Guest post by Alec Rawls
Andrew Orlowski at the UK Register has an anecdotal account of Downing College’s skeptics-vs-believers mash-up. Ace of Spades pulled the juiciest bit:
In short, the day lined up Phil Jones, oceanographer Andrew Watson, and physicist Mike Lockwood, the latter to argue that the sun couldn’t possibly have caused recent warming. He was followed by the most impressive presentation from Henrik Svensmark, whose presentation stood out head and shoulders above anyone else. Why? For two reasons. The correlations he shows are remarkable, and don’t need curve fitting, or funky statistical tricks. And he has advanced a mechanism, using empirical science [image above], to explain them.
At the other end of the scale, by way of contrast, the Met’s principle research scientist John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
Yes, you could say that.
Lockwood’s failed argument against a solar explanation
Orlowski on Lockwood:
The strongest argument, according to Lockwood, for the sun not being a driver in recent climatic activity is that “it has been going in the wrong direction for 30 years.”
Hmmm. So as soon as solar magnetic activity passed its peak, when it was still at some of the highest levels ever recorded, these very high levels of solar activity could no longer have caused warming?
As I have noted a number of times, this argument depends on an unstated assumption that, by 30 years ago (by 1980 or so), ocean temperatures had equilibrated to whatever forcing effect the 20th century’s high level of solar activity might be having. Otherwise the continued high level of forcing would continue to create warming until equilibrium was reached, regardless of whether solar activity had peaked yet. (The actual peak seems to have been solar cycle 22, from 1986-96, not 1980, as Lockwood claims.)
When I pressed Lockwood on his implicit equilibrium assumption he justified it by citing evidence that ocean temperature response to solar activity peters out (as measured by decorrelation) within a few years:
Almost all estimates have been in the 1-10 year range.
But decorrelation between surface temperatures and solar activity is very different from equilibrium. All decorrelation is measuring is the rapid temperature response of the upper ocean layer when solar activity rises or falls. That rapid response indicates that the sun is indeed a powerful driver of global temperature, but it says next to nothing about how long it takes for heat to carry into and out of deeper ocean layers.
This was brought out by AGW believers like Gavin Schmidt who are concerned about the energy balance implications of equilibration-speed. In a simple energy balance model, rapid equilibration implies (other things equal) that climate sensitivity must be low. Since belief depends on high climate sensitivity, the rapid equilibration claim cited by Lockwood had to be shot down, which was managed quite successfully (ibid).
In sum, Lockwood’s rapid equilibrium assumption is dead and buried, leaving him no grounds for dismissing a solar explanation for post 70’s warming. I’ll keep an eye out for video of Lockwood’s presentation, but I doubt he mentioned the rapid equilibrium assumption upon which his argument depends.
More punk students
Remember these graduate student “climate scientists,” going all Clockwork Orange for the planet or something:
Sounds like they made an appearance at Downing College too:
The audience had been good enough to heed Howard’s opening advice that “if anybody mentions Climategate, they’ll be evicted”. Nobody ambushed the CRU crew all day – it was all very polite. I noted that the skeptics made a point of listening politely to the warmists, and applauding them all. A group of students and a few others, simply giggled and mocked the skeptics, however from start to finish. One of their tutors (I presume) was in hysterics all day.
Give ’em an A. They learned their “observational evidence is not very useful” lesson well.
How satisfying it is when someone advancing a totally idiotic position is hammered by his own people. Though I cannot say that there is hope for the lot of them or even one of them.
Why isn’t this Quote of the Week?
“John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” ”
Really really?
If anyone has video evidence of this statement (audible), please, please get it posted and displayed with some context. It’s possibly the worst anti-science statement I’ve ever read.
After all, if they used observational evidence, somebody might observe that plants and animals thrive better in the summer than in the Spring and Fall, not to mention winter, and that could be the end of the hysteria.
Observational data has only 1 minor role when doing science by model. When you find your model doesn’t agree with the observations you know you have to can it and try again. Other than that, empirical data , who needs it?
Buffoon
The statement: “People underestimate the power of models. Observational evidence is not very useful,” is perfectly accurate. It is a statement about The Agenda which has little if anything to do with science.
“Why isn’t this Quote of the Week?”
My thoughts exactly. I just wonder if he actually kept a straight face will uttering such nonsense…
Can’t say much for the video.
“I am a climate scientist”
“I am the walrus”
“I Am the Very Model of a Modern Major-General”
Beatles and Gilbert & Sullivan got ’em beat, homey.
BTW, the sun is NOT a light switch. Have any of these idiots ever heard of thermal inertia? Just because I turn the stove off does not mean the kitchen immediately starts cooling off…
“People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
Apparently he was addressing how to persuade elected officials.
Pompous Git says: “It is a statement about The Agenda which has little if anything to do with science.”
Perfectly correct. All of the junk science propaganda is simply to make a case for a huge wealth and power grab, redistribution of wealth to cripple the undeveloped world, and to create a one-world government. Why else do you think that they are already planning to try to implement a UN world level environmental monitoring agency, the brand new World Environmental Organisation (WEO), at the meetings in 2012? They also want to give UNEp more power to pushing their policies.
On John Mitchell’s comment that “people underestimate the power of models. Observational evidence is not very useful.”
And Buffoon’s comment that “it’s possibly the worst anti-science statement I’ve ever read.”
I couldn’t disagree more. Mitchell is giving very sage advice here on the state of observational data in climate science (and no I am not being sarcastic). By running models, climate scientists should be able to test their theories without having to wade through the high noise levels and/or short-term high amplitude variations in global temps that make the data record so complex (and of limited use).
Sadly, it seems, many of these scientists are looking for disaster scenarios so we take every quote from a climate scientist with maximum skepticism – occasionally to the point of missing one.
John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
===============================================
Sounds like a bad re-run of Max Headroom…….
Climate models invalidate the real world
Observational evidence is worse than ‘not very useful’, it can be extremely damaging to beautifully crafted, lovingly polished, highly expensive models.
It is a bit like saying that a porcupine is ‘not very useful’ in a baloon factory.
There must be some kind of Stockholm Syndrome/Tron thing going on here. They seem to have become imprisoned by the computer models they created, and cannot bring themselves to disagree with the models, no matter how far the models deviate from reality. Bizarre.
“John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful”
I guess then, we can unequivocally say that: melting glaciers don’t mean squat; sea level changes have no relevance; polar bears aren’t really in danger; the thickness of arctic sea ice doesn’t matter, nor its extent; who cares if the Antarctic is warming?; changes in atmospheric CO2 don’t correlate to anything important; the hockey stick really was somebody’s bad joke; GISS and NCAR are wasting their time fudging the temperature history; Yamal trees really are just old firewood…
No, no, no. It’s a perfectly rational and justifiable statement. Determining how the Earth’s climate works by using observations is very difficult, because the climate signal is swamped by noise (weather, seasonal). Instead, with a model, you can fiddle with forcing functions and feedbacks, and run the model hundreds of times in experiments. The actual observational data is just another instance of those climate experiments. All you have to do is show that that your model could have generated the historical measurements, if only you had had enough butterfly wings to initialize the model with. As the feedbacks and forcing are fiddled with, the model results agree with, then don’t agree with, the observational data. Once the feedbacks and forcings are all tuned up, the model is golden, and has predictive capability.
I have no idea if this is /sarc or not, and I wrote it. But I can imagine a climate modeler saying it in all seriousness, and daring you all to point out the fallacy.
Steve from Rockwood says:
May 16, 2011 at 6:09 pm
Sadly, it seems, many of these scientists are looking for disaster scenarios so we take every quote from a climate scientist with maximum skepticism – occasionally to the point of missing one.
=================================================
“even a blind squirrel finds a nut once in a while”
Steve, First off, do you really believe climate science is advanced enough to make predictions that anyone should listen to?
And which ones should you listen to: warmcold, snowrain, droughtflood, windcalm…….
could, might, may, if……
Miss what?
“John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,”
Great- I assume this means we don’t need to spend anymore money on equipment to measure those pesky attributes anymore………………………….
Lockwood only recently acknowledged that the sun likely was responsible for the recent strong negative NAO and southerly displacement of the jet stream. He stated that it only had a local effect on England’s cold temps in December and January but did not have a global influence. The Altai glacier temperature reconstruction from an ice core demonstrates a twenty year lag from group sunspot number and atmospheric temperature over the last 750 years. This years decline (.56 degrees today from last year) is right on schedule.
Science is dispensable when politics and finances are at the heart of the matter.
Climategate only helped discrediting their PR campaign yet the war is raging upon us: utilities, smart grids, money grab etc…
While so many skeptics celebrated the fall of Copenhagen thanks to climategate, Big Green has regrouped and is now winning.
This whole thing will not be resolved peacefully, no way. This is totalitarism after all.
