Dennis Bray and Hans von Storch have been making surveys of climate scientists for a number of years with the reasonable aim of seeing what the community thinks (about IPCC, climate change, attribution etc). They have unfortunately not always been as successful as one might like - problems have ranged from deciding who is qualified to respond; questions that were not specific enough or that could be interpreted in very different ways; to losing control of who answered the questionnaire (one time the password and website were broadcast on a mailing list of climate 'sceptics'). These problems have meant that the results were less useful than they could have been and in fact have occasionally been used to spread disinformation. How these surveys are used obviously plays into how willing scientists are to participate, since if your answers are misinterpreted once, you will be less keen next time. Others have attempted similar surveys, with similar problems.

As people should know, designing truly objective surveys is very tricky. However, if you are after a specific response, it's easy to craft questions that will favour your initial bias. We discussed an egregious example of that from Steven Milloy a while ago. A bigger problem is not overt bias, but more subtle kinds - such as assuming that respondents have exactly the same background as the questioners and know exactly what you are talking about, or simply using questions that don't actually tell you want you really want to know. There are guides available to help in crafting such surveys which outline many of the inadvertent pitfalls.

Well, Bray and von Storch have sent out a new survey.

The questions can be seen here (pdf) (but no answers, so you can't cheat!), and according to Wikipedia, the survey respondents are controlled so that each anonymised invite can only generate one response. Hopefully therefore, the sampling will not be corrupted as in past years (response rates might still be a problem though). However, the reason why we are writing this post is to comment on the usefulness of the questions. Unfortunately, our opinion won't change anything (since the survey has already gone out), but maybe it will help improve the interpretations, and any subsequent survey.

There are too many questions in this survey to go over each one in detail, and so we'll just discuss a few specific examples (perhaps the comments can address some of the others). The series of questions Q15 through Q17, typify a key issue - precision. Q15 asks whether the "current state of scientific knowledge is developed well enough to allow for a reasonable assessment of the effects of turbulence, surface albedo, etc..". But the subtext "well enough for what?" is not specified. Global energy balance? regional weather forecasting? Climate sensitivity? Ocean circulation? Thus any respondent needs to form their own judgment about what the question is referring to. For instance, turbulence is clearly a huge scientific challenge, but how important is it in determining climate sensitivity? or radiative transfer? Not very. But for ocean heat transports, it might very well be key. By aggregating multiple questions in one and not providing enough other questions to determine what the respondent means exactly, the answers to these questions will be worth little.

The notion of 'temperature observations' used in Q16 and Q17 is similarly undefined. Do they mean the global average temperature change over the 20th Century, or the climatology of temperature at a regional or local scale? Or it's variability? You might think the first is most relevant, but the question is also asked about 'precipitation observations' for which a century-scale global trend simply doesn't exist. Therefore it must be one of the other options. But which one? Asking about what the ability of models is for modelling the next 10 years is similarly undefined, and in fact unanswerable (since we don't know how well they will do). Implicit is an assumption that models are producing predictions (which they aren't - though at least that is vaguely addressed in questions 45 and 46). What 'extreme events' are being referred to in the last part? Tornadoes? (skill level zero), heat waves (higher), drought (lower), Atlantic hurricanes (uncertain). By being imprecise the likely conclusion that respondents feel that global climate models lack the ability to model extreme events is again meaningless.

Q52 is a classic example of a leading question. "Some scientists present extreme accounts of catastrophic impacts related to climate change in a popular format with the claim that it is their task to alert the public. How much do you agree with this practice?" There is obviously only one sensible answer (not at all). However, the question neither defines what the questioners mean by 'extreme' or 'catastrophic', or who those 'scientists' might be or where they have justified such practices. The conclusion will be that the survey shows that most scientists do not approve of presenting extreme accounts of catastrophic impacts in popular formats with the aim of alerting the public. Surprise! A much more nuanced question could have been asked if actual examples were used. That would have likely found that what is considered 'extreme' varies widely and that there is plenty of support for public discussions of potential catastrophes (rapid sea level rise for instance) and the associated uncertainties. The implication of this question will be that no popular summaries can do justice to the uncertainties inherent in the science of abrupt change. Yet this is not likely to have been the answer had that question been directly addressed. Instead, a much more nuanced (and interesting) picture would have emerged.

