The RC open thread.
With a reminder that this is not a dumping ground for anything under the sun, but is rather for discussing climate science topics that don’t fit neatly into ongoing discussions.
Reader Interactions
366 Responses to "Unforced variations, July 2011"
Didactylossays
“Such a stand-alone statement however is not sufficient”
And that’s the problem, Gwinnevere. Your statistical skill is not yet advanced enough to see the obvious truth, still less to do the analysis required to assess it objectively. Yet you are presenting your result with confidence that comes from not understanding its significance (or lack of significance).
I suggest you ask for some help at Tamino’s blog. Or better yet, read some of Tamino’s past replies to curve fitters.
You are right in one way: if your goal was to approximate the data using a curve that fits extremely closely, and you aren’t concerned with what the curve means – then in that limited sense you did extremely well. But your curve has no explanatory power or physical basis, so it is no more likely to predict the future than any other guess.
So, if you think I am wrong and that you know exactly what you are doing, then go ahead and show us what happens when you withhold data from your model and recalculate the parameters – does it predict the withheld data to a significant degree? Compare your model to a simple linear model over the last 30 years. Which model has the most explanatory power? The “relative goodness of fit”? This is like an r^2 test, but it takes into account the number of parameters in the model.
I could do this for you, I suppose – but what would you learn then? :-) If you need help, ask here or in Tamino’s open thread.
Consumersays
Pete @ #250, thanks so much for that chart. It looks like average temperatures are about 1 to 1.5C during the summer, which I would guess means that the 2C temperature anomaly is pretty significant. I wonder if that is pretty much the upper limit, as long as there is ice up there to keep it cool.
jyyhsays
No, +3.5C is not the upper limit, it’s quite common to have +10C degrees over snow or ice, warm enough air fowing on site warms the cold thin layer fast enough so it won’t get to the thermometer.
Captcha neforea follows
Radge Haverssays
I think it’s hard for even the best intentioned people to truly wrap their heads around the fact that human activity can screw up the whole planet in a major way. Partly it’s a matter of non-intuitive scales, we’re not wired to think in those terms and need significant training to do so. Partly it’s habitual wisdom that s**t happens and when it does, as the legalism states, it’s “an act of God,” and thus who can fathom or dare to question such mysteries. Partly we just think we’re somehow exempt. There’s wonderful us, and then there’s everything else, put here for our benefit.
On top of that, you see people responding to problems by trying to forcibly match items from a repertoire of stock responses to imagined patterns. That might not be so bad for starters were it not for an abuse of authority that keeps people boxed in and unable to move to a point where they can think effectively for themselves, perpetuating a clueless class as it were. Even if someone manages get it, sort of, it’s often too easy and expedient to fall back into a default position.
It’s a jungle out there and up hill all the way.
Susan @ 247
Not political ambitions, ambitions of professionalism.
Joe Cushleysays
Well, who would have thought it, Dr Roy Spencer is a rabid free-marketeer…
Not content with laying waste to “warmists” arguments he is now set on putting Commie, pinko, Keynesian types in their place
Well, who would have thought it, Dr Roy Spencer is a rabid free-marketeer…
Everyone? Seriously …
[edit – too far OT]
Pete Dunkelbergsays
Jagged focus:
After removal of presumably major sources of noise, the adjusted surface temperature graph still has almost as much noise as before. Does anyone have an idea why? (I mean besides “noise happens”.)
Let’s talk about the Younger Dryas. The global warming thing is getting old. There isn’t much to talk about. It’s happening. There are positive feedbacks speeding it up, as well as anthropomorphic emissions slowing it down, but it’s still proceeding unabated, nevertheless. On the other hand, the Younger Dryas problem remains, unsolved and wonderfully controversial.
doi:10.1016/j.jphotochemrev.2011.05.002
Fighting global warming: The potential of photocatalysis against CO2, CH4, N2O, CFCs, tropospheric O3, BC and other major contributors to climate change
(Full text is paywalled; you can see the outline at the link
So, ah, how’s the “worst that can happen” list look nowadays? We should learn from the nuclear industry to to be overly optimistic.
Does Peter Ward still hold the candle for worst case? That would require very unlikely events — major floods, pulse of sediment into the oceans from the rivers, large areas of the ocean surface along the continental shelves going anoxic, a good bit of sulfur reaching the surface, and an extinction event.
So far I haven’t mention in the news of … Oh, wait …
Gwinneveresays
Improved information on precise CO2-quantities from AGW-math to no209 wili:
General equation (referenced at post no140),
Note that this expression is a (very) close approximation to the actual integral solution (as yet, no available world source is able to give its algebraic form). It is limited to approximately year 2028 [by a proceeding tangent of ca 3.4]. Above that, we must use exact values from a numerical solution (Simpson Formula, or the »Hypo-series» formula).
Preferences in the basic AGW-math accounts for an offset margin of ±5 years, mainly due to a (least) general surface ocean (0-500 M) period (see also note below).
a shorter investigation (13Jul2011/Gwinnevere) on the AGW-math’s CO2 industry integral shows a nearly exact match by the horizontal scale OffsetYear = 1811:
With (MaunaLoa)/(AGW) the lowest up to the last MaunaLoa-value 2010 is 99.69%, highest 100.61%. That gives at most a ±0.7% deviation. These ±-levels are skittering (or sidestepping) to and fro in the table roughly but not exactly on a 5-10 year base, interval 1959-2010.
To find the exact year by a given CO2-value is then calculated by
1811 + (121.41)([CO2(ppmv) – 286]/[12.7576])^1/4.25 = YEAR
With 400 ppm input (no209 wili), the precise AGW-answer is
YEAR = 2014.26
0.26×365=94.9 (-Jan31, -Feb28, -Mar31 = 90)
(Phillip Shaw already did point out a similar value in post no225).
= 4Apr2014 at 21:36 after midnight [9:36 PM]
No extra CO2 besides the industrial contribution
——————————————————————————————
The presumption of an eventual CO2-addition from side-effects is effectively erased by the above clarification. That is, there is yet (2011) according to the given AGW-math no (direct observable) additional CO2 added in the atmosphere besides the part given through the AGW-math (precise) CO2-levels from the industrial fossil carbon emissions (as measured at Mauna Loa). That is (very) good news, in the middle of the bad ones.
NOTE — precise ocean data are sparse.
——————————————————————————————
The only available public free sources seen on INTERNET as I have found prior to the AGW-math description, are the ones referenced by me in post no140 together with some information on https://www.realclimate.org/index.php/archives/2004/11/atlantic-multidecadal-oscillation-amo/
Some older (primary) data from early investigations may be found in different books of reference in physics in general (in different countries), such as f.ex. the Swedish FOCUS MATERIEN Almquist & Wiksell 2:nd ed. 1975 p487col2b [surface period 5 years 0-500 M, polar ocean period ca 50 years].
(If any of you should believe thath the AGW-math [post no140] is BASED on »D’Aleo-data» you are in deep delusion).
— Due to the great difficulties of observation and general theory, no general agreement is yet (2011) found on ocean data.
