My co-authors and I have just published an article in Nature Geoscience (advance online publication here; associated press release here) which seeks to explain certain enigmatic features of tree-ring reconstructions of Northern Hemisphere (NH) temperatures of the past millennium. Most notable is the virtual absence of cooling in the tree-ring reconstructions during what ice core and other evidence suggest is the most explosive volcanic eruption of the past millennium–the AD 1258 eruption. Other evidence suggests wide-spread global climate impacts of this eruption [see e.g. the review by Emile-Geay et al (2008)]. We argue that this–and other missing episodes of volcanic cooling, are likely an artifact of biological growth effects, which lead to a substantial underestimation of the largest volcanic cooling events in trees growing near treeline. We speculate that this underestimation may also have led to overly low estimates of climate sensitivity in some past studies attempting to constrain climate model sensitivity parameters with proxy-reconstructed temperature changes.

Tree rings are used as proxies for climate because trees create unique rings each year that often reflect the weather conditions that influenced the growing season that year. For reconstructing past temperatures, dendroclimatologists typically seek trees growing at the boreal or alpine treeline, since temperature is most likely to be the limiting climate variable in that environment. But this choice may also prove problematic under certain conditions. Because the trees at these locations are so close to the threshold for growth, if the temperature drops just a couple of degrees during the growing season, there will be little or no growth and therefore a loss of sensitivity to any further cooling. In extreme cases, there may be no growth ring at all. And if no ring was formed in a given year, that creates a further complication, introducing an error in the chronology established by counting rings back in time.

We compared simulated temperature of the past millennium derived by driving theoretical climate models with estimated natural (volcanic+solar) and anthropogenic forcings for the past millennium. We employed two different climate model simulations: (1) the simulation of the NCAR CSM 1.4 coupled atmosphere-ocean General Circulation Model (GCM) analyzed by Ammann et al (2007) and (2) simulations of a simple Energy Balance Model (EBM). While the GCM provides a more comprehensive and arguably realistic description of the climate system, the computational simplicity of the EBM lends itself to extensive sensitivity tests. As the target for our comparison, we used a state-of-the-art tree-ring based Northern Hemisphere (NH) mean temperature reconstruction of D’Arrigo et al (2006). The reconstruction was based on a composite of tree ring annual ring width series from boreal and alpine treeline sites across the northern hemisphere, and made use of a very conservative (“RCS”) tree-ring standardization procedure designed to preserve as much low-frequency climatic information as possible.

Interestingly, the long-term variations indicated by the model simulations compared remarkably well with those documented by the tree-ring reconstruction, showing no obvious sign of the potential biases in the estimated low-frequency temperature variations that have been the focus of much previous work (see e.g. this previous RealClimate review). Instead, the one glaring inconsistency was in the high-frequency variations, specifically, the cooling response to the largest few tropical eruptions, AD 1258/1259, 1452/1453 and the 1809+1815 double pulse of eruptions, which is sharpy reduced in the reconstruction relative to the model predictions. Indeed, this was found to be true for any of several different published volcanic forcing series for the past millennium, regardless of the precise geometric scaling used to estimate radiative forcing from volcanic optical depth, and regardless of the precise climate sensitivity assumed.

Following the AD 1258 eruption, the climate model simulations predict a drop of 2C, but the tree ring-based reconstruction shows only about a 0.5C cooling. Equally vexing, the cooling in the reconstruction occurs several years late relative to what is predicted by the model. The other large eruptions showed similar discrepancies. An analysis using synthetic proxy data with spatial sampling density and proxy signal-to-noise ratios equivalent to those of the D’Arrigo et al (2006) tree-ring network suggest that these discrepancies cannot be explained in terms of either the spatial sampling/extent or the intrinsic “noisiness” of the network of proxy records.

However, using a tree growth model that accounts for the temperature growth thresholding effects discussed above, combined with the complicating effects of chronological errors due to potential missing growth rings, explains the observed features remarkably well.

Show in the above figure (Figure 2d from the article) is the D’Arrigo et al tree-ring based NH reconstruction (blue) along with the climate model (NCAR CSM 1.4) simulated NH mean temperatures (red) and the “simulated tree-ring” NH temperature series based on driving the biological growth model with the climate model simulated temperatures (green). The two insets focus on the response to the AD 1258 and AD 1809+1815 volcanic eruption sequences. The attenuation of the response is produced primarily by the loss of sensitivity to further cooling for eruptions that place growing season temperatures close to the lower threshold for growth. The smearing and delay of the cooling, however, arises from another effect: when growing season lengths approach zero, we assume that no growth ring will be detectable for that year. That means that an age model error of 1 year will be introduced in the chronology counting back in time. As multiple large eruptions are encountered further back in time, these age model errors accumulate. This factor would lead to a precise chronological error, rather than smearing of the chronology, if all treeline sites experienced the same cooling. However, stochastic weather variations will lead to differing amounts of cooling for synoptically distinct regions. That means that in any given year, some regions might fall below the “no ring” threshold, while other regions do not. That means that different chronological errors accumulate in synoptically-distinct regions of the Northern Hemisphere. In forming a hemispheric composite, these errors thus lead to a smearing out of the signal back in time as slightly different age model errors accumulate in the different regions contributing to the composite.

