Future Climate of the Bridgers

Ten years ago, I explored future climate analogs for my location in Montana:

When things really warm up, to +9 degrees F (not at all implausible in the long run), 16 of the top 20 analogs are in CO and UT, …

Looking at a lot of these future climate analogs on Google Earth, their common denominator appears to be rattlesnakes. I’m sure they’re all nice places in their own way, but I’m worried about my trees. I’ll continue to hope that my back-of-the-envelope analysis is wrong, but in the meantime I’m going to hedge by managing the forest to prepare for change.

I think there’s a lot more to worry about than trees. Fire, wildlife, orchids, snowpack, water availability, …

Recently I decided to take another look, partly inspired by the Bureau of Reclamation’s publication of downscaled data. This solves some of the bias correction issues I had in 2008. I grabbed the model output (36 runs from CMIP5) and observations for the 1/8 degree gridpoint containing Bridger Bowl:

Then I used Vensim to do a little data processing, converting the daily time series (which are extremely noisy weather) into 10-year moving averages (i.e., climate). Continue reading “Future Climate of the Bridgers”

Does statistics trump physics?

My dissertation was a critique and reconstruction of William Nordhaus’ DICE model for climate-economy policy (plus a look at a few other models). I discovered a lot of issues, for example that having a carbon cycle that didn’t conserve carbon led to a low bias in CO2 projections, especially in high-emissions scenarios.

There was one sector I didn’t critique: the climate itself. That’s because Nordhaus used an established model, from climatologists Schneider & Thompson (1981). It turns out that I missed something important: Nordhaus reestimated the parameters of the model from time series temperature and forcing data.

Nordhaus’ estimation focused on a parameter representing the thermal inertia of the atmosphere/surface ocean system. The resulting value was about 3x higher than Schneider & Thompson’s physically-based parameter choice. That delays the effects of GHG emissions by about 15 years. Since the interest rate in the model is about 5%, that lag substantially diminishes the social cost of carbon and the incentive for mitigation.

DICE Climate Sector
The climate subsystem of the DICE model, implemented in Vensim

So … should an economist’s measurement of a property of the climate, from statistical methods, overrule a climatologist’s parameter choice, based on physics and direct observations of structure at other scales?

I think the answer could be yes, IF the statistics are strong and reconcilable with physics or the physics is weak and irreconcilable with observations. So, was that the case?

Continue reading “Does statistics trump physics?”

DICE

This is a replication of William Nordhaus’ original DICE model, as described in Managing the Global Commons and a 1992 Science article and Cowles Foundation working paper that preceded it.

There are many good things about this model, but also some bad. If you are thinking of using it as a platform for expansion, read my dissertation first.

Units balance.

I provide several versions:

  1. Model with simple heuristics replacing the time-vector decisions in the original; runs in Vensim PLE
  2. Full model, with decisions implemented as vectors of points over time; requires Vensim Pro or DSS
  3. Same as #2, but with VECTOR LOOKUP replaced with VECTOR ELM MAP; supports earlier versions of Pro or DSS
    • DICE-vec-6-elm.mdl (you’ll also want a copy of DICE-vec-6.vpm above, so that you can extract the supporting optimization control files)

Note that there may be minor variances from the published versions, e.g. that transversality coefficients for the state variables (i.e. terminal values of the states for optimization) are not included. The optimizations use fewer time decision points than the original GAMS equivalents. These do not have any significant effect on the outcome.

Workshop on Modularity and Integration of Climate Models

The MIT Center for Collective Intelligence is organizing a workshop at this year’s Conference on Computational Sustainability entitled “Modularity and Integration of Climate Models.” Check out the  Agenda.

Traditionally, computational models designed to simulate climate change and its associated impacts (climate science models, integrated assessment models, and climate economics models) have been developed as standalone entities. This limits possibilities for collaboration between independent researchers focused on sub-­?problems, and is a barrier to more rapid advances in climate modeling science because work is not distributed effectively across the community. The architecture of these models also precludes running a model with modular sub -­? components located on different physical hardware across a network.

In this workshop, we hope to examine the possibility for widespread development of climate model components that may be developed independently and coupled together at runtime in a “plug and play” fashion. Work on climate models and modeling frameworks that are more modular has begun, (e.g. Kim, et al., 2006) and substantial progress has been made in creating open data standards for climate science models, but many challenges remain.