— Some persons here at RealClime might have the impression that the referenced ocean data from Joseph D’Aleo (2008) at post no140 should have been qualified as RELIABLE. That adjective has never been used by me in connection with ocean data. The word of description is: AVAILABLE. Together with the RealClime-reference above: There are no other publicly, free, available data for the average Internet user to access on ocean data, as far as I know. The rest is up to the measured NASA/CRU/GISS-temperature curves, and their equivalents by known — reliable — components.
Gwinnevere
Gwinneveresays
no237 Ray Ladbury:
— Hello Ray Ladbury.
I was aiming at a confrontation with some PRINCIPLE argument on the AGW-quest. I think I have found one now.
— By QUALITY: Of course there is nothing such as »AGW-math». It has no notation in the established academic community. That is also clear from the post no140: the present established »climate-math» is entirely referenced to Arrhenius math. As the post reference shows, however, this Arrhenius math ”as accepted by 97-98% of publishing climate scientists” as you say, is an approximation to the three derivative-integral functions that EXPLAIN current data (Sea, Industry, CO2), including Arrhenius math as a (close) approximation. To exemplify, your »AGW-math», not Arrhenius math, explains current CO2-measured (Mauna Loa) data. To be noted.
— By QUANTITY, hence, the term »AGW-math» is appropriate in use to refer the actual connections, comparisons, results and presentations, and only as far as the quantities DO match observations from research. There is nothing else to it.
(In »ancient science», such »formulae» we held to be »empirical»).
I really appreciate your arguing. It just promotes the purpose. Thank you very much.
Gwinnevere
Gwinneveresays
no239 JCH:
— Hello JCH.
First: You seem to be asking if I think 2008 was a year from the warmest decade?
— I don’t know that, really, JHC. I have to pass it on.
Second:
”reconcile [»try to fit or match»] these with your ”lull””
— The HADCRUT (global mean), GISTEMP (land-ocean global mean), UAH (lower trop. global mean) are not that easy to interpret on a now-basis — yet.
Last averaged value in the last updated version http://climate.nasa.gov/keyIndicators/
ends at 2007.
— To be honest with you, from my personal side JHC, I am unable to match not yet settled average data to the same general curvature as the one in the past (up to 2007).
— For the record, we can exclude the UAH- data as these deal with atmospheric layers far above the one in concern of the AGW-math part (maximum h=60 M).
— The other two, mutually showing the same picture, has a mean horizontal trend the period 1998-2009.
— It is too early as I understand it, yet, to run to (general) conclusions. You seem to point out that HADCRUT and GISTEMP data would indicate the AGW-math-dotted continuing (from 2005 an on) to be erroneous.
— In that case, JCH, you are at first perfectly right, the AGW-match is corrupt, and at second we are in exceptional trouble as to the possible change of the oceanic behavior.
Gwinnevere
Gwinneveresays
no 242 Rich Creager:
”Are you a text generator”?
— RealClimate WebSite is no exception in generating (unwanted) invitations to persons not interested in the scientific matter.
— I have no whish to escape these individuals in their off-the-record-posts. I would like to meet them and share the arguing. However, as you already know, this web page is not intended for such discussions. Thank you for sharing.
Gwinnevere
Gwinneveresays
no251 Didactylos:
”Your curve has no explanatory power or physical basis”.
— I think I am awake in reading the above statement.
Didactylos, a »model» connects to statistics, probability. Knowledge connects to certainty, which is an abstract concept for statistics. AGW has no connection to probability.
How is it Didactylos?
IF, as you say, the »AGW-math» would have zero accountability in any scientific sense, how is it that the top function — to exemplify — of the three power functions having the Arrhenius logarithmic/exponent functions as close approximations, the CO2-part, matches measured (Mauna Loa) values with a maximum deviation of ±0.7%?
— You don’t find a finer qualitative match by a set of three power functions explaining the measured quantities (Sea, Industry, CO2) — the cause of AGW, its process and its extension.
To me, that seems rather the opposite to your claim:
»Your curve HAS explanatory power AND physical basis».
— The authoritative recommendations you make at the end of your post, in the light of the actual quantities, seems to testify you are understanding mathematics as such in a principal erroneous (irrelevant) way. Thank you for sharing.
Gwinnevere
Lloyd Flacksays
I’m trying to get a friend to reevaluate her scepticism on climate change. Her scpicism isnot ideologically based. Rather it comes from a combination of over generalization from her experience in her field and from getting her information from biased sources. Her work has been mostly in safety-critical computer systems.
Now I remember seeing here and somewhere else a list of about five points comparing the sorts of models that scientists that are likely to understand climate change work on to the sorts of models that experience with predisposes someone to doubt it. It might have been a comment of John Mashey’s wrote or a response to one of his but I’m not sure. Con anyone direct me to it.
Pete Dunkelbergsays
@ 265, is that a “yes”?
;)
Didactylossays
Gwinnevere: No.
You’re not even wrong.
Learn to walk before you try running.
skgsays
Hi all,
I have been lurking here for many years, and this is my first post. It’s not even directly about climate science, but more about statistics in general. I have had no formal training in statistics but I am interested in measuring the complexity of something (criminal trials). I have brainstormed and come up with about 20 variables that I would think would correlate somewhat with complexity of criminal trials. But I don’t think I need 20 variables to estimate complexity. Moreover I would guess that many of them correlate quite highly with each other (multi-collinearity?). So I am sort of stuck trying to decide which of the possible explanatory variables to use.
My plan at the moment is to take a random sample of criminal trials (how many would I need? 30?), read the records, and then manually arrange them from least to most complex. I would then test my possible explanatory variables to see how well they correlate with the “expert ordering” and pick the one or two (or maybe three or four?) that show the highest correlation. Then I can use these explanatory variables to go back to the main data set and calculate complexity scores for the entire population.
Does that sound reasonable? Are there better ways to do it?
Thanks in advance.
Gwinneveresays
RealClimate-Questionability about the reliability of mathematical physics in the AGW-quest
——————————————————————————————
In mathematical physics, a triple power function unity by integral-derivatives is, as far as I know, considered one of the strongest structures that exist at all in this beautiful Universe of ours. It is to be understood as a reference of exceptional solidity, especially in communicating quantitative results.
If any single one of the individual functions shows a clear and unmistakable mismatch to experimental observation, we can safely disregard the other two too: the structure is not the one we are looking for. Next.
If on the other hand any single one of the individual functions shows a match, a correspondence, with experimental, measured, observation of the kind 99.3%, so the other two have to.
— The AGW-quantities, here in strong question by several persons, are seen to correspond within 99.3%, as mentioned by the post connected to the CO2-question by wili in post no209.
From that point of view, I find it really bizarre that some persons here at RealClimate »have the nerve» to sentence — erase — the entire complex with such finalizing power as, TYPE
”It is wrong”,
”You don’t understand statistics”,
”You are executing a primitive level of mathematical skill”,
”You need help” (my favorite),
not to say other incitements of the kind not related to this WebSite.
