Guest commentary by Barry R. Bickmore, Brigham Young University
If you look around the websites dedicated to debunking mainstream climate science, it is very common to find Lord Christopher Monckton, 3rd Viscount of Brenchley, cited profusely. Indeed, he has twice testified about climate change before committees of the U.S. Congress, even though he has no formal scientific training. But if he has no training, why has he become so influential among climate change contrarians? After examining a number of his claims, I have concluded that he is influential because he delivers “silver bullets,” i.e., clear, concise, and persuasive arguments. The trouble is his compelling arguments are often constructed using fabricated facts. In other words, he makes it up. (Click here to see a number of examples by John Abraham, here for a few by myself, and here for some by Tim Lambert).
Here I’m going to examine some graphs that Lord Monckton commonly uses to show that the IPCC has incorrectly predicted the recent evolution of global atmospheric CO2 concentration and mean temperature. A number of scientists have already pointed out that Monckton’s plots of “IPCC predictions” don’t correspond to anything the IPCC ever predicted. For example, see comments by Gavin Schmidt (Monckton’s response here,) John Nielsen-Gammon (Monckton’s response here,) and Lucia Liljegren. Monckton is still happily updating and using the same graphs of fabricated data, so why am I bothering to re-open the case?
My aim is to more thoroughly examine how Lord Monckton came up with the data on his graphs, compare it to what the IPCC actually has said, and show exactly where he went wrong, leaving no excuse for anyone to take him seriously about this issue.
Atmospheric CO2 Concentration
By now, everyone who pays any attention knows that CO2 is an important greenhouse gas, and that the recent increase in global average temperature is thought to have been largely due to humans pumping massive amounts of greenhouse gases (especially CO2) into the atmosphere. The IPCC projects future changes in temperature, etc., based on projections of human greenhouse gas emissions. But what if those projections of greenhouse gas emissions are wildly overstated? Lord Monckton often uses graphs like those in Figs. 1 and 2 to illustrate his claim that “Carbon dioxide is accumulating in the air at less than half the rate the UN had imagined.”
Figure 1. Graph of mean atmospheric CO2 concentrations contrasted with Monckton’s version of the IPCC’s “predicted” values over the period from 2000-2100. He wrongly identifies the concentrations as “anomalies.” Taken from the Feb. 2009 edition of Lord Monckton’s “Monthly CO2 Report.”
Figure 2. Graph of mean atmospheric CO2 concentrations contrasted with Monckton’s version of the IPCC’s “predicted” values over the period from Jan. 2000 through Jan. 2009. Taken from the Feb. 2009 edition of Lord Monckton’s “Monthly CO2 Report.”
It should be noted that Lord Monckton faithfully reproduces the global mean sea surface CO2 concentration taken from NOAA, and the light blue trend line he draws through the data appears to be legitimate. Unfortunately, nearly everything else about the graphs is nonsense. Consider the following points that detail the various fantasies Monckton has incorporated into these two graphics.
Fantasy #1.
Lord Monckton claims the light blue areas on his graphs (Figs. 1 and 2) represent the IPCC’s predictions of atmospheric CO2 concentrations.
Reality #1.
The IPCC doesn’t make predictions of future atmospheric CO2 concentrations. And even if we ferret out what Lord Monckton actually means by this claim, he still plotted the data incorrectly.
The IPCC doesn’t really make predictions of how atmospheric CO2 will evolve over time. Rather, the IPCC has produced various “emissions scenarios” that represent estimates of how greenhouse gas emissions might evolve if humans follow various paths of economic development and population growth. The IPCC’s report on emissions scenarios states, “Scenarios are images of the future, or alternative futures. They are neither predictions nor forecasts. Rather, each scenario is one alternative image of how the future might unfold.” Lord Monckton explained via e-mail that he based the IPCC prediction curves “on the IPCC’s A2 scenario,which comes closest to actual global CO2 emissions at present” (2). In his “Monthly CO2 Report” he added, “The IPCC’s estimates of growth in atmospheric CO2 concentration are excessive. They assume CO2 concentration will rise exponentially from today’s 385 parts per million to reach 730 to 1020 ppm, central estimate 836 ppm, by 2100,” which is consistent with the A2 scenario. In other words, Monckton has picked one of several scenarios used by the IPCC and misrepresented it as a prediction. This is patently dishonest.
Monckton’s misrepresentation of the IPCC doesn’t end here, however, because he has also botched the details of the A2 scenario. The IPCC emissions scenarios are run through models of the Carbon Cycle to estimate how much of the emitted CO2 might end up in the atmosphere. A representative (i.e., “middle-of-the-road”) atmospheric CO2 concentration curve is then extracted from the Carbon Cycle model output, and fed into the climate models (AOGCMs) the IPCC uses to project possible future climate states. Figure 3 is a graph from the most recent IPCC report that shows the Carbon Cycle model output for the A2 emissions scenario. The red lines are the output from the model runs, and the black line is the “representative” CO2 concentration curve used as input to the climate models. I digitized this graph, as well, and found that the year 2100 values were the same as those cited by Monckton. (Monckton calls the model input the “central estimate.” )
Figure 3. Plot of atmospheric CO2 concentrations projected from 2000-2100 for the A2 emissions scenario, after the emissions were run through an ensemble of Carbon Cycle models. The red lines indicate model output, whereas the black line represents the “representative” response that the IPCC used as input into its ensemble of climate models (AOGCMs). Taken from Fig. 10.20a of IPCC AR4 WG1.
Now consider Figure 4, where I have plotted the A2 model input (black line in Fig. 3), along with the outer bounds of the projected atmospheric CO2 concentrations (outer red lines in Fig. 3). However, I have also plotted Monckton’s Fantasy IPCC predictions in the figure. The first thing to notice here is how badly Monckton’s central tendency fits the actual A2 model input everywhere in between the endpoints. Monckton’s central tendency ALWAYS overestimates the model input except at the endpoints. Furthermore, the lower bound of Monckton’s Fantasy Projections also overestimates the A2 model input before about the year 2030. What appears to have happened is that Lord Monckton chose the correct endpoints at 2100, picked a single endpoint around the year 2000-2002, and then made up some random exponential equations to connect the dots with NO REGARD for whether his lines had anything to do with what the IPCC actually had anywhere between.