Two questions of some relevance to us are Q61 and Q62, which ask whether making discussions of climate science open to potentially everyone through the use of "blogs on the w.w.w." is a good or bad idea, and whether the level of discussion on these blogs is any good. These questions are unfortunately very poorly posed. Who thinks that anyone has any control over what gets discussed on blogs in general? The issue is not whether that discussion should take place (it surely will), it is whether scientists should participate or not. If all blogs are considered, then obviously the quality on average is abysmal (sorry blogosphere!). If the goal of the question was to be able to say that the level of discussion on specific blogs is good or not, then specific questions should have been asked (for instance a list of prominent blogs could have been rated). As it is, the conclusion will be that discussion of climate science on blogs on the w.w.w. is a good idea but the discussion is thought to be poor. But that is hardly news.

One set of questions (Q68+Q69) obviously come from a social rather than a climate scientist: Q68 asks whether science has as its main activity to falsify or verify existing hypothesis or something else; and Q69 whether the role of science tends towards the deligitimization or the legitimization of existing 'facts' or something else. What is one to make of them? There are shades of Karl Popper and social constructivism in there, but we'd be very surprised if any working scientist answered anything other than 'other'. Science and scientists generally want to find out things that people didn't know before - which mostly means choosing between hypotheses and both examining old 'facts' as well as creating new ones. Even the idea that one fact is more legitimate than another is odd. If a 'fact' isn't legitimate, then why is it a fact at all? Presumably this is all made clear in some science studies text book (though nothing comes up in google), but our guess is that most working scientists will have no idea what is really behind this. You would probably want to have a whole survey just devoted to how scientists think about what they do to get anything useful from this.

To summarise, we aren't in principle opposed to asking scientists what they think, but given the track history of problems with these kinds of surveys (and their remaining flaws), we do suggest that they be done better in future. In particular, we strongly recommend that in setting up future surveys, the questions should be openly and widely discussed - on a wiki or a blog - before the surveys are sent out. There are a huge number of sensible people out there whose expertise could help in crafting the questions to improve both their precision and usefulness.

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What reduces emissions more?
A. Someone swapping their old SUV (which gets 12 miles per gallon) for a hybrid version (18 mpg) or
B. someone upgrading their 25 mpg compact to a new 46 mpg Prius?
(ignore for a minute manufacturing issues or driving habits and assume the miles driven are the same).

The surprising answer (for those who don't work it out) is A. It's easy enough to see why this is the case. If the driving distance is 100 miles, then for case A the saving in fuel used (and hence emissions) is 100/12-100/18 = 2.8 gallons, while for B, you have 100/25-100/46 = 1.8 gallons. The confusion arises because people like to think linearly about numbers, not inversely, and so tend to assume that a similar change in mpg has a similar impact on fuel usage. This is not however the case - improvements in efficiency at the low end of the scale are much more useful at reducing emissions. This is actually a very general point - when trying to raise efficiency it is always sensible to start with the least efficient processes.

This confusion got some attention a couple of months ago after a piece that was published in Science by Larrick and Soll. They tested peoples instinctive reactions to changes in mpg numbers and found that people very often got it wrong, leading to less than optimal decisions. They also tested a different way of giving fuel usage information (the number of gallons used per mile), and since this is linear in emissions, people made the correct judgment much more often (it's worth noting that the standard in most of Europe is already litres per 100 km). Rewritten in those terms, the choices above become:

A. Someone swapping their old SUV (which takes 8.3 gallons to go 100 miles) for a hybrid version (5.6 gallons/100 miles) or
B. someone upgrading their 4 gallons/100 miles compact to a new 2.2 gallons/100 mile Prius?

Much easier, right? The authors of the Science piece are trying hard to get US manufacturers and the EPA to switch over from mpg to this new standard (though they prefer gallons/10,000 miles). It all seems eminently sensible to us.