Including this effect, our model accounts not only for the level of attenuation of the signal, but the delayed and smeared out cooling as well. This is particularly striking in comparing the behavior following both the AD 1258 and AD 1809 eruptions (compare the green and blue curves in the insets of the figure). Our model, for example, predicts the magnitude of the reduction of cooling following the eruptions and the delay in the apparent cooling evidence in the tree-ring record (i.e. in AD 1262 rather than AD 1258). We have also included a minor additional effect in these simulations. While volcanic aerosols cause surface cooling due to decreased shortwave radiation at the surface, they also lead to increased indirect, scattered light at the surface. Plant growth benefits from indirect sunlight, and past studies show that e.g. a Pinatubo-sized eruption (roughly -2W/m^2 radiative forcing) can result in a 30% increase in carbon assimilation by plants. This effect turns out to be relatively small because it is proportional in nature, and thus results in a very small absolute increase when growth is suppressed i the first place by limited growing seasons. However, not including this effect results in a slightly less good reproduction (purple dashed curves in the two insets of the figure) of the observed behavior.

As noted earlier, our main conclusions are insensitive to the precise details of the forcing estimates used, the volcanic scaling assumptions made, and the precise assumed climate sensitivity. They were also insensitive to the details of the biological tree growth model over a reasonable range of model assumptions. The conclusion that tree-ring temperature reconstructions might suffer from age model errors due to missing rings is bound to be controversial. A few points are worth making here. First of all, our conclusion is quite specific to temperature-sensitive trees at treeline, and it does not imply more general problems in the larger discipline of dendrochronology. Secondly, the conclusion at this stage simply a hypothesis, a hypothesis that can account for these key enigmatic features in the actual tree-ring hemisphere temperature reconstruction: the attenuation, and the increasing (back in time) delay and temporal smearing of the cooling response to past volcanic forcing. Were an equally successful and more parsimonious hypothesis to be provided for these observations, I would be the first to concede and defer to this alternative explanation.

One argument against the specific conclusion of missing growth rings is that trees are carefully cross-dated when forming regional chronologies, and this precludes the possibility of chronological errors. That, however, assumes that there are at least some trees within a particular region that will not suffer a missing ring during the years where our model predicts it. Yet our prediction is that all trees within a region of synoptic or lesser scale where growing season temperatures lie below the growth threshold will experience a missing ring. Thus, cross-dating within that region, regardless of how careful, cannot resolve the lost chronological information. It is my hope that dendroclimatologists will reassess raw chronologies more carefully and critically assess the extent to which the predicted features might indeed be present in the underlying tree-ring data. Again, this paper presents a hypothesis for explaining some enigmatic features of existing tree-ring temperature reconstructions. It is hardly the last word on the matter.

Finally it is worth discussing the potential wider implication of these findings. Climate scientists use the past response of the climate to natural factors like volcanoes to better understand how sensitive Earth’s climate might be to the human impact of increasing greenhouse gas concentrations, e.g. to estimate the equilibrium sensitivity of the climate to CO2 doubling i.e. the warming expected for an increase in radiative forcing equivalent to doubling of CO2 concentrations. Hegerl et al (2006) for example used comparisons during the pre-industrial of EBM simulations and proxy temperature reconstructions based entirely or partially on tree-ring data to estimate the equilibrium 2xCO2 climate sensitivity, arguing for a substantially lower 5%-95% range of 1.5–6.2C than found in several previous studies. The primary radiative forcing during the pre-industrial period, however, is that provided by volcanic forcing. Our findings therefore suggest that such studies, because of the underestimate of the response to volcanic forcing in the underlying data, may well have underestimated the true climate sensitivity.

It will be interesting to see if accounting for the potential biases identified in this study leads to an upward revision in the estimated sensitivity range. Our study, in this regard, once again only puts forward a hypothesis. It will be up to other researchers, in further work, to assess the validity and potential implications of this hypothesis.

Guest Commentary by Eugenie Scott, National Center for Science Education

Imagine you’re a middle-school science teacher, and you get to the section of the course where you’re to talk about climate change. You mention the “C” words, and two students walk out of the class.

Or you mention global warming and a hand shoots up.

“Mrs. Brown! My dad says global warming is a hoax!”

Or you come to school one morning and the principal wants to see you because a parent of one of your students has accused you of political bias because you taught what scientists agree about: that the Earth is getting warmer, and human actions have had an important role in this warming.

Or you pick up the newspaper and see that your state legislature is considering a bill that declares that accepted sciences like global warming (and evolution, of course) are “controversial issues” that require “alternatives” to be taught.

Incidents like these have happened in one or more states, and they are likely to continue to happen. Teachers are encountering pushback from many directions as they try to teach global warming and other climate science topics.

The importance of climate change education is, to the RealClimate community, a no-brainer. Numerous professional science organizations, from the American Chemical Society to the American Geophysical Union to the Geological Society of America have stressed the imperative of climate science being an integral part of science education.

So What’s a Teacher to Do?

Long a defender of the teaching of evolution, the National Center for Science Education has recently launched an initiative to support and defend the teaching of climate change science.

The “support” part has challenges all its own. Unlike evolution, which easily fits into biology and other life science courses, climate science spans multiple disciplines and can fall through disciplinary cracks in biology, chemistry and physics, or appear briefly in more specialized disciplines like ecology or Earth sciences. Moreover, climate science is complex and often non-intuitive, and students (and all too often teachers) stumble over misinformation and misconceptions that are hard to overcome. Many educational institutions are wrestling with how to support climate science in the K-12 curriculum.