Figure 4. Here the black lines represent the actual A2 input to the IPCC climate models (solid) and the upper and lower bounds of the projected CO2 concentrations obtained by running the A2 emissions scenario through an ensemble of Carbon Cycle models. This data was digitized from the graph in Fig. 3, but a table of model input concentrations of CO2 resulting from the different emissions scenarios can be found here. The red lines represent Monckton’s version of the IPCC’s “predicted” CO2 concentrations. The solid red line is his “central tendency”, while the dotted lines are his upper and lower bounds. Monckton’s data was digitized from the graph in Fig. 1.
John Nielsen-Gammon also pointed some of this out, but Lord Monckton responded:,
[Nielsen-Gammon] says my bounds for the 21st-century evolution of CO2 concentration are not aligned with those of the UN. Except for a very small discrepancy between my curves and two outliers among the models used by the UN, my bounds encompass the output of the UN’s models respectably, as the blogger’s own overlay diagram illustrates. Furthermore, allowing for aspect-ratio adjustment, my graph of the UN’s projections is identical to a second graph produced by the UN itself for scenario A2 that also appears to exclude the two outliers.
It is fair enough to point out that Fig. 10.26 in IPCC AR4 WG1 has a plot of the projected A2 CO2 concentrations that seems to leave out the outliers. However, Monckton’s rendition is still not an honest representation of anything the IPCC ever published. I can prove this by blowing up the 2000-2010 portion of the graph in Fig. 4. I have done this in Fig. 5, where I have also plotted the actual mean annual global CO2 concentrations for that period. The clear implication of this graph is that even if the A2 scenario did predict atmospheric CO2 evolution (and it doesn’t,) it would actually be a good prediction, so far. In Figures 1 and 2, Lord has simply fabricated data to make it seem like the A2 scenario is wrong.
Figure 5. This is a blow-up of the graph in Fig. 4 for the years 2000-2010. I have also added the annual global mean atmospheric CO2 concentrations (blue line), obtained from NOAA.
Fantasy #2.
Monckton claims that “for seven years, CO2 concentration has been rising in a straight line towards just 575 ppmv by 2100. This alone halves the IPCC’s temperature projections. Since 1980 temperature has risen at only 2.5 °F (1.5 °C) per century." In other words, he fit a straight line to the 2002-2009 data and extrapolated to the year 2100, at which time the trend predicts a CO2 concentration of 575 ppm. (See the light blue line in Fig. 1.)
Reality #2.
It is impossible to distinguish a linear trend from an exponential trend like the one used for the A2 model input over such a short time period.
I pointed out to Lord Monckton that it’s often very hard to tell an exponential from a linear trend over a short time period, e.g., the 7-year period shown in Fig. 2. He replied,
I am, of course, familiar with the fact that, over a sufficiently short period (such as a decade of monthly records), a curve that is exponential (such as the IPCC predicts the CO2 concentration curve to be) may appear linear. However, there are numerous standard statistical tests that can be applied to monotonic or near-monotonic datasets, such as the CO2 concentration dataset, to establish whether exponentiality is being maintained in reality. The simplest and most direct of these is the one that I applied to the data before daring to draw the conclusion that CO2 concentration change over the past decade has degenerated towards mere linearity. One merely calculates the least-squares linear-regression trend over successively longer periods to see whether the slope of the trend progressively increases (as it must if the curve is genuinely exponential) or whether, instead, it progressively declines towards linearity (as it actually does). One can also calculate the trends over successive periods of, say, ten years, with start-points separated by one year. On both these tests, the CO2 concentration change has been flattening out appreciably. Nor can this decay from exponentiality towards linearity be attributed solely to the recent worldwide recession: for it had become evident long before the recession began.
In other words, the slope keeps getting larger in an exponential trend, but stays the same in a linear trend. Monckton is right that you can do that sort of statistical test, but Tamino actually applied Monckton’s test to the Mauna Loa observatory CO2 data since about 1968 and found that the 10-year slope in the data has been pretty continuously rising, including over the last several years. Furthermore, look at the graph in Fig. 5, and note that the solid black line representing the A2 climate model input looks quite linear over that time period, but looks exponential over the longer timeframe in Fig. 4. I went to the trouble of fitting a linear trend line to the A2 model input line from 2002-2009 and obtained a correlation coefficient (R2) of 0.99967. Since a perfectly linear trend would have R2 = 1, I suggest that it would be impossible to distinguish a linear from an exponential trend like that followed by the A2 scenario in real, “noisy” data over such a short time period.
Temperature Projections
Atmospheric CO2 concentration wouldn’t be treated as such a big deal if it didn’t affect temperature; so of course Lord Monckton has tried to show that the Fantasy IPCC “predictions” of CO2 concentration he made up translate into overly high temperature predictions. This is what he has done in the graph shown in Fig. 6.
Figure 6. Lord Monckton’s plot of global temperature anomalies over the period January 2002 to January 2009. The red line is a linear trend line Monckton fit to the data, and the pink/white field represents his Fantasy IPCC temperature predictions. I have no idea what his base period is. Taken from the Feb. 2009 edition of Lord Monckton’s “Monthly CO2 Report.”.
FANTASY #3. Lord Monckton uses graphs like that in Fig. 6 to support his claim that the climate models (AOGCMs) the IPCC uses to project future temperatures are wildly inaccurate.
REALITY #3.
Monckton didn’t actually get his Fantasy IPCC predictions of temperature evolution from AOGCM runs. Instead, he inappropriately fed his Fantasy IPCC predictions of CO2 concentration into equations meant to describe the EQUILIBRIUM model response to different CO2 concentrations.
Monckton indicated to me (5) that he obtained his graph of IPCC temperature predictions by running his Fantasy CO2 predictions (loosely based on the A2 emissions scenario) through the IPCC’s standard equation for converting CO2 concentration to temperature change, which can be found here.
The problem is that the equation mentioned is meant to describe equilibrium model response, rather than the transient response over time. In other words, they take the standard AOGCMs, input a certain stabilized CO2 concentration, and run the models until the climate output stabilizes around some new equilibrium. But it takes some time for the model systems to reach the new equilibrium state, because some of the feedbacks in the system (e.g., heat absorption as the ocean circulates) operate on fairly long timescales. Therefore, it is absolutely inappropriate to use the IPCC’s equation to describe anything to do with time evolution of the climate system. When I brought this up to Lord Monckton, he replied that he knows the difference between equilibrium and transient states, but he figures the equilibrium calculation comes close enough. But since the IPCC HAS published time-series (rather than just equilibrium) model output for the A2 scenario (see Fig. 7,) why wouldn’t he just use that?
