The projected timing of climate departure from recent variability, part two

I’ve had a little more time to look at this paper–discovering in the process that it had already made headlines in the popular media, including at a number of blogs. A few of those articles discuss some details, but not many and not too deep, while others are just rehashes or synopses of what the authors say. Painful experience teaches me that I’m not going to learn much of what I really want to know from that stuff. Google the article title if you want to read some of it.

In part one, I made some general, and tangential, comments about reading science papers. Here, I’ll look specifically at analytical issues of the paper in more depth, asking some questions if nothing else. Please get hold of the paper and read it if you can. It helps nothing whatsoever if you just take my word here–I’m not after that, it doesn’t foster progress in understanding. Maybe I’ve missed, or mis-interpreted, something important. Maybe something crucial in fact.

The authors are to be commended for paying the extra money to make the paper open access (assuming that’s what happened). However, there appear to me to be a number of serious questions to be raised. These fall under (at least) four different categories as I see it: (1) subject matter issues dealing with recent past, and future, climate estimation, (2) biodiversity-related issues as affected by climate change, (3) terminology/scale/scope issues and (4) statistical/mathematical/data issues. These are quick and rough categories and not mutually exclusive.

The paper is essentially a large GIS exercise, and in fact the authors state that the paper originated from a class exercise. They took the spatially specific, monthly and yearly output for seven climate variables from the 39 GCMs used in the CMIP5 that had data going back to 1860, and overlaid those onto coarse-scale species richness maps for 13 very broadly defined taxa, as obtained from the IUCN among others, using an interpolation routine to account for the different native spatial resolutions of the climate and taxon information. From this they compute the first year in which the future annual state of each variable always exceeds the range established from 1860 to 2005. They also do this for monthly data, and they do some sensitivity testing to things like the length of the historical period used. Then they add a paragraph about probable species climatic tolerances (and range limits) as a function of latitude, state very generally what that might imply for “biodiversity”… and that’s it. As a GIS class exercise, great, as a paper published in Nature, I’m not at all so sure.

The authors used the data from two of the emissions scenarios used in CMIP5–one of which (they state), RCP4.5, takes the atmosphere to just under 540 ppm by 2100 (mean of 1.69 ppm/year) and the other (RCP8.5) to just under 940 ppm; they refer to these as the “concerted rapid CO2 mitigation” and “business-as-usual” scenarios, respectively. The former value might indeed turn out to be unrealistically low, but is not greatly different from the current rate of about 1.85 ppm/year. The latter value, conversely, differs from the current rate by a vastly larger amount, averaging roughly (936-378)/95 = 5.9 ppm/year. One could certainly question the usefulness of using a rate that is over 300% of the current rate, and also the descriptive labels applied to the numbers; in what sense is a 300 percent increase in any way “business as usual”? The results from that extreme scenario (and that one alone) are what are presented in their Figure 2 and “Extended Data Figure 4“.

Also, how did they come up with their stated year 2100 CO2 concentration values of 538 and 936 for the two RCPs (Representative Concentration Pathways)? The RCPs used in CMIP5 are defined in terms of radiative forcing in W/m^2 (or, CO2 equivalent ppm), not CO2 concentration per se. Their paper cites Taylor et al 2012, but in looking at that, and also the paper on which it is based (Taylor et al, 2008), I can find in neither publication just where/how they got their CO2 concentration numbers. Why also, did they not analyze the less extreme scenario embodied by RCP6.0, which represents about a doubling of radiative forcing from 2006 to 2100? The basis for this choice is not stated. And what exactly is the justification for using only a 20 year period, 1986 to 2005, to test for correlations between modeled and actual climate variables? That’s a very big issue by itself, a central focus for climate modelers.

But to get to some specific results, below are the precipitation and transpiration panels, cut from their “Extended Data Figure 4”. It represents results under the extreme RCP8.5 scenario.

Look at the middle panel in each row (“Absolute Change”). Note that the scale for precipitation is roughly about 10 fold higher than that for transpiration. Note also, in the left-most panels of each row, that the expected year of climate departure over a vast chunk of the planet (deep blue color), is the last decade, 2090-2010, especially for precipitation. But 2100 is just an arbitrarily defined end point of the CMIP5 simulations, nothing more. So this might well indicate that for much of the planet, the expected year of departure actually falls out somewhere beyond 2100. And again, this is for the worst case scenario, the RCP8.5, about three times the current radiative forcing.