Lockwood is correct iff solar radiance is the sole energy input into the earth-system.
He is wrong if plasma universe model is used, for then the measured millions of amperes of electrical current entering and exiting the earth system via the polar Birkeland currents add energy in addition to that supplied by solar radiance.
MattN says:
May 16, 2011 at 6:00 pm
BTW, the sun is NOT a light switch. Have any of these idiots ever heard of thermal inertia? Just because I turn the stove off does not mean the kitchen immediately starts cooling off…
_____________
Let’s change that to: “the kitchen is immediately cool…”
Paul Coppin, other than the antarctic not warming, you just about got it right.
You know I always thought is was ill advised that climate scientiests in England used global circulation models to make seasonal forecasts for Great Britain 3 months in advance since the models were never shown to be skillful in regional predictions. I had no idea a person like John Mitchell existed. Given his statement, its now perfectly understandable to me now that they use them (even if they are horrendously inaccurate). So please, lets not discourage John Mitchell, he is a great of falsifiable predictions.
” …specially built for this purpose. It takes Deep Thought 7½ million years to compute and check the answer, which turns out to be 42. ”
“Six by nine. Forty two.”
“That’s it. That’s all there is.”
“I always thought something was fundamentally wrong with the universe”
Douglas Adams (1 January 1980). The Restaurant at the End of the Universe
Latitude says:
May 16, 2011 at 6:36 pm
Steve, First off, do you really believe climate science is advanced enough to make predictions that anyone should listen to?
And which ones should you listen to: warmcold, snowrain, droughtflood, windcalm…….
could, might, may, if……
Miss what?
======================================================
Latitude, lets pretend for a few thoughts that we don’t dislike climate scientists and that they aren’t totally useless. I for one think that a few of them must be honest, but I don’t track the field so I don’t know the players.
A guy shows up at a climate conference and he suggests that looking at model responses can be more beneficial (to climate scientists) than observational data. You and I may knee-jerk react to think he is polishing up his model when in fact he may be making a very honest statement about the general usefulness of observational data in climate science (i.e. it’s of low use). So we can poop on him right there and then or we can give him some room to discuss how his models can help scientists learn more about climate science. My gut feeling is that the variation in output of these models is far below the observational variance (that was really the point of my earlier post).
And as for miss what? well miss his point. His point is that the usefulness of observational data is lower than the model outputs. Set the bar where you like, but the observational bar is lower than the model bar.
On a final note, someone posted Jim Hansen’s original discussions on global warming circa 1990s (?) where he discusses what the changes to global climate might look like. He lists only summer heat and drought. Your comments on snowrain, droughtflood etc while somewhat funny (and nicely sarcastic) really sums up my rejection of climate science. You can’t have two faces (the climate scientists). Hansen only had one when this whole thing started. It was a warming world with less water. Bottom line is even the climate scientists think the observational data is less useful than their models.
Just exactly when did the world go insane?
I don’t mean the druggies and alcoholics, they’ve always been insane.
I’m talking about the scientists and other educated elites.
When did they lose their marbles?
How can statements like these be made with a straight face?
I have seen and heard prats like John Mitchell at many a scientific conference. His type is not that unusual.
RE: Lew Skannen says:
May 16, 2011 at 6:21 pm
“It is a bit like saying that a porcupine is ‘not very useful’ in a balloon factory.”
Excellent! I am going to quote you, somewhere down the road. Is that original?
Latitude says:
May 16, 2011 at 6:36 pm
“even a blind squirrel finds a nut once in a while”
===============================================
But what if a blind squirrel had access to a state-of-art modeling program?
Yah he would probably starve. Forget it…
Sounds like a confession.
Movements morph. In Breckenridge, Colorado where I live the town just had their second annual sustainability conference. Last year a young Kennedyesque Aspen greenie started the conference announcing that oil companies are spreading misinformation to discredit global warming. He pointed to Kevin Rudd as an inspiration for the US the day before he was sacked. This year it was all about ‘sustainability’ and not climate change. The local college has announced they will be offering their two first four year degrees in business and sustainability. The conference was lightly attended this year. I think there was a notable lack of enthusiasm given the economy and this winters six hundred inches of snow. It still looks like a normal mid winter there with more snow on the way.
I wonder, was that video peer reviewed?
I guess those guys are “climate scientists”. After all, they do jump up and down a lot, make clownish facial contortions, cop an attitude, and scream a lot of totally unintelligible gibberish.
That is the sum total of their arguments.
The strongest argument, according to Lockwood, for the sun not being a driver in recent climatic activity is that “it has been going in the wrong direction for 30 years.”
Ok, let’s look at a more discernible situation: Has anybody out ever found that the hottest day of the summer is June 21st? Based on the above logic, it certainly should be (greatest amount of sunlight in the N. hemisphere). But we all know it never is. Never! The hottest day of summer is generally the latter part of July/first part of August–considerably later that the “longest day”.
So much for their argument!
Observational evidence IS the power of the model. Has Lockwood never seen a Victoria’s Secret girl?
QUOTE OF THE YEAR
With their guru Hansen floating the lingering Pinutubo aerosol theory to explain the lack of ocean heat uptake they know their in trouble.
Models showed that wind turbines would be cost effective. As if.
Steve from Rockwood, I’ve read your post several times. There are many words so I’m thinking there must be a complete explanation if I would just follow the reasoning. Maybe it’s just more than I should worry my pretty little head over but I still don’t get it.
Can you tell me what you mean by “useful”? Does this mean “accurate” or “revealing trends” or “providing a path to a better understanding of climate”? Something else?
I thought the issue was about whether models could tell us what climate has been and what we can expect in the future and why. At 1990, 2011 was the future, not far but still a period in which we had predictions from the models. Now that we are here, how can observational data be less “useful” that models? Aren’t we interested in using observational data to check the results of the models to verify we are on the right track? Or what? Are you smart enough to write clearly and educate me?
Thanks! Oh, IA(obviously)NAS
“People underestimate the power of models. Observational evidence is not very useful.”
This is a true statement if the your objective is to promote irrational fear of Catastrophic Anthropogenic Global Warming.
I would go further, far from being “not very useful”, observational evidence actually falsifies the Catastrophic Anthropogenic Global Warming hypothesis .
They weren’t allowed to bring up climategate? It just demonstrates how warmist defense of this scandal is dependent on the ‘out of context’ line, which if you read more emails, just falls apart by the seams.
Observational evidence isn’t very useful? So how do you validate the models? Against other models? Of course not, against observational evidence. Of course, you are really not comparing the results of one model run against one observation. You are looking at the average weather data against the average model run. N=30 to meet the assumption that you are drawing from a normal distribution. But is the weather a normal distribution? Can you make that assumption with any sample size? It doesn’t seem responsible to do so. If you look at the summer data for any point on Earth, you’re likely to see an average that is closer to the upper bound than the lower bound. In the winter, the data is likely to be skewed to the colder value. It would make infinitely more sense to only make a single day the comparison point. Position relative to the sun is more important.
“People underestimate the power of models. Observational evidence is not very useful.”
The above quote describes the alarmist side perfectly, observed reality has not been kind to the CAGW position and so the claim is correct. Their models alone describe and validate their theories while observational evidence has simply served to contradict those models. The inner conflict and central contradiction within climate science has always been the widening gap between modelled reality and observed reality. Pro CAGW climate scientists can not let go of their models because it is all they have, a one trick pony that has a broken leg.
Those few words are remarkable in that they describe perfectly why CAGW theory is not valid and why it should be laid to rest so the world of science can move on to much more important challenges. Those words are true, the person who uttered them was speaking the truth, it should be the final epitaph carved in stone and placed outside every place of learning. I have never yet heard so few words so perfectly describe a theory.
Science is built on the foundation of matching theory against observed reality, no theory has ever survived the conflict between theory and observed reality until now, CAGW is in essence a theory and this theory has not been able to describe and match what we see in reality. At any other point in history the theory would have been disowned and disposed of but we now see a revolution in science.
Those at the heart of CAGW research are attempting what amounts to a coup against science, the attempted eviction of observed reality from its place as the ultimate validator of theoretical science. The replacement of unproven theory ahead and over observed and proven reality is of course a gross perversion of science but it is easy to see why this is occurring and why it has been all too obvious from the start.
Climate science began its remarkable life with a conclusion which climate science then attempted to validate with the new science of modelling, this new branch of science took advantage of the huge increase in computing power, coupled with a massive influx of money. Climate science made the basic error of trying to find evidence to back up their models, the increasingly desperate search for any evidence they could find and use that validated their models and so desperate did they become they tried to use anything that remotely looked like it might validate their models until it reached hilarious proportions with less rain/more rain/hotter/cooler/more snow/less snow proving CAGW.
