It’s worse than we thought — again….
Fusulo and Trenberth scored headlines around the world recently with a new paper that suggested that a few models got the relative humidity right in some tropical spots, and they also happened to be the models that predicted the hottest global outcomes.
John Christie pointed out that the models with the highest climate sensitivity are also the ones which are the worst at predicting future temperatures.
But there is more to this. It is a likely a case of twenty models predicting 40 parameters, and you can take your pick of the permutations and combinations which give one or two models a “success” here and there on one or two factors. But in the end, as Richard Courtney says, all the models are different so only one model can possibly be The Right One for the whole atmosphere, and quite likely they are all wrong.
In this case, they are still all wrong. The hot spot is still missing, and the region below it with which they scored some success is not that important.
The words hot spot and humidity over the tropics lead many commentators to think this was something to do with the hotspot, but lets make it clear: the (missing) hotspot is at a higher altitude than the area they are referring too. That prediction of warming in the upper troposphere is up around 200-300 hPa. This reduction in relative humidity is centered well below that, at 500Hpa.
Why does that matter? Because the most powerful greenhouse gas (water vapor) does its thing at the top of the troposphere (around 200 hPa) — that’s where it radiates energy out to space. Below that level the energy is effectively ricocheting back and forward — bouncing between molecules or causing collisions and generally rarely getting out to space where it is then gone for good.
This explains the paradox that humidity at lower levels can be relatively unimportant compared to the humidity in the top most layers of our troposphere. Water is so important that the wet part of our atmosphere has a different name to the dry part — that’s the troposphere versus the stratosphere above it. But for most of the thickness of the troposphere there is generally so much water vapor — even at low pressures — that the radiative effect of water is saturated. It’s only on the surface boundary, right at the top of the troposphere, that a change in humidity matters, because it changes the amount of energy that flows off the planet.
Note the strange technique in the graph below of doing relative humidity with the lower numbers on the right. The marketing department probably felt that a line of stars rising from left to right fitted the scare campaign better than a falling line would. This is PR-science, not science for scientists.
…
…
In this graph the colours are for relative humidity, the contour lines are for model predicted cloud loss.
Figure 2: The zonal height structure over ocean of observed climatological annual mean RH from AIRS (2002–2007) (color scale), with model mean projected changes in cloud amount from the CMIP3 model archive (contour lines, 0.5% intervals, dashed for cloud loss). The cloud loss in a warming climate at about 40°N/S coincides with broadening of the dry zones, as indicated by the arrows. Figure 2 from FS12.
…
The red bars are the latitude points where the change in shortwave flux as predicted in models matches the ECS at the 5% level. (Note that this is not longwave, or infra red flux, this is the UV flux — light coming in from the sun and bouncing off clouds.)
Figure 3: Median change in simulated top-of-atmosphere net shortwave flux as a function of latitude under 21st-century warming in CMIP3 SRES A1B projections. Red bars denote latitudes at which the change in net shortwave flux correlates with ECS at the 5% confidence limit. Figure 3a from FS12.
….
The boxes here are the parts of the atmosphere the models do best at predicting relative humidity. These wet and dry regions matched observations at the 1% level. (Everything outside those boxes didn’t). Remember the part of this graph that really matters (in order to predict the radiation that leaves the planet) is the layer around 200-300 hPa near the equator. The models could get the rest right and still exaggerate the amount of heat that was trapped if they get this critical region — the “hot spot” — wrong.
Figure 4: Zonal mean vertical structure of the correlation between present-day (1980–1999) simulated RH over ocean from May to August in CMIP3 models and ECS. Boxed regions highlight peak positive and negative correlations in the moist (M) and dry (D) zones, respectively, where the statistical significance of the relationships exceeds the 1% confidence limit. Figure 3b from FS12.
If the relative humidity is falling between 500 hPa and 300 hPa that could mean clouds are forming at that height, or clouds are forming lower. It seems that high clouds are those above 400hpa, and more often those high clouds are cirrus, the warming kind of cloud. But it doesn’t appear that this paper can tell us which sort of clouds are forming and at which height. About a third of all clouds observed exist between 700 – 400hpa, (and about one third are below that and one third above that). We’re stabbing in the dark with clouds.
The predictions that matter
Note the all important hot-spot below from the IPCC in 2007 (not mentioned in this paper). Even advocates of man-made global warming admit it is missing from observations and is important. It’s between 200-300 hPa (about 10km up, over the tropics).
