Tag: Climate

Sea Level Rise Models – IV

So far, I’ve established that the qualitative results of Rahmstorf (R) and Grinsted (G) can be reproduced. Exact replication has been elusive, but the list of loose ends (unresolved differences in data and so forth) is long enough that I’m not concerned that R and G made fatal errors. However, I haven’t made much progress against the other items on my original list of questions:

  • Is the Grinsted et al. argument from first principles, that the current sea level response is dominated by short time constants, reasonable?
  • Is Rahmstorf right to assert that Grinsted et al.’s determination of the sea level rise time constant is shaky?
  • What happens if you impose the long-horizon paleo constraint to equilibrium sea level rise in Rahmstorf’s RC figure on the Grinsted et al. model?

At this point I’ll reveal my working hypotheses (untested so far):

  • I agree with G that there are good reasons to think that the sea level response occurs over multiple time scales, and therefore that one could make a good argument for a substantial short-time-constant component in the current transient.
  • I agree with R that the estimation of long time constants from comparatively short data series is almost certainly shaky.
  • I suspect that R’s paleo constraint could be imposed without a significant degradation of the model fit (an apparent contradiction of G’s results).
  • In the end, I doubt the data will resolve the argument, and we’ll be left with the conclusion that R and G agree on: that the IPCC WGI sea level rise projection is an underestimate.

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Sea Level Rise Models – III

Starting from the Rahmstorf (R) parameterization (tested, but not exhaustively), let’s turn to Grinsted et al (G).

First, I’ve made a few changes to the model and supporting spreadsheet. The previous version ran with a small time step, because some of the tide data was monthly (or less). That wasted clock cycles and complicated computation of residual autocorrelations and the like. In this version, I binned the data into an annual window and shifted the time axes so that the model will use the appropriate end-of-year points (when Vensim has data with a finer time step than the model, it grabs the data point nearest each time step for comparison with model variables). I also retuned the mean adjustments to the sea level series. I didn’t change the temperature series, but made it easier to use pure-Moberg (as G did). Those changes necessitate a slight change to the R calibration, so I changed the default parameters to reflect that.

Now it should be possible to plug in G parameters, from Table 1 in the paper. First, using Moberg: a = 1290 (note that G uses meters while I’m using mm), tau = 208, b = 770 (corresponding with T0=-0.59), initial sea level = -2. The final time for the simulation is set to 1979, and only Moberg temperature data are used. The setup for this is in change files, GrinstedMoberg.cin and MobergOnly.cin.

Moberg, Grinsted parameters

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Sea Level Rise Models – II

Picking up where I left off, with model and data assembled, the next step is to calibrate, to see whether the Rahmstorf (R) and Grinsted (G) results can be replicated. I’ll do that the easy way, and the right way.

An easy first step is to try the R approach, assuming that the time constant tau is long and that the rate of sea level rise is proportional to temperature (or the delta against some preindustrial equilibrium).

Rahmstorf estimated the temperature-sea level rise relationship by regressing a smoothed rate of sea level rise against temperature, and found a slope of 3.4 mm/yr/C.

Rahmstorf figure 2

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Sea Level Rise Models – I

A recent post by Stefan Rahmstorf at RealClimate discusses a new paper on sea level projections by Grinsted, Moore and Jevrejeva. This paper comes at an interesting time, because we’ve just been discussing sea level projections in the context of our ongoing science review of the C-ROADS model. In C-ROADS, we used Rahmstorf’s earlier semi-empirical model, which yields higher sea level rise than AR4 WG1 (the latter leaves out ice sheet dynamics). To get a better handle on the two papers, I compared a replication of the Rahmstorf model (from John Sterman, implemented in C-ROADS) with an extension to capture Grinsted et al. This post (in a few parts) serves as both an assessment of the models and a bit of a tutorial on data analysis with Vensim.

My primary goal here is to develop an opinion on four questions:

  • Can the conclusions be rejected, given the data?
  • Is the Grinsted et al. argument from first principles, that the current sea level response is dominated by short time constants, reasonable?
  • Is Rahmstorf right to assert that Grinsted et al.’s determination of the sea level rise time constant is shaky?
  • What happens if you impose the long-horizon paleo constraint to equilibrium sea level rise in Rahmstorf’s RC figure on the Grinsted et al. model?

Paleo constraints on equilibrium sea level

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Four Legs and a Tail

An effective climate policy needs prices, technology, institutional rules, and preferences.