Figure 7. Ensemble AOGCM output for the A2 emissions scenario, taken from Fig. 10.5 of IPCC AR4 WG1.
The answer is that if Lord Monckton had used the time-series model output, he would have had to admit that the IPCC temperature projections are still right in the ballpark. In Fig. 8, I have digitized the outer bounds of the model runs in Fig. 7, and also plotted the HadCRUT3 global annual mean temperature anomaly over the same period. The bottom line is that Monckton has put the wrong data into the wrong equation, and (surprise!) he got the wrong answer.
Figure 8. The blue and green lines represent the upper and lower bounds of the global average temperature anomaly from AOGCM output for the A2 emissions scenario during the 2002-2010 period. The black line represents the HadCRUT3 global temperature anomalies for that timeframe, normalized to the same base period.
Summary
I have shown here that in order to discredit the IPCC, Lord Monckton produced his graphs of atmospheric CO2 concentration and global mean temperature anomaly in the following manner:
- He confused a hypothetical scenario with a prediction.
- He falsely reported the data from the hypothetical scenario he was confusing with a prediction.
- He plugged his false data into the wrong equation to obtain false predictions of time-series temperature evolution.
- He messed up the statistical analyses of the real data.
These errors compound into a rather stunning display of complete incompetence. But since all, or at least nearly all, of this has been pointed out to Monckton in the past, there’s just no scientifically valid excuse for this. He’s just making it up.
objective
Date: 1647
1 b : of, relating to, or being an object, phenomenon, or condition in the realm of sensible experience independent of individual thought and perceptible by all observers : having reality independent of the mind
3 a : expressing or dealing with facts or conditions as perceived without distortion by personal feelings, prejudices, or interpretation
from
http://www.merriam-webster.com/dictionary/objective
David B. Benson-
Thank you for that link. I was familiar with that information and indeed, one of the reasons why I did the analysis of the Mauna Loa data myself was to satisfy my own curiosity.
My professor encourages us to do the work ourselves where possible and not to simply rely upon what someone else, claiming to be an expert, states.
In doing the work myself, I have come to a better understanding about what the real world data says about increasing CO2 levels, such as the shape of the curve and the rate of change.
I also have some insight into why finer detail, such as that found in the monthly data, rather than annual data is so important.
Again, thank you for the link.
Re 402 Orkneygal – I see why you say you didn’t make a mistake, and – not having actually checked any math here, but there isn’t anything obvious to suggest you made a mistake. The point I believe Steve Metzler was making was that you may get a better fit to a relatively simple curve by first subtracting some value and then using the anomalies. Regarding monthly vs annual data, I’d just point out that not all of the annual cycle is necessarily from natural sources and sinks. I don’t know the relative importance of this, but there are some energy uses that are seasonal.
—
Re 351 sambo – wouldn’t the proper libertarian attitude be – ‘well, Alberta should’ve known better; they had economic incentive to investigate issues; they should’ve realized that issues of climate change and pollution would eventually put a damper on the profits realizable from such a project; the government shouldn’t subsidize their mistake’? (it may seem hypocritical or illogical to suggest the government shouldn’t protect the private sector (PS glossing over whatever public money went into this, as I’m not familiar with those specifics, it’s not really important to the point I’m making) from government actions, but if a government action is sensible and justified, the private sector really should just deal with it. Of course, changing the rules in the middle of the game does have some unfair impacts and some compensation might be allowed, but preferably in the form of offering Alberta different opportunities and help getting there, rather than exempting them from, for example, the full force of a tax or cap/trade and some specific regulations pertaining to extraction, etc.)
Here is a peer-reviewed study of loss of snowmass in the Antarctic, based on gravimetry:
http://www.sciencemag.org/cgi/content/full/311/5768/1754
Here is another:
http://rsta.royalsocietypublishing.org/content/364/1844/1637.abstract
I have now read that Antarctic ice is accumulating, that it is disappearing; that it is predicted to accumulate, and that it is predicted to disappear. All in the peer-reviewed literature. Today’s 3 papers are a sample.
Does anybody know what Antarctic ice is really doing (expanse seems to have increased recently) and what is really predicted according to AGW?
[Response: Try reading the papers. There is a difference between sea ice (floating and made in situ in the ocean) and the ice sheet (created by accumulating snow on the continent). – gavin]
Patric 027 @403-
Thank you for your comment.
Even the linear regression has R^2=0.9771, or R=0.9885 for the Mauna Loa monthly CO2 data beginning in 1958 through July 2010.
With values like these, it’s not clear to me why one would want to resort to modifying the raw data to then look at anomalies. Perhaps that might be useful with low R^2 values or where more sinusodial or random factors are at play. But in those cases I would suspect you would really want to use FFT, anyway.
Again, thank you for your comments.
http://friendsofginandtonic.org/files/867576d3dfe135ff8dcd26715bd86ac5-187.html
Apparently this link shows that an inquiry to the information officer at the house of lords has resulted in the truth coming out that Monckton never was a Lord and that they are looking into his misuse of the title and emblem.
#404–unhelpful link (unless one is paid up, I presume)–it just takes you to a generic “pay for access” page. If you’d like to post the name of the study, Septic, so we can at least read the abstract–?
#401–That’s my definition, too, DB, more or less–but appears not be that of Fox–IMO, at least. I suppose my sarcasm was unbecoming.
By the way (and OT, strictly speaking) I’ve got a summary/review of Gwynne Dyer’s “Climate Wars” out as of yesterday. It’s an interesting take on CC impacts, focussing primarily on possible social and military consequences. Interested readers can find it here:
http://hubpages.com/hub/Climate-Wars-A-Review
Re: Kevin McKinney @ 408 @ 17 August 2010 at 7:05 AM above:
Try this:
The Abstract can be found here.
Hope this helps!
The Yooper
Septic Matthew, Gavin (405), I’m confused. I read the abstract referenced by Septic, and with one minor exception it was clearly describing large loss of sheet/land-based ice. This seems contrary to Septic’s assertions, implications, and questions and opposite Gavin’s implication in 405. Am I just missing your points? Is Antarctic sheet ice, in total, increasing or decreasing? I seem to recall an RC thread that concluded it was increasing in total with a significant and opposing difference between large areas.