— The only way to »KILL» the AGW-math part, is to Find/GIVE REFERENCES by comparing quantities. As yet, I have seen none — but I would very much like to.
First, I suggest using far more than 30 samples for your model. You say you have 20 variables which might be useful, then there’s also a constant (roughly speaking, the “mean value” of complexity), so if you used all explanatory variables you’d have 21 degrees of freedom in the model and only 30 in your sample, leaving only 9 degrees of freedom for other variation (call it “natural variation). That’s very small!
I suggest you use at least 100, and far more if you can. I know it seems like a lot of work, and it is. But that’s the price you pay — the more data you have, the better your answer, the less data, the worse.
Your general plan seems reasonable: take a sample, fit a model, then apply it to the entire population. The question of how many explanatory variables to include is tricky. Too few, you don’t get as useful an answer as possible. Too many, you become susceptible to “overfitting” in which your model matches the randomness rather than the reality.
There are strict ways to determine which variables to use. Perhaps most intuitive is stepwise regression. There are two versions. One is to start with no explanatory variables, then add one at a time, each time adding the one which gives the greatest improvement to the model. At each step you test whether or not adding a new variable gives improvement which is statistically significant. When it doesn’t, you stop.
The other way is to start with all the explanatory variables, then eliminate one at a time, each time removing the one which causes the least degradation of the model. At each step you test whether or not the degradation is statistically significant. When it is, you stop.
There are other approaches too. There are things called “information criteria” which evaluate model performance, accounting for both how well the model fits and how many parameters (explanatory variables) it uses. The best-known is AIC (Akaike Information Criterion) and its cousin AICc (corrected AIC, for small samples), also prominent is BIC (Bayesian Information Criterion aka Schwartz Information Criterion), and there are others too.
There are also ways to reduce the number of parameters by combining explanatory variables. A good example is “principal component analysis” (PCA), which finds combinations of explanatory variables that account for most of the variability in your model. And there are other ways too.
Frankly: the problem is an intricate one. If you can find a pro to help, that will make things go a lot faster and you’ll avoid the almost inevitable mis-steps.
If you must do it yourself, the best advice is to use as much data as possible and try a heckuva lot of possibilities. More data = better answer.
In mathematical physics, a “triple power function unity by integral-derivatives” is, as far as I know, a nonsense phrase. It sounds like a bunch of words you strung together but you don’t really have a clue what it means.
Perhaps you should seek the help of someone who speaks English.
What I learned from Statistics 101: consult a statistician first, before taking data. In all seriousness, that was the single thing our instructor wanted us all to take away from the lessons, after learning and no doubt forgetting the details.
Nobody can give you a simple answer to your question; ask a statistician (not some guy on a blog; try your local college or university, you may be able to hire a few hours of a statistics grad student’s time quite reasonably to get you started)
> AGW-math
This appears to be a buzzword on the “INTERNET” but not to relate to anything coherent. Is it boring yet?
skgsays
Thanks tamino.
I can probably get my dean to agree to a little outside statistical consulting. So all hope is not lost.
P.s. I follow your blog too. I swear I have learned more about statistics from it than from the statistics texts I have on my desk.
A ‘gwinnevere’ shows up elsewhere discoursing on climate as ‘wkg/gwinnevere’ — this stuff may be coming out of an explanation of everything found at http://www.universumshistoria.se/
“… there is apparently a fixed pattern geometry for nuclear physics, like the Pythagorean theorem to the mathematics of geometry. But it is completely unknown in modern academia and science….”
(ps, that was a Google Translate version from the original Swedish)
Meowsays
Once again, Gwinnevere, you are fitting a curve to the data using variables that have no foundation in the applicable physics, then using the curve to extrapolate into the future.
If I want to estimate atmospheric CO2 concentrations in some future year, I’ll want to start by understanding the existing CO2 content, how much CO2 is likely to enter the atmosphere, and how much is likely to leave it. That leads me to look up the existing (well-measured) content, then to try to understand the nature and magnitude of the processes that add CO2 (e.g., decomposition, anthro burning, land use changes, natural burning, oxidation of CH4, etc.) and those that remove it (e.g., biomass uptake, ocean uptake, weathering, etc.).
Why do I do that, rather than just projecting a curve? Because those phenomena actually govern the concentration I’m trying to determine. A curve that fits some portion of the existing CO2 concentration record does not do that. While it might be usable for an off-the-cuff estimate good enough for blogs, it’s not going to catch, for example, the effects of a (hypothetical) economic depression that halves anthro burning input, or an (I hope hypothetical) study finding that clathrates’ decomposition is about to accelerate wildly. Why not? Because it isn’t based in the phenomena underlying the data it’s being used to extrapolate.
If you want insight into climate, you should try to understand the phenomena that drive it. And those are things like heat inputs, outputs, and means of transport; concentrations of various gases in the atmosphere and solids in the oceans; absorptivities, emissivities, and reflectivities of various surfaces; and so on. Fitting a temperature curve tells you nothing about those phenomena, and thus nothing about climate.
CAPTCHA: allimpe Habits
ccposays
Re: #271 (Gwinnevere)
In mathematical physics, a “triple power function unity by integral-derivatives” is, as far as I know, a nonsense phrase. It sounds like a bunch of words you strung together but you don’t really have a clue what it means.
Perhaps you should seek the help of someone who speaks English.
Comment by tamino — 13 Jul 2011 @ 1:16 PM
Absolutely. Having taught EFL for years, I’m fairly skilled at deciphering Second Language text. I am completely lost with Gwinnevere’s samples. I believe you have hit on the solution. There is another option. Given her science chops, so far as anyone can tell through the mangled English, seem to be in trouble, too, she may want to stop posting altogether.
It might be interesting to see what happens if the English is tidied up first, though. If Hank’s intel is right, maybe one of our Swedish friends can sort out what she’s trying to say.
Rustysays
Hello (somehow I am mistaken for spam), I was wondering if there are any GCMs which deal with 21st century temperatures? (Is that the Hadcm3?) Obviously I am a layperson, so lay-explanations or websites would be appreciated. Thanks.
[Response: Yes, all of them. There is a lot of information in Ch. 10 of the AR4 report, and you can download the raw data at climateexplorer for instance. – gavin]
Gwinneveresays
Answer from Gwinnevere on previous posts:
— I have been trying to post answers to the previous comments from you, all. But they seem to have been lost — while still more commenting from you on the previous Gwinnevere’s posting continue to pop in.
— Unless given space to answer, I am in no position to given appropriate arguments to any of you.
Gwinnevere
[Moderator: there will be no more comments from or about you, until you have something constructive and sensible to say. Sorry.]
Hunt Janinsays
Can Bayesian networks be used to study sea level rise? If so, how?
The greatest mystery of the modern world is not how the pyramids were made, nor is whether HARP is causing changes in weather patterns, the greatest mystery is how ignorant contrarians are, and how utterly devoid of cognition they suffer. The proper way to see this is amazement, ice vanishes fast clearly visible from space while they argue that there is a lull in temperature or the whole global warming thing is a hoax. I should have pity on them, but their influence is so negative and damaging, they should go away to unimportant oblivion like News International. But the outrage is for those who know, and we share poorly our opinions.