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This year's edition of The Effect includes research that is supporting climate change policy in the EU, the UK, Mexico, China, Burkina Faso, Uganda, Tanzania, South Africa, major cities, coastal England, and at the United Nations.
Hard copies are available please email:

tyndall@uea.ac.uk

In a recent post about sea level rise, we highlighted a paper by the University of Colorado's Tad Pfeffer and others in which they show that one can rule out more than 2 meters of sea level rise in the next century. While we liked the paper very much, we also complained that Pfeffer and colleagues had created a bit of a straw man, by implying that it had been seriously proposed that Greenland's near term contribution to sea level rise could be much larger than that. In fact (we said), none of us in the climate science community ever took such ideas seriously, even if the popular press thought we did. Tad responds by pointing out that in fact there is published work attributing considerable likelihood to such extreme scenarios, and that there are numerous studies that at the very least strong imply it. He also reminded me that their paper actually rules out a contribution of more than about 50 cm from Greenland, significantly below some other recent published estimates. That makes their work even more important, since there are several publications that definitely consider upwards of one meter (from Greenland alone) by 2100 to be plausible. Pfeffer et al. conclude that that is simply not the case (at least in their informed view). Still, we remind readers that our chief complaint was that Pfeffer et al.'s work was taken by many in the media as a downward revision to sea level rise estimates, whereas in fact most informed estimates had put an upper limit well below that. See our earlier post on the IPCC Sea Level numbers.

In any case. Pfeffer et al'.s response to our post follows below. Fair enough.

A response to RealClimate’s post on our paper about sea level rise

W.T. Pfeffer, J.T. Harper, and S. O’Neel
15 September 2008

We have read with interest – and, we admit, surprise – the RealClimate post concerning our 5 September publication in Science entitled “Kinematic Constraints on 21st Century Sea Level Rise.” The source of our surprise, however, is probably not what the RealClimate authors imagine – we had fully expected a vigorous defense of very high rates of sea level rise (greater than 2 m/century), but not a denial that such rates had ever been hypothesized.

We do not state anywhere in our paper that 2m or more of SLR by 2100 has been published as a peer reviewed and “informed estimate”. We do state that this has been ‘inferred’ and ‘argued’ as a “viable 21st century scenario”. We believe there is value in constraining the upper limits to the role of ice dynamics in future SLR. And, from what we know about historical rates of SLR in conjunction with what ‘we know we don’t know’ about ice dynamics, we believe it is reasonable to ponder very high rates of SLR in the next century. However, we also believe that it is problematic to project such a ‘hypothesis’ as a supported theory without proper testing by the scientific method. The question raised by RC is whether or not this hypothesis has circulated within the scientific community.

In his 2007 paper (Environ. Res. Lett. 2(2007)) Hansen proposes a rate of sea level rise of “5 m this century.” This is hypothetical, but he is confident that it is a “far better estimate than a linear response”. This is accompanied by his statement that he finds it “almost inconceivable that BAU climate change would not yield a sea level change of the order of meters on the century timescale.” The provisional nature of his discussion is irrelevant; it is an explicit statement that 5 m of sea level rise in this century is a possibility he regards as viable, published in the scientific literature by the person who is arguably (and deservedly) the most visible and authoritative climate scientist in the world. No reader of this paper would assume that Hansen didn’t actually mean what he said. Hansen reinforced this idea in other publications and statements, including in his briefing to Congress on 23 June 2008 (“sea level rise of at least two meters is likely this century”). Our analysis specifically tested the likelihood of next-century sea level rise of more than 2 m, and Hansen explicitly hypothesized 5 m of sea level rise in this century.

Hansen has gone on record with specific numbers, but other published studies including the 2006 Overpeck and Otto-Bliesner Science papers left the upper limit open ended, and certainly implied it could be quite high. The fact that this idea was present in the scientific community was confirmed for us by 8 scientific presentations we gave on this topic in the past year (5 in the US, including the Fall 2007 AGU and 3 in Europe). At none of those talks did anyone in the audience question what high forecasts we were referring to. The comments we got back on our work were overwhelmingly positive, and were along the lines that what we had presented was a good next step – both to move past the IPCC’s low sea level forecasts, and as a response to the persistent hypotheses of very high rates of sea level rise that were circulating. Criticisms, where they were voiced, were largely that we were underestimating the power of dynamics and that rates of sea level rise well in excess of 2 m/century might occur in spite of our conclusions.