A goal of this workshop is to characterize issues like these more precisely, and to brainstorm about approaches to addressing them. Another desirable outcome of this workshop is the creation of an informal working group that is interested in promoting more modular climate model development.

C-ROADS & climate leadership workshop

In Boston, Oct. 18-20, Climate Interactive and Seed Systems will be running a workshop on C-ROADS and climate leadership.

Attend to develop your capacities in:

  • Systems thinking: Causal loop and stock-flow diagramming.
  • Leadership and learning: Vision, reflective conversation, consensus building.
  • Computer simulation: Using and leading policy-testing with the C-ROADS/C-Learn simulation.
  • Policy savvy:  Attendees will play the “World Climate” exercise.
  • Climate, energy, and sustainability strategy: Reflections and insights from international experts.
  • Business success stories: What’s working in the new low Carbon Economy and implications for you.
  • Build your network of people sharing your aspirations for Climate progress.

Save the date.

EPA gets the bathtub

Eli Rabett has been posting the comment/response section of the EPA endangerment finding. For the most part the comments are a quagmire of tinfoil-hat pseudoscience; I’m astonished that the EPA could find some real scientists who could stomach wading through and debunking it all – an important but thankless job.

Today’s installment tackles the atmospheric half life of CO2:

A common analogy used for CO2 concentrations is water in a bathtub. If the drain and the spigot are both large and perfectly balanced, then the time than any individual water molecule spends in the bathtub is short. But if a cup of water is added to the bathtub, the change in volume in the bathtub will persist even when all the water molecules originally from that cup have flowed out the drain. This is not a perfect analogy: in the case of CO2, there are several linked bathtubs, and the increased pressure of water in one bathtub from an extra cup will actually lead to a small increase in flow through the drain, so eventually the cup of water will be spread throughout the bathtubs leading to a small increase in each, but the point remains that the “residence time” of a molecule of water will be very different from the “adjustment time” of the bathtub as a whole.

Having tested a lot of low-order carbon cycle models, including I think all possible linear variants up to 3rd order, I agree with EPA – anyone who claims that the effective half life or time constant of CO2 uptake is 10 or 20 or even 50 years is bonkers.

States' role in climate policy

Jack Dirmann passed along an interesting paper arguing for a bigger role for states in setting federal climate policy.

This article explains why states and localities need to be full partners in a national climate change effort based on federal legislation or the existing Clean Air Act. A large share of reductions with the lowest cost and the greatest co-benefits (e.g., job creation, technology development, reduction of other pollutants) are in areas that a federal cap-and-trade program or other purely federal measures will not easily reach. These are also areas where the states have traditionally exercised their powers – including land use, building construction, transportation, and recycling. The economic recovery and expansion will require direct state and local management of climate and energy actions to reach full potential and efficiency.

This article also describes in detail a proposed state climate action planning process that would help make the states full partners. This state planning process – based on a proven template from actions taken by many states – provides an opportunity to achieve cheaper, faster, and greater emissions reductions than federal legislation or regulation alone would achieve. It would also realize macroeconomic benefits and non-economic co-benefits, and would mean that the national program is more economically and environmentally sustainable.

Continue reading “States' role in climate policy”

Climate Science, Climate Policy and Montana

Last night I gave a climate talk at the Museum of the Rockies here in Bozeman, organized by Cherilyn DeVries and sponsored by United Methodist. It was a lot of fun – we had a terrific discussion at the end, and the museum’s monster projector was addictive for running C-LEARN live. Thanks to everyone who helped to make it happen. My next challenge is to do this for young kids.

MT Climate Schematic

My slides are here as a PowerPoint show: Climate Science, Climate Policy & Montana (better because it includes some animated builds) or PDF: Climate Science, Climate Policy & Montana (PDF)

Some related resources:

Climate Interactive & the online C-LEARN model

Montana Climate Change Advisory Committee

Montana Climate Office

Montana emissions inventory & forecast visualization (click through the graphic):

Cb009aee-64f1-11df-8f87-000255111976 Blog_this_caption
Related posts:

Flying South

Montana’s Climate Future

Kerry-Lieberman "American Power Act" leaked

I think it’s a second-best policy, but perhaps the most we can hope for, and better than nothing.