Gwinneveresays
[edit – enough is enough. Please take it elsewhere]
the greatest mystery is how ignorant contrarians are, and how utterly devoid of cognition they suffer.
I’m still leaning towards the Younger Dryas rerouting and Lake Agassiz discharge hypothesis as the ‘big mystery’ myself. What’s your take, MacKenzie River and the Arctic as per Murton et al., or some mysterious and still unexplained Lake Superior discharge event through the Laurentide Ice Sheet across Lake Superior and the on through Champlain Sea as proposed by Rayburn et al.?
Timothy Fisher once claimed the Lake Agassiz Moorehead discharge is not even correlative with the Younger Dryas, and so that’s even up for grabs. Feel free to change your hypotheses, your theories and your minds, often and dramatically, if necessary. Or perhaps Murton and Broecker finally have you convinced, even though they can’t seem to make up their minds either. In fact, looking over the literature, almost every single player here (besides the impact hypothesis crowd) have changed their minds at least once, and contradicted their own work with further newer work several times already. If that isn’t exciting, I don’t know what is!
Jack R.says
I submitted a letter to the editor of The Toledo Blade, and it got published today. They condensed it down, leaving out much of what I wrote. One thing I wrote that was deleted was my statement that if the non-condensable GHGs were removed from the atmosphere, the surface temp would drop about 30 C, ending at about 4 F. I wrote that the planet would end up being a frozen ball of ice. I’m sure they couldn’t verify that, so it was deleted. Was I right? I guess I added something that wasn’t in the recent NASA study.
[Response: The Lacis et al study showed an even bigger drop, but it is in the right ballpark. – gavin]
[Response: Thanks Jack; these letters are important. Appreciated seeing yours, and the one before it, in the old home town paper that I used to deliver.–Jim]
#285 During summer, I study from still an island which was once amongst the sea of Champlain. I can see its shorelines of long ago daily. Climate science is ever evolving but some cant get the very basics, the clues are in the fossils, lots of work to unravel. Glacial monster lakes are of interest because of the similarities between fresh water dumping to sea, as we do have this in terms of millions of cubic kilometers from sea ice melts of now a days.
“A group of some of Britain’s best-known authors and artists has condemned the British Council’s “extraordinary” decision to all but end its groundbreaking international work on climate change and demanded the decision be reconsidered.
The move has also been criticised by Foreign and Commonwealth Office (FCO) minister Jeremy Browne who, in a letter leaked to the Guardian, admonished the council’s chief executive for his apparent “termination” of one of the council’s “success stories”.
[…]
The work has been praised as highly effective in fostering action on climate change by China’s ministry of education, as well as the NDRC, and by groups working in China such as the International Energy Agency and the Carbon Trust.”
Perhaps some climate scientists could chip in?
AICsays
Significance of climate science:
Accurate projections of future climate provide an economic basis for taking action now.
Administration Grossly Underestimated Carbon Cost, Says Study
“The chief of the world’s leading physics lab at CERN in Geneva has prohibited scientists from drawing conclusions from a major experiment. The CLOUD (“Cosmics Leaving Outdoor Droplets”) experiment examines the role that energetic particles from deep space play in cloud formation. CLOUD uses CERN’s proton synchrotron to examine nucleation.
CERN Director General Rolf-Dieter Heuer told Welt Online that the scientists should refrain from drawing conclusions from the latest experiment.
“I have asked the colleagues to present the results clearly, but not to interpret them,” reports veteran science editor Nigel Calder on his blog. Why?”
It then goes on to quote Svensmark and Calder making disparaging statements. Anyway, I’m interested to see what comes out of this. I think it’s smart to not make interpretations from one experiment myself, even if the conclusions seem obvious, especially since the experimental conditions are so unlike anything done before. Oh course that isn’t what folks like Svensmark want. Anyone else have thoughts on this or more interesting news on it?
[Response: The context is that people (specifically Svensmark and Calder) have been grossly overinterpreting the results from earlier experiments to the almost certain embarrassment of anyone sensible connected to the CERN project. The fact of the matter is that these experiments will not by themselves demonstrate the impact of GCR on climate however well they turn out. This is because it is not that the role of ionisation in creating aerosols that is disputed, but rather how modulations of that effect impact the overall growth of the much larger cloud-condensation nuclei and where this makes a difference to clouds (via an aerosol indirect effect). The demonstration of an ionisation source of aerosols doesn’t even tell you the sign of the impact on climate, let alone the magnitude. And furthermore, the trends in GCR have been flat for over half a century and so have no role to play in recent trends in climate, regardless of the size of the putative GCR-clouds link. – gavin]
Shirley Pulawskisays
Thanks for providing the context, Gavin. I’ve wondered for years now what, if any, dynamic existed between Svensmark and the research, because it’s been hard to find anything that doesn’t at least try to hint that the massively expensive facility was perhaps inspired by Svensmark’s work, no doubt because the rare times anything ends up in press about it, Svensmark gets quoted, and often the piece makes Svensmark seem linked to the research.
It’s also interesting to see the way deniers language hasn’t evolved (no surprise). It’s nice the way Calder takes the translated “…make the results clear, however, not to interpret” and then further translates that into “forbids” which is what we learn in science classes to no do. Or at least what really good profs try to pound into our skulls.
And thanks also for the graph. I was looking for something like that a while back so I’ve added that to my collection.
When you go far enough out any spoke of the political wheel, in any direction from the political center, you find you’re among people who went a little too far. Here’s another nutty noose: http://www.act-responsible.org/ACT/ACTINCANNES/THEEXPO2009.htm
Tomsays
I’ve noticed the heat wave in the Midwest/Plains is accompanied by some seriously high dewpoints, some in the low 80’s. A thousand miles from the gulf I might add. I wonder if all that corn (especially the genetically engineered variety) and associated evapotranspiration plays a role?
Of course not. Humans can’t affect the atmosphere that way.
“Such a stand-alone statement however is not sufficient”
And that’s the problem, Gwinnevere. Your statistical skill is not yet advanced enough to see the obvious truth, still less to do the analysis required to assess it objectively. Yet you are presenting your result with confidence that comes from not understanding its significance (or lack of significance).
I suggest you ask for some help at Tamino’s blog. Or better yet, read some of Tamino’s past replies to curve fitters.
You are right in one way: if your goal was to approximate the data using a curve that fits extremely closely, and you aren’t concerned with what the curve means – then in that limited sense you did extremely well. But your curve has no explanatory power or physical basis, so it is no more likely to predict the future than any other guess.
So, if you think I am wrong and that you know exactly what you are doing, then go ahead and show us what happens when you withhold data from your model and recalculate the parameters – does it predict the withheld data to a significant degree? Compare your model to a simple linear model over the last 30 years. Which model has the most explanatory power? The “relative goodness of fit”? This is like an r^2 test, but it takes into account the number of parameters in the model.