We agree that the media coverage of our paper (as well as others before it) has undesirable side effects. Wherever we had the opportunity we pressed media writers not to use terms like “exaggerated” or “high sea level forecasts debunked,” and we have consistently stressed that our results indicate a very significant sea level rise and are no justification for any kind of complacency. We have stressed that even our low end scenario of 0.8 m of SLR would have tremendous consequences. However, we stand by our statements that sea level rise at rates of substantially more than 2 m this century were in fact put forward as a likely possibility.

Earlier this summer Andy Revkin published a piece in the New York Times about what he has termed the “Whiplash Effect”: confusion created in the public mind by media coverage of rapidly evolving scientific ideas. There has certainly been some whiplash in this case. However it is others who cracked the whip. We have simply refused to let go of the other end.

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Guest commentary by Spencer R. Weart, American Institute of Physics

I often get emails from scientifically trained people who are looking for a straightforward calculation of the global warming that greenhouse gas emissions will bring. What are the physics equations and data on gases that predict just how far the temperature will rise? A natural question, when public expositions of the greenhouse effect usually present it as a matter of elementary physics. These people, typically senior engineers, get suspicious when experts seem to evade their question. Some try to work out the answer themselves (Lord Monckton for example) and complain that the experts dismiss their beautiful logic.

The engineers' demand that the case for dangerous global warming be proved with a page or so of equations does sound reasonable, and it has a long history. The history reveals how the nature of the climate system inevitably betrays a lover of simple answers.

The simplest approach to calculating the Earth's surface temperature would be to treat the atmosphere as a single uniform slab, like a pane of glass suspended above the surface (much as we see in elementary explanations of the "greenhouse" effect). But the equations do not yield a number for global warming that is even remotely plausible. You can't work with an average, squashing together the way heat radiation goes through the dense, warm, humid lower atmosphere with the way it goes through the thin, cold, dry upper atmosphere. Already in the 19th century, physicists moved on to a "one-dimensional" model. That is, they pretended that the atmosphere was the same everywhere around the planet, and studied how radiation was transmitted or absorbed as it went up or down through a column of air stretching from ground level to the top of the atmosphere. This is the study of "radiative transfer," an elegant and difficult branch of theory. You would figure how sunlight passed through each layer of the atmosphere to the surface, and how the heat energy that was radiated back up from the surface heated up each layer, and was shuttled back and forth among the layers, or escaped into space.

When students learn physics, they are taught about many simple systems that bow to the power of a few laws, yielding wonderfully precise answers: a page or so of equations and you're done. Teachers rarely point out that these systems are plucked from a far larger set of systems that are mostly nowhere near so tractable. The one-dimensional atmospheric model can't be solved with a page of mathematics. You have to divide the column of air into a set of levels, get out your pencil or computer, and calculate what happens at each level. Worse, carbon dioxide and water vapor (the two main greenhouse gases) absorb and scatter differently at different wavelengths. So you have to make the same long set of calculations repeatedly, once for each section of the radiation spectrum.

It was not until the 1950s that scientists had both good data on the absorption of infrared radiation, and digital computers that could speed through the multitudinous calculations. Gilbert N. Plass used the data and computers to demonstrate that adding carbon dioxide to a column of air would raise the surface temperature. But nobody believed the precise number he calculated (2.5ºC of warming if the level of CO₂ doubled). Critics pointed out that he had ignored a number of crucial effects. First of all, if global temperature started to rise, the atmosphere would contain more water vapor. Its own greenhouse effect would make for more warming. On the other hand, with more water vapor wouldn't there be more clouds? And wouldn't those shade the planet and make for less warming? Neither Plass nor anyone before him had tried to calculate changes in cloudiness. (For details and references see this history site.)