Moreover, look at the axis scales. How can it be that for a large percentage of the planet’s land surface, the projected drop in precipitation rate (light blue-green shading, and white) is, very roughly, about ten times greater than is the drop in transpiration rate? This implies directly that in much of the tropics, which are the focus of much of the discussion and emphasis in the paper, there is a pronounced excess in precipitation relative to what thermal energy can transpire, and that the projected increase in temperature therefore does not come anywhere close to removing this water from the land in most places. This in turn has very important implications for vegetation stability, and with it, a whole slew of ecological variables (diversity, biomass, etc), since continued transpiration is absolutely vital to plant temperature regulation, and plants form the basis of any ecosystem. Granted that I am looking only at large scale graphical displays in making these judgements, not spatially-specific numerical values, and therefore cannot discriminate between say, the wet and seasonally dry tropics, but that is the information they provided. There might be some tropical areas in which water would be predicted to become limiting, but again, we are talking about an extreme radiative forcing (RCP8.5 radiative forcing is equal to ~ 1350 ppm CO2 equivalent, according to Taylor et al., linked to above) assumed to occur less than 90 years from the present.

There are also very important questions to be raised regarding the validity of using 145 years as the historical reference period when you are addressing the issue of climate change on biodiversity dynamics. The world’s species did not evolve within, or adapt to, a 145 year climate window. This is a positively enormous topic that I unfortunately can’t begin to do justice to at the moment, but it needs to be at least mentioned in passing.

Another issue. I was slow to wrap my mind around the authors’ intent here, but once I got it the thought immediately occurred that, certainly, other groups must have done this kind of analysis, given (1) the importance of the potential speed of climate change, and (2) that the CMIP5 and AR5 are both very recent. If so, then the authors could just focus on the spatial and biodiversity effects issues, given that the lead author is a biogeographer (and presumably many of the junior authors as well, who are in his lab, many of them graduate students). Projected/modeled climate change from climate models is one subject, and how climatic changes might affect coarse taxonomic groupings on large spatial scales is another, no?

In looking for data used in, or from, the study, I found, at the lead author’s web site, a page titled “clarifications“, which contains an apology for not having cited nine relevant works since 2009, which the authors were made aware of, after publication, by Ed Hawkins, studies which Mora says support their findings. Coincidentally, Hawkins, who has published on this topic (time of climate departure from historical ranges), had just blogged on the topic about a week earlier. Were Mora et al. not aware of these studies? That’s how it appears. How can you get a paper published in Nature without being fully up to date on recent work in a field and/or bringing it into the discussion? Well, one way would be if the reviewers and handling editor were also ignorant of them, or for whatever reason did not raise the issue in their comments. Is that the case here?

That’s all I have time for, I will have to leave it there, at least for now.

9 thoughts on “The projected timing of climate departure from recent variability, part two

  1. The RCPs used in CMIP5 are defined in terms of radiative forcing in W/m^2 (or, CO2 equivalent ppm), not CO2 concentration per se.

    The number in the RCP title refers to radiative forcing but it’s only meant to be an approximate/representative figure. In CMIP5 models CO2 is prescribed either by emissions or by concentrations, depending on whether the simulation utilises an interactive carbon-cycle module. There are standardised CO2 concentration datasets available, which have been created by running climate-carbon cycle models with emissions scenarios. They are described in Meinshausen et al. 2011 and the 2100 numbers agree with those quoted.

    Note that carbon-cycle feedbacks are included in these numbers which partially explains the larger CO2 concentration increase: the climate change is larger in RCP8.5 so the natural CO2 contribution increases by a larger amount.

    These datasets are also available from Climate Explorer.

    I don’t really get why you think RCP8.5 is so unrealistic given an assumption that industrialisation is allowed to continue unchecked. The annual increase 50 years ago was ~ 0.7ppm/yr compared to current rate ~ 2ppm/yr (a near 300% increase). If that acceleration continues for another 50 years that’s already 5.7ppm/yr by 2060. Chinese emissions are still growing rapidly, albeit at a slightly reduced rate and other heavily-populated countries in Asia, South America and Africa have barely got going in terms of emissions. It’s “business-as-usual” because business-as-usual so far has greatly accelerated the rate, not kept it steady.

    • Very helpful comment (and links) Paul, thanks. I had looked at Meinshausen etal some time ago, maybe when it came out, and will need to again, or something similar.