Climate science grew too big too fast with no solid foundation on which to base its existence and now the final and ultimately useless attempt to deny reality in favour of models, it must be that observed reality that is wrong and not the models? This inevitable conclusion to this comic tragedy that sceptics saw coming years ago, the epitaph that will be carved on the metaphorical gravestone of CAGW theory. Never before has so few words described so perfectly the demise of a mass delusion.
I’ve noted previously that Economics and Climate Science are very similar in a number of ways. Both are closed shops with certain orthodoxies, both have political import, both have recently been caught with their pants down.
In the post above is noted the response from Climate Science a couple of years on. we have the more considered response in the economic field.
Just yesterday there was a post by Paul Vaughan titled Interannual Terrestrial Oscillations. A great lot of observational evidence was presented. The general tone of the comments was that the contribution to climate science was underwhelming. ( aka “not very useful”)
Perhaps, John Mitchell meant that with a complex system and much data some method(s) or model(s) [equations] might be helpful – a “not entirely empirical” approach.
Does everyone but me have a problem with that?
The headline of this article is classic.
I just watched the “I’m a Climate Scientist” video. What I have to say may be simplistic to many of you. Remember, I already confessed that I am (obviously) not a scientist. I just have to get this off my chest!
Look, there was a time when I read the articles about global warming and previously global cooling. Yes, I’m old enough for that and I read the LA Times daily. It was all interesting but what did I know? How could I know? IANAS. I was just watching the studies unfold. Al Gore was entertaining in his “documentary”. Bjorn Lomborg’s “Cool It” seems rational and balanced but I could be mistaken. Real Climate-too much anger and arrogance. I love the many posts and charts at Wattsupwiththat and I check it out every day. So you might think I lean to the “lukewarm” side. Nope. I’m skeptical. How’d that happen? Well,
Big Oil didn’t turn me.
Climate Scientists didn’t fail to present their views properly.
Bloggers didn’t convince me.
Alex Jones is a nut ball, IMO.
Our beloved host didn’t provide the information that made me see the light.
Here are the two ideas that stopped the Dixie cup from reaching my lips:
1. “Global Warming is Real, It’s Here and the Debate is Over!” ::blink, blink:: This is how we do science now? Declare a consensus and close the debate?
2. Month after month, year after year, for at least ten years, I’ve read about horrific weather events and the news includes the information that the event is attributable to CAGW. Here’s what else is included: “The worst cyclone since 1890!” “Hottest year since 1934!” “Catastrophic flooding occurs every 10-12 years but this one is the worst since 1963” “Tornado swarms-hundreds of tornadoes! We haven’t seen as many ‘killer tornadoes’ since 1957!”
One might ask (I certainly do) what was going on in 1890, 1934, 1957, 1963 and 1978 that caused these weather events and why do we think CO2 and CAGW is the cause of more recent events? The answer: Because there is much more CO2 now and therefore, there can be no other reason. Everyone know this but you! What? Huh?
So here I am, resenting how my significant tax contributions will be spent and not liking those giggling, snarky “Climate Scientist” grad students very much, either.
Cassandra King
Thanks! This is certainly what it looks like to me.
I think the video would have been better sung to the tune of ‘Firestarter’ by the Prodigy. Just replace the word ‘Firestarter’ with Climate Scientist.
Were these people drafted from the Drama Department to play pretend scientists?
“The hottest day of summer is generally the latter part of July/first part of August–considerably later that the “longest day”. ”
The sea surfaces reach their highest temperature in late September when the sun is halfway towards the weakest point in December.
Likewise the coldest tempeature is in late March.
Then the deeper one goes into the oceans the longer the lag times right up to the length of the thermohaline circulation which is estimated at 1000 to 1500 years.
So when I go outside in the rain, I cannot be certain that the rain is the real cause of my getting wet, unless I have modelled it? I may have accidentally walked into a lake, but just not be aware of it? I cannot take observational empirical evidence as a guide?
So, my being wet and outside at the same time as it is raining may not be a causal effect?
After all, correlation is not the same as causation.
I think I am getting the hang of this AGW think.
Laurie, “One might ask (I certainly do) what was going on in 1890, 1934, 1957, 1963 and 1978 that caused these weather events and why do we think CO2 and CAGW is the cause of more recent events? The answer: Because there is much more CO2 now and therefore, there can be no other reason. Everyone know this but you! What? Huh?”
Hang on… But I thought that correlation did not equal causation. Dammit! Just when I thought I had gotten a hang of this AGW think too!
So if I go outside when it is raining, then it might be the rain that is getting me wet? I don’t need a computer model to tell me?
“Observational evidence is not very useful”.
Correct because it keeps being changed, cherry picked and hidden. What else could he have meant?
I made an A4 sign of that quote, and I’m going to stick it the rear window of the van. 🙂
Alec, couldn’t agree more. Seems that is the same thing many have come back with after doing any concentrated analysis of what the sun has been up to the last few decades. That is how I found WUWT and why I stuck, the solar aspect.
It does seems the drop in UV level and the simple collapse of the vertical height of the atmosphere have been pointing telltales that the sun did, in fact, have a big hand in the warming, no denying those.
John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
The only one I know who could have answered John Mitchel would be Ben Kingsley!
Jo Nova’s got a good write up about the (rap squad, http://joannenova.com.au/2011/05/climate-science-rappers/ , they say, by use of models, the Murry river has not been this dry in 1500 years and there 97.7% sure of that?
Looks like there big believers in models not the real world.
There are misconceptions on both sides of the argument. Neither side (CO2 or solar including Svensmark) have produced conclusive proof.
There is an alternative view:
http://www.vukcevic.talktalk.net/CD.htm
with more details to follow.
What have these ‘so called’ scientists got against the sun and it’s obvious influence on our climate? When did statistical modelling become more important than empirical evidence?
Reminds me of Wilkie Collins the Moonstone:
‘Betteredge lifted my glass, and put it persuasively into my hand.
“Facts?” he repeated. “Take a drop more grog, Mr. Franklin, and you’ll get over the weakness of believing in facts!’
John Mitchell’s statement is a reminder of the child-like other-worldliness of some scientists, who become irritated when reality intrudes upon their imagined ideal world, their world of models and modelling that is as neat and tidy and cleverly detailed as a carefully-made scale model electric train set, complete with painted dioramas and sound effects, where they can run trains from a big and comfortable chair behind their control console all day and night, without ever having to venture outside that world until their Mum calls them for meals.
But it is often inconvenient?
Laurie says:
May 16, 2011 at 10:45 pm
________
Very good post Laurie.
John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
We don’t know how element A affects element B, element C overpowers element A, etc., deja vu? Lockwood ought to get his act together. Sun, 99.9% of mass of Solar System, Earth, a few hundreths of the mass of same, a tenth of one percent change in TSI & around 6-10% change in Extreme UV? When asked a couple of years ago about the quiet Sun, he claimed that if there was going to be a cooling effect we would have seen it by now! Does he, like so many, not listen to his past quotes? Room & elephant spring to mind.
John Mitchell: “Observational evidence is not very useful.”
Galileo Galilei: “It still moves.”
One small addition: they need to remove people’s ability to doubt.
So they associate “sceptic” with “holocaust denier.”
(Of course, being able to question independently, to think for ourselves, was the basis of the Western Enlightenment, so then, “remove questioning” might create some unintended consequences…)
Climate Science – Observational evidence is not very useful.
Con Artist – Who are you going to believe, me or your own eyes?
Slick Attorney – My client could not have been seen at the crime scene as he was wearing his cloak of invisibility at the time
Super Slick Attorney – The six eye witnesses who saw my client were all exposed to the exact same poisinous chemicals in the area, and so it is to be expected that they a mass hallucination which was identical to all of them, but that doesn’t mean it was real.
Witness – It was an accident. I was sitting at the end of the bar, pealing an apple with my knife, when all of a sudden this guy comes running around the end of the bar and ran right onto the end of my knife.
Egregiously slick Attorney – see? A perfectly natural explanation for the observed knife wound on the victim.
Exasperated Prosecutor – TWENTY SIX TIMES?
Politician – its a revenue neutral tax. Neutral being a relative term. We can’t help but emphasize NEUTRAL really loud because neatral is such a nice word compared to tax. Oh, and we need to charge a small fee on the revenue neutral tax to pay for the collecting of it and the redistrubution of it, and sometimes when we’re short staff we just stick it into general revenue instead. But it is a neutral tax because that’s its name, never mind how much money goes where.
Observational evidence is not very usefull for people who want to make up their own reality and convince the rest of us to live in it.
I used to give the “climate scientists”a small amount of leeway on their hypothesis about global warming. I foolishly thought they were working from contaminated data sources, such as poorly sited stevenson screens, misunderstood processes, etc.
Now, however, it’s quite clear that some of the researchers are using EA game’s Sim Earth as their working model………
The more I think about this statement, the more angry I get.