[Response: huh? The GRACE data are the most useful here and they show a net loss of Antarctic ice sheet mass. This loss is predominantly from WAIS, with EAIS roughly stable (increased accumulation, balanced by increased coastal loss). Do you have a cite for where we indicated otherwise? – gavin]
410 re 404 and other fantasies by Matthew the septic, who has conflated the study “Measurements of Time-Variable Gravity Show Mass Loss in Antarctica” into “a study of loss of snowmass in the Antarctic, based on gravimetry”. Don’t let his please say it ain’t so blinders confuse you Rod B.
Patrick 027 (#403)
I wouldn’t agree with you that they “should have known better” but I would probably agree with most of what you said there. As for my views, I’m a moderate conservative, which means I do think there is a role for government, although I don’t like when every solution for any problem is to reach for a new government program. I believe we need to be careful about how we implement policy because of the law of unintended consequences. I would support any plan that allows all regions to decarbonize their economy. I believe that we should reward hard work and not just transfer wealth because we think it should happen (which is how I see the current treaties being proposed).
Don’t forget, this is all political advice that I’m giving (freely) to someone who want’s to secure action on climate change. I believe the current arguments are causing more debate and scepticism than are actually needed, and are actually delaying action by being much more “hardline” than they need to be. That’s all my opinion however so take it how you want to.
I’d be happy to explain my position in more detail regarding Alberta, however not in this forum. Ask a moderator for my email and I’d be happy to talk to you about it. Suffice it to say, it’s not just climate change that has shaped my views.
401, Gavin: [Response: huh? The GRACE data are the most useful here and they show a net loss of Antarctic ice sheet mass. This loss is predominantly from WAIS, with EAIS roughly stable (increased accumulation, balanced by increased coastal loss). Do you have a cite for where we indicated otherwise? – gavin]
Also responding to your earlier response to me. With estimates of sea ice extent, ice shelf thickness, and ice mass, is there a consensus view of whether total Antarctic ice mass is increasing or decreasing, over decades or the past few years? Is it fair to say that total Antarctic ice mass is the most important quantity to measure?
I apologize if I am repeating. I think I hit “Close this window” instead of “Say It!”
408, Kevin McKinney:
#404–unhelpful link (unless one is paid up, I presume)–it just takes you to a generic “pay for access” page. If you’d like to post the name of the study, Septic, so we can at least read the abstract–?
Sorry about that, but Yooper fixed it — thanks Yooper.
Re 412 sambo – I (moderate liberal/green) agree that we need to be careful (unintended consequences) and that every solution for every problem is not a (new) government program.
While acknowledging the imperfections/troubles of a market economy (bubbles, negative sum games, possible concave PPCs…), for supporters of market economics, a tax on a public cost (externality) (or a cap-and-trade with 100 % auction) can be implemented without much worry of unintended consequences (caveat of assuming well-calculated tax and efficient policy design (apply the tax at points of large volume through a small number of channels, to reduce paperwork, etc.) – and enforcement mechanism that is hard to corrupt); for ideal (efficient) market behavior, whatever consequences there are are the consequences that should be (regarding efficiency); in particular, unintended consequences can be avoided if all relevant externalities are taxed at the proper rate (so that demand for non-fossil fuels doesn’t increase deforestation or cement production too much, or people don’t make the most efficient choice between reducing red meat and dairy consumption (or choosing different sources for those things) and conserving energy, etc.) – of course for the sake of not having too costly a bureaucracy involved, some approximations will have to be made for some types/sources of the externalities and thus the effect will be an approximately ideal response, but that’s always going to be the case to some extent. Of course, variations in policy across political boundaries would be a problem, but there are solutions to that issue. Non-ideal market behavior can be addressed, such as with targeted incentives and mandates for energy efficient buildings, maybe with solar roofs, and public funding for some R&D as well as projects to help new industries (selected on an objective basis as those likely to be winners – ie this is not the government simply ‘picking’ winners) scale up and gain experience to bring costs down faster. If the public costs were realized at the same time as they were produced, the most obvious (and fair) use of the tax revenue would be to compensate people’s losses; this shouldn’t be in the form of subsidizing an inefficient behavior (continuing to farm land that has turned to desert or continuing to live in a flood prone area with increasing insurance costs or public costs via FEMA etc – PS ideally FEMA should at least in part be payed for by a tax that would be like paying for insurance based on the actual risks), but could take other forms (investment in infrastructure that makes the best of the situation, compensation for loss when a property is sold at reduced value or must be abandoned). On the international level, ideally, there would be funds from emitting nations to compensate climate-change refugees and their new host-countries. Because much of the cost will be realized after the emissions occur, the funds would have to be invested in order to produce resources in the future to compensate or make the best of conditions then; this can be investment in infrastructure (aquaducts and flood water management planning) and such things as R&D for drought/flood resistant crops, efforts to save ecosystems (those parts that will survive the climate change, or otherwise planting trees, etc, where they will do well in the future, or otherwise reducing other stresses so that ecosystems will be more resilient to climate change) (remember that ecosystems provide us with ecosystem services), etc, and/or investment in the economy in general so that more resources will be available in the future to compensate for losses and pay for adaptation. PS some changes in agricultural policy (at least in the U.S., but maybe elsewhere too) would help both with climate change mitigation and with adaptation, as it would help with more efficient agriculture in general and more efficient responses to weather variability even without climate change (as it is, maladaptive behavior is subsidized).
Of course, this could be done stupidly, but why settle for that? The problem I have with many complainers is that they are not interested in better ideas, rather, they just want to water-down whatever solutions are proposed (and ignore ethical considerations and pretend that the word ‘fair’ has nothing to do with international effects).
Okay, I did a stupid thing. I told a denialist to name one climate scientist (publishing in top peer-review journals within the past 5 years) who disagreed that anthropogenic global warming was happening. I was thinking that there are some who think industrial emissions might not be the overarching factor, but I thought all agreed that GHGs do play some role in the warming (and that there is some warming).
Then I also asked him to name just one climate scientist (whether peer-review publishing or not) who claims global warming (whatever the suggested cause — sun spots, cosmic rays) is not happening. I was thinking that even Monckton and some others admit to the warming, but just say it isn’t GHG or human caused.
So he came up with this list below. If any of these in the peer lit claim GHGs have nothing to do with climate and there has been no evidence of warming, please let me know. Also which journals are not “highly respected” among climatologists.
BTW, it only took them a few minutes to come up with this list….
