Greg Craven's viral climate ‘decision grid’ video

This got mentioned in early 2014 at Planet3.0. To be fair to mt, he wasn’t really pushing the video itself, just using it to illustrate his point (which I think is uncertainty-is-not-your-friend; I agree with that), though he did call it “excellent”. But since, as I said in the comments there I don’t think its great video; I think its terrible, I wasn’t desperately happy. But, I shrugged and turned away. Now I see that Dana Nuccitelli is giving it space in the Graun, (and DA is linking to it, though possibly only because he likes the headline and sub), so I’ll repeat myself more publically. What I said, in full, was:

I don’t think its great video; I think its terrible.

Minorly, A / True doesn’t have a happy face – it still has an appalling financial meltdown (in his scenario).

But more importantly, he makes no attempt to assess the probability of B / True. So he’s trying to short-circuit, or evade, the cost-benefit analysis that needs to be done.

That wasn’t the question you asked in this post, of course.

[You need to know that A is “we took action on GW”, B is “we didn’t”. True is “GW turns out to be real”, False is “It was all a dream”.]

mt answers starting with “I think there is a point to what you say”, which is enough for me to excuse him, but not DN. Note that the assertion of the video (see around 1 min in) is that the argument contained therein means “we don’t need to know whether its true or not”.

Note that there’s a a trick: in A / Yes, he takes the extreme, for illustration, and gets global economic meltdown. In B / False, he says “since we granted the extreme in A / Yes, we should grant the extreme here too”. But they aren’t connected, except in both being very simplistic.

At 5:15 he asserts that if you add in the subtleties and intermediate cases, his conclusion (to come) still holds.

And that conclusion is that B / True (“GW is real and we took no action”) is so bad, that the best thing to do is avoid any possibility of “being in that column”. My answer to that is above. At P3, Walter Manny said Craven’s exercise is simply Pascal’s Wager and I don’t think he got a good answer.

wager To make the comparison clearer, I’ve scribbled on a still from the video. Wittily, that makes GW “God”. We can see its not quite Pascal’s wager. Conventionally, in PW, you assign a small positive to “no God, and no Belief” and a small negative to “no God, Belief” to reflect the life of sin that good Christians can’t enjoy; in this case, “no GW, Belief-aka-action” has substantial costs, but they are assumed small compared to the “Hell” square. Similarly, in PW the “God, Belief” square is infinitely positive, whereas here its actually worse than “no God, no belief” which is the best possible outcome, though we’re not supposed to believe in it. Indeed the comparison to PW is only that “God-aka-GW, no-belief-aka-no-action” is effectively infinitely bad in both.

The useful point about comparing it to PW, though, is that no-one believes in God because of it. So if the comparison is good (I think it is) you can assert “no-one will believe in action on GW just because of this grid”.

The good atheist assigns zero probability to “God exists”, and so zero probability to Hell, so that part becomes irrelevant in the calculations. The experienced denialist assigns zero probability to “GW will be catastrophic”, and so ignores that bit. I’m not an experienced denialist, so I’m not ignoring it, but I am downplaying it. Why? Mostly because i think we want to do something more sensible, which is to attempt a reason-based cost-benefit type analysis, which this isn’t. If forced to go further, I’d say that current best-guess is that GW won’t be an utter catastrophe; indeed, in economic terms (say, those of Stern which I think is on the high side) its perhaps (from memory) 10-20% of global GDP by 2100. To make it catastrophic – somewhere close to the infinity that is implied – you need to try much harder than Stern, and I think that’s unlikely (I also think that if starting looking that way, we’d probably have time to go into emergency mode (yes, despite the inertia of the pol/econ system, and our infrastructure base); a time-dependent element is necessary in the analysis, but lacking here. He makes a small comment in this direction at 7:20 – that we’ve recently learnt that the disaster could happen quickly, within a decade, so it affects us not our grandchildren; I don’t know what he means by that).

In case you’re wondering, no, I’m not arguing that the failure of the argument in the video means we should do nothing about GW. I’m only arguing that the failure of the argument in the video means it should have no (logical) consequences.

To paraphrase Einstein, you should reduce a problem to the simplest possible, but no simpler. This square reduces the problem past the minimum degree of simplicity that is useful.

As I said near the start, mt’s main argument around this point is uncertainty-is-not-your-friend; and I agree with that. There’s an essentially-sane take on that at The Conversation: Uncertainty isn’t cause for climate complacency – quite the opposite. But then again, it doesn’t reach the same conclusions as Greg Craven.

Good grief, you’re behind the times

It turns out that the video dates from 2007, duh. And Greg Craven wrote a book about the same idea in 2009. Which I haven’t read, but judging from reviews (treehugger, Simon Singh, Grist) it says much the same as the video. mt has a review at P3 that focusses on a completely different aspect of the book – how to know, to which the answer for most people is “trust”, which is correct, though its important to know how to know who to trust. But at that time, he doesn’t address what I (and the other reviewers) are taking as the book’s central argument.

There’s a wiki page. He even had a website about it, now apparently defunct. But via the wayback machine I can read which points me at a response by “climate skeptic” (the wiki page used to ref this, but it got rm’d as non-RS).

I rally can’t endorse “climate skeptic” in general, because he links with approval to himself at coyote blog to show that feedbacks are probably negative, which says nothing useful but points to himself again. At that points he actually starts to say things, but they’re wrong (in a traditional-septic-but-not-actually-barking way, so I’ll spare you the details). And now I read it, I can’t really endorse his crit of the video, either, except in very general terms.