I could do this for you, I suppose – but what would you learn then? :-) If you need help, ask here or in Tamino’s open thread.
Pete @ #250, thanks so much for that chart. It looks like average temperatures are about 1 to 1.5C during the summer, which I would guess means that the 2C temperature anomaly is pretty significant. I wonder if that is pretty much the upper limit, as long as there is ice up there to keep it cool.
No, +3.5C is not the upper limit, it’s quite common to have +10C degrees over snow or ice, warm enough air fowing on site warms the cold thin layer fast enough so it won’t get to the thermometer.
Captcha neforea follows
I think it’s hard for even the best intentioned people to truly wrap their heads around the fact that human activity can screw up the whole planet in a major way. Partly it’s a matter of non-intuitive scales, we’re not wired to think in those terms and need significant training to do so. Partly it’s habitual wisdom that s**t happens and when it does, as the legalism states, it’s “an act of God,” and thus who can fathom or dare to question such mysteries. Partly we just think we’re somehow exempt. There’s wonderful us, and then there’s everything else, put here for our benefit.
On top of that, you see people responding to problems by trying to forcibly match items from a repertoire of stock responses to imagined patterns. That might not be so bad for starters were it not for an abuse of authority that keeps people boxed in and unable to move to a point where they can think effectively for themselves, perpetuating a clueless class as it were. Even if someone manages get it, sort of, it’s often too easy and expedient to fall back into a default position.
It’s a jungle out there and up hill all the way.
Susan @ 247
Not political ambitions, ambitions of professionalism.
Well, who would have thought it, Dr Roy Spencer is a rabid free-marketeer…
Not content with laying waste to “warmists” arguments he is now set on putting Commie, pinko, Keynesian types in their place
– http://www.drroyspencer.com/2011/07/fundanomics-the-free-market-simplified/
Is there no beginning to this man’s talents?
Winds too much for Chicago.
Everyone? Seriously …
[edit – too far OT]
Jagged focus:
After removal of presumably major sources of noise, the adjusted surface temperature graph still has almost as much noise as before. Does anyone have an idea why? (I mean besides “noise happens”.)
too far OT
Too far off topic for an open thread?
Let’s talk about the Younger Dryas. The global warming thing is getting old. There isn’t much to talk about. It’s happening. There are positive feedbacks speeding it up, as well as anthropomorphic emissions slowing it down, but it’s still proceeding unabated, nevertheless. On the other hand, the Younger Dryas problem remains, unsolved and wonderfully controversial.
Discuss, if you wish. Thanks in advance.
Another geoengineering approach?
http://www.sciencedirect.com/science/article/pii/S1389556711000281
doi:10.1016/j.jphotochemrev.2011.05.002
Fighting global warming: The potential of photocatalysis against CO2, CH4, N2O, CFCs, tropospheric O3, BC and other major contributors to climate change
(Full text is paywalled; you can see the outline at the link
So, ah, how’s the “worst that can happen” list look nowadays? We should learn from the nuclear industry to to be overly optimistic.
Does Peter Ward still hold the candle for worst case? That would require very unlikely events — major floods, pulse of sediment into the oceans from the rivers, large areas of the ocean surface along the continental shelves going anoxic, a good bit of sulfur reaching the surface, and an extinction event.
So far I haven’t mention in the news of … Oh, wait …
Improved information on precise CO2-quantities from AGW-math to no209 wili:
General equation (referenced at post no140),
CO2(ppmv) = (12.7576)*(((YEAR-OffsetYear)/121.41)^4.25)+286
Note that this expression is a (very) close approximation to the actual integral solution (as yet, no available world source is able to give its algebraic form). It is limited to approximately year 2028 [by a proceeding tangent of ca 3.4]. Above that, we must use exact values from a numerical solution (Simpson Formula, or the »Hypo-series» formula).
Preferences in the basic AGW-math accounts for an offset margin of ±5 years, mainly due to a (least) general surface ocean (0-500 M) period (see also note below).
With respect to the available (from 1959) CO2-data from Mauna Loa at
ftp://ftp.cmdl.noaa.gov/ccg/co2/trends/co2_annmean_mlo.txt
a shorter investigation (13Jul2011/Gwinnevere) on the AGW-math’s CO2 industry integral shows a nearly exact match by the horizontal scale OffsetYear = 1811:
CO2(ppmv) = (12.7576)*(((YEAR-1811)/121.41)^4.25)+286
With (MaunaLoa)/(AGW) the lowest up to the last MaunaLoa-value 2010 is 99.69%, highest 100.61%. That gives at most a ±0.7% deviation. These ±-levels are skittering (or sidestepping) to and fro in the table roughly but not exactly on a 5-10 year base, interval 1959-2010.
To find the exact year by a given CO2-value is then calculated by
1811 + (121.41)([CO2(ppmv) – 286]/[12.7576])^1/4.25 = YEAR
With 400 ppm input (no209 wili), the precise AGW-answer is
YEAR = 2014.26
0.26×365=94.9 (-Jan31, -Feb28, -Mar31 = 90)
(Phillip Shaw already did point out a similar value in post no225).
= 4Apr2014 at 21:36 after midnight [9:36 PM]
No extra CO2 besides the industrial contribution
——————————————————————————————
The presumption of an eventual CO2-addition from side-effects is effectively erased by the above clarification. That is, there is yet (2011) according to the given AGW-math no (direct observable) additional CO2 added in the atmosphere besides the part given through the AGW-math (precise) CO2-levels from the industrial fossil carbon emissions (as measured at Mauna Loa). That is (very) good news, in the middle of the bad ones.
NOTE — precise ocean data are sparse.
——————————————————————————————
The only available public free sources seen on INTERNET as I have found prior to the AGW-math description, are the ones referenced by me in post no140 together with some information on
https://www.realclimate.org/index.php/archives/2004/11/atlantic-multidecadal-oscillation-amo/
Some older (primary) data from early investigations may be found in different books of reference in physics in general (in different countries), such as f.ex. the Swedish FOCUS MATERIEN Almquist & Wiksell 2:nd ed. 1975 p487col2b [surface period 5 years 0-500 M, polar ocean period ca 50 years].
(If any of you should believe thath the AGW-math [post no140] is BASED on »D’Aleo-data» you are in deep delusion).
— Due to the great difficulties of observation and general theory, no general agreement is yet (2011) found on ocean data.
— Some persons here at RealClime might have the impression that the referenced ocean data from Joseph D’Aleo (2008) at post no140 should have been qualified as RELIABLE. That adjective has never been used by me in connection with ocean data. The word of description is: AVAILABLE. Together with the RealClime-reference above: There are no other publicly, free, available data for the average Internet user to access on ocean data, as far as I know. The rest is up to the measured NASA/CRU/GISS-temperature curves, and their equivalents by known — reliable — components.
Gwinnevere
no237 Ray Ladbury:
— Hello Ray Ladbury.
I was aiming at a confrontation with some PRINCIPLE argument on the AGW-quest. I think I have found one now.