Re. 416 Lynn Vincentnathan
Looks like you have evidence for the meme claiming that dissenting climate scientists can’t get funded or published is a load of hooey. No doubt that one will raise its head in conversation with your deniamate. One to keep up your sleeve ;)
Lynn Vincentnathan @416 — The last papaer, by G&T, is absolutely chcok-a-block with erros. A rebuttal has been prepared (and I believe sent to the same journal). Details on Rabett Run.
Lynn, look them up in Scholar, then click the “cited by” list — note the dates on most of those and the followups in the journals.
PS, Lynn, also look for the source. Could be Heartland’s list.
… Scores_of_PeerReviewed_Studies_Contradict_Global_Warming_Alarmism.html
And they may not say what the person claims they’re saying (if they’re from the CO2science list, look even harder). For example, the papers citing Monin are listed by Scholar here. Take a look what it’s cited for.
http://scholar.google.com/scholar?cites=5814055319258450651&as_sdt=2005&sciodt=2000&hl=en
Hmmm…Lynn, funny how your chappy failed to cite a later paper by Lahsen.
LAHSEN, M. (2008). Experiences of modernity in the greenhouse: A cultural analysis of a physicist ‘‘trio’’ supporting the backlash against global warming. Global Environmental Change, 18, 204-219.
It’s an Oreskes-style exposure of the George C. Marshall Institute gang’s tactics, which in my view more than balances out her earlier work.
The later LAHSEN paper Hasis refers to – quite snippy about the Marshall Institute. :)
Re 416 Lynn Vincentnathan –
Yes, that last one (the infamous G&T paper) has no new scientific results, it is just an attempt to use known physics to falsify known physics, and it fails miserably, because they don’t understand what they’re actually trying to talk about. It’s worth less than the paper it’s printed on.
(On a related note, I think some people misinterpret those Energy budget diagrams showing upward and downward fluxes of radiation and convection, such as K&T and the later K,T&F (Trenberth et al 2009, first diagram here http://chriscolose.wordpress.com/2010/03/02/global-warming-mapsgraphs-2/ ). Some people think that the backradiation violates the second law of thermodynamics and at least one person thinks that K,T&F forgot to apply vector math properly; they don’t realize that radiative fluxes are often given as fluxes in one direction and in another, rather than the net flux in one direction. Astonishingly, I encountered one person who insisted that energy is not conserved in such diagrams, which is obviously not the case.)
See also: http://chriscolose.wordpress.com/2010/05/08/stoat-taking-science-by-the-throat-latest-posts-archives-about-rss-contact-profile-me-my-family-and-me-more-make-sure-youre-familiar-with-the-comment-polic/
Lindzen’s Iris effect has not been satisfactorally demonstrated, and global climate sensitivity can’t be constrained by measurements in just one region. (At least one of Lindzen’s studies appeared to have used cherry-picked data.)
There are still issues with the tropical upper-tropospheric hot spot in the observations, but earlier mismatches between data and models were larger and it was found the observations had errors; plus, that hot spot is not a ‘fingerprint’ for AGW; it is a general to warming.
I’ve seen some of Idso’s writing and it’s not good.
As for the rest, I’d suggest you ask the denier to some work, and actually point out where in the article it states that global warming isn’t happenning or isn’t caused at least in large part by increasing greenhouse gas concentrations, and to be on the safe side (because things can be taken out of context), ask him/her to also quote the abstract and the conclusion.
Lynn @ 416
Ugh. Nice of them to spew on you. No quick answers for the list in its entirety.
I see Lindzen on the list. That says something right there.
C. R. de Freitas (Bulletin of Canadian Petroleum Geology!)
Quick Google, calling him a climate scientists may be a stretch.
This C.V. has his area of expertise listed as Geography; Environmental Studies.
Busy guy: Wikipedia
@13 “In fact HadCRUT3 global temperature anomalies are at the very low range of the IPCC scenarios, (had we been using a ball park it would have been called a foul having bounced outside the diamond”
In addition in many other mistakes, you are wrong about the rules of baseball; a ball is not made foul by bouncing outside the diamond, but only by its position as it crosses first or third base. It can bounce outside the diamond and still be fair, provided it bounces fair.
[Response: Uh oh, baseball talk. To be even more precise, it’s fairness or foulness relative to 1st or 3rd only applies if it first hits the ground before passing either bag; otherwise it’s determined strictly by where it first touches either the ground (or a fielder if it has not yet touched the ground, regardless of whether it’s passed the bag or not), relative to the foul lines/poles. Just to show that I can go OT with the best of ’em– Jim]
Much like the man you defend, you are sloppy and factually inaccurate both as to matters or substance and relative trivia.
Lynn @ 416
Or alternatively if you haven’t responded yet and you want to buy some time (and since deniers just love playing games with language) you could mention that you haven’t got all day and that “I said pick ONE that best represents your case.” Then uproot the non-climatologists, poor reading skills, and the purveyors of bad science one at a time.
Lynn: Aren’t the cut’n’pasters hateful? All the usual suspects in one convenient list. Yet even then they failed to answer your question, since I see quite a few names there that have publicly stated that global warming is real (even if they can’t deal with the cause).
Answering the actual question: Wikipedia provides a useful crib sheet, although I wouldn’t rely on it absolutely. It has three scientists claiming the “no warming” position, none of them climatologists, only one of them publishing (Carter).
You may find the wiki article useful, since nearly all of the scientists in your list appear in other categories (with references to public statements of position).
(Monckton is an oddball, since he sometimes claims warming is real, and sometimes that it is not. But then, we don’t expect consistency or logic from him.)
@416 Lynn. Hmm, almost sounds like “poptech”.
He has a database of “lists” he uses to instantly spam thread discussions, in the classic “mine is bigger than yours” tactic used by many denialati over the years. It’s especially popular in climate debates (evolution too). As with most people who use such lists, the main body of their discussion is normally totally devoid of any verifiable scientific facts, statements, or explanations. They generally don’t know or understand what their list references actually say, and have almost certainly never read the papers themselves!
I think you really asked the wrong question, as occasionally in all professions the odd awful paper slips through the imperfect peer-review process. What’s really important is how well it stands up to scrutiny after it has been published. You should’ve asked: Name one climate scientist who has published a peer-reviewed paper showing AGW is not the cause of the observed temperature rises in the industrial age, or not happening at all, or showing a likely alternative cause for those rises, and which has withstood all subsequent scientific scrutiny. This is the point at which their “list” dies out with nary a feeble whimper.