But the “defend” part is where NCSE will make a unique contribution. Our experience over the decades helping teachers and school boards resolve the problems that have arisen over the teaching of evolution should stand us in good stead in helping them deal with this newer “controversial science”. Of course, there are many perspectives affecting the objections to climate science education, and each requires its own response.

Some of the denial is literal (It’s not happening! The science is bad!), some of it may be interpretive (it’s maybe happening but people aren’t to blame), and some of it stems more from the implications of climate change (it’s happening and maybe humans are responsible, but someone else is to blame and/or there’s nothing I can do about it). We’re going to help teachers understand where pressure against climate science education comes from, as the first step in helping them construct a response. From the evolution education controversy we learned long ago that one does not solve these problems merely by piling on more or better science: the underlying, motivating issues must be addressed. The science is essential, but not sufficient.

Climate change education should be an integral part of science education. Students should graduate from high school and certainly college with at least a basic understanding of the foundational concepts of climate science so they can understand human activities and how they are impacting climate and other aspects of the earth system.

This is no small task, and obviously NCSE as a relatively small non-profit can only do so much. We need your help.

We have been successful because we marshal allies, like scientists, teachers, parents, and other citizens, at the grassroots. NCSE’s success over recent decades in defending the teaching of evolution has been due in large measure to scientists and others who are willing to support good science education locally and at the state level. We also need scientists to provide us with their scientific expertise.

If you are a climate scientist, please give us your contact information so we can consult with you. Also, your contact information will be helpful to us if something occurs in your region or state where we need a scientist to write a letter, testify before a committee, support a teacher, or help in some other way.

Of course, an obvious way you can help is to join NCSE, but even if you don’t, your expertise will be helpful to us.

Visit our website, and contact our new Programs and Policy Director, Mark McCaffrey, who will be helping spearhead the new initiative, to let us know you support our effort. Teachers will thank you.

This month’s open thread. Current topics are focused on the laughingly bad Daily Mail article by David Rose, the fallout from the Wall Street Journal’s latest regurgitation of why no-one should ever do anything ever. And perhaps someone might want to audit some of David Whitehouse’s arithmetic and reading comprehension…

Or anything else. Within reason.

Back in 2007, the IPCC AR4 SPM stated that:

“Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”

This is a clear statement that I think is very well supported and correctly reflects the opinion of most climate scientists on the subject (and was re-affirmed in two recent papers (Jones and Stott, 2011;, Huber and Knutti, 2011)). It isn’t an isolated conclusion from a single study, but comes from an assessment of the changing patterns of surface and tropospheric warming, stratospheric cooling, ocean heat content changes, land-ocean contrasts, etc. that collectively demonstrate that there are detectable changes occurring which we can attempt to attribute to one or more physical causes.

Yet, in a paper just out in BAMS (Curry and Webster, 2011) this statement is apparently evidence that IPCC is unable to deal with uncertainty. Furthermore, Judith Curry has reiterated on her blog that the term ‘most’ is imprecise and undefined. For instance:

Apart from the undefined meaning of “most” in AR4 (which was subsequently clarified by the IPCC), the range 50.1-95% is rather imprecise in the context of attribution.

However, Curry’s argument is far from convincing, nor is it well formed (why is there a cap at 95%?). Nor was it convincing when I discussed the issue with her in the comments at Collide-a-Scape last year where she made similar points. Since the C&W paper basically repeats that argument (as has also been noticed by Gabi Hegerl et al who have a comment on the paper (Hegerl et al.)), it is perhaps worth addressing these specific issues again.

Let’s start with what the statement actually means. “Most” is an unambiguous adjective (meaning more than half), and ‘very likely’ in IPCC-speak means that the statement is being made with between 90 to 99% confidence (i.e. for every 10 such statements, the scientists expect 9 or more to pan out). Given that some people have found this confusing, it may help somewhat if the contents of the statement are visualised:

Figure 1: Two schematic distributions of possible ‘anthropogenic GHG contributions’ to the warming over the last 50 years. Note that in each case, despite a difference in the mean and variance, the probability of being below 50, is exactly 0.1 (i.e. a 10% likelihood).

The figure shows two Gaussian distributions, both of which have the probability of x being less than 50 at 0.1. i.e. P(x<50)=0.1. If either of them had been the distribution of the estimated increase in global temperatures due to anthropogenic greenhouse gas increases relative to the observed increase, the IPCC statement would have been almost exactly correct (i.e. if x=100*trend_caused_by_GHG/actual_trend). These distributions show a number of key issues that need to be appreciated. First, the actual increase of temperatures purely due to the rise in GHGs is not precisely known (and therefore there is a distribution of potential values). Note that we are presuming that there is a single ‘true’ answer, so the distribution is a measure of our ignorance, not a claim that the answer itself is a random variable.

Second, the IPCC statement is not a declaration about what the most likely value of ‘x’ is. It states merely that P(x> 50%) is at least 0.9. In the two figures, one has the mean value of x at 80%, while the other has the mean value at 100%. Both fit the IPCC statement equally well. Some people have interpreted the IPCC statement confusing the likelihood of the statement with the actual relative trend (i.e. that the 90% refers to the expected attribution), but that would be a big misreading of the text.

Third, there is certainly a potential for the increase in temperatures due to anthropogenic GHG changes to be greater than the observed trend because we know that there have been both natural (volcanic and solar) and human-caused (reflective aerosols, land use change) factors that are expected to have lead to cooling over the post-1950 period (therefore there is no cut off at 95% of the actual trend). The actual trend will be a function of the warming factors, balanced by the cooling factors. And of the warming factors, the well-mixed greenhouse gas (CO₂, CH₄, N₂O, CFCs) changes are the dominant term (about 75% of the increase in warming factors from 1950, the rest is related to black carbon effects, ozone etc.).