— By QUALITY: Of course there is nothing such as »AGW-math». It has no notation in the established academic community. That is also clear from the post no140: the present established »climate-math» is entirely referenced to Arrhenius math. As the post reference shows, however, this Arrhenius math ”as accepted by 97-98% of publishing climate scientists” as you say, is an approximation to the three derivative-integral functions that EXPLAIN current data (Sea, Industry, CO2), including Arrhenius math as a (close) approximation. To exemplify, your »AGW-math», not Arrhenius math, explains current CO2-measured (Mauna Loa) data. To be noted.
— By QUANTITY, hence, the term »AGW-math» is appropriate in use to refer the actual connections, comparisons, results and presentations, and only as far as the quantities DO match observations from research. There is nothing else to it.
(In »ancient science», such »formulae» we held to be »empirical»).
I really appreciate your arguing. It just promotes the purpose. Thank you very much.
Gwinnevere
no239 JCH:
— Hello JCH.
First: You seem to be asking if I think 2008 was a year from the warmest decade?
— I don’t know that, really, JHC. I have to pass it on.
Second:
”reconcile [»try to fit or match»] these with your ”lull””
— The HADCRUT (global mean), GISTEMP (land-ocean global mean), UAH (lower trop. global mean) are not that easy to interpret on a now-basis — yet.
Last averaged value in the last updated version
http://climate.nasa.gov/keyIndicators/
ends at 2007.
— To be honest with you, from my personal side JHC, I am unable to match not yet settled average data to the same general curvature as the one in the past (up to 2007).
— For the record, we can exclude the UAH- data as these deal with atmospheric layers far above the one in concern of the AGW-math part (maximum h=60 M).
— The other two, mutually showing the same picture, has a mean horizontal trend the period 1998-2009.
— It is too early as I understand it, yet, to run to (general) conclusions. You seem to point out that HADCRUT and GISTEMP data would indicate the AGW-math-dotted continuing (from 2005 an on) to be erroneous.
— In that case, JCH, you are at first perfectly right, the AGW-match is corrupt, and at second we are in exceptional trouble as to the possible change of the oceanic behavior.
Gwinnevere
no 242 Rich Creager:
”Are you a text generator”?
— RealClimate WebSite is no exception in generating (unwanted) invitations to persons not interested in the scientific matter.
— I have no whish to escape these individuals in their off-the-record-posts. I would like to meet them and share the arguing. However, as you already know, this web page is not intended for such discussions. Thank you for sharing.
Gwinnevere
no251 Didactylos:
”Your curve has no explanatory power or physical basis”.
— I think I am awake in reading the above statement.
Didactylos, a »model» connects to statistics, probability. Knowledge connects to certainty, which is an abstract concept for statistics. AGW has no connection to probability.
How is it Didactylos?
IF, as you say, the »AGW-math» would have zero accountability in any scientific sense, how is it that the top function — to exemplify — of the three power functions having the Arrhenius logarithmic/exponent functions as close approximations, the CO2-part, matches measured (Mauna Loa) values with a maximum deviation of ±0.7%?
— You don’t find a finer qualitative match by a set of three power functions explaining the measured quantities (Sea, Industry, CO2) — the cause of AGW, its process and its extension.
To me, that seems rather the opposite to your claim:
»Your curve HAS explanatory power AND physical basis».
— The authoritative recommendations you make at the end of your post, in the light of the actual quantities, seems to testify you are understanding mathematics as such in a principal erroneous (irrelevant) way. Thank you for sharing.
Gwinnevere
I’m trying to get a friend to reevaluate her scepticism on climate change. Her scpicism isnot ideologically based. Rather it comes from a combination of over generalization from her experience in her field and from getting her information from biased sources. Her work has been mostly in safety-critical computer systems.
Now I remember seeing here and somewhere else a list of about five points comparing the sorts of models that scientists that are likely to understand climate change work on to the sorts of models that experience with predisposes someone to doubt it. It might have been a comment of John Mashey’s wrote or a response to one of his but I’m not sure. Con anyone direct me to it.
@ 265, is that a “yes”?
;)
Gwinnevere: No.
You’re not even wrong.
Learn to walk before you try running.
Hi all,
I have been lurking here for many years, and this is my first post. It’s not even directly about climate science, but more about statistics in general. I have had no formal training in statistics but I am interested in measuring the complexity of something (criminal trials). I have brainstormed and come up with about 20 variables that I would think would correlate somewhat with complexity of criminal trials. But I don’t think I need 20 variables to estimate complexity. Moreover I would guess that many of them correlate quite highly with each other (multi-collinearity?). So I am sort of stuck trying to decide which of the possible explanatory variables to use.
My plan at the moment is to take a random sample of criminal trials (how many would I need? 30?), read the records, and then manually arrange them from least to most complex. I would then test my possible explanatory variables to see how well they correlate with the “expert ordering” and pick the one or two (or maybe three or four?) that show the highest correlation. Then I can use these explanatory variables to go back to the main data set and calculate complexity scores for the entire population.
Does that sound reasonable? Are there better ways to do it?
Thanks in advance.
RealClimate-Questionability about the reliability of mathematical physics in the AGW-quest
——————————————————————————————
In mathematical physics, a triple power function unity by integral-derivatives is, as far as I know, considered one of the strongest structures that exist at all in this beautiful Universe of ours. It is to be understood as a reference of exceptional solidity, especially in communicating quantitative results.
If any single one of the individual functions shows a clear and unmistakable mismatch to experimental observation, we can safely disregard the other two too: the structure is not the one we are looking for. Next.
If on the other hand any single one of the individual functions shows a match, a correspondence, with experimental, measured, observation of the kind 99.3%, so the other two have to.
— The AGW-quantities, here in strong question by several persons, are seen to correspond within 99.3%, as mentioned by the post connected to the CO2-question by wili in post no209.
From that point of view, I find it really bizarre that some persons here at RealClimate »have the nerve» to sentence — erase — the entire complex with such finalizing power as, TYPE
”It is wrong”,
”You don’t understand statistics”,
”You are executing a primitive level of mathematical skill”,
”You need help” (my favorite),
not to say other incitements of the kind not related to this WebSite.
— The only way to »KILL» the AGW-math part, is to Find/GIVE REFERENCES by comparing quantities. As yet, I have seen none — but I would very much like to.
Gwinnevere
Re: #270 (skg)
First, I suggest using far more than 30 samples for your model. You say you have 20 variables which might be useful, then there’s also a constant (roughly speaking, the “mean value” of complexity), so if you used all explanatory variables you’d have 21 degrees of freedom in the model and only 30 in your sample, leaving only 9 degrees of freedom for other variation (call it “natural variation). That’s very small!
I suggest you use at least 100, and far more if you can. I know it seems like a lot of work, and it is. But that’s the price you pay — the more data you have, the better your answer, the less data, the worse.
Your general plan seems reasonable: take a sample, fit a model, then apply it to the entire population. The question of how many explanatory variables to include is tricky. Too few, you don’t get as useful an answer as possible. Too many, you become susceptible to “overfitting” in which your model matches the randomness rather than the reality.