A quick glance at those “sceptical scientists” names shows some fairly notorious ones. Not so much for being outright deceptive, but more for just not producing very good papers.
In 413 Septic asks:
Also responding to your earlier response to me. With estimates of sea ice extent, ice shelf thickness, and ice mass, is there a consensus view of whether total Antarctic ice mass is increasing or decreasing, over decades or the past few years? Is it fair to say that total Antarctic ice mass is the most important quantity to measure?
Septic, of what use is this number you’re looking for?
I would definitely not agree that total ice mass is the most important quantity to measure.
Adding the mass of ice that had accumulated over hundreds of thousands of years on the ice sheet to the mass of seawater that freezes on the surface seems pretty useless to me. Each are affected by different processes, and the loss or gain of either has different effects on the world around us.
It *sounds* like someone wants to deny the changes occurring by being able to say that ice sheet losses are “offset” by sea ice gains, so the loss of the ice sheet “really doesn’t matter”.
428, David Miller: Adding the mass of ice that had accumulated over hundreds of thousands of years on the ice sheet to the mass of seawater that freezes on the surface seems pretty useless to me.
And yet, significant resources are being devoted to appraise the losses and gains of ice. I think that the scientists in the field have decided that it is important. It is a part of appraising all of the heat flows relevant to climate change and climate oscillations.
Over at WUWT, Monckton has explained more clearly how he gets his predicted CO2 graph for the A2 scenario and one of the commenters there has identified the problem ( http://wattsupwiththat.com/2010/08/14/monckton-why-current-trends-are-not-alarming/#comment-459457 ): Monckton basically fit the CO2 concentration to an exponential function, using the actual value for concentration in 2000 and the “central value” for the A2 scenario of 836ppm in 2100.
The problem with such a fit is it has neither empirical nor theoretical support. Empirically, it does a horrible job backcasting because you don’t have to go back very far before the concentrations it backcasts are well below the ~280ppm pre-industrial levels.
And theoretically, if one were to (simplistically) expect exponential behavior, it would be only for the component of the CO2 concentration above the the pre-industrial baseline, not for the CO2 concentration as a whole. And, if one does the fit to a function of a constant baseline + and an exponential function in the same way Monckton did his fit simply for an exponential function (with a real data constraint in 2000 and the central A2 scenario value in 2100), one gets pretty good agreement between the predicted 2010 value of CO2 concentration and the actual value. In fact, the result is that the actual CO2 concentration is running a bit HIGH of the predicted value.
So, it is not just that Monckton has chosen a simplistic model to produce his predicted CO2 curve. It is that the model is clearly not justifiable (even as a crude approximation) on a theoretical level and is empirically pathetic at backcasting. And, if one modifies the model to be more theoretically-justiable (albeit still simplistic), it does a much better job both backcasting and forecasting from the year 2000 data.
Lynn Vincentnathan 17 August 2010 at 3:06 PM
“I told a denialist to name one climate scientist (publishing in top peer-review journals within the past 5 years) who disagreed that anthropogenic global warming was happening.”
Douglass et all found that computer models and observations both show warming, but by differing amounts in different levels of the atmosphere – from the later paper – “What is new in this article is the determination of a very robust estimate of the magnitude of the model trends at each atmospheric layer. These are compared with several equally robust updated estimates of trends from observations which disagree (in size, not sign,) with trends from the models.” FAIL (Not to mention that they chose an earlier observation dataset that had larger differences with models instead of a later more accurate dataset which they had access to – can you say cherrypicking?)
Arking found that the “Effects of bias in solar radiative transfer codes” to be “quite small and in most cases negligible.” They did find “the main impact is in the energy exchange terms between the surface and atmosphere and in the convective transport in the lower troposphere” which might explain some of the differences Douglass et all find between models and observations. FAIL
Govindan, et al say “(i) In the (standard) fluctuation analysis (FA), we calculate the difference of the profile at both ends of each segment. The square of this difference represents the square of the fluctuations in each segment.” – by squaring the differences at the ends, they remove any trends – for example, suppose one has a linear trend from 28 to 32 degrees, with an average of 30 degrees; the difference at the first point is -2, and the last point is +2 and a difference of 4 degrees over the interval. The square of -2 is 4, and the square of +2 is 4, and the difference between the squares is zero
“(ii) In the ‘first order detrended fluctuation analysis’ (DFA1), we determine in each segment the best linear fit of the profile.”
“Note that FA (which does not remove trends) overestimates the fluctuation exponent as can be seen when comparing to DFA.”
Basically all this paper shows is that if one removes the warming trends shown in the models and the warming trends shown in real data, “fluctuation analysis” “indicates loss of long-term correlations.” In other words, they have rediscovered (and maybe more rigorously quantified) the butterfly effect, but shows nothing about AGW trends. FAIL
(according to Reuters Schellnhuber said “It would be wonderful if some mechanism that we haven’t yet been able to understand could still have an impact and manage to stabilize global warming at a high level for a while,” he said in an interview in his institute’s office outside Berlin.”I would be delighted if it turns out that we haven’t understood the system as well as we think we do and that we might get a 20- to 30-year ‘breathing period’ when global warming slows or is even halted,”)
McKitrick and Michaels show “Using the regression model to filter the extraneous, nonclimatic effects reduces the estimated 1980–2002 global average temperature trend over land by about half.” In other words, they still see AGW, just not as much, and only over land. FAIL
The nonclimatic effects they are talking about are Urban Heat island trends caused by “socioeconomic determinants of surface processes and data inhomogeneities.” Menne et al http://www1.ncdc.noaa.gov/pub/data/ushcn/v2/monthly/menne-etal2010.pdf, following the pioneering work done by Anthony Watts and his surfacestations.org volunteers, found “…no evidence that the CONUS average temperature trends are inflated due to poor station siting.” On the contrary, they found that the corrections made to the data resulted in “… bias in unadjusted maximum temperature data from poor exposure sites relative to good exposure sites is, on average, negative while the bias in minimum temperatures is positive (though smaller in magnitude than the negative bias in maximum temperatures).”