Fourth, the statement clearly encompasses many different estimates of what the actual trends are being driven by and is not therefore a particularly strong conclusion. Myles Allen (Allen, 2011) points out that during the drafting, the text was changed from ‘contributed substantially’ to ‘most’, and focused on greenhouse gases rather than the total anthropogenic effect specifically in order to have a more quantitative conclusion and more justifiable statement.

Now let’s put some real numbers in here. Attribution is fundamentally a modelling task, and the principal models that can be used are the coupled GCMs – at least to start with. What do they estimate the warming trend from the well-mixed GHGs to have been over the last 50 years? The figure below shows this for some of the GISS CMIP5 models (more model data can be downloaded from CMIP5 portal):

The 50 year trends (here, from 1956 to 2005, 5 ensemble members), are 0.84ºC (range [0.79,0.92]) for just greenhouse gas forcing. and 0.67ºC (range [0.54,0.76]) for the all-forcings case (in CMIP3, the envelope of the all-forcing trends is [0.4,1.3], or equivalently 0.74 +/- 0.22ºC (1 sigma spread) using 55 individual model simulations – the wider spread reflecting structural variations in the models and forcings). As in the more recent model simulations, the GISS CMIP3 50 year trends using only well-mixed GHG forcings is around 0.1ºC more than the ‘all-forcing’ case (data here).

The actual observed trend depends a little on the dataset used, but is around 0.6 +/- 0.05ºC (1 sigma uncertainty in the OLS fit). If we then estimate the percentage (as illustrated above), assuming a 0.2ºC sigma in the model spread, ‘x’ is roughly 140% +/- 35% (1 sigma). If we interpreted that range as a Gaussian distribution (not really a good idea, but simple enough for illustration), we’d estimate that P(x<50%) would be less than 1% (even less likely than the IPCC AR4 statement allowed for).

There are good reasons why the IPCC assessed that the probability was not as low as suggested by the models or any individual attribution paper. Specifically, the overall assessment must take into account potential structural uncertainties that don’t come into the straight model analysis. For instance, the models may systematically be overestimating the GHG-driven trend, they may be underestimating the internal variability, and they may be undersampling the structural uncertainty in making models themselves. The first kind of error would cause an overestimate in the mean of the distribution, while the other factors would cause an underestimate in the variance of the trends – all would increase P(x < 50%). On the other hand, the net forcing is almost certainly less than the effect of anthropogenic GHGs alone and so that biases the mean of the ‘all-forcings’ trends low, and some of the spread in the trends is related to different models having different forcings (biasing the spread wide). These elements can be quantified during the attribution (using fingerprint scaling, monte-carlo emulators etc.), but when they are all taken into account, the difference is less than one might think (it turns out that structural uncertainty likely isn’t being underestimated and the internal variability in models comfortably spans the range inferred in the real world (Yokohata et al., 2011; Santer et al., 2011)).

Curry and Webster specifically bring up two issues that, they claim, lessen the confidence one should have in the IPCC statement: that the history of solar forcing is uncertain in scale, and that aerosol forcings have a huge error bar. These two statements are true as far as they go – the scale of solar forcing is not tightly constrained prior to about 1960, and the total aerosol forcing and it’s variation in time is uncertain. But C&W’s specific complaint is that the attribution studies used in AR4 used solar forcing that was too large compared to more recent studies. However, reducing any warming trend associated with solar actually makes the attribution statement more likely which somewhat undercuts their point.

With respect to aerosols, the key thing to remember that regardless of the magnitude of the change, the sign of the forcing is almost certainly negative (i.e. the net aerosol effect has been one of cooling). The dominant anthropogenic aerosols are sulphates (derived from the SO₂ emitted during the burning of sulphur-containing fossil fuels), which are reflective, and hence cooling. Other aerosols (black carbon, organic carbon, nitrates) are more uncertain, but have a net effect that is smaller.

Now, the statement in AR4 specifically states that the effect of greenhouse gases is more than half of the observed trend, which is actually independent of the effects of aerosols. But with the high probability of aerosols being a net cooling, this increases the ratio of the GHG-driven trends to the actual forced trend.

The final issue is whether the internal variability of the system on multi-decadal timescales has been properly characterised. For instance, it is possible that all the models grossly underestimate the internal variability, in which case any expected trend due to GHGs would be drowned out in the noise. But there is no positive evidence for this at all – as Hegerl et al point out, the estimates of multi-decadal variability in the models and observational records all overlap within their (substantial) uncertainties (arising from the shortness of the record, and the difficulty in estimating internal variability in the presence of multiple forcings). So while it is conceivable be that there is a bias, it is currently undetectable, which implies it can’t be that large.

In summary then, the IPCC AR4 statement was a fair, even conservative, assessment. There is an unfortunate tendency to reify the particular statements made by IPCC, since there were clearly other correct statements that could have been made. For instance, it might well have been worthwhile to add a statement about the likely range of the anthropogenic trends (i.e 80-120% of the actual trend or similar), so that a better picture of the appropriate distribution could be given (see Huber and Knutti (2011) for examples). But claims that the statement was unsupported, or that it demonstrated that IPCC was ignoring uncertainty are simply untenable.