There are strict ways to determine which variables to use. Perhaps most intuitive is stepwise regression. There are two versions. One is to start with no explanatory variables, then add one at a time, each time adding the one which gives the greatest improvement to the model. At each step you test whether or not adding a new variable gives improvement which is statistically significant. When it doesn’t, you stop.
The other way is to start with all the explanatory variables, then eliminate one at a time, each time removing the one which causes the least degradation of the model. At each step you test whether or not the degradation is statistically significant. When it is, you stop.
There are other approaches too. There are things called “information criteria” which evaluate model performance, accounting for both how well the model fits and how many parameters (explanatory variables) it uses. The best-known is AIC (Akaike Information Criterion) and its cousin AICc (corrected AIC, for small samples), also prominent is BIC (Bayesian Information Criterion aka Schwartz Information Criterion), and there are others too.
There are also ways to reduce the number of parameters by combining explanatory variables. A good example is “principal component analysis” (PCA), which finds combinations of explanatory variables that account for most of the variability in your model. And there are other ways too.
Frankly: the problem is an intricate one. If you can find a pro to help, that will make things go a lot faster and you’ll avoid the almost inevitable mis-steps.
If you must do it yourself, the best advice is to use as much data as possible and try a heckuva lot of possibilities. More data = better answer.
Re: #271 (Gwinnevere)
In mathematical physics, a “triple power function unity by integral-derivatives” is, as far as I know, a nonsense phrase. It sounds like a bunch of words you strung together but you don’t really have a clue what it means.
Perhaps you should seek the help of someone who speaks English.
> skg
What I learned from Statistics 101: consult a statistician first, before taking data. In all seriousness, that was the single thing our instructor wanted us all to take away from the lessons, after learning and no doubt forgetting the details.
Nobody can give you a simple answer to your question; ask a statistician (not some guy on a blog; try your local college or university, you may be able to hire a few hours of a statistics grad student’s time quite reasonably to get you started)
> AGW-math
This appears to be a buzzword on the “INTERNET” but not to relate to anything coherent. Is it boring yet?
Thanks tamino.
I can probably get my dean to agree to a little outside statistical consulting. So all hope is not lost.
P.s. I follow your blog too. I swear I have learned more about statistics from it than from the statistics texts I have on my desk.
A ‘gwinnevere’ shows up elsewhere discoursing on climate as ‘wkg/gwinnevere’ — this stuff may be coming out of an explanation of everything found at http://www.universumshistoria.se/
“… there is apparently a fixed pattern geometry for nuclear physics, like the Pythagorean theorem to the mathematics of geometry. But it is completely unknown in modern academia and science….”
You read it there first.
(ps, that was a Google Translate version from the original Swedish)
Once again, Gwinnevere, you are fitting a curve to the data using variables that have no foundation in the applicable physics, then using the curve to extrapolate into the future.
If I want to estimate atmospheric CO2 concentrations in some future year, I’ll want to start by understanding the existing CO2 content, how much CO2 is likely to enter the atmosphere, and how much is likely to leave it. That leads me to look up the existing (well-measured) content, then to try to understand the nature and magnitude of the processes that add CO2 (e.g., decomposition, anthro burning, land use changes, natural burning, oxidation of CH4, etc.) and those that remove it (e.g., biomass uptake, ocean uptake, weathering, etc.).
Why do I do that, rather than just projecting a curve? Because those phenomena actually govern the concentration I’m trying to determine. A curve that fits some portion of the existing CO2 concentration record does not do that. While it might be usable for an off-the-cuff estimate good enough for blogs, it’s not going to catch, for example, the effects of a (hypothetical) economic depression that halves anthro burning input, or an (I hope hypothetical) study finding that clathrates’ decomposition is about to accelerate wildly. Why not? Because it isn’t based in the phenomena underlying the data it’s being used to extrapolate.
If you want insight into climate, you should try to understand the phenomena that drive it. And those are things like heat inputs, outputs, and means of transport; concentrations of various gases in the atmosphere and solids in the oceans; absorptivities, emissivities, and reflectivities of various surfaces; and so on. Fitting a temperature curve tells you nothing about those phenomena, and thus nothing about climate.
CAPTCHA: allimpe Habits
Re: #271 (Gwinnevere)
In mathematical physics, a “triple power function unity by integral-derivatives” is, as far as I know, a nonsense phrase. It sounds like a bunch of words you strung together but you don’t really have a clue what it means.
Perhaps you should seek the help of someone who speaks English.
Comment by tamino — 13 Jul 2011 @ 1:16 PM
Absolutely. Having taught EFL for years, I’m fairly skilled at deciphering Second Language text. I am completely lost with Gwinnevere’s samples. I believe you have hit on the solution. There is another option. Given her science chops, so far as anyone can tell through the mangled English, seem to be in trouble, too, she may want to stop posting altogether.
It might be interesting to see what happens if the English is tidied up first, though. If Hank’s intel is right, maybe one of our Swedish friends can sort out what she’s trying to say.
Hello (somehow I am mistaken for spam), I was wondering if there are any GCMs which deal with 21st century temperatures? (Is that the Hadcm3?) Obviously I am a layperson, so lay-explanations or websites would be appreciated. Thanks.
[Response: Yes, all of them. There is a lot of information in Ch. 10 of the AR4 report, and you can download the raw data at climateexplorer for instance. – gavin]
Answer from Gwinnevere on previous posts:
— I have been trying to post answers to the previous comments from you, all. But they seem to have been lost — while still more commenting from you on the previous Gwinnevere’s posting continue to pop in.
— Unless given space to answer, I am in no position to given appropriate arguments to any of you.
Gwinnevere
[Moderator: there will be no more comments from or about you, until you have something constructive and sensible to say. Sorry.]
Can Bayesian networks be used to study sea level rise? If so, how?
With nearly and surely to exceed 5 million cubic kilometers of fresh arctic ocean ice gone,
http://psc.apl.washington.edu/wordpress/wp-content/uploads/schweiger/ice_volume/BPIOMASIceVolumeAnomalyCurrentV2.png
The greatest mystery of the modern world is not how the pyramids were made, nor is whether HARP is causing changes in weather patterns, the greatest mystery is how ignorant contrarians are, and how utterly devoid of cognition they suffer. The proper way to see this is amazement, ice vanishes fast clearly visible from space while they argue that there is a lull in temperature or the whole global warming thing is a hoax. I should have pity on them, but their influence is so negative and damaging, they should go away to unimportant oblivion like News International. But the outrage is for those who know, and we share poorly our opinions.
[edit – enough is enough. Please take it elsewhere]
the greatest mystery is how ignorant contrarians are, and how utterly devoid of cognition they suffer.
I’m still leaning towards the Younger Dryas rerouting and Lake Agassiz discharge hypothesis as the ‘big mystery’ myself. What’s your take, MacKenzie River and the Arctic as per Murton et al., or some mysterious and still unexplained Lake Superior discharge event through the Laurentide Ice Sheet across Lake Superior and the on through Champlain Sea as proposed by Rayburn et al.?