Lahsen’s abstract says “Drawing on participant observation and interviews with climate modelers and the atmospheric scientists with whom they interact, the study discusses how modelers, and to some extent knowledge producers in general, are sometimes less able than some users to identify shortcomings of their models.” In other words, its is a study of scientists, and doesn’t address the science of AGW; even scientists may be subject to the Dunning Krueger effect, but the competition of peer review will minimize this. FAIL (Denialists often conflate “inaccurate”- doubling of CO2 will result in ~2-4.5 degrees C temperature rise- with “wrong” – the greenhouse effect violates the Second Law. Real science always recognizes and attempts to quantify inaccuracy, and to identify sources and reduce it.)
Monnin et al opens – “The concentration of atmospheric CO2 has been increasing steadily since the beginning of industrialization, from ~280 parts per million by volume (ppmv) to its present value of ~368 ppmv (1-4). By investigating earlier, natural CO2 variations, we expect to obtain information about feedbacks between the carbon cycle and climate and also the possible impact of the anthropogenic CO2 on the climate system.” FAIL
Kouwenberg et al using tree stomata as a proxy for CO2 concentration see “Alternating CO2 maxima of 300–320 ppmv are present at A.D. 1000, A.D. 1300, and ca. A.D. 1700…” which are at variance with multiple direct CO2 ice core measurements from Greenland and Antarctica, and there wasn’t significant anthropogenic industrial fossil fuel consumption and CO2 emissions at those dates. Diurnal and seasonal growth changes are well known to affect CO2 levels in forested areas – http://www.springerlink.com/content/0a5b32ljqb4wm7x4/, and water, sunlight, and temperature all have significant effects on ecosystem carbon exchange -treephys.oxfordjournals.org/cgi/reprint/28/4/509.pdf. Natural stomatal variations due to CO2, sunlight, precipitation, temperature, or other natural causes don’t address mechanisms of AGW. FAIL
Lindzen states “In connection with this question we can go a bit further, and state that increasing CO2 is likely to cause some climate change, and that the resulting change will involve average warming of the earth.” FAIL
He went on to say (in 1997) “The more serious question then is do we expect increasing CO2 to produce sufficiently large changes in climate so as to be clearly discernible and of consequence for the affairs of humans and the ecosystem of which we are part.”
In 2002, the Larsen B ice shelf collapsed;
in 2003, the World Glacial Monitoring Service reported that “The recent increase in the rates of ice loss over reduced glacier surface areas as compared with earlier losses related to larger surface areas (cf. the thorough revision of available data by Dyurgerov, 2002) becomes even more pronounced and leaves no doubt about the accelerating change in climatic conditions.” and the accelerating negative trend continues;
in 2006 Rignot et al published satellite data which showed “Accelerated ice discharge in the west and particularly in the east doubled the ice sheet mass deficit in the last decade from 90 to 220 cubic kilometers per year.”
in 2007, summer sea ice extent in the Arctic reached an historic low.
in 2008, the Wilkins Ice shelf began collapsing; its ice bridge to Charcot Island failed in 2009, and it is continuing to lose area;
in 2010 so far, the period from January to June is the warmest six months on record.
AGW is clearly discernible.
Spencer et al find some potential support for Lindzen’s “infrared iris” hypothesis of climate stabilization, which presupposes AGW,; it might hypothetically, potentially, be reduced but not eliminated. FAIL
They are also extrapolating data from intraseasonal oscillations into longterm trends. Removing any trend from the data before looking for something that might affect the trend is not the most robust method of analysis.
Idso’s calculations for climate sensitivity are greatly at odds with the paleoclimate data; if sensitivity were as small as he proposes, the Milankovic changes in solar forcing wouldn’t be enough to kickstart the climb out of an ice age, but this still presupposes AGW, that CO2 emissions will increase the temperature by some amount. He also says that natural variation in temperatures absent concurrent changes in CO2 “imply very little (and possibly nothing at all) about the potential for future CO2-induced climatic change.” – not a robust denial of AGW. FAIL
He asserts “First, there is the demonstrated propensity for oceanic phytoplankton to increase their productivity in response to an increase in temperature…” producing dimethylsulfoniopropionate, which decomposes to produce DMS which acts to increase cloudiness and cooling albedo. Once again accepting that warming is occurring, but arguing that its magnitude will be less than mainstream science thinks. However, recent research has revealed a significant decrease in phytoplankton – http://www.nature.com/news/2010/100728/full/news.2010.379.html as the globe has warmed.
Idso’s arguments for CO2 enhanced growth of plants fails to recognize that experiments have shown concurrent lower nutrition, and ignores warming which will come from the lower albedo of plant growth compared to soil.
Gerlich and Tscheuschner, despite their apparent mastery of the mathematics of radiative transfer, don’t know the difference between gross and net radiative flux, and they are apparently unaware of the concept of causality in an Einsteinian framework – a molecule of CO2 emitting a photon in a random direction can’t know if there is a (cooler or warmer) surface in the direction of emission until time has elapsed for the photon to travel to the surface and back, and has no mechanism to remember from one photon to the next whether there was a source of photons in that direction, or what the apparent temperature of the emitter was.
J.K. Galbraith said something to the effect that immortality could be assured by spectacular failure – I suspect that G&T will be “long remembered”. FAIL, (or perhaps “not even wrong”)
Dan 409,
And don’t miss this one:
Velicogna, I. 2009. “Increasing rates of ice mass loss from the Greenland and Antarctic ice sheets revealed by GRACE.” Geophys. Res. Lett. 36, L19503-L19506.
“Conclusion. We showed that a detailed analysis of the GRACE time series over the time period 2002–2009 unambiguously
reveals an increase in mass loss from both ice sheets. The combined contribution of Greenland and Antarctica to global
sea level rise is accelerating at a rate of 56 ± 17 Gt/yr2 during April 2002–February 2009, which corresponds to an equivalent acceleration in sea level rise of 0.17 ± 0.05 mm/yr2 during this time. This large acceleration explains a large
share of the different GRACE estimates of ice sheet mass loss published in recent years. It also illustrates that the two
ice sheets play an important role in the total contribution to sea level at present, and that contribution is continuously and rapidly growing…” 4/2002-2/2009 period covered for Greenland and Antarctica.
Joel Shore #430:
Spot on. This is exactly what I have been saying in posts #385, #390, and #396, which seems to have blown right by Orkneygal (amongst others). Beeson does make the point more eloquently in that comment over at WUWT by explaining in great detail Monckton’s *error* in not separating the pre-industrial baseline CO2 from it’s exponentially rising anthropogenic component. But I *did* say that, albeit more tersely:
For the record, the equation that both Beeson and I are using comes originally (I believe) from Rick Baartman, on a thread over at Tamino’s place:
Monckey Business, comment #41412
ETA: the fact that Monckton’s fit backcasts so badly is enough to discredit it all by itself!