How can ANY SCIENTIST even think that this is a rational statement ??????????
John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
Good god… and this man is paid out of the public purse and is a part of the organisation that is set up to protect from our country from the planets weather systems, is he going to ignore a severe storm/blizzard looming down on the UK
and then tell us “Observational evidence is not very useful,….. go, go now,
So, observation is not as ‘good’ as model output.
Yeah? Only because observation shows that the UK Met Office models are rubbish.
When the Met Office get back to real science instead of spending my tax pounds on a bigger computer to get a better model is the day I believe one of their weather forecasts.
richcar 1225 says:
May 16, 2011 at 7:50 pm
Proof of morphing is found in the oddest ways. Look at the name change of the town you are living in.
From http://en.wikipedia.org/wiki/Breckenridge,_Colorado
So the name of Breckinridge morphed into Breckenridge, due to political pressure and the change of thinking from one of currying favor to patriotism. Much as CAGW morphed into Climate Change and Climate Change has morphed into sustainability.
The more things change, the more they stay the same.
“People underestimate the power of models. Observational evidence is not very useful.”
I have a perfect example of unreasoning faith in the power of models, in this case, satnav.
We were going on holiday, flying out from Bristol Airport. Our driver had a new satnav. He fed in the required information. Now, this man had been to Bristol Airport before. However, he slavishly followed the satnav, even though we pointed out signs for the airport going another way. We ended up in a cul de sac in Chew Magna, Somerset, nearly 7 miles from the airport, with the voice insisting ‘You have reached your destination, you have reached your destination.’
We very nearly missed our flight, and the poor chap has never lived it down.
Some people have driven onto railway lines and into rivers or lakes following satnavs, such is the devotion to the magical power of the computer.
Is this some sort of mental block? It would explain a lot.
Well said Cassandra: my thoughts entirely!
Never before has so few words described so perfectly the demise of a mass delusion.
John A. Fleming says:
May 16, 2011 at 6:26 pm
“The actual observational data is just another instance of those climate experiments. All you have to do is show that that your model could have generated the historical measurements, if only you had had enough butterfly wings to initialize the model with.”
I guess your subconscious is rational and brilliant. This is the heart of the matter. Notice that the big problem here is a confusion of science (my model produced and I selected the results as the model’s product) with scientific methodology (your model could have generated those results, though it didn’t). It is not enough that models are open to investigation through scientific method; they must also produce results that become reasonably well-confirmed in experience.
Laurie says:
May 16, 2011 at 8:40 pm
[snip]… There are many words …[snip] should I worry my pretty little head …[snip] Are you smart enough to write clearly…[snip]?
Laurie, I am not a great writer. I was enrolled by my boss once in a writing class where was asked to submit a sample (of my writing). The teacher wrote “wordy” at the top and nothing else. The sarcasm was burning as I looked around to see everyone else had only written a single page. I had written three.
But let’s put your pretty little head in charge of climate science. You run the show. Judging from your earlier posts, probably the first thing you would do is to tell scientists to stop making shrill comments about the end of the world. Next you tell them to stop blaming extreme weather conditions on global warming. Then you move on to detach environmental causes and political motivation from climate science. You’ve done a great job in your first day on the job. Now what? You really want to advance the science of climate science and not just add to the noise.
So you look to the observational record which has large swings in both directions from El Ninos, volcanic eruptions etc and a definite warming trend starting in the 1880s that was interrupted twice by cooling trends. At the same time humans have been adding CO2 to the atmosphere by burning fossil fuels. And you know that humans do have an impact on temperatures at a local level and you measure it as the Urban Heat Island Effect.
People are pressing you for predictions about the future. You remind people that climate science is something that happens over several decades. You can’t point to 1998 and compare it to 1934 as the warmest year anymore than the last ten years show an end to a long term multi-decadal, greater than a century warming trend.
So you look to the models. What do they say? Well if you add aerosols to the atmosphere it tends to have a cooling effect. If you introduce more CO2 to the atmosphere it tends to have a warming effect.
Then some guy (on your team) shows up at a conference and out of a short fit of honesty concedes that the observational data is almost useless – less useful than the models.
So Laurie, as you are now head of climate science, I’ll let you finish the story because I’m not very good at endings.
Steve from Rockwood says:
May 16, 2011 at 7:32 pm
“My gut feeling is that the variation in output of these models is far below the observational variance (that was really the point of my earlier post).”
To readers of this forum, you are likely to come across as unaware of the relevant context. Most everyone here will probably agree that there is no connection between models used by climate scientists and observation.
Now we know who writes all those lottery prediction apps that have been floating around the internet for years – John Mitchell and Phil Jones. Actually, they’ve got an order of magnitude greater than their climate models.
So, essentially, nobody can trust his observation about neither models nor observations.
Has the ever so LSD colorful output of their models anything to do with they putting their trust in the “great and all knowing model-god”?
There goes 2000 years of science down the gurgler, no useful evidence until they started using computers in the 50’s.
Since so many are complaining about that one quote, I fixed it:
“People underestimate the
powerprofitability of models. Observational evidence is not veryusefulconvenient,” adding, “Our approach is notentirelynoticeablyempiricalscientific.”John Mitchell told us: “People underestimate the power of models.”
These people are “power” mad.
——
Mike McMillan says:
May 16, 2011 at 5:58 pm
“I am a climate scientist”
“I am the walrus”
“I Am the Very Model of a Modern Major-General”
Beatles and Gilbert & Sullivan got ‘em beat, homey.
You left out one of the best:
http://en.wikipedia.org/wiki/Michael_Flanders
I’m a gnu. I’m a gnu.
The g-nicest work 0f g-nature in the zoo.
Over at NRO, I recently had a warmista tell me that not only have the models perfectly hindcasted past climates, but that models predicted the existence of oceanic cycles such as the PDO years before they were recognized by other scientists.
The arguments advanced by Lockwood are very questionable in many and several aspects.
In this peer review paper of mine I explicitly show the several limits of Lockwood’s assumptions and methodology.
N. Scafetta, “Empirical analysis of the solar contribution to global mean air surface temperature change,” Journal of Atmospheric and Solar-Terrestrial Physics 71 1916–1923 (2009), doi:10.1016/j.jastp.2009.07.007.
http://www.fel.duke.edu/~scafetta/pdf/ATP2998.pdf
See also:
http://wattsupwiththat.com/2009/08/18/scafetta-on-tsi-and-surface-temperature/
This is the comment on Lockwood contained on my paper
“The above wide range strongly contrasts with some recent
estimates such as those found by Lockwood (2008), who
calculated that the solar contribution to global warming is
negligible since 1980: the sun could have caused from a -3.6%
using PMOD to a +3+1% using ACRIM. In fact, Lockwood’s model is
approximately reproduced by the ESS1 curve that refers to the
solar signature on climate as produced only by those processes
characterized with a short time response to a forcing. Indeed, the
characteristic time constants that Lockwood found with his
complicated nonlinear multiregression analysis are all smaller
than one year (see his table 1) and the climate sensitivity to TSI
that he found is essentially equal to my k_{1S}! Likely, Lockwood’s
model was unable to detect the climate sensitivity to solar
changes induced by those climate mechanisms that have a
decadal characteristic time response to solar forcing: mechanisms
that must be present in nature for physical reasons. As proven
above, these mechanisms are fundamental to properly model the
decadal and secular trends of the temperature because they yield
high climate sensitivities to solar changes.”
A similar response works also for Lean and Rind’s approach. Always from my paper
“Analogously, my findings contrast with Lean and Rind (2008),
who estimated that the sun has caused less than 10% of the
observed warming since 1900. The model used by Lean and Rind,
like Lockwood’s model, is not appropriate to evaluate the multidecadal
solar effect on climate. In fact, Lean and Rind do not use
any EBM to generate the waveforms they use in their regression
analysis. These authors assume that the temperature is just the
linear superposition of the forcing functions with some fixed
time-lags. They also ignore ACRIM TSI satellite composite. While
Lean and Rind’s method may be sufficiently appropriate for
determining the 11-year solar cycle signature on the temperature
records there used, the same method is not appropriate on
multidecadal scales because climate science predicts that time-lag
and the climate sensitivity to a forcing is frequency dependent.
Consequently, as Lockwood’s model, Lean and Rind’s model too
misses the larger sensitivity that the climate system is expected to
present to solar changes at the decadal and secular scales.
I have shown that the processes with a long time response to
climate forcing are fundamental to correctly understanding the
decadal and secular solar effect on climate (see ESS2 curve). With
simple calculations it is possible to determine that if the climate
parameters (such as the albedo and the emissivity, etc.) change
slowly with the temperature, the climate sensitivity to solar
changes is largely amplified as shown in Eq. (10).”
Moreover, about the issue of whether Lockwood or Lean methodology agree with the climate models.