Fritz Möller followed up with a pioneering computation that took into account the increase of absolute humidity with temperature. Oops… his results showed a monstrous feedback. As the humidity rose, the water vapor would add its greenhouse effect, and the temperature might soar. The model could give an almost arbitrarily high temperature! This weird result stimulated Syukuro Manabe to develop a more realistic one-dimensional model. He included in his column of air the way convective updrafts carry heat up from the surface, a basic process that nearly every earlier calculation had failed to take into account. It was no wonder Möller's surface had heated up without limit: his model had not used the fact that hot air would rise. Manabe also worked up a rough calculation for the effects of clouds. By 1967, in collaboration with Richard Wetherald, he was ready to see what might result from raising the level of CO₂. Their model predicted that if the amount of CO₂ doubled, global temperature would rise roughly two degrees C. This was probably the first paper to convince many scientists that they needed to think seriously about greenhouse warming. The computation was, so to speak, a "proof of principle."

But it would do little good to present a copy of the Manabe-Wetherald paper to a senior engineer who demands a proof that global warming is a problem. The paper gives only a sketch of complex and lengthy computations that take place, so to speak, offstage. And nobody at the time or since would trust the paper's numbers as a precise prediction. There were still too many important factors that the model did not include. For example, it was only in the 1970s that scientists realized they had to take into account how smoke, dust and other aerosols from human activity interact with radiation, and how the aerosols affect cloudiness as well. And so on and so forth.

The greenhouse problem was not the first time climatologists hit this wall. Consider, for example, attempts to calculate the trade winds, a simple and important feature of the atmosphere. For generations, theorists wrote down the basic equations for fluid flow and heat transfer on the surface of a rotating sphere, aiming to produce a precise description of our planet's structure of convective cells and winds in a few lines of equations… or a few pages… or a few dozen pages. They always failed. It was only with the advent of powerful digital computers in the 1960s that people were able to solve the problem through millions of numerical computations. If someone asks for an "explanation" of the trade winds, we can wave our hands and talk about tropical heating, the rotation of the earth and baroclinic instability. But if we are pressed for details with actual numbers, we can do no more than dump a truckload of printouts showing all the arithmetic computations.

I'm not saying we don't understand the greenhouse effect. We understand the basic physics just fine, and can explain it in a minute to a curious non-scientist. (Like this: greenhouse gases let sunlight through to the Earth's surface, which gets warm; the surface sends infrared radiation back up, which is absorbed by the gases at various levels and warms up the air; the air radiates some of this energy back to the surface, keeping it warmer than it would be without the gases.) For a scientist, you can give a technical explanation in a few paragraphs. But if you want to get reliable numbers - if you want to know whether raising the level of greenhouse gases will bring a trivial warming or a catastrophe - you have to figure in humidity, convection, aerosol pollution, and a pile of other features of the climate system, all fitted together in lengthy computer runs.

Physics is rich in phenomena that are simple in appearance but cannot be calculated in simple terms. Global warming is like that. People may yearn for a short, clear way to predict how much warming we are likely to face. Alas, no such simple calculation exists. The actual temperature rise is an emergent property resulting from interactions among hundreds of factors. People who refuse to acknowledge that complexity should not be surprised when their demands for an easy calculation go unanswered.

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… is the question people have been putting a lot of thought into since the IPCC AR4 report came out. We analysed what was in the report quite carefully at the time and pointed out that the allowance for dynamic ice sheet processes was very uncertain, and actually precluded setting a upper limit on what might be expected. The numbers that appeared in some headlines (up to 59 cm by 2100) did not take that uncertainty into account.

In a more recent paper, our own Stefan Rahmstorf used a simple regression model to suggest that sea level rise (SLR) could reach 0.5 to 1.4 meters above 1990 levels by 2100, but this did not consider individual processes like dynamic ice sheet changes, being only based on how global sea level has been linked to global warming over the past 120 years. As Stefan discussed, any non-linear or threshold behavior of ice sheets could lead to sea level rising faster than this estimate. Thus, otherwise quite conservative voices have been stressing the 'unknown unknown' nature of this problem and suggesting that, based on paleo-data (for instance), it was really hard to rule out sea level rises measured in feet, and not in inches. (Note too, the SLR is very much a lagging indicator, and will continue for centuries past the time that atmospheric temperatures have stabilised).

The first paper to really try and assess the future limits on dynamic ice sheet loss appeared in Science this week. Pfeffer et al looked at the exit glaciers for Greenland and West Antarctica and made some back of the envelope calculations of how quickly the ice sheets could dynamically drain.