Timothy Fisher once claimed the Lake Agassiz Moorehead discharge is not even correlative with the Younger Dryas, and so that’s even up for grabs. Feel free to change your hypotheses, your theories and your minds, often and dramatically, if necessary. Or perhaps Murton and Broecker finally have you convinced, even though they can’t seem to make up their minds either. In fact, looking over the literature, almost every single player here (besides the impact hypothesis crowd) have changed their minds at least once, and contradicted their own work with further newer work several times already. If that isn’t exciting, I don’t know what is!
I submitted a letter to the editor of The Toledo Blade, and it got published today. They condensed it down, leaving out much of what I wrote. One thing I wrote that was deleted was my statement that if the non-condensable GHGs were removed from the atmosphere, the surface temp would drop about 30 C, ending at about 4 F. I wrote that the planet would end up being a frozen ball of ice. I’m sure they couldn’t verify that, so it was deleted. Was I right? I guess I added something that wasn’t in the recent NASA study.
[Response: The Lacis et al study showed an even bigger drop, but it is in the right ballpark. – gavin]
[Response: Thanks Jack; these letters are important. Appreciated seeing yours, and the one before it, in the old home town paper that I used to deliver.–Jim]
#285 During summer, I study from still an island which was once amongst the sea of Champlain. I can see its shorelines of long ago daily. Climate science is ever evolving but some cant get the very basics, the clues are in the fossils, lots of work to unravel. Glacial monster lakes are of interest because of the similarities between fresh water dumping to sea, as we do have this in terms of millions of cubic kilometers from sea ice melts of now a days.
Soil carbon and climate change: from the Jenkinson effect to the compost-bomb instability
http://climateforce.net/2011/07/14/soil-carbon-and-climate-change-from-the-jenkinson-effect-to-the-compost-bomb-instability/
The British Council decides to axe its highly successful climate programme.
Authors and artists publish an open letter asking them to reconsider.
“A group of some of Britain’s best-known authors and artists has condemned the British Council’s “extraordinary” decision to all but end its groundbreaking international work on climate change and demanded the decision be reconsidered.
The move has also been criticised by Foreign and Commonwealth Office (FCO) minister Jeremy Browne who, in a letter leaked to the Guardian, admonished the council’s chief executive for his apparent “termination” of one of the council’s “success stories”.
[…]
The work has been praised as highly effective in fostering action on climate change by China’s ministry of education, as well as the NDRC, and by groups working in China such as the International Energy Agency and the Carbon Trust.”
Perhaps some climate scientists could chip in?
Significance of climate science:
Accurate projections of future climate provide an economic basis for taking action now.
Administration Grossly Underestimated Carbon Cost, Says Study
http://www.nytimes.com/cwire/2011/07/14/14climatewire-administration-grossly-underestimated-carbon-69396.html
The “Social Cost of Carbon” and Climate Change Policy
http://www.wri.org/stories/2011/07/social-cost-carbon-and-climate-change-policy
Climate denier brandishes noose to scientist at climate conference
That was Lyndon LaRouche of Australia’s Citizens Electoral Council.
Anyone hear about the CERN CLOUD project news?
http://www.theregister.co.uk/2011/07/18/cern_cosmic_ray_gag/
“The chief of the world’s leading physics lab at CERN in Geneva has prohibited scientists from drawing conclusions from a major experiment. The CLOUD (“Cosmics Leaving Outdoor Droplets”) experiment examines the role that energetic particles from deep space play in cloud formation. CLOUD uses CERN’s proton synchrotron to examine nucleation.
CERN Director General Rolf-Dieter Heuer told Welt Online that the scientists should refrain from drawing conclusions from the latest experiment.
“I have asked the colleagues to present the results clearly, but not to interpret them,” reports veteran science editor Nigel Calder on his blog. Why?”
It then goes on to quote Svensmark and Calder making disparaging statements. Anyway, I’m interested to see what comes out of this. I think it’s smart to not make interpretations from one experiment myself, even if the conclusions seem obvious, especially since the experimental conditions are so unlike anything done before. Oh course that isn’t what folks like Svensmark want. Anyone else have thoughts on this or more interesting news on it?
[Response: The context is that people (specifically Svensmark and Calder) have been grossly overinterpreting the results from earlier experiments to the almost certain embarrassment of anyone sensible connected to the CERN project. The fact of the matter is that these experiments will not by themselves demonstrate the impact of GCR on climate however well they turn out. This is because it is not that the role of ionisation in creating aerosols that is disputed, but rather how modulations of that effect impact the overall growth of the much larger cloud-condensation nuclei and where this makes a difference to clouds (via an aerosol indirect effect). The demonstration of an ionisation source of aerosols doesn’t even tell you the sign of the impact on climate, let alone the magnitude. And furthermore, the trends in GCR have been flat for over half a century and so have no role to play in recent trends in climate, regardless of the size of the putative GCR-clouds link. – gavin]
Thanks for providing the context, Gavin. I’ve wondered for years now what, if any, dynamic existed between Svensmark and the research, because it’s been hard to find anything that doesn’t at least try to hint that the massively expensive facility was perhaps inspired by Svensmark’s work, no doubt because the rare times anything ends up in press about it, Svensmark gets quoted, and often the piece makes Svensmark seem linked to the research.
On that note, it’s ironic that in the original article in German (thank you, Google Translate) http://www.welt.de/wissenschaft/article13488331/Wie-Illuminati-den-Cern-Forschern-geholfen-hat.html the first question asked if there are other CERN projects that don’t get any attention because of the LHC, then when Heuer talks about anything else, the interviewer goes back to the LHC.
It’s also interesting to see the way deniers language hasn’t evolved (no surprise). It’s nice the way Calder takes the translated “…make the results clear, however, not to interpret” and then further translates that into “forbids” which is what we learn in science classes to no do. Or at least what really good profs try to pound into our skulls.
And thanks also for the graph. I was looking for something like that a while back so I’ve added that to my collection.
>> Climate denier brandishes noose
> That was Lyndon LaRouche of Australia …
When did Australia get their own?
That one doesn’t much resemble the Lyndon Rouche of the USA.
No, I’m poking fun; the noose-hanger is supposedly a club member of some sort, not the boss of them.
When you go far enough out any spoke of the political wheel, in any direction from the political center, you find you’re among people who went a little too far. Here’s another nutty noose: http://www.act-responsible.org/ACT/ACTINCANNES/THEEXPO2009.htm
I’ve noticed the heat wave in the Midwest/Plains is accompanied by some seriously high dewpoints, some in the low 80’s. A thousand miles from the gulf I might add. I wonder if all that corn (especially the genetically engineered variety) and associated evapotranspiration plays a role?
Of course not. Humans can’t affect the atmosphere that way.
The heatpocalypse!
http://www.savagechickens.com/2011/07/heatpocalypse.html
Or, difficulties renaming things.
@ Hank Roberts 294
I know. My bad :/
Mad sky panoramic interlude.
Does anyone care to comment ?
http://climaterealists.com/index.php?id=8073
[Response: Fruit loops. – gavin]