      If “business as usual” is defined with respect to a continuation of an accelerating atmospheric CO2 rate, as determined over much of the 20th century, as a function of economic/industrial development, then what you say absolutely makes sense. I think I had in the back of my mind the slowdown in the rate of CO2 increase over the last several years (due presumably to the recession), relative to say, the several previous decades. But if the previous, high acceleration rate resumes, which it certainly could, you are exactly right.

    • Stagnation of the atmospheric CO2 accumulation rate over the past several years is likely more to do with climatic factors affecting natural sources/sinks – tendency towards La Nina conditions and possibly the quiet Sun. The recession has slowed things but, despite that, anthropogenic emissions over the past decade as a whole have been growing faster than ever (and I’m talking >60% over the previous fastest decadal growth rates, mainly in the 1960s), according to estimates cited at CDIAC.

      Regarding the non-use of RCP6.0 in the paper, one reason for not including it would be that modelling groups have tended to concentrate on RCP4.5 and RCP8.5. There are only about half as many RCP6.0 model runs available at PCMDI.

  2. Jim

    You seem to have a knack for picking out stuff! This paper is so dense that a layman like me has no chance of working out where it is on the scale from “batshit crazy” to “totally orthodox”. There is no doubt that this stuff is difficult and complicated. But there seems to be a strand in this area that wants to create big-scary headlines from everything – cheetah or polar bear extinctions for example – and then, when people look at the evidence and wonder what the fuss was about, they say “we were mis-quoted by the journalists”. You can look at figure 12.4 in the the policy-makers’ brief from the latest IPCC report and conclude that there is not a lot of real scientific certainty underlying the need for urgent action to stop the climate changing in the way it seems to be changing. http://storage/thumbnails/902844-23625139-thumbnail.jpg?__SQUARESPACE_CACHEVERSION=1380746813865

    Where exactly is the mis-communication happening? Obviously scientists have views on how the world should be – otherwise they would not be people – but where do you draw the line when it comes to talking about scientific evidence and drawing out conclusons for a basis for action?

    • Diogenes, that link doesn’t work. Are you referring to this, Fig 12.40 of the full WGI report (not the SPM)?:

      Figure 12.40: Temperature projections for SRES scenarios and the RCPs. (a) Time-evolving temperature distributions (66% range) for the four RCP scenarios computed with the ECS distribution from Rogelj et al. (2012) and a model setup representing closely the carbon-cycle and climate system uncertainty estimates of the AR4 (grey areas). Median paths are drawn in yellow. Red shaded areas indicate time periods referred to in panel b. (b) Ranges of estimated average temperature increase between 2090 and 2099 for SRES scenarios and the RCPs respectively. Note that results are given both relative to 1980–1999 (left scale) and relative to pre-industrial (right scale). Yellow ranges indicate results obtained by Rogelj et al. (2012). Colour-coding of AR4 ranges is chosen to be consistent with AR4 (Meehl et al., 2007). RCP2.6 is labelled as RCP3-PD here.

    • In my opinion, the mis-communication occurs in many places. The popular media is particularly egregious, being highly sensationalistic and seemingly often operating under a set of rules that amount to nothing more than “anything for the sake of a story that gets readers”, the driving force of which is usually $$. Strictly speaking, scientists should stick to purely technical matters, and I really believe the vast majority do (or try to). If they do venture into making policy sorts of statements, which they have the right to do just like anyone does, they should not allow their personal viewpoints to affect their science. Some do though, and they create problems. Sometimes though it’s just a simple matter of ego and not wanting to be shown to be wrong.

      One reminder on taking action though–it’s a risk assessment issue. The uncertainty of what will happen may indeed be great, based on the available evidence, but if the potential consequences are also great (and potentially, very negative), then you’ve got a very thorny problem on your hands. Which is what we have.

    • thanks Jim…I think you managed to find the right link. This whole “consensus” thing really bothers me, though. What is the main cause of stomach ulcers……the mainstream answer has changed over the last 40 years. Scientific consensus should not be used to stifle reasoned debate and yet we can see clearly that it was. Is it a good idea for climate science to cling so hard to concensus, after all, your highly reasoned paper was notm accepted for discussion!

    • My opinion is that a claimed consensus, in and of itself, means–and proves–exactly nothing, because scientists are humans, humans are social animals, and social animals are highly vulnerable to peer pressure and power.

      All of those papers, polls and popular media articles about climate change consensus are just an enormous waste of time IMO, and I pay no attention to them whatsoever.

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