The next iteration (IPCC AR5) is now underway, but given the early results of the CMIP5 models (which are on the whole very similar, as discussed at fall AGU), and more recent literature on this issue (see refs below), I see no reasons in the recent literature why the conclusions in AR5 will be much different. But if anyone still finds the assessment confusing, they have an opportunity to make their points via the IPCC review process, and the resulting conclusions will likely be clearer because of them.

References

1. G.S. Jones, and P.A. Stott, "Sensitivity of the attribution of near surface temperature warming to the choice of observational dataset", Geophysical Research Letters, vol. 38, 2011. DOI.
2. M. Huber, and R. Knutti, "Anthropogenic and natural warming inferred from changes in Earth’s energy balance", Nature Geoscience, vol. 5, 2011, pp. 31-36. DOI.
3. J.A. Curry, and P.J. Webster, "Climate Science and the Uncertainty Monster", Bulletin of the American Meteorological Society, vol. 92, 2011, pp. 1667-1682. DOI.
4. G. Hegerl, P. Stott, S. Solomon, and F. Zwiers, "Comment on “Climate Science and the Uncertainty Monster” J. A. Curry and P. J. Webster", Bulletin of the American Meteorological Society, vol. 92, 2011, pp. 1683-1685. DOI.
5. M. Allen, "In defense of the traditional null hypothesis: remarks on the Trenberth and Curry WIREs opinion articles", Wiley Interdisciplinary Reviews: Climate Change, vol. 2, 2011, pp. 931-934. DOI.
6. T. Yokohata, J.D. Annan, M. Collins, C.S. Jackson, M. Tobis, M.J. Webb, and J.C. Hargreaves, "Reliability of multi-model and structurally different single-model ensembles", Climate Dynamics. DOI.
7. B.D. Santer, C. Mears, C. Doutriaux, P. Caldwell, P.J. Gleckler, T.M.L. Wigley, S. Solomon, N.P. Gillett, D. Ivanova, T.R. Karl, J.R. Lanzante, G.A. Meehl, P.A. Stott, K.E. Taylor, P.W. Thorne, M.F. Wehner, and F.J. Wentz, "Separating signal and noise in atmospheric temperature changes: The importance of timescale", Journal of Geophysical Research, vol. 116, 2011. DOI.

A group of researchers at Carnegie Mellon University is trying to get a better understanding of the views of earth scientists regarding various climate change topics. They have set up an ongoing poll to do this, called Vision Prize. It’s a short (10 question) poll, covering topics like the rate of CO2 increase, predicted future temperatures, sea ice and sea level states, and hurricane frequencies. Early participants can designate a $20 donation from the group to a charity of their choice, upon completion. Please take a few minutes to help them out if qualified.

Update January 27: There is also another recent dog-based animations from Victoria (southeast Australia) explaining some of the key drivers of our climate and how some are changing.

A TV series that ran on Norwegian TV (NRK) last year included a simple and fun cartoon that demonstrates some important concepts relative to weather and climate:

In the animation, the man’s path can be considered as analogous to a directional climatic change, while the path traced by his dog’s whimsical movements represent weather fluctuations, as constrained by the man’s path, the leash, and the dog’s moment-by-moment decisions of what seems important to investigate in his small world. What might the leash length represent? The man’s momentary pause? The dog’s exact route relative to concepts of random variation? The messages in this animation are similar to the recent results of Grant Foster and Stefan Rahmstorf in ERL (see post here).

We’d also like to praise the TV-series ‘Siffer‘, hosted by an enthusiastic statistician explaining how most things in our world relate to mathematics. The series covers a range of subjects, for instance gambling theory, the Tragedy of the Commons, anecdotes about mathematical riddles, medical statistics, and construction design; it even answers why champagne from a large bottle tastes better than that from a smaller one. There is also an episode devoted to weather forecasting and climate.

Success in understanding our universe often depends on how the ‘story’ about it is told, and a big part of that often involves how mental images are presented. Mathematics and statistics can describe nature in great detail and “elegance”, but they are often difficult and inaccessible to the average person. Conversely, the man-and-dog animation is intuitive and easy to comprehend. Similarly, Hans Rosling’s Fun with Stats provides some very nice demonstrations of how to convey meaning via the creative display of numbers.

Almost 3000 non-science major undergraduates at the University of Chicago have taken PHSC13400, Global Warming: Understanding the Forecast, since Ray Pierrehumbert and I (David Archer) first developed it back in 1995. Since the publication of the textbook for the class in 2005 (and a much-cleaned-up 2nd edition now shipping), enrollment has gone through the roof, it’s all I’ve been able to teach the last few years, trying to keep up with demand. I hear it is the largest class on campus, with 4-500 students a year out of an annual class of only around 1400. Now the content of this class is being served to the internet world at large: Open Climate 101.

You can watch video lectures followed by quizzes to challenge and hopefully stimulate your understanding, and work your way through tutorials with interactive models and simple mathematical ideas. Actually all that stuff has been available for a long time, online or in the textbook, but now it’s packaged into an interactive assessing system, which admittedly lacks the personality and finesse of our graduate student teaching assistants, but I hope it’ll get the job done. You can work at your own pace, on your own time. You don’t get University of Chicago credit, but it’s free, and if you get to the end of it you can download a certificate of accomplishment with your name and a verification code, signed by me. I hope people find it useful.

