Guest Post by Ira Glickstein
As I continue to plow through Vol 1 Issue 1 of the new Journal Nature Climate Change, I came to the following amazing statement:
Communicating the value of climate modelling … requires confronting such apparent contradictions as the fact that increasing a model’s complexity — by adding the behaviour of clouds, people or ecosystem feedbacks, for example — may actually increase the uncertainty in climate projections. Atmospheric scientist Kevin Trenberth of the US National Centre for Atmospheric Research in Boulder, Colorado, has explicitly warned that unless such seemingly paradoxical results are communicated carefully, the more complex modelling being used in climate simulations for the upcoming fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC) may confuse both the public and decision-makers, thereby reducing their willingness to act. [My emphasis]
“Apparent contradictions”? Heck yes, and more than simply “apparent”! The Warmists finally understand that including the major natural cycles and processes that affect climate change in their models will make it that much harder for them to convince the public that human activities are the main cause and, therefore, changing our activities the main solution!
Yet, the title of the paper that includes the above quote is The role of social and decision sciences in communicating uncertain climate risks – as if communications was the major problem, rather than the fact it is largely nonsense they are trying to communicate.
They base their opinion on Trenberth’s 2010 paper which includes these equally amazing words:
[An IPCC AR5 chapter] will deal with longer-term projections, to 2100 and beyond, using a suite of global models. Many of these models will attempt new and better representations of important climate processes and their feedbacks — in other words, those mechanisms that can amplify or diminish the overall effect of increased incoming radiation. Including these elements will make the models into more realistic simulations of the climate system, but it will also introduce uncertainties.
So here is my prediction: the uncertainty in AR5’s climate predictions and projections will be much greater than in previous IPCC reports, primarily because of the factors noted above. This could present a major problem for public understanding of climate change. Is it not a reasonable expectation that as knowledge and understanding increase over time, uncertainty should decrease? But while our knowledge of certain factors does increase, so does our understanding of factors we previously did not account for or even recognize. …
Trial and error
It has been said that all models are wrong but some are useful. …
Performing cutting-edge climate science in public could easily lead to misinterpretation, and it will take a great deal of work communicating carefully with the public and policymakers to ensure that the results are used appropriately. … what to do about climate change is a high-profile, politically charged issue involving winners and losers, and such results can be misused. In fact — to offer one more prediction — I expect that they will be.
[My emphasis]
When confused, when in doubt, run in circles, scream and shout.
Here is what they say (and what they may be thinking):
- Including important forcings, such as clouds, will increase uncertainty. (Yeah, we were much more certain when our simple models gave nice crisp conclusions that matched our political biases. Then we added some of the complexity of the real-world climate, and now the conclusions are uncertain. Could it be that our political biases are at fault? Nope, we just have to work on our communications tactics and “social and decision sciences” to sell this load of baloney to the great unwashed public.)
- The contradictions are merely “apparent” and the results merely “paradoxical”. (Yeah, if we merely communicate this stuff carefully so as not to confuse the public and decision makers and make them unwilling to act in the politically-correct way.)
- There are mechanisms that can amplify or diminish the overall effect of increased incoming radiation. (OOPS, we forgot about those effects that diminish the overall warming. How can we include them in a way that does not add to public uncertainty about our competence?)
- Scientific knowledge and uncertainty are supposed to increase over time. (So how come we keep looking dumber?)
- All models are wrong, but some are useful. (Why is it that as our models become less wrong they become less useful to our political agenda?)
- Public disclosure of climate science research results can lead to misinterpretation and results can and will be misused. (We better keep our climate research results away from the public until we get a chance to misinterpret and misuse them before the skeptics find out the truth behind our methods.)
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‘Adding clouds to the models increases uncertainty’?
Tomorrow’s weather forecast is to a degree uncertain so what chance do rubbish models have.
They just don’t know what they are talking about and can’t cope any more; Game set and match to the sceptics?
Kevin Trenberth of the US National Centre for Atmospheric Research in Boulder, Colorado, has explicitly warned that unless such seemingly paradoxical results are communicated carefully, the more complex modelling being used in climate simulations for the upcoming fifth assessment report of the Intergovernmental Panel on Climate Change (IPCC) may confuse both the public and decision-makers, thereby reducing their willingness to act.
————————————————–
Does that not say it all right there? Let’s tighten that sentence up a bit for both brevity and clarity:
Unless accompanied by marketing spin, the results will reduce the public’s willingness to act.
Boggles the mind. The “need to act” has already been decided, so any results that cannot be clearly intepreted in that manner are “seemingly paradoxical”. In fact, they are so strongly “seemingly paradoxical” that they have to be “carefully communicated” to that everone understands that we need to act. Otherwise they might just get interpreted as oh… the old resutls missed half the data, the new ones have more and there’s no need to act.