…IPCC AR4 page 675.
Above is what the climate models predict as a profile of temperature trends.
The observations that don’t match
Below is what many millions of radiosondes (weather balloons) recorded. The scales are different, but you get the picture. The models are wildly wrong, and since the upper troposphere matters because it’s the part that radiates energy to space, the changes there count.
…
Skepticalscience thinks this is evidence from clouds?
Follow the reasoning.
1. Clouds feedbacks are uncertain, and we don’t have much data:
“Unfortunately, as FS12 discuss, the currently available observational cloud data are not very good.
“Constraining simulated clouds is a challenge, however, as clouds are complex and difficult to observe. The historical record is plagued by errors associated with the drift and failure of satellites, inconsistencies in the detection of clouds, and instrument biases. Moreover, clouds can vary not just in their bulk characteristics but also in their microphysical properties, for which global observations are lacking generally, and considerable uncertainty persists regarding the feedbacksnof various cloud types that may occur in a changing climate.”
2. So instead of examining the data we don’t have, we’ll look at relative humidity instead. It’s like looking at a cloud, really, and if we just knew all the details of what conditions exactly form clouds (seeding particles anyone?), it would be almost as good as having actual cloud data.
“Thus rather than examining clouds directly, FS12 take a different approach and instead look at the conditions in which clouds form.
“Variations in clouds and relative humidity (RH) are inherently linked in nature, and the approach here is motivated by the fact that models generally use RH to parameterize clouds”
So if models use relative humidity to generate clouds, and we know that the models don’t work, does that tell us something about how much we don’t know about cloud formation?
They have a failed theory on their hands, and many of the world’s bureaucrats and politicians have staked their reputations on it, not to mention the billions of dollars at risk. What if people find out they are wrong? Hmmm, tricky situation. Papers like this one help provide the cover and delay the inevitable. The Team knows they can cite it, and most people won’t check the details. Journalists will just reprint the press release.
REFERENCES
Fasulo, J., & Trenberth, K. (2012): A Less Cloudy Future: The Role of Subtropical Subsidence in Climate Sensitivity, Science, Vol. 338 no. 6108 pp. 792-794 DOI: 10.1126/science.1227465 [Abstract]
My posts on the missing hot spot
- Models get the core assumptions wrong– – the hot spot is missing
- So is the hotspot a “fingerprint” or signature? Is it unique?
- This is 90% certainty? Really? (Yet another paper shows the hot-spot is missing.)
- Thorne 2010: A very incomplete history of the missing hot spot
- Dessler 2010: How to call vast amounts of data “spurious”
- The models are wrong (but only by 400%)
- Sherwood 2008: Where you can find a hot spot at zero degrees
- How John Cook unskeptically believes in a hotspot (that thermometers can’t find)
- Even gurus of warming admit the hot spot went missing
- The missing hotspot
- Found: the hot spot? Not
John Brookes wrote this comment earlier when the draft of this post appeared. His comment has disappeared. Sorry John. Here’s what it was:
512
Is it possible to give you a thumbs up, while giving brooksie a thumbs down, on the same comment?
153
Great lesson on how to confuse a “skeptic”.
58
… try to comprehend dunces like you?
21
Or perhaps ask them to expain how climate sensitivity is low and the MWP was supposedly warmer than today.
33
Climate sensitivity is low.
You explain why it is high.
33
Sure.
http://itsnotnova.wordpress.com/2012/04/02/climate-sensitivity-idso-idsnot/
10
Look Brooksie, the atmosphere and total climate system is a mess of interacting physics. If there is even ONE part that is wrong it affects the rest the system. The models getting a piece here or there correct simply means the rest is still wrong and the correct bit(s) are ACCIDENTAL or TUNED!!! It is nearly impossible to draw any conclusions from a mess like they represent.
271
JB…
What would be the impact on the models accuracy of setting climate sensitivity to CO2 at < 1?
(I.e. Net Negative Feedbacks on CO2 Concentration in the Atmosphere – has it been tried?)
60
I think John’s comment on models is perfectly OK, as he obviously is not referring to climate models.
40
An inacurate model does indeed tell you much.
1/ Accepting that your model is not correct is a great first step.
2/ Your understanding is incomplete.
3/ Your programming may have bugs or logic errors.
4/ At least one (possibly more) of your formula is not correct.
5/ If you wish to use the output of your model, its range of usefulness will be limited.