I’ve put together an easy-to-play-with online model of methane in the atmosphere. I’m going to use it for teaching along with the rest of the Understanding the Forecast webmodels, but it was designed to be relevant to the issue of abrupt new methane burps as we’ve been ruminating about lately on Realclimate.

The model runs in three stages: a pre-anthropogenic steady state which ends in the model year
-50, addition of a new chronic source for 50 years (from human activity),then a spike beginning at model year 0 (supposed to be today) and running for 100 years into the model future. Here are results from the “worst case scenario” in the last post (whether you believe it is the true worst case or not): 200 Gton C over 100 years.

Looks like we got the factor of 10 methane increase about right.

Source and sink of methane in the model.

The lifetime of methane in the atmosphere, used to calculate the methane sink in any time step, is parameterized as a function of concentration following Schmidt and Shindell (2003).

The atmospheric lifetime of methane, used to calculate the sink flux.

The radiative forcing is parameterized from output from the NCAR model, scaled by an efficacy factor of 1.4 from Hansen et al, (2005). The radiative forcing is compared with Business-as-usual CO₂ radiative forcing with the model year 0 corresponding roughly to year 2010, and with CO₂ rising at 0.65% per year. The methane radiative forcing before year 0 is not time-realistic because the real human sources did not switch on instantaneously 50 years ago, but you can compare the future evolution of radiative forcing from CO₂ and methane, from year 0 onwards.

The radiative forcings of CO₂ and methane compared. The scenario is more-or-less comparable to 750 ppm CO₂, as we thought.

The CO₂ concentration used to generate the last figure.

Timing is everything

Four simulations with the same amount of carbon released as methane in the “spike”, on different time scales for the release.

10 Gton C release in 1 year — the spike.

Same spike but not as sharp: 10 Gton over 20 years.

Same 10 Gton but spread over 50 years.

100 years.

Enjoy. Go and get your swamp gas on, and give the poor model planet your worst. Bwahahahahaha!

References

1. G.A. Schmidt, "Atmospheric composition, radiative forcing, and climate change as a consequence of a massive methane release from gas hydrates", Paleoceanography, vol. 18, 2003. DOI.
2. J. Hansen, "Efficacy of climate forcings", Journal of Geophysical Research, vol. 110, 2005. DOI.

Let’s suppose that the Arctic started to degas methane 100 times faster than it is today. I just made that number up trying to come up with a blow-the-doors-off surprise, something like the ozone hole. We ran the numbers to get an idea of how the climate impact of an Arctic Methane Nasty Surprise would stack up to that from Business-as-Usual rising CO₂

Walter et al (2007) says that Arctic lakes are 10% of natural global emissions, or about 5% of total emissions. I believe that was considered to be remarkably high at the time but let’s take it as a given, and representing the Arctic as a whole. If the number of lakes or their bubbling intensity suddenly increased by a factor of 100, and it persisted this way for 100 years, it would come to about 200 Gton of carbon emission, which is on the same scale as our entire fossil fuel emission so far (300 Gton C), or roughly the amount of traditional reserves of natural gas (although I’m not sure where estimates are since fracking) or petroleum. It would be a whopper of a surprise.

Scaling Walter’s Arctic lake emission rates up by a factor of 100 would increase the overall emission rate, natural and anthropogenic, by about a factor of 5 from where it is today. The weak leverage is because the high latitudes are a small source today relative to tropical wetlands and anthropogenic sources, so they have to grow a lot before they make much difference to the sum of all sources.

The steady-state methane concentration in the air scales nearly linearly with the emission rate. Actually, the concentration goes up somewhat faster than a constant times the emission rate, because the lifetime in the atmosphere gets longer (IPCC TAR). Let’s err on the side of flamboyance (great word in this context) and say the concentration of methane in the air goes up by a factor of 10 for the duration of the extra methane emission (meaning that the lifetime doubles).

Using the modtran model on line I get a radiative forcing from 10 * atmospheric methane of 3.4 Watts/m² (the difference in the instantaneous IR flux out, labeled I_out, between cases with and without 10x methane). Using the TAR estimates of radiative forcing gives 2.7 Watts/m².

But methane is a reactive gas and its presence leads to other greenhouse forcings, like the water vapor it decomposes into. Hansen estimates the “efficacy” of methane radiative forcing to be 1.4 (Hansen et al, 2005, Shindell et al, 2009), so that puts us to 4 or even 5 Watts/m².

This is about twice the radiative forcing today from all anthropogenic greenhouse gases today, or (again according to Modtran) it would translate to an equivalent CO₂ at today’s methane concentration of about 750 ppm. That seems significant, for sure.

Or, trying to “correct” for the different lifetimes of the gases using Global Warming Potentials, over a 100-year time horizon (which still way under-represents the lifetime of the CO₂), you get that the methane would be equivalent to increasing CO₂ to about 500 ppm, lower than 750 because the CO₂ forcing lasts longer than the methane, which the GWP calculation tries in its own myopic way to account for.

But the methane worst case does not suddenly spell the extinction of human life on Earth. It does not lead to a runaway greenhouse. The worst-case methane scenario stands comparable to what CO₂ can do. What CO₂ will do, under business-as-usual, not in a wild blow-the-doors-off unpleasant surprise, but just in the absence of any pleasant surprises (like emission controls). At worst comparable to CO₂ except that CO₂ lasts essentially forever.