Good news: they rule out more than 2 meters of sea level coming from Greenland alone in the next century. This is however more than anyone has ever suggested and would be comparable to the amount that disappeared at the Eemian (125,000 years ago) (see this post for more on that).

Bad news: they can't rule out up to 2 meters in total.

In summary, they estimate that including dynamic ice sheet processes gives projected SLR at 2100 somewhere in the 80 cm to 2 meter range, and suggest that 80 cm should be the 'default' value. This is remarkable in a number of ways - first, these are the highest estimates of sea level rise by 2100 that has been published in the literature to date, and secondly, while they don't take into account the full uncertainty in other aspects of sea level rise considered by IPCC, their numbers are significantly higher in any case. And this week the Dutch 'Delta Commission' published its estimate of sea level rise that the Dutch need to plan for (p111): 55 to 110 cm globally and a bit more for Holland, based on a large number of scientists' input. [Clarifying update: this is meant to be a "high end estimate".]

Lest readers think this is no big deal, the estimates for the number of people who would be affected by 1 meter of sea level rise is more than 100 million - mainly in Asia. Of some recent relevance is the fact that the storm surge caused by Gustav in New Orleans was within 1 foot of the top of the levees. Another 3 ft caused by global sea level rise would have put a lot more water into the 'bowl'.

Thus better estimates of sea level rise from ice sheets remain a high priority for the climate community. More sophisticated models and deeper understanding are coming along and hopefully those results will be out soon.

We were going to leave it at that, but we've just seen the initial media coverage where this result is being spun as a downgrading of predictions! (exemplified by this Reuters piece, drawing mainly from the U. Colorado press release). This is completely backwards. We stress that no-one (and we mean no-one) has published an informed estimate of more than 2 meters of sea level rise by 2100. Tellingly, the statement in the paper that suggests otherwise has no reference.

There have certainly been incorrect assertions and headlines implying that 20 ft of sea level by 2100 was expected, but they are mostly based on a confusion of a transient rise with the eventual sea level rise which might take hundreds to thousands of years. And before someone gets up to say Al Gore, we'll point out preemptively that he made no prediction for 2100 or any other timescale. The nearest thing I can find is Jim Hansen who states that "it [is] almost inconceivable that BAU climate change would not yield a sea level change of the order of meters on the century timescale". But that is neither a specific prediction for 2100, nor necessarily one that is out of line with the Pfeffer et al's bounds.

Thus, this media reporting stands as a classic example of how scientists get caught up trying to counter supposed myths but end up perpetuating others, and miss an opportunity to actually educate the public. The problem is not that people think that we will get 6 meters of sea level rise this century, it's that they don't think there'll be anything to speak of. Headlines like that in the Reuters piece (or National Geographic) are therefore doing a fundamental disservice to the public understanding of the problem.

Update: Marc Roberts sends along this cartoon illustrating the problem… (click for full size).

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What makes science different from politics?

That's not the start of a joke, but it is a good jumping off point for a discussion of the latest publication on paleo-reconstructions of the last couple of millennia. As has been relatively widely reported, Mike Mann and colleagues (including Ray Bradley and Malcolm Hughes) have a new paper out in PNAS with an update of their previous work. And this is where the question posed above comes in: the difference is that with time scientists can actually make progress on problems, they don't just get stuck in an endless back and forth of the same talking points.

We discussed what would be required in an update of these millennial reconstructions a few months back and the main principles remain true now. You need proxies that are a) well-dated, b) have some fidelity to a climate variable of interest, c) have been calibrated to those variable(s), d) that are then composited together somehow, and e) that the composite has been validated against the instrumental record.

The number of well-dated proxies used in the latest paper is significantly greater than what was available a decade ago: 1209 back to 1800; 460 back to 1600; 59 back to 1000 AD; 36 back to 500 AD and 19 back to 1 BC (all data and code is available here). This is compared with 400 or so in MBH99, of which only 14 went back to 1000 AD. The increase in data availability is a pretty remarkable testament to the increased attention that the paleo-community has started to pay to the recent past - in part, no doubt, because of the higher profile this kind of reconstruction has achieved. The individual data-gatherers involved should be applauded by all.

