitious executive order targeting 2050 emissions 80% below 1990 levels). California’s electric power market restructuring debacle jumps to mind. I think underpowered analysis is partly a function of history. Other programs, like emissions markets for SOx, energy efficiency programs, and local regulation of criteria air pollutants have all worked OK in the past. However, these activities have all been marginal, in the sense that they affect only a small fraction of energy costs and a tinier fraction of GDP. Thus they had limited potential to create noticeable unwanted side effects that might lead to damaging economic ripple effects or the undoing of the policy. Given that, it was feasible to proceed by cautious experimentation. Greenhouse gas regulation, if it is to meet ambitious goals, will not be marginal; it will be pervasive and obvious. Analysis budgets of a few million dollars (much less in most regions) seem out of proportion with the multibillion $/year scale of the problem.

One result of the omission of a true top-down design process is that there has been no serious comparison of proposed emissions trading schemes with carbon taxes, though there are many strong substantive arguments in favor of the latter. In California, for example, the CPUC Interim Opinion on Greenhouse Gas Regulatory Strategies states, “We did not seriously consider the carbon tax option in the course of this proceeding, due to the fact that, if such a policy were implemented, it would most likely be imposed on the economy as a whole by ARB.” It’s hard for CARB to consider a tax, because legislation does not authorize it. It’s hard for legislators to enable a tax, because a supermajority is required and it’s generally considered poor form to say the word “tax” out loud. Thus, for better or for worse, a major option is foreclosed at the outset.

With that little rant aside, here’s a survey of some of the modeling activity I’m familiar with:

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Exhibit A – the Social Cost of Carbon

I recently discovered a cool set of tools from MIT’s Simile project. My favorites are Timeline and Exhibit, which provide a fairly easy way to create web sites where visitors can interact with data. As a test, I built an Exhibit containing Richard Tol’s survey of assessments of the social cost of carbon (SCC):

Social Cost of Carbon Exhibit

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SRES – We've got a bigger problem now

Recently Pielke, Wigley and Green discussed the implications of autonomous energy efficiency improvements (AEEI) in IPCC scenarios, provoking many replies. Some found the hubbub around the issue surprising, because the assumptions concerned were well known, at least to modelers. I was among the surprised, but sometimes the obvious needs to be restated loud and clear. I believe that there are several bigger elephants in the room that deserve such treatment. AEEI is important, as are other hotly debated SRES choices like PPP vs. MEX, but at the end of the day, these are just parameter choices. In complex systems parameter uncertainty generally plays second fiddle to structural uncertainty. Integrated assessment models (IAMs) as a group frequently employ similar methods, e.g., dynamic general equilibrium, and leave crucial structural assumptions untested. I find it strange that the hottest debates surround biogeophysical models, which are actually much better grounded in physical principles, when socio-economic modeling is so uncertain.

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Better Get a Bucket

Nature News and Climate Feedback report that cooling of sea surface temperatures ca. 1945 is an artifact of changes in measurement technology. ClimateAudit claims priority. Lucia comments.

Will this – like the satellite temperature trend – be another case of model-data discrepancies resolved in favor of the models?

Update: Prometheus wonders if this changes IPCC conclusions.

Business & Climate – What to Wish For?

One observation from my recent experience with climate policy in California is that businesses – even energy intensive ones – are uncertain how to engage in the public debate. Climate policy is a messy space with many competing options, and it’s hard to know what to wish for. With that in mind, here’s a quick survey of what various business groups are saying.

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God is my coauthor

DeSmogBlog documents scientists’ outrage at inclusion on Dennis Avery’s list of 500 Scientists with Documented Doubts of Man-Made Global Warming Scares. Amusingly, the scientists concerned, a few of whom are deceased, are listed as “Co-Authors”. I’m going to put this new “open coauthoring” concept to work – I’m already working on abstracts. First, I think I’ll lower my Erdős number – Paul, dude, you can be my second. Next, I think I’ll team up with Einstein and Bohr to finish up quantum gravity.