References

1. K.M. Walter, L.C. Smith, and F. Stuart Chapin, "Methane bubbling from northern lakes: present and future contributions to the global methane budget", Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, vol. 365, 2007, pp. 1657-1676. DOI.
2. J. Hansen, "Efficacy of climate forcings", Journal of Geophysical Research, vol. 110, 2005. DOI.
3. D.T. Shindell, G. Faluvegi, D.M. Koch, G.A. Schmidt, N. Unger, and S.E. Bauer, "Improved Attribution of Climate Forcing to Emissions", Science, vol. 326, 2009, pp. 716-718. DOI.

Methane is a powerful greenhouse gas, but it also has an awesome power to really get people worked up, compared to other equally frightening pieces of the climate story.

What methane are we talking about?

The largest methane pools that people are talking about are in sediments of the ocean, frozen into hydrate or clathrate deposits (Archer, 2007). The total amount of methane as ocean hydrates is poorly constrained but could rival the rest of the fossil fuels combined. Most of this is unattractive to extract for fuel, and mostly so deep in the sediment column that it would take thousands of years for anthropogenic warming to reach them. The Arctic is special in that the water column is colder than the global average, and so hydrate can be found as shallow as 200 meters water depth.

On land, there is lots of methane in the thawing Arctic, exploding lakes and what not. This methane is probably produced by decomposition of thawing organic matter. Methane could only freeze into hydrate at depths below a few hundred meters in the soil, and then only at “lithostatic pressure” rather than “hydrostatic”, meaning that the hydrate would have to be sealed from the atmosphere by some impermeable layer. The great gas reservoirs in Siberia are thought to be in part frozen, but evidence for hydrate within the permafrost soils is pretty thin (Dallimore and Collett,1995)

Is methane escaping due to global warming?

There have been observations of bubbles emanating from the sea floor in the Arctic (Shakhova, 2010; Shakhova et al., 2005) and off Norway (Westbrook, 2009). The Norwegian bubble plume coincides with the edge of the hydrate stability zone, where a bit of warming could push the surface sediments from stable to unstable. A model of the hydrates (Reagan, 2009) produces a bubble plume similar to what’s observed, in response to the observed rate of ocean water warming over the past 30 years, but with this warming rate extrapolated further back in time over the past 100 years. The response time of their model is several centuries, so pre-loading the early warming like they did makes it difficult to even guess how much of the response they model could be attributed to human-induced climate change, even if we knew how much of the last 30 years of ocean warming in that location came from human activity.

Lakes provide an escape path for the methane by creating “thaw bulbs” in the underlying soil, and lakes are everywhere appearing and disappearing in the Arctic as the permafrost melts. (Whether you get CO₂ or a mixture of CO₂ plus methane depends critically on water, so lakes are important for that reason also.)

Methane bubbles captured in freezing lake ice in Alaska

So far there hasn’t been strong evidence presented for detection enhanced methane fluxes due to anthropogenic warming yet. Yet it is certainly believable for the coming century however, which brings us to the next question:

What effect would a methane release have on climate?

The climate impact of releasing methane depends on whether it is released all at once, faster than its lifetime in the atmosphere (about a decade) or in an ongoing, sustained release that lasts for longer than that.

When methane is released chronically, over decades, the concentration in the atmosphere will rise to a new equilibrium value. It won’t keep rising indefinitely, like CO₂ would, because methane degrades while CO₂ essentially just accumulates. Methane degrades into CO₂, in fact, so in simulations I did (Archer and Buffett, 2005) the radiative forcing from the elevated methane concentration throughout a long release was about matched by the radiative forcing from the extra CO₂ accumulating in the atmosphere from the methane as a carbon source. In the figure below, the dashed lines are from a simulation of a fossil fuel CO₂ release, and the solid lines are the same model but with an added methane hydrate feedback. The radiative forcing from the methane combines the CH4 itself which only persists during the time of the methane release, plus the added CO₂ in the atmosphere, which persists throughout the simulation of 100,000 years.

The possibility of a catastrophic release is of course what gives methane its power over the imagination (of journalists in particular it seems). A submarine landslide might release a Gigaton of carbon as methane (Archer, 2007), but the radiative effect of that would be small, about equal in magnitude (but opposite in sign) to the radiative forcing from a volcanic eruption. Detectable perhaps but probably not the end of humankind as a species.

What could happen to methane in the Arctic?

The methane bubbles coming from the Siberian shelf are part of a system that takes centuries to respond to changes in temperature. The methane from the Arctic lakes is also potentially part of a new, enhanced, chronic methane release to the atmosphere. Neither of them could release a catastrophic amount of methane (hundreds of Gtons) within a short time frame (a few years or less). There isn’t some huge bubble of methane waiting to erupt as soon as its roof melts.

And so far, the sources of methane from high latitudes are small, relative to the big player, which is wetlands in warmer climes. It is very difficult to know whether the bubbles are a brand-new methane source caused by global warming, or a response to warming that has happened over the past 100 years, or whether plumes like this happen all the time. In any event, it doesn’t matter very much unless they get 10 or 100 times larger, because high-latitude sources are small compared to the tropics.

Methane as past killing agent?