The increase in proxy records allows a whole bunch of new things to be done. First off, the importance of tree rings can be tested more robustly. With the original MBH98 proxies, there was only enough other data to go back to 1760 if you left out the tree rings. The match was pretty good over multi-decadal periods, but the interannual variability was much larger without tree-rings. Now though, the Northern hemisphere land temperature reconstructions without tree rings can go back to 1500 AD or 1000 AD depending on which of two methodologies are used. For the NH land and ocean target, it's even possible to get a coherent non-tree ring reconstruction back to 700 AD! As before, there are some differences (notably in the 17th Century where the tree rings indicate colder temperatures), but the recent warming is anomalous regardless.

Secondly, you can screen records and pick targets more finely: do you want only records that match local temperatures? Done. You want to get a handle on global and southern hemisphere means as well as the northern hemisphere? Done. Other screens could easily be implemented.

The two methodologies used themselves span the range of different approaches that people have used. 'Composite and scale' (CPS) is perhaps the simplest method - it is basically an average of all the temperature proxies scaled to the target time series. The other method is denoted 'Error in variables' (EIV) in this paper, but is really a simplified application of the RegEM climate field reconstruction method used in a couple of more recent papers. It is essentially a fancy multiple regression to the target time series that can incorporate non-local proxies as well. The point of using two methods is to demonstrate what is, and what is not, robust, and to give an idea of what the structural uncertainty in these estimates is - something not easily calculated using standard statistics. That uncertainty is clearly larger as you go back in time, and larger still for the southern hemisphere.

Other improvements over previous work are that more proxy data sets go past 1980, and so calibration up to 1995 is possible. That allows more of the recent trends to feed into the calibration and highlights the so-called divergence problem in some (but not all) recent tree-ring records. That divergence is significantly lessened without tree-rings or using the EIV method.

Figure: Spaghetti plot of the new reconstructions over a) 1800 and b) 1000 years
along with selected older ones for comparison.

So what does it all mean? First off, this paper (like MBH98 before it) is not an attribution study. That means that the reasons for any of the ups-and-downs in the records are not demonstrated by these papers alone. Attribution of the recent trends (as discussed in IPCC AR4) to anthropogenic effects has mostly focussed on the last 150 years and did not use any paleo-data. Nonetheless, there have been a couple of key studies that have used this kind of data along with simple energy balance models (Crowley, 2000; Hegerl et al, 2006 for instance) and it will be interesting to see if this new reconstruction will make any difference to their conclusions.

Secondly, in comparison with previous reconstructions, the current analysis does not provide many surprises. Medieval times are warmer than the Little Ice Age as before, and a little warmer using the EIV method than was the case in MBH99. The differences in the 11th Century are on the order of a couple of tenths of a degree - well within the published error bars in IPCC TAR though. Interestingly, there are quite rapid and strong drops in temperature near 1100 AD and around 1350 AD which may make interesting case studies for attribution to solar or volcanic forcings in future. Overall, there are a few more wiggles than before, but basically nothing much has changed. (Though one should always be aware of the maxim that one person's noise is another person's signal).

Finally, while the headline numbers 'likely warmest since XXXX' are of some contextual value, they aren't the real point of this kind of study. Most of the interesting work - looking for patterns associated with solar forcing say - will start when the spatial patterns of temperature change start to be discerned - and that is still a work in progress.

So, onto the inevitable discussion! One test of whether that discussion is more political than scientific will be the extent to which people acknowledge the progress that has been made. Repetitions of tired and oft-debunked one-liners will be telling!

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Kevin Anderson and Alice Bows have today published a rigorous analysis of where modern-day emissions might be heading

Their paper, published by the Royal Society, is the first to look at global emissions since 2000 and so includes the rapidly industrialising economies of Asia and South America and incorporates recent deforestation, and spans the six 'main' greenhouse gases. They conclude "By focussing on long-term emission targets, such as 50% by 2050, climate policy has essentially ignored the crucial importance of current emission trends and their impact on cumulative emissions. As a consequence, although we should aim to reduce global emissions in line with a 2ºC target, adaptation policy must focus on climate change impacts associated with 4ºC or more."