It is important to note that both Lockwood and Lean’s methodologies apparently agree with the climate models claiming that the sun is a small driver of the climate. However the agreement is only apparent.
In fact, Lockwood and Lean’s methodologies assume that there exist only a very fast characteristic climate time response to solar variations that imply a very small heat capacity of the system. Lockwood uses a characteristic time response of T<1 year and Lean, with her linear regression model assume essentially T=0 year!
The climate model instead have at least a decadal climate time response by more properly model the heat capacity of the ocean.
Thus the apparent agreement between Lockwood and Lean's methodologies and the climate models is due to the fact that on one side Lockwood and Lean uses methodologies that imply only very fast time responses (= very small heat capacities) to solar related forcings and on the other side the climate models that do not contain a lot of alternative solar-climate mechanisms such as the sun-cosmic ray-cloud system.
“People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
Funny how “observational (empirical) evidence” is “very useful” when it nicely fits your predetermined outcome. Witness Mann, Briffa, etal.
When your paleo- reconstruction hits a point in time where the extrapolations no longer suit your predetermined outcome, and you splice in an “observational” (empirical) instrumental record to help overcome the problem, it’s funny how “useful” the empirical becomes.
The abrogation of scientific method is unabashed and blatant.
And the best disinfectant for this deadly virus is sunlight. The more of it these “scientists” are exposed to, the quicker we can dispense with the Thermageddon politics.
To think that a scientist could be this delusional, is not only sad, but that he is excepted as sane by his peers is madness. The belief system these people carry is a two edged sword with no handle , no matter which way it falls it will hurt. Time and tide belong to no man, and I would suggest neither does the weather, that we can control the weather by taxation on CO2 has to be the greatest scam in the history of the world. Good grief!!
Steve from Rockwood says; ” I’ll let you finish the story because I’m not very good at endings.” How about, “Gee whiz, we don’t know squat.”
Here is another load of quack science and fakery dumped on us from above.
[…] TSA faked its safety data on its X-ray airport scanners. […] We now live in an age where the federal government simply fakes whatever documents, news or evidence it wants people to believe, then releases that information as if it were fact.
http://www.naturalnews.com/032425_airport_scanners_radiation.html
[…]
The evidence of the TSA’s fakery is now obvious thanks to the revelations of a letter signed by five professors from the University of California, San Francisco and Arizona State University. You can view the full text of the letter at: http://www.propublica.org/documents
[…]
From the letter we learn:
• To this day, there has been no credible scientific testing of the TSA’s naked body scanners. The claimed “safety” of the technology by the TSA is based on rigged tests.
• The testing that did take place was done on a custom combination of spare parts rigged by the manufacturer of the machines (Rapidscan) and didn’t even use the actual machines installed in airports. In other words, the testing was rigged.
• The names of the researchers who conducted the radiation tests at Rapidscan have been kept secret! This means the researchers are not available for scientific questioning of any kind, and there has been no opportunity to even ask whether they are qualified to conduct such tests
[…]
• The final testing report produced from this fabricated testing scenario has been so heavily redacted that “there is no way to repeat any of these measurements,”
[…]
• The dose rates of X-rays being emitted by the Rapidscan machines are actually quite high — comparable to that of CT scans, say the professors. Yes, the dose duration is significantly lower than a CT scan, but the dose intensity is much higher than what you might think. And as anyone who knows a bit about physics and biology will tell you, the real danger from radiation is a high-intensity, short-duration exposure. That’s exactly what the TSA’s backscatter machines produce.
• The radiation detection device used by Rapidscan to measure the output of the machines — an ion chamber — is incapable of accurately measuring the high-intensity burst of radiation produced by the TSA’s naked body scanners, say the professors.
• At the same time, the radiation field measurement device used by the TSA — a Fluke 451 instrument — is incapable of measuring the high dose rates emitted by backscatter machines. The measurement devices, in effect, “max out” and cannot measure the full intensity of the exposure. Thus, the TSA’s claims of “low radiation” are actually fraudulent.
[…]
• The amount of electrical current applied to the X-ray tubes has been redacted by the TSA (working with John Hopkins). This makes it impossible for third-party scientists to accurately calculate the actual radiation exposure, and it hints at yet more evidence of a total TSA cover-up. As explained by the professors:
…the X-ray dose is proportional to the current through the X-ray tube. Not having access to the current used in the JHU test, or in the field application of the scanner means that the measurements at JHU are irrelevant to the dose at the airport. There is also no data on the pixel size and overscanning ratio, which also bear directly on the dose delivered to subjects. The statement in the HHS letter that the fluence is not a relevant quantity ignores fundamental physics.
[…]
There shall be no independent testing whatsoever.
The TSA adamantly refuses to allow independent testing of the radiation levels being emitted by the machines.
[…]
Actual radiation emitted by the machines is far higher than what the TSA claims.
John Sedat, a professor emeritus in biochemistry and biophysics at UCSF and the primary author of the letter says, “..the best guess of the dose is much, much higher than certainly what the public thinks.” This indicates the public has been deeply misled by the actual amount of radiation emitted by the machines.
• Peter Rez, the physics professor from Arizona State, says that the high-quality images described by the TSA could not be produced with the low levels of radiation being claimed by the TSA. The images, in other words, don’t match up with the TSA’s cover story. Rez estimates the actual radiation exposure is 45 times higher than what we’ve previously been told.
• The TSA machines are capable of firing even higher levels of radiation into a “region of interest” (such as your anus or scrotum, in which the TSA seems to be taking great interest these days), thereby exposing that region to even higher levels of radiation than the rest of your body.
Is there a link to the presentation made by Henrik Svensmark?
I OBSERVE… THEREFORE I AM
The key here is that a model is something that he created, while observational data is only something that he observed. Ego trip.
Or, if we are being charitable, perhaps he was trying to quote “Without models there is no learning” (can’t find a reference, but I’ve heard it somewhere and in context I believe it’s true).
Francisco,
Fascinating comments, thanks. The TSA has plenty to hide. They’re not protecting us, they are endangering us. El-Al airlines doesn’t play these x-ray games, and when is the last time an Israeli airliner was hijacked or flown into a building? The only countermeasure that really works is profiling.
@- He was followed by the most impressive presentation from Henrik Svensmark, whose presentation stood out head and shoulders above anyone else. Why? For two reasons. The correlations he shows are remarkable, and don’t need curve fitting, or funky statistical tricks. And he has advanced a mechanism, using empirical science [image above], to explain them.
I suspect this comment is intended to be ironic?
After all Svensmark is notorious for dubious statistical methods to obtain a correlation in the graphs first used to justify the CERN experiments, and clearly no correlation is possible between the last ~50 years of stable or falling solar output and GCR flux.
And while the mechansim may be ’empirical’, as yet there is no empirical evidence of it, and substantial evidence that cloud nucleation is provided by other empirical processes.
The claim advanced by some that a consistantly rising temperature trend is compatable with a stable or falling solar output/GCR flux because the higher absolute output, and lower resultant cloud cover is still acting to warm the oceans that have not reached equilibrium is unsupported by any empirical evidence, and must therefore be an example of where empirical evidence is inferior to modeling arguments.
But it has the implication that if the additional energy from the reduced cloud cover during the high solar activity period is STILL warming the planet because the oceans have not reached equilibrium then the additional energy from the DLR from the increased CO2 will ALSO continue to warm the atmosphere for ~30 years after it has ceased to increase when emissions are reduced.
izen says:
“The claim advanced by some that a consistantly rising temperature trend is compatable with a stable or falling solar output/GCR flux because the higher absolute output, and lower resultant cloud cover is still acting to warm the oceans that have not reached equilibrium is unsupported by any empirical evidence, and must therefore be an example of where empirical evidence is inferior to modeling arguments.”
Empirical [real world] evidence is never inferior to modeling arguments.
I luv the rapid equilibrium finger-trap Lockwood got himself caught in! Hilarious.
Maybe we should all model our income for the IRS and get away from misleading observational evidence of earnings.
“People underestimate the power of models. Observational evidence is not very useful,” — John Mitchell
Indeed, John, that’s why we spend hundreds of billions on satellites and barely a hundred million or so on computational power. Observational evidence is obviously not very useful when you consider that we continue to add to long chains of orbiting satellites pointing back at earth to gather this “observational evidence”.
I agree that the human eye can be fooled by evidence, but it’s the human part of that equation that does the fooling.
Acutally, the kitchen can continue to warm even if the stove heat is reduced from its previous maximum.
Additionally, the northern hemisphere continues to warm during the summer months despite the fact that the sun reached its maximum output on the hemisphere on June 21.
@-Smokey says:
May 17, 2011 at 7:03 am
“Empirical [real world] evidence is never inferior to modeling arguments.”
Depends on the quality of the empirical evidence.