Climate Progress has a first analysis and links to the leaked draft legislation outline and short summary of the Kerry-Lieberman American Power Act. [Update: there’s now a nice summary table.] For me, the bottom line is, what are the emissions and price trajectories, what emissions are covered, and where does the money go?

The target is 95.25% of 2005 by 2013, 83% by 2020, 58% by 2030, and 17% by 2050, with six Kyoto gases covered. Entities over 25 MTCO2eq/year are covered. Sector coverage is unclear; the summary refers to “the three major emitting sectors, power plants, heavy industry, and transportation” which is actually a rather incomplete list. Presumably the implication is that a lot of residential, commercial, and manufacturing emissions get picked up upstream, but the mechanics aren’t clear.

The target looks like this [Update: ignoring minor gases]:

Kerry Lieberman Target

This is not much different from ACES or CLEAR, and like them it’s backwards. Emissions reductions are back-loaded. The rate of reduction (green dots) from 2030 to 2050, 6.1%/year, is hardly plausible without massive retrofit or abandonment of existing capital (or negative economic growth). Given that the easiest reductions are likely to be the first, not the last, more aggressive action should be happening up front. (Actually there are a multitude of reasons for front-loading reductions as much as reasonable price stability allows).

There’s also a price collar:

Kerry Lieberman Price

These mechanisms provide a predictable price corridor, with the expected prices of the EPA Waxman-Markey analysis (dashed green) running right up the middle. The silly strategic reserve is gone. Still, I think this arrangement is backwards, in a different sense from the target. The right way to manage the uncertainty in the long run emissions trajectory needed to stabilize climate without triggering short run economic dislocation is with a mechanism that yields stable prices over the short to medium term, while providing for adaptive adjustment of the long term price trajectory to achieve emissions stability. A cap and trade with no safety valve is essentially the opposite of that: short run volatility with long run rigidity, and therefore a poor choice. The price collar bounds the short term volatility to 2:1 (early) to 4:1 (late) price movements, but it doesn’t do anything to provide for adaptation of the emissions target or price collar if emissions reductions turn out to be unexpectedly hard, easy, important, etc. It’s likely that the target and collar will be regarded as property rights and hard to change later in the game.

I think we should expect the unexpected. My personal guess is that the EPA allowance price estimates are way too low. In that case, we’ll find ourselves stuck on the price ceiling, with targets unmet. 83% reductions in emissions at an emissions price corresponding with under $1/gallon for fuel just strike me as unlikely, unless we’re very lucky technologically. My preference would be an adaptive carbon price, starting at a substantially higher level (high enough to prevent investment in new carbon intensive capital, but not so high initially as to strand those assets – maybe $50/TonCO2). By default, the price should rise at some modest rate, with an explicit adjustment process taking place at longish intervals so that new information can be incorporated. Essentially the goal is to implement feedback control that stabilizes long term climate without short term volatility (as here or here and here).

Some other gut reactions:

Good:

  • Clean energy R&D funding.
  • Allowance distribution by auction.
  • Border adjustments (I can only find these in the summary, not the draft outline).

Bad:

  • More subsidies, guarantees and other support for nuclear power plants. Why not let the first round play out first? Is this really a good use of resources or a level playing field?
  • Subsidized CCS deployment. There are good reasons for subsidizing R&D, but deployment should be primarily motivated by the economic incentive of the emissions price.
  • Other deployment incentives. Let the price do the work!
  • Rebates through utilities. There’s good evidence that total bills are more salient to consumers than marginal costs, so this at least partially defeats the price signal. At least it’s temporary (though transient measures have a way of becoming entitlements).

Indifferent:

  • Preemption of state cap & trade schemes. Sorry, RGGI, AB32, and WCI. This probably has to happen.
  • Green jobs claims. In the long run, employment is controlled by a bunch of negative feedback loops, so it’s not likely to change a lot. The current effects of the housing bust/financial crisis and eventual effects of big twin deficits are likely to overwhelm any climate policy signal. The real issue is how to create wealth without borrowing it from the future (e.g., by filling up the atmospheric bathtub with GHGs) and sustaining vulnerability to oil shocks, and on that score this is a good move.
  • State preemption of offshore oil leasing within 75 miles of its shoreline. Is this anything more than an illusion of protection?
  • Banking, borrowing and offsets allowed.

Unclear:

  • Performance standards for coal plants.
  • Transportation efficiency measures.
  • Industry rebates to prevent leakage (does this defeat the price signal?).