I’m continuously irked by calls for R&D to save us from climate change. Yes, we need it very badly, but it’s no panacea. Without other signals, like a price on carbon, technology isn’t going to do a lot. It’s a one-legged dog. True, we might get lucky with some magic bullet, but I’m not willing to count on that. An effective climate policy needs four legs:

  1. Prices
  2. Technology (the landscape of possibilities on which we make decisions)
  3. Institutional rules and procedures
  4. Preferences, operating within social networks

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News Flash: There Is No "Environmental Certainty"

The principal benefit cited for cap & trade is “environmental certainty,” meaning that “a cap-and-trade system, coupled with adequate enforcement, assures that environmental goals actually would be achieved by a certain date.” Environmental certainty is a bit of a misnomer. I think of environmental certainty as ensuring a reasonable chance of avoiding serious climate impacts. What people mean when they’re talking about cap & trade is really “emissions certainty.” Unfortunately, emissions certainty doesn’t provide climate certainty:

Emissions trajectories yielding 2C temperature change

Even if we could determine a “safe” level of interference in the climate system, the sensitivity of global mean temperature to increasing atmospheric CO2 is known perhaps only to a factor of three or less. Here we show how a factor of three uncertainty in climate sensitivity introduces even greater uncertainty in allowable increases in atmospheric CO2 CO2 emissions. (Caldeira, Jain & Hoffert, Science)

The uncertainty about climate sensitivity (not to mention carbon cycle feedbacks and other tipping point phenomena) makes the emissions trajectory we need highly uncertain. That trajectory is also subject to other big uncertainties – technology, growth convergence, peak oil, etc. Together, those features make it silly to expend a lot of effort on detailed plans for 2050. We don’t need a ballistic trajectory; we need a guidance system. I’d like to see us agree to a price on GHGs everywhere now, along with a decision rule for adapting that price over time until we’re on a downward emissions trajectory. Then move on to the other legs of the stool: ensuring equitable opportunities for development, changing lifestyle, tackling institutional barriers to change, and investing in technology.

Unfortunately, cap & trade seems ill-suited to adaptive control. Emissions commitments and allowance allocations are set in multi-year intervals, announced in advance, with long lead times for design. Financial markets and industry players want that certainty, but the delay limits responsiveness. Decision makers don’t set the commitment by strictly environmental standards; they also ask themselves what allocation will result in an “acceptable” price. They’re risk averse, so they choose an allocation that’s very likely to lead to an acceptable price. That means that, more often than not, the system will be overallocated. On balance, their conservatism is probably a good thing; otherwise the whole system could unravel from a negative public reaction to volatile prices. Ironically, safety valves – one policy that could make cap & trade more robust, and thus enable better mean performance – are often opposed because they reduce emissions certainty.

Cap & Trade – How Soon?

I’m a strong advocate for a price on carbon, but I have serious reservations about cap & trade. I’m thrilled that climate policy is finally getting off the dime, but I wish enthusiasm were focused on a carbon tax instead. Consider this:

Jurisdiction Instrument Started Operational Status
EU Cap & Trade 2003 2005 Phase 1 overallocated & underpriced; still wrangling over loopholes for subsequent phases
British Columbia Tax Feb 2008 July 2008 Too low to do much yet, but working
Sweden Tax 1991 1991 Running, at $150/TonCO2; emissions down
RGGI Cap & Trade 2003 2008 Overallocated
Norway Tax 1990 1991 Works; not enough to lower emissions substantially
California Cap & Trade (part of AB32) 2007 Earliest 2012 Punted
WCI Cap & Trade 2007 Earliest 2012 Draft design

The pattern that stands out to me is timing – cap & trade systems are slow to get out of the gate compared to carbon taxes. They entail huge design challenges, which often restrict sectoral coverage. Price uncertainty makes it difficult to work out the implications of allowance allocation (unless you go to pure auction, in which case you lose the benefit of transitional grandfathering as a mechanism to buy carbon-intensive industry participation). I think we’ll be lucky to see an operational cap & trade system in the US, with meaningful prices and broad coverage, by the end of the first Obama administration.

Next Generation Climate Policy Models

Today I’m presenting a talk at an ECF workshop, Towards the next generation of climate policy models. The workshop’s in Berlin, but I’m staying in Montana, so my carbon footprint is minimal for this one (just wait until next month …). My slides are here: Towards Next Generation Climate Policy Models.

I created a set of links to supporting materials on del.icio.us.

Update Workshop materials are now on a web site here.