To tell the truth, I smell a rat. Their case is falling apart and they know the tied is turning, they can’t maintain the fiction any longer, mommy nature just ain’t cooperating. So… new model adds some things that were missing, increasing the uncertainty. Over time the models will get better and better, more accurate, and each rev there will, paradoxicaly, be less of a problem. At some point they’ll converge with actual observations and actual trends, call a press conference, and declare the whole thing a raging success and how lucky they are to have all been part of it. Anyone asks but hey, what about all those prophecies of doom from bedore?
Of those… yeah we weren’t as good at communicating back then as we are now… just a misunderstanding by the reporters. They really don’t know much about science you know.
This admission of the underestimation of the effect of clouds on their models must, by extension, also apply to their appraisal of past climate change.
I am reminded of Roy Spencer’s study:
http://www.drroyspencer.com/research-articles/global-warming-as-a-natural-response/
Maybe the crux of the IPCC Fifth Assessment Report will read:
“Some of the observed increase in global average temperatures since the mid-20th century could possibly be due to the observed increase in anthropogenic greenhouse gas concentrations.”
(“could possibly” means the assessed likelihood, using expert judgment, somewhere between 0% and 100%)
Adding clouds to models increases the uncertainity of getting a grant increase.
To continue on from Ziiex Zeburz says:
The ‘safety culture’ and ‘precautionary principle’ have come to to fore so much.
See the recent news about firefighters not being allowed in to rescue victims of London’s 7-7 bombings and how police officers watched a 10 year old boy drown in a pond (after he’d rescued his baby sister) because none of them had had “the required (pond-rescue) training”
Also, especially since Tony Blair tripled the size of the UK statute book (the number of things that make you A Criminal), the whole UK system treats its subjects as naughty and ignorant children that are simply not to be trusted with ANYTHING. Its almost to the point where we cannot change a lightbulb in our own homes without getting a qualified/registered/approved electrician to do it – lest we invalidate our home insurance policies.
Then, number of expensive hoops(s) he has to jump through to get that approval are simply mind blowing and have to be repeated annually, at great cost to everyone.
The whole climate change bandwagon is an extension of that because only governments employ climate scientists, only governments can afford them.
Oh what a tangled web we weave,
When first we practice climate science.
Andrew 30 says “I disagree; show me the actual measured data that supports that conjecture.”
Thank you Andrew. I wonder when science is going to realise that no-feedback climate sensitivity is a complete load of nonsense. DeltaT = Dedlta F/Lambda is one of the biggest pieces of scientific garbage that has ever produced.
So expect more hide the decline from AR5 in the cause clarifying the “message” (but there’s no agenda here you understand – just science).
So here is my prediction: the uncertainty in AR5′s climate predictions and projections will be much greater than in previous IPCC reports [..]
Interesting that the high “certainty” levels expressed in AR4 will have to be glossed over to make way for the new. Surely if you were 95% certain last time but now you are less certain then that is an admission that the previous 95% figure was simply plucked out of thin air.
Increasing model complexity it will not increase uncertainty, if the models become more accurate as a result.
The “apparent”, paradoxical situation results from the fact they are not being honest about huge uncertainty that is produced by using inadequate, oversimplified models that have been frigged to produce a match to historical data and pretending they can extrapolate out 100 years by matching a model to 50 years of data.
If they gave a true, scientifically calculated uncertainty of their model results only due to the way they (don’t) “model” clouds, everyone would see that the emperor has no clothes and would realise their models have no value even ten years into the future.
The post-normal scientific methods says that when the stakes are high and the results uncertain, we must act. Now, the results are becoming more uncertain, therefore we must act more. I hope i got that right. Mr. Hulme? Mr. Ravetz? Care to comment?
‘Clouds’ is the elephant in the room. It’s like driving at night with all headlights off – you can’t see where you are going (projections).
“thereby reducing their willingness to act.”
And there you have it.
First decide we all need to act, then decide on what we need to act upon, thereby making sure we still need to act upon something, anything.
Got to love the looney communist hippie hunters that hunt for unregulated revenue streams.
How does one deal with the complete illogic of the warmie position? I look at it this way, the reasonable ones are skeptics now, leaving the unreasonable ones, like Japanese soldiers in Pacific island caves, fighting on.
Jack says:
April 28, 2011 at 8:44 pm
How much wool can a warmist pull
Over everyones eyes?
Between us Aus and NZ, we produce a lot of bloody wool, and I don’t wreckon it’s enough. It may be a start though. 🙂
Add in a random factor and the results are less predictable. And they are surprised.