Do you have ANY empirical evidence that the thermal inertia of the oceans is such that they are continuing to rise in temperature BECAUSE of the level of solar output that has been static for ~30years?
Or is this hypothesis better supported by modeling arguments??
I’m under the impression that we use modeling in place of observation for GISSTemp and others because of the lack of surface stations in the arctic. If this is correct, then we are already substituting models for reality.
Insert cheesy pop-culture sci-fi reference here. Extra points for not reference ‘The Matrix.’
izen says:
May 17, 2011 at 6:47 am
“…unsupported by any empirical evidence, and must therefore be an example of where empirical evidence is inferior to modeling arguments…”
________
This is an interesting comment IMO because it clearly illustrates where belief is inserted into the CAGW mantra. I refer to the words, “must therefore”. The case here where izen gives a more verbose and “technical” reason for Mitchell’s wholly unsupportable assertion then adds the belief words: “must therefore”. If you start with a false presupposition (earth climate is too noisy/ it is what it is: climate reality) your result will also be false (the models are better than empirical evidence / scientific method). Somehow reality is too noisy to descern a readable signal, and the models do not contain this noise and so, “must therefore” be superior to direct observation and empirical evidence. Adding those two little words does not change reality. And the reality is that the models fail at having any predictive value either when forecasting or hindcasting.
Take out, “must therefore” and the whole thing reverts back to the original ridiculus comment that John Mitchell made which has been fully deconstructed in comments above.
________
“Smokey says:
May 17, 2011 at 7:03 am
“Empirical [real world] evidence is never inferior to modeling arguments.”
What he said…
*Well, on reflection, I guess that modeling arguments might be superior to empirical evidence for the astrologer or alchemist.*
Frank: excellent idea!
I’ve been working on a new model that shows no matter how hard I press the accelarator on my car, it cannot exceed 55 MPH. Therefore officer, you may have observed me doing 75 MPH, but obviousely my model proves your observation was incorrect. It has to do with all that “noise” of all those other cars and trucks on the road with me.
“And while the mechansim may be ‘empirical’, as yet there is no empirical evidence of it, and substantial evidence that cloud nucleation is provided by other empirical processes.” – izen
izen,
Are you being ironic here, or are you just that out of touch? Here is a nice overview with links to articles.
http://motls.blogspot.com/2011/05/new-danish-experiment-confirms.html
Smokey says:
May 17, 2011 at 7:03 am
…
Empirical [real world] evidence is never inferior to modeling arguments.”
Correct. Arguments based on models are fallacious: reification : (also known as hypostatisation, concretism, or the fallacy of misplaced concreteness) is a fallacy of ambiguity, when an abstraction (abstract belief or hypothetical construct) is treated as if it were a concrete, real event, or physical entity.[1][2] In other words, it is the error of treating as a “real thing” something which is not a real thing, but merely an idea. For example: if the phrase “holds another’s affection”, is taken literally, affection would be reified.
Another common manifestation is the confusion of a model with reality. Mathematical or simulation models may help understand a system or situation but real life always differs from the model. In extreme cases, the butterfly effect causes the model to rapidly diverge from what is occurring in real life.
Mitchell’s statement is unabashed propaganda. The models have always failed regardless of all the little tweaks, to forcings, feedbacks or flatulence. And he/they know it. Now we are told that we have been underestimating them (?), and that modeling arguements are superior to emperical evidence (?). Not in this lifetime and not on this planet. No amount of redirect with specific technical dissertation on solar flux or sea levels, on correlation or causation can detract from the over-arching reality that the models fail, have failed, and will continue to fail to predict anything to do with climate. Period.
It would be easier if we could just agree that we do not have all the information / data / technology, etc, required (and may never have) to predict a chaotic system. We will never know everything about the climate, sorry if that is an affront to anyones ego, get used to it.
Observational evidence is not always useful. Actually this is a correct statement. The observations we obtain may not assist the building of hypothesises or theories but without observational evidence, we are stuck in the realm of speculation. Without good evidence we cannot build a theory. Without a theory we cannot predict. Unless you are of the religious persuasion; and then you can predict anything you like but it’s certainly not science.
izen says:
“Depends on the quality of the empirical evidence.”
Now the goal posts have been moved to ‘quality’? If so, then the ‘quality’ of the model must be matched, no?
As a delegate at the Downing College conference I concur with the accounts above. I can add a few oddments.
Phil Jones’ lecture was pretty lame, he commented that no one had downloaded his data now that he’d put it in the public domain. Maybe because it’s worthless anyway.
Eric Wolff (Scott Polar Inst.) seemed to think that althought heating precedes CO2 rise in the ice cores, nonetheless its the CO2 that causes the warming (I think he means escalates the warming). Back to time travel issues maybe.
He was also apparently a bit disingenuous when asked if the ice core CO2 records were reliable. He explained that the last 50 years matched the ML levels very well. I rather think the questioner wanted to know if ice a mile down could be relied on to maintain ‘correct’ levels of CO2. Contacting Wolff later by email, he asured me that the ice 1 mile down was in that respect quite unchanged… hmmm.. under 20,000kN/m2 ?
Andrew Watson’s efforts were interesting in that the CO2 absorbed in the biosphere was an acknowledge ‘unknown’ – which of course upset all his careful calculations. Strangely though he was keen to tell us that the ocean were warming, yet they were apparently absorbing even more CO2: shomeshing wrong shurely?
John Mitchell agreed with me during the lunch break that the ‘greenhouse’ concept was a total misnomer… even though he had trotted out the Mars, Earth, Venus canard earlier. I explained that the moon had a similar ST elevation (30-40K in fact) without any ‘GHGs’. I’m not sure whether he was aware of that.
Morner was excellent, flamboyant but devastating: the evidence of ‘no sea level rise’ was there in reality for all to see – not in some computer graphic.
Vaclav Klaus quite quiet but equally devastating – what a breath of fresh air! He’d be very welcome in the UK as Prime Minister (technically possible as we’re in the EU!!) as a substitute for our current pink model.
He blew away the rather pathetic assertion that climate models were better than economic models made by AGWers earlier on in the day. LOL.
Smokey says:
izen says:
“Depends on the quality of the empirical evidence.”
Now the goal posts have been moved to ‘quality’? If so, then the ‘quality’ of the model must be matched, no?
Seems to me that if the quality of the observational evidence is poor, then the resultant model must be either equally poor (if modeling a linear system) or worse by orders of magnitude (if modeling a chaotic system – i.e. climate).
Unless, of course, you are simply making up your initial data.
This whole thing goes back to what I keep saying – these are people who don’t live in the real world.
“People underestimate the power of models. Observational evidence is not very useful.”
Is there any doubt that if observational evidence began to agree with their models then it would suddenly become useful to them again?
As a side note, one of the benefits of Global Warming is that as the temperature increases, models wear fewer clothes. But that is just an observation, so it can’t be very useful to climate scientists.
Experimental confirmation of the solar-cosmic-cloud seed paradigm is in. Nobels for Svensmark and all concerned?
http://calderup.wordpress.com/2011/05/17/accelerator-results-on-cloud-nucleation-2/
Orlowski notes a contrast of opinion:
RockyRoad says:
May 16, 2011 at 8:08 pm
The strongest argument, according to Lockwood, for the sun not being a driver in recent climatic activity is that “it has been going in the wrong direction for 30 years.”
Ok, let’s look at a more discernible situation: Has anybody out ever found that the hottest day of the summer is June 21st? Based on the above logic, it certainly should be (greatest amount of sunlight in the N. hemisphere). But we all know it never is. Never! The hottest day of summer is generally the latter part of July/first part of August–considerably later that the “longest day”.
Ok – but there was high solar activity up until ~1790 – doesn’t this mean that the Dalton Minimum (1790-1820) was warm?
So much for their argument!
“People underestimate the power of models. Observational evidence is not very useful.”
Part of the essence of religion …
What really happened to the scientific view that we are in an interglacial period and still are recovering after the last ice age? That is, it will first be hotter and then get colder by gradually approaching a new ice age. Have we reached the tipping point, regarding the past decades or are that it just a temporary “time out”? ( Rhetorical question, since no one knows the correct parameters to respond to this … Since many parameters are of the volatility nature ( without historical traces ), we will never be able to answer the question. .. Reasonable, it can never be scientifically acceptable to guess …)
At the other end of the scale, by way of contrast, the Met’s principle research scientist John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
Maybe he meant the power of hypnotic suggestion, like throwing a big party at the beachhouse while a Hurricane draws near.
a group of students and a few others, simply giggled and mocked the skeptics, however from start to finish.
“Students” on an after-school field trip comprised by Kindergartners, no doubt? Perhaps someone should have honored them by having them and their “teacher” stand up and take a bow?