* Things I thought were obvious! – ATTP
* Is Climate Risk Systematically Understated? – asks mt at P3. Likely, yes.
* Taxonomy of climate/energy policy perspectives – essentially a rip-off of the same thing; from Curry

Anthropogenic influence on recent circulation-driven Antarctic sea ice changes

Oh good grief I hear you cry, not more science. Yes. Sorry. And its even about sea ice, but the Antarctic kind. This is in the trail of Holland and Kwok and so on.

Observations reveal an increase of Antarctic sea ice over the past three decades, yet global climate models tend to simulate a sea ice decrease for that period. Here we combine observations with model experiments (MPI-ESM) to investigate causes for this discrepancy and for the observed sea ice increase. Based on observations and atmospheric reanalysis, we show that on multidecadal time scales Antarctic sea ice changes are linked to intensified meridional winds that are caused by a zonally asymmetric lowering of the high-latitude surface pressure. In our simulations, this surface pressure lowering is a response to a combination of anthropogenic stratospheric ozone depletion and greenhouse gas increase. Combining these two lines of argument, we infer a possible anthropogenic influence on the observed sea ice changes. However, similar to other models, MPI-ESM simulates a surface-pressure response that is rather zonally symmetric, which explains why the simulated sea ice response differs from observations.

So, maybe the GCMs wind-pattern response, aka MSLP, around Antarctica is a bit off?

No growth stimulation of tropical trees by 150 years of CO2 fertilization but water-use efficiency increased

As an experiment, I thought I’d try posting some science instead of nonsense or mountains. From Nurture (Peter van der Sleen et al., Nature Geoscience 8, 24–28 (2015) doi:10.1038/ngeo2313):

The biomass of undisturbed tropical forests has likely increased in the past few decades1, 2, probably as a result of accelerated tree growth. Higher CO2 levels are expected to raise plant photosynthetic rates3 and enhance water-use efficiency4, that is, the ratio of carbon assimilation through photosynthesis to water loss through transpiration. However, there is no evidence that these physiological responses do indeed stimulate tree growth in tropical forests. Here we present measurements of stable carbon isotopes and growth rings in the wood of 1,100 trees from Bolivia, Cameroon and Thailand. Measurements of carbon isotope fractions in the wood indicate that intrinsic water-use efficiency in both understorey and canopy trees increased by 30–35% over the past 150 years as atmospheric CO2 concentrations increased. However, we found no evidence for the suggested concurrent acceleration of individual tree growth when analysing the width of growth rings. We conclude that the widespread assumption of a CO2-induced stimulation of tropical tree growth may not be valid.

This is a partial antidote to the CO2-is-plant-food people, but also to the ZOMG-crop-yields-are-falling people, since increased water efficiency is good. Mind you, not all plants are exactly the same, so it may not apply to the crops we care about in the circumstances we care about. Biology is complex, no?

Carbon cycle extremes during the 21st century in CMIP5 models: Future evolution and attribution to climatic drivers

While I’m here, Zscheischler et al., DOI: 10.1002/2014GL062409 is on a similar theme:

Climate extremes such as droughts and heat waves affect terrestrial ecosystems and may alter local carbon budgets. However, it still remains uncertain to what degree extreme impacts in the carbon cycle influence the carbon cycle-climate feedback both today and the near future. Here we analyze spatiotemporally contiguous negative extreme anomalies in gross primary production (GPP) and net ecosystem production (NEP) in model output of the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble and investigate their future development and attribution to climatic drivers. We find that relative to the overall increase in global carbon uptake, negative extremes in GPP and NEP lose importance toward the end of the 21st century. This effect can be related to elevated CO2 concentrations and higher amounts of available water at the global scale, partially mitigating the impacts of droughts and heat waves, respectively. Overall, based on CMIP5 models, we hypothesize that terrestrial ecosystems might be more resilient against future climate extremes than previously thought. Future work will have to further scrutinize these results considering that various biological and biogeochemical feedbacks are not yet integrated within Earth system models.

And to complete the trilogy, one including our very own William Ingram:

Correcting precipitation feature location in general circulation models

Adam A. L. Levy, Mark Jenkinson, William Ingram, Myles Allen, DOI: 10.1002/2014JD02235:

There is much evidence that precipitation responses to global warming involve wet regions becoming wetter and dry regions drier. This presents challenges for the interpretation of projections from general circulation models (GCMs) which have substantial biases in the location of precipitation features. While improving GCM simulated precipitation is the most desirable solution, adaptation and mitigation decisions must be made with the models already available. Many techniques have been developed to correct biases in grid point precipitation intensities, but few have been introduced to correct for location biases. Here, we describe a new technique for correcting the spatial and seasonal location of climatological precipitation features. We design this technique to respect the geometry of the problem (spherical spatial dimensions, with cyclic seasons), while conserving either precipitation intensities, or integrated precipitation amount. We discuss the mathematical basis of the technique and investigate its behaviour in different regimes. We find that the resulting warps depend smoothly on the most influential parameter, which determines the balance between smoothness and closeness of fit. We show that the technique is capable of removing more than half the RMS error in a model’s climatology, obtaining consistently better results when conserving integrated precipitation. To demonstrate the ability of the new technique to improve simulated precipitation changes, we apply our transformations to historical anomalies and show that RMS error is reduced relative to GPCP’s anomalies by approximately 10% for both types of warp. This verifies that errors in precipitation changes can be reduced by correcting underlying location errors in a GCM’s climatology.

I don’t really approve of correcting the models, though.