They make me feel old.
When it comes down to it, I am a determinist. I believe in strict causality down to the level and including every thought that pops into your or my head. But i am not the flavor of fool that thinks we will ever come anywhere near to mapping it to the level where we can predict anything but the crudest results and even then we’re likely wrong.
So, for practical purposes it might as well be random, even though, being a strict causalist, I don’t even believe in “randomness”, per se, when it comes right down to it. Bohr wasn’t wrong; it’s just that his model was incomplete — according to my live-dead cat.
But these bozos not are not only my fellow causalists, it seems, but they have the unmitigated egoism to imagine they can construct a tactically predictive climate model. What hubris!
So they are surprised that when they add an additional factor, their results become less predictable. Sheesh! WHAT are they THINKING?
The only thing absolutely predictable in this whole mess is my above comment . . .
The modellers inherited two bits of incorrect physics which because they were supposed to cancel each other out, misled the subject for 30 years.
1. There’s no ‘back radiation’: not only is the concept a breach of the 2nd law of Thermodynamics, Miskolczi showed it’s an artefact of Milne’s wrong choice of boundary condition when he solved a PDE: http://met.hu/doc/idojaras/vol111001_01.pdf
2. The modellers were misled by incorrect aerosol optical physics which predicts the cloud part of global dimming, ‘cloud albedo effect’ cooling in AR4.
By 2004, when Miskolczi left NASA frustrated by a bar on publication, NASA knew there was no proof of the optical effect. The wheels had come off the CAGW wagon.
The apparent way out was to substitute Twomey’s partially correct Mie physics with a fake ‘surface reflection’ explanation: http://geo.arc.nasa.gov/sgg/singh/winners4.html
This misled the rest of climate science. AR4 was incorrect when published. Correct the physics and ‘cloud albedo effect’ cooling changes to heating, another GW which explains palaeo-climate better than CO2-GW with its 800 year delay, also recent ocean heating [Asian aerosol pollution reducing the albedo of low level tropical clouds, a self limiting process when albedo asymptotes to 0.5].
I think I’ve never heard so loud
The quiet message in a cloud.
===========
Joe Miner said: “Don’t confuse them with facts, baffle them with BS!”
The prof in the next office to me in grad school had a poster with a similar motto(“if you can’t dazzle them with brilliance baffle them with BS”). I thought he actually lived it, which made the poster quite ironic.
As most of us probably know that the answer to the ultimate question is 42.
But what is the question? Thats what we need to find out. The new whizz-bang models might be able to tell us? Not.
So the formulation of the question will have to evolve away from its origins. That is what being a climate scientist is all about.
Sounds like a kind of ‘coded message’ to his colleagues and other climate mystics – sorry – scientists, suggesting they bury, obfuscate or diminish any results from future model runs that disagree with predetermined CAGW conclusions. Not to do science, actual scientists, or models down, but ‘climate science’ is a now a contradiction in terms. The total substitution of cherry-picked computer simulation for reality as ‘evidence’ would be hilarious but for the fact the ‘team’ seem to have actually convinced themselves it is a legitimate thing to do. Any real branch of science, this would be seen as confirmation bias, tautology ridden madness. Or maybe they don’t really buy their own nonsense? Maybe they just believe it’s okay to lie to the public on the back of little more than a superstitious hunch; that the public are as gullible and pliant as lazy journalists, and will see a lab coat (a la Milgram) and happily swallow any computer simulated BS they are fed? Maybe this insistence from those such as Trenberth that black equals white, and two plus two will now equal five is simply a face-saving exercise? Maybe they feel the public just won’t ‘get’ anthropogenic climate change if it is far in the future, slow, not particularly catastrophic or unprecedented, so feel the need to construct a more immediate narrative, forgetting in their fog of smug, statistics driven hubris that their long-term hunch is just that – a belief – no more real or provable than a belief in the impending wrath of an angry sun god. Or maybe it is just about the money and prospect of tenure? One thing that is certain is that once their own models start to betray them, unless they can hide the undesirable results, they’ve got a problem..
Reality is a messy, inconvenient thing, isn’t it? ;->
If they want more certainty in their climate projections, I think they should come up with a simpler model. In particular, get water out of it – I don’t understand how any model can successfully deal with something that goes from GHG vapor to albedo increasing cloud in under 100 meters.
Now, if they want accuracy too, well, then they’ll just have accept that it’s a tough to impossible task and spend a lot of time learning how to model water.
It’s not about communicating uncertainty…
it’s not about communication… it’s about
EVIDENCE .
I think the problem they have is with the English language. The word they wanted wasn’t
“add”, it was “acknowledge.”