Coincidentally, I was just thinking again about this particular anti-scientific, anti-free thought tactic as used by some other “students” who were led by a Duke University Professor at a talk David Horowitz gave at Duke Univ. some years ago.
Once again an impressive infantilism combined with an intent to obstruct the rational consideration of an issue rises up to demonstrate our age’s own version of the pre-Enlightenment Brain and its Post Normal “Science”.
Another one of this Duke University Professor’s tactics was to disrobe down to bra-level. This was right before some Duke Teachers and Students next helped create the non-existent Duke LaCrosse Team’s “rape” of Crystal Mangum, who it seems might have recently done away with one of her boyfriends iirc. – my point here being that the Duke teachers and students didn’t help Crystal Mangum, either, starting right from the time of the non-existent “rape”.
Poster says: “I couldn’t disagree more. Mitchell is giving very sage advice here on the state of observational data in climate science (and no I am not being sarcastic). By running models, climate scientists should be able to test their theories without having to wade through the high noise levels and/or short-term high amplitude variations in global temps that make the data record so complex (and of limited use).
Sadly, it seems, many of these scientists are looking for disaster scenarios so we take every quote from a climate scientist with maximum skepticism – occasionally to the point of missing one.”
This reasoning is so flawed I don’t know where to begin. I work with geophysical forward models of the excitation of metallic objects by pulsed EM induction. We have good physics that support the model and, in test circumstances, data taken is well fit by an inversion of the forward models. Even in this context, we spent years trying to get good inversions out of the models to the data. The problem was noisy data. Until we developed an entirely new generation of sensors, the problem of inverting an overdefined model to data sometimes produces good results and sometimes not very good results. The key though is good physics and (today) good data.
The approach described in the quoted language makes mincemeat of this approach. It says that, in effect, the model is self validating because of noisy data. I can tell you with certainty that in our domain, models just produced bad results on noisy data. You couldn’t tell they were bad results until you dug up a detected metallic item at great expense.
In the AGW world, the models are not solid physics models–they are better described as physics speculations about how things might work. These models are far more complex than the simple dipole models we use because they include positive feedback loops and lots more parameters to set. That these models may, no, probably do, produce bad results when fit to noisy data is no surprise. Fitting to data is not difficult when you have a lot of parameters to play with. The difficulty is getting a good fit. Yet, the accomplishment (ta da) of actually getting a fit is seen as a validation of the model. That’s entirely erroneous. With enough parameters, you can fit any data with any model if you spend enough time.
The complaint about noisy data seems to me to say that this is an area in which models and their predictions are largely useless or at a minimum, very dangerous for the modeler’s reputation. The failure of the AGW models to predict the temperature leveling off of the 2000’s is an example of the type of failure I would expect from the AGW process. The failure of the AGW prediction regarding equatorial troposphere temperatures is another.
After the trend of the 2000’s became clear, I predicted that AGW groups would discover a new factor that accounts for it but that preserves the basic global warming hypothesis. Sure enough, about two years later, group after group released them. This is not predictive modeling science. It is scrambling to make complex models fit the modeler’s preconceived notions.
John Mitchell told us: “People underestimate the power of models. Observational evidence is not very useful,” adding, “Our approach is not entirely empirical.”
Power? Computational power, yes, predictive power? zero.
The idiocy of this statement by Mitchell underlines the absolute and undying validity and authority of Karl Popper’s “Laws of scientific inquiry” (they indeed have the status of laws).
The scientific method is deductive, not inductive. There are no inductive inferences. If it cant be falsified, it aint science.
According to Richard Feynman…http://www.youtube.com/watch?v=8qAi_9quzUY
According to John Mitchell… our models show that the Challenger never exploded.
And to me as a layman it would produce bad results in the domain of “common sense.” I just don’t understand how scientists (or anyone) can fail to see this.
If the rock concert is too loud and I can’t hear what the person nearby is saying, I can certainly try to guess what they might have said, but I know I am just guessing.
@-moptop says:
May 17, 2011 at 8:24 am RE:- empirical evidence of ionizing radiation causing changes in cloud cover. –
“izen,
Are you being ironic here, or are you just that out of touch? Here is a nice overview with links to articles.”
As you link indicates, yes there is some evidence that ionizing radiation can cause cloud nucleation centers, or at least that it can provide the initial precursers of cloud nucleation centers. But given the very poor empirical observations of cloud cover with no reliable long-term trend or correlation with any solar or other hypothesized driving factor I stand by my assertion that there is no empirical evidence that GCR flux has any effect on actual cloud cover in the real world. As the recent research mentioned, and the Svensmark work at CERN describes the hypothesis that cloud cover changes is a MODELING assumption, not evidenced based.
“Ok – but there was high solar activity up until ~1790 – doesn’t this mean that the Dalton Minimum (1790-1820) was warm? ”
The oceanic lag times seem to be variable.
A change in the level of solar activity seems to have a rapid effect in the air to alter the surface pressure distribution but in addition to that solar top down effect there is a bottom up oceanic effect and we do not yet have a grip on the timing of oceanic variability beyond the most basic and merely regional 60 year ENSO/PDO cycle.
The oceanic effect can either supplement or offset the solar effect over variable periods of time hence the difficulty in acquiring correlations that stand up well over time.
The best thing to do is start afresh from now since we have much bettor sensors in the air and oceans. Watch how both sun and oceans vary over time and see whether the net effect of the two variables combined has an effect on the atmospheric heights and surface pressure distribution.
We can see the effect that the active sun and warm sea surfaces combination had in the late 20th century, namely zonal jets and warming troposphere.
Now with the current combination of a quiet sun and a newly negative PDO we have more meridional jets and troposphere not currently warming.
The test will be how things develop from here on. That will tell us whether the pattern holds.
I anticipate continuing low solar activity and a continuing negative PDO which should translate into continuing jetstream meridionality, more clouds, higher albedo, less energy into the oceans and in due course noticeable tropospheric cooling.
Silly me! And here I always thought models used temperature record databases and other “observed” proxies as core data, hmmmm……
J.
@-Stephen Wilde says:
May 18, 2011 at 3:22 am
“I anticipate continuing low solar activity and a continuing negative PDO which should translate into continuing jetstream meridionality, more clouds, higher albedo, less energy into the oceans and in due course noticeable tropospheric cooling.”
Do you ‘anticipate’ the timescale for this reversal of the trend over the last century?
How many decades will this “in due course” take to get back to 1980s levels of temperature?
@Smokey:
May 17, 2011 at 6:45 am
The TSA has plenty to hide.
====================
They keep getting caught stealing from travelers, too. Some excerpts from article that came out today:
[…]
Yet another TSA agent has been caught engaging in criminal behavior. The regularity with which this occurs makes it look like committing felonies is a prerequisite to get a job in airport security.
“A Transportation Security Administration officer at LAX has been arrested for stealing from a traveler’s suitcase,” reports KABC.
“Ryan Driscoll, 31, was arrested on May 10 at Terminal 6. He faces a felony theft charge.”
The case is the 14th in just the last three years (which the TSA admits to) of its workers stealing large amounts of cash and other valuables from airport travelers. Back in February, TSA agents Persad Coumar and Davon Webb were arrested for stealing $40,000 dollars from a check-in bag at John F. Kennedy Airport. They were later discovered to have stolen an additional $160,000 in valuables from people’s luggage, mostly laptops and jewelry.
[…]
Just days prior to this case, TSA supervisor Michael Arato pleaded guilty in a federal court to multiple counts of theft, as well as admitting to taking bribes and kickbacks from another TSA worker to “look the other way”, while the agent he was supervising stole more money from travelers at Newark Liberty Airport. Arato stole up to $700 a day from passengers for a staggering eight years before he was caught.
[…]
http://truthiscontagious.com/2011/05/18/is-criminal-behavior-a-prerequisite-to-get-a-job-with-the-tsa
“If the rock concert is too loud and I can’t hear what the person nearby is saying, I can certainly try to guess what they might have said, but I know I am just guessing.”
LOL. You could find NLP/audio recognition programs that would predict what they are saying. But I wouldn’t make or break a friendship based on the model’s output. I might decide to get them a hot-dog vs a hamburger at the concession stand based on the model’s output because it’s not a very important decision.
But if the decision is important, I would want a high degree of certainty about what he is saying. In the modeling world, that’s the “cost” of a wrong decision. Spending trillions of dollars and remaking the world economy would fall into the “important decision” category for me.
And that’s really the main difference between AGW advocates and “skeptics.” If you push them hard enough on the empirical data, most will fall back to “well, getting rid of carbon based fuels would be good for so many reasons, we should not be worried about holes in the data.” If you ask a skeptic, the skeptic will usually tell you that he wants a good reason to remake the world economy and spend trillions of dollars. There are value judgments at the bottom of both positions. But most skeptics do not pretend that science proves their value judgment or that their position is free of value judgments.