#405 Septic Matthew
Try to think of things in order of occurrence and expectation simultaneously.
– First we increase the greenhouse gases
– then that causes warming in the atmosphere and oceans
– as the oceans warm up, they evaporate more H2O
– more moisture in the air means more precipitation (rain, snow)
– the southern hemisphere is essentially lots of water and a really big ice cube in the middle called Antarctica
– land ice is different than sea ice
– climate models indicated that more snowfall would cause increases in the frozen H2O
– climate models indicated that there would be initial increases in sea ice extent
– observations confirm the indications and expectations that precipitation is increasing, calving rates are accelerating and sea ice extent is increasing.
So for land ice, more snow falls on Antarctica, but the land ice mass is dropping due to increased calving rates.
Pretty simple once you visualize it.
#413 Septic Matthew
Take a look at the data on ice mass loss for Antarctica
http://www.ossfoundation.us/projects/environment/global-warming/current-climate-conditions/antarctica
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#416 Lynn Vincentnathan
To avoid such confusion and cut down on my digging time I always say peer reviewed and survived peer response.
As tot he provided list, well, grab a shovel and start looking for facts out of context arguments and/or general errors.
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433, Barton Paul Levenson
Thanks for the reference.
So where does that leave us? Antarctic ice mass is diminishing concomitantly with Antarctic ice extent increasing? And both effects are predicted by AGW, which also predicts increased Antarctic snow mass? These are not necessarily contradictory.
In 430 Septic Matthew says:
And yet, significant resources are being devoted to appraise the losses and gains of ice. I think that the scientists in the field have decided that it is important. It is a part of appraising all of the heat flows relevant to climate change and climate oscillations.
I’m very certain that intense research is underway for what’s happening to both sea ice and sheet ice. No one questions that.
But if you think that scientists are particularly interested the sum of sea + sheet ice because it’s an important number I’ll have to ask for a cite.
It still sounds like a denialist meme to me to be able to say “sure, sheet ice is decreasing but it’s not a problem because sea ice is increasing”, and I’ve never heard the “total ice mass” used outside that context.
John P. Reisman (OSS Foundation) says:
18 August 2010 at 9:30 AM
Think your first chart could do with a title alteration to “Antarctic Ice Mass Change” as else some Ain’t Truthospheric Inhabitant might interpret the minus and plus.
Septic Matthew’s problem is that “concern trolling” is something you can only do once. Teh Internets have long memories.
As for the problem at hand: Antarctic sea ice is nearly all first year ice. That means it is very thin*. Thanks to GRACE, we now have a much better handle on the continent-wide mass changes. However, sea ice volume remains very poorly estimated. Zhang (2007) finds a discrepancy of a factor of 3 between models and observations. To me, that says: let’s wait until someone puts together the IceSat and Cryosat data and forms a complete picture. But that won’t happen for years.
Critically, the change in sea ice extent is linear, but the loss of continental ice is accelerating.
* Ironically, global warming seems to be causing more precipitation in the region, leading to thicker ice.
#338 Septic Matthew
The increase in precip and ice loss as well as the ice extent increase are not contradictory, they are observations and logical in accord with the models and expectations.
#440 Sekerob
I used the source header “Antarctic Ice Mass Loss” from NASA/JPL. I am in agreement with their labels.
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Instead of putting up Figure 10.20a, I think the original poster should have linked to http://www.ipcc.ch/ipccreports/tar/wg1/531.htm: this clearly shows that the ISAM model predicted 2010 concentrations of 388 to 393, and the Bern model predicted 2010 concentrations of 385 to 390. Actual concentration looks like it will be a touch over 388 (http://www.esrl.noaa.gov/gmd/ccgg/trends/#global_data). That looks right on target to me, and is easier to explain that a graph that shows model predictions based on spinning up models from decades ago and therefore with very large uncertainty bounds on even year 2000 concentrations.
-M
In case anyone is interested, Monckton has “responded” to my piece about his graphs here:
http://wattsupwiththat.com/2010/08/14/monckton-why-current-trends-are-not-alarming/#comment-460664
I have now posted a response to his non-response here:
http://bbickmore.wordpress.com/2010/08/17/the-monckton-files-a-bold-monckton-prediction/
442, John P. Reisman: The increase in precip and ice loss as well as the ice extent increase are not contradictory, they are observations and logical in accord with the models and expectations.
Thank you. Is it fair to say that total ice mass is the most important quantity to know? Is there a “most important quantity”?
“Thank you. Is it fair to say that total ice mass is the most important quantity to know? Is there a “most important quantity”?”
I’d suggest climate sensitivity would be the most important quantity to know. And we know it quite well.
After that, I’d probably suggest that the impact of climate change on rainfall in a range of populated areas would be important to know.
After that? Predicted glacier melt rates and their impact on drinking water and irrigation for people who depend on them.
After that? What sea level rise will look like in 2050 and 2100.
What happens in Antarctica, except where it impacts on the above, is not of as much interest to the majority of humans.
#445 Septic Matthew
I’m pretty close to what Silk said. I was going to say Atmospheric CO2 and sensitivity. Gavin has been working with others on Earth System Sensitivity (ESS). It looks to be more sensitive than previously estimated and many have made qualitative arguments to that effect.
The better we can calculate sensitivity, the more we will generally know about what to expect. ESS to a given amount of CO2 is very important.
But then again, there are many important quantities, depending on the scope of the question. How much food we can successfully grow in a warmer world more prone to droughts and flood events? That’s pretty important too.
How much strain can the fiat currencies of the world handle before inflation gets out of hand? Important quantities also.
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> Is there a “most important quantity”?”
Level of comprehension; note this may be a negative number.
When asked how much ice you have in your freezer, the answer depends: an estimate of ice cubes for cold drinks, or how frozen up the coils are and how much defrosting time may be needed.
When asked how much ice there is in Antartctica, similar questions arise.
#445 Septic Matthew
Actually, right now, Hanks answer might be the best.
As I’m still under the influence of Dyer’s “Climate Wars,” I’d venture that the most important thing to know is where human responses to warming will fall on a continuum from cooperative to belligerent. When agricultural output drops, will we see rationing or raiding?
Unfortunately, prospectively quantifying that wouldn’t be easy.