Mass extinctions like the end-Permean and the PETM do typically leave tantalizing spikes in the carbon isotopic records preserved in limestones and organic carbon. Methane has an isotopic signature, so any methane hijinks would be recorded in the carbon isotopic record, but so would changes in the size of the living biosphere, soil carbon pools such as peat, and dissolved organic carbon in the ocean. The end-Permean extinction is particularly mysterious, and my impression is that the killing mechanism for that is still up for grabs. Methane is also one of the usual suspects for the PETM, which consisted of about 100,000 years of isotopically light carbon, which is thought to be due to release of some biologically-produced carbon source, similar to the way that fossil fuel CO₂ is lightening the carbon isotopes of the atmosphere today, in concert with really warm temperatures. I personally believe that the combination of the carbon isotopes and the paleotemperatures pretty much rules out methane as the original carbon source (Pagani et al., 2006), although Gavin draws an opposite conclusion, which we may hash out in some future post. In any case, the 100,000-year duration of the warming means that the greenhouse agent through most of the event was CO₂, not methane.

Could there be a methane runaway feedback?.

The “runaway greenhouse effect” that planetary scientists and climatologists usually call by that name involves water vapor. A runaway greenhouse effect involving methane release (such as invoked here) is conceptually possible, but to get a spike of methane concentration in the air it would have to released more quickly than the 10-year lifetime of methane in the atmosphere. Otherwise what you’re talking about is elevated methane concentrations, reflecting the increased source, plus the radiative forcing of that accumulating CO₂. It wouldn’t be a methane runaway greenhouse effect, it would be more akin to any other carbon release as CO₂ to the atmosphere. This sounds like semantics, but it puts the methane system into the context of the CO₂ system, where it belongs and where we can scale it.

So maybe by the end of the century in some reasonable scenario, perhaps 2000 Gton C could be released by human activity under some sort of business-as-usual scenario, and another 1000 Gton C could come from soil and methane hydrate release, as a worst case. We set up a model of the methane runaway greenhouse effect scenario, in which the methane hydrate inventory in the ocean responds to changing ocean temperature on some time scale, and the temperature responds to greenhouse gas concentrations in the air with another time scale (of about a millennium) (Archer and Buffett, 2005). If the hydrates released too much carbon, say two carbons from hydrates for every one carbon from fossil fuels, on a time scale that was too fast (say 1000 years instead of 10,000 years), the system could run away in the CO₂ greenhouse mode described above. It wouldn’t matter too much if the carbon reached the atmosphere as methane or if it just oxidized to CO₂ in the ocean and then partially degassed into the atmosphere a few centuries later.

The fact that the ice core records do not seem full of methane spikes due to high-latitude sources makes it seem like the real world is not as sensitive as we were able to set the model up to be. This is where my guess about a worst-case 1000 Gton from hydrates after 2000 Gton C from fossil fuels in the last paragraph comes from.

On the other hand, the deep ocean could ultimately (after a thousand years or so) warm up by several degrees in a business-as-usual scenario, which would make it warmer than it has been in millions of years. Since it takes millions of years to grow the hydrates, they have had time to grow in response to Earth’s relative cold of the past 10 million years or so. Also, the climate forcing from CO₂ release is stronger now than it was millions of years ago when CO₂ levels were higher, because of the band saturation effect of CO₂ as a greenhouse gas. In short, if there was ever a good time to provoke a hydrate meltdown it would be now. But “now” in a geological sense, over thousands of years in the future, not really “now” in a human sense. The methane hydrates in the ocean, in cahoots with permafrost peats (which never get enough respect), could be a significant multiplier of the long tail of the CO₂, but will probably not be a huge player in climate change in the coming century.

Could methane be a point of no return?

Actually, releasing CO₂ is a point of no return if anything is. The only way back to a natural climate in anything like our lifetimes would be to anthropogenically extract CO₂ from the atmosphere. The CO₂ that has been absorbed into the oceans would degas back to the atmosphere to some extent, so we’d have to clean that up too. And if hydrates or peats contributed some extra carbon into the mix, that would also have to be part of the bargain, like paying interest on a loan.

Conclusion

It’s the CO₂, friend.

References

1. D. Archer, "Methane hydrate stability and anthropogenic climate change", Biogeosciences, vol. 4, 2007, pp. 521-544. DOI.
2. N. Shakhova, I. Semiletov, I. Leifer, A. Salyuk, P. Rekant, and D. Kosmach, "Geochemical and geophysical evidence of methane release over the East Siberian Arctic Shelf", Journal of Geophysical Research, vol. 115, 2010. DOI.
3. N. Shakhova, "The distribution of methane on the Siberian Arctic shelves: Implications for the marine methane cycle", Geophysical Research Letters, vol. 32, 2005. DOI.
4. G.K. Westbrook, K.E. Thatcher, E.J. Rohling, A.M. Piotrowski, H. Pälike, A.H. Osborne, E.G. Nisbet, T.A. Minshull, M. Lanoisellé, R.H. James, V. Hühnerbach, D. Green, R.E. Fisher, A.J. Crocker, A. Chabert, C. Bolton, A. Beszczynska-Möller, C. Berndt, and A. Aquilina, "Escape of methane gas from the seabed along the West Spitsbergen continental margin", Geophysical Research Letters, vol. 36, 2009. DOI.
5. M.T. Reagan, and G.J. Moridis, "Large-scale simulation of methane hydrate dissociation along the West Spitsbergen Margin", Geophysical Research Letters, vol. 36, 2009. DOI.
6. D. Archer, "Time-dependent response of the global ocean clathrate reservoir to climatic and anthropogenic forcing", Geochemistry Geophysics Geosystems, vol. 6, 2005. DOI.
7. M. Pagani, K. Caldeira, D. Archer, and J.C. Zachos, "ATMOSPHERE: An Ancient Carbon Mystery", Science, vol. 314, 2006, pp. 1556-1557. DOI.