I find it amusing that when you point out the models are flawed, they point to observational data. Glaciers melting, icepack etc..
The biggest thing to me that shows the models are flawed is this. The original hockey stick was created by Michael Mann from models. This hockey stick has been shown to be completely wrong. Model used produce the same result even when garbage is input. Yet some how all the models since then (produced by the team) get the same result. So, Mann did it totally wrong, but got it right? What is the statistical likely hood of that? The more logical explanation is that when a model used did not get the previously thought of as “correct” result, it was tweaked until it produced the near same result as Mann’s. Thus, affirming the model was “correct” and the results ready for publication. His statement may have been accurate if it placed the modifier a “properly done” in front of model. But, as we now know and the climate gate emails show data was tweaked to get the expected results. My personnel favorite was the email where the two “scientists” discussed smoothing out the bump in ocean temps so that they got the desired result, but then discussing how they made sure they did not remove it entirely because someone may notice it was in the land temps and question the descrepancy.
“This is not predictive modeling science. It is scrambling to make complex models fit the modeler’s preconceived notions.”
Exactly, the models are not predicting future climate. They are predicting what the model builders expect the future climate to be. If they don’t, the model builders will “adjust” them until they do.
This “experimenter-expectation” effect is well documented and result when double blind controls are not applied to the experiment (model). The classic example was “Clever Hans”, the horse that could do aritmetic. Now we have “climate models”, the computers that can predict the future.
“In honour of Pfungst’s study, the anomalous artifact has since been referred to as the Clever Hans effect and has continued to be important knowledge in the observer-expectancy effect and later studies in animal cognition.”
Hindcasting is a form or machine learning as you are training the model to reproduce the past. As with animal cognition studies it requires double blind techniques.
“In experimental science, experimenter’s bias is subjective bias towards a result expected by the human experimenter. David Sackett,[1] in a useful review of biases in clinical studies, states that biases can occur in any one of seven stages of research:
1.in reading-up on the field,
2.in specifying and selecting the study sample,
3.in executing the experimental manoeuvre (or exposure),
4.in measuring exposures and outcomes,
5.in analyzing the data,
6.in interpreting the analysis, and
7.in publishing the results.
The inability of a human being to be objective is the ultimate source of this bias. It occurs more often in sociological and medical sciences, where double blind techniques are often employed to combat the bias. But experimenter’s bias can also be found in some physical sciences, for instance, where the experimenter rounds off measurements.
http://en.wikipedia.org/wiki/Experimenter's_bias
http://en.wikipedia.org/wiki/Clever_Hans
http://en.wikipedia.org/wiki/Observer-expectancy_effect
fdf says:
“And that’s really the main difference between AGW advocates and “skeptics.” If you push them hard enough on the empirical data, most will fall back to “well, getting rid of carbon based fuels would be good for so many reasons, we should not be worried about holes in the data.” If you ask a skeptic, the skeptic will usually tell you that he wants a good reason to remake the world economy and spend trillions of dollars. There are value judgments at the bottom of both positions. But most skeptics do not pretend that science proves their value judgment or that their position is free of value judgments.”
Exactly.
This is something that’s been written about a lot by a philosopher/psychologist/mystic called Ken Wilber. He was a biochemistry student who got interested in Eastern religions, and Western psychology, and whether, if at all, any of it was approachable with a modern rational questioning mind. Eventually, he found, in his thinking, that you had to recognise that values and science were two different domains. By “domain” he meant that they involved different methods of inquiry. Science is primarily about objectivity, whereas values are primarily about how people ought to treat each other — and to find that out, you need people talking about their experience, so it isn’t objective, rather, it is inter-subjective. Thus, most discussions that try to mix the two, values and science, are mush. You can’t mix objectivity with inter-subjectivity; that’s like trying to prove scientifically that Picasso was better than Mondrian.
One thing to bear in mind is that inquiry into values does have a method, or a set of methods. We can as people come to certain agreements about what is Good. Although, from developmental psychology, it was found that “what is good” changes for a person as they go through life. It takes about 10 years for major changes in an individual. See the people who were major players in a movement, and then left. What’s really interesting is that people tend to go in one direction, from one set of values, to another, to another. So you can model them as value A, value B, value C, etc. There are various models. And they chart on there, what many of us here call “greenies”, and, if you waited ten years, how those greenies might change.
Of course those models might be very wrong, but the point is, they’re using a method to investigate into our inter-subjective values. The method is there but it isn’t “science” in the usual sense of cold hard instruments. When people talk values they have to use interpretation and that’s a whole mine field. On the other hand, we already have a feel for what a “greenie” is, simply because there’s a lot of people out there who tend to say similar things. What the models add is that if you follow people over time, you tend to see shifts in values in a certain direction.
Anyway, I’m trying desperately to keep this brief. Wilber noticed that the ecology movement was desperately worried about the planet, however, because they were trained in the usual notion that its only real if its “science”, they ignored all the psychological side of stuff. So Ecology claims to be “holistic” but it leaves out psychology, or just, the basic questions about what motivates people. Given that it is people who are consuming and throwing stuff away, wouldn’t ecology want to understand what motivates people to do that? Sorta like, how economists might be interested in whether individuals are actually motivated to act as rational choosers, or whether there are other things that also motivate people… like say, different sets of values? If 10 million religiously fundamentalist people moved into a country, people who valued social cohesion and tradition above all, people who didn’t value self-interested pursuits of career and achievement, if they moved into your country, what effect would that different values set have on the economy? There’s all sorts of qualities or parameters to what makes up a values system and we see many different worldviews and people and movements and sub-cultures around. The greens are one such movement.
So here’s the situation: ecologists want to save the world, and they consider themselves scientists. But the way to save the world might involve getting people to change their behaviour (because you don’t value entrepreneurship, you value quite village life, so you’re anti-industrialisation, and that’s a different lifestyle, so you want people’s behaviour to change). Now that’s a psychological problem. But from an ecology point of view, there’s nothing special about humans, we are just another species. The ecologists themselves have an inherent values system, which they don’t recognise — who don’t realise that they themselves are operating out of a particular viewpoint and values system. They don’t like colonialism, sexism — many are also feminists, for instance — they don’t like phallologocentrism, and they don’t like species-ism… the imagining that humans are any better than other species. They have this inherent values system (which the psychologists have noticed as a particular distinct values system, one of about 7 or 8 major systems around today.)
So the ecologists are in a bind: they want people to change, but they ignore values as a topic, they ignore what it is that motivates people. They want people to change to become more caring about the environment, but they deny that humans are better than animals. I mean, I don’t see lions caring about the environment. But humans often do — strange, interesting, useful? Nope, humans are worse than animals, they say. Now if humans are not better than animals, how do you get humans to be better humans?
“Better” is all about values. Having tried to remain “scientific” about the planet, they ignored entirely the human developmental inter-subjective story about values, and how people gradually move from being selfish to becoming more selfless.
As you’ve seen, greenies don’t actually care about global warming, or any of the science. At the end of the conversation, they’ll just drop down to their core and say something like, “but isn’t life just moving too fast?” The psychologists who study values say that this is what you do; you keep asking and keep asking until you come to the statement that they settle on at the end. That is their values.
They found this also with many Vietnam war protesters. After talking about pros and cons of the war, many protesters eventually settle on, “nobody tells me what to do!!” ie. that’s really why they were refusing to fight, not out of selflessness for the “enemy”, but out of the selfishness of putting themselves above their country’s needs.
The green movement is all about values. Anybody who’s glanced at the models of values can recognise that when they say “the science” it is really more like a shampoo advert, where they always say “here’s the science” because “science” is supposed to be objective and rational and convincing. But then they add their own agenda on top of it, an agenda that look suspiciously like a set of values. It is obvious because when geoengineering or other technical fixes are suggested, they recoil in horror. See, that’s an affront to their values.
But whilst greens continue to mush their values into the guise of a scientific certainty, the whole thing will go nowhere.
If those psychology models have any predictive value, here’s what they suggest: there is another values set that has been identified more recently in people, people who are part of the generations that came after the 60s. If green is sorta correlated with post-modernism, this new values set is post-post-modern. These are kids who have incorporated the green values but also re-incorporated modern rationality and other stuff. According to the models they are also much more effective at getting things done. Unlike say, green wind farms that don’t produce anything, the post-post-moderns are interested in what works, and they are willing to get there in very flexible and adaptable ways. It is estimated that a significant percentage of kids today are arriving with this new set of values. (ie. about 5%)
They actually value flexibility and adaptability in a complex world where multiple cultures are at war with different values systems. So, in many way, the green generation from the 60s got into politics and NGOs and got some power. But they were never very good at getting things done.
The newer generation is very likely to value ecology, but also value industry and human development, and so find adaptive flexible ways to reintegrate systems.
Sorry for the long comment, but you mentioned “values” 🙂