PS: I write hydraulic software (the rainfall type).
00
It looks like desperation has set in. Let’s give a thumbs down to the models and be done with it. And John Brookes is flailing his arms around looking for attention. And there’s really not much to see here…
122
The only model I have found to be perfect was…
Elle Macpherson in her prime !!
It’s an a absolute travesty that we cannot find the perfect model nowadays …. Bemoans Trenberth.
Poor Kevin….
161
Now there you have a model to warm the heart of any skeptic — well, at last half of us. Doesn’t help much with high blood pressure though.
I shall repent of my thumbs down comment and do appropriate penance.
BB
40
Is that what it’s called these days?
Appropriate penance it is.
HT to Elle (in my prime)
40
Now there’s a can of worms, we’ll have to start making distinctions between Models and Super-Models…
40
If Elle is the model….
Then Jo is the super nova errrr I mean super model …
Heheheheheeee……
40
As another blogger has noted, ‘all models are wrong, but some are useful’.
71
Figures 2 & 4 do have data in the 200 hPa height over the tropics. The increased humidity there SHOULD support the hot spot theory of CAGW. If you normalized for humidity, would not the upper troposphere be COLDER?
Yeah, the humidty vs altitude graph is backwards for the political sentiment it induces in the non-technically observant.
21
We used to do that sort of thing in science lab at school: Keep going until you get the right result, then stop. At least that was our interpretation of Scientific Method.
71
Danish Meteorological Institute (DMI) gave it just an extra twist:
Den globale temperatur følger de varmeste klimamodeller
21.11.2012
De klimamodeller, der giver den kraftigste globale opvarmning, er de mest nøjagtige klimamodeller
Those models that gives the largest GW are the most accurate.
They merely stress the point in the following text, where they just say that the models that best capture processes of humidity and clouds in important parts of the atmosphere also was the models with the highest CO2 sensitivity.
The paper itself is more moderate, but the writers seems to be happy for all the extraordinary claims, even if they are far out.
41
The psychologists and sociologists would call it counterintuitive, the rest of us call it delusional.
111
The Distortion continues.
These so called “MODELS” are not models.
By definition a model is used where there are too many background variables to do a calculation involving them all.
A Scientifically Credible models therefore has three main elements:
1. The observable and measurable INPUT factor. In the case of AGW that variable is atmospheric CO2 level.
2. A group of background variables whose effect can be determined “in bulk” by observing the system
with zero change of the main Input factor to be observed.
A proportionality factor can then be assigned which may be used within certain boundary limits.
3. The observed output of the system, in this case atmospheric temperature, as the main factor is varied
during observation.
Items 1 and 3 suffer from the problem of actually determining values that can be used. The world is a big , variable complex system and is open to measurement errors on large scale.
But item 2 is the BIG problem.
Global Warming enthusiasts have simply said, OK, we believe , trust us, that ALL of the other variables are inconsequential and only CO2 variability is important.
This is NOT correct.
The list of major effects from other factors like, water vapour, orbital mechanics, Galactic radiation and Earth Magnetic field effects says that Item 2 has never been dealt with in a scientific manner.
Item 2 has been neutered for political purposes.
These are NOT Models and any academic who refers to these “things” as such is being deliberately
Dishonest.
KK
132
Scientific Models for atmospheric physics are a complete load of crap and a fraud.
But they are convenient for:
1. Minimizing the importance of inconvenient objective data.
2. Providing bullet proof propoganda to complicit politicians.
3. Justifying enormous tax payer grants to the “scientists”.
Number on rule with computer modeling is:
SHIT IN = SHIT OUT.
This also seems to apply to the human brain as well.
163
The problem arises due to starting an inquiry with a pre-determined conclusion.
The presence of the pre-determined conclusion shapes the methodology of the inquiry – out with falsification, and rigorous empirical data, and in with easily manipulated models and dubious proxies that can be held up as “evidence”.
Only the ignorant, credulous or devious would accept such a methodology.
70
JB says that a limited model may still be useful. It brings to mind a stopped clock that is correct twice a day.
Another model that seems to have limited utility:
http://web.mit.edu/newsoffice/2012/ocean-currents-and-sea-ice-1121.html
100
It surprises me how educated people who consider themselves to professionals can keep churning garbage out and ignore that what they are doing is always detected.
91
Well done to those that read it as it is a very dense read. Not so well done to those that feel that a sufficient critique is to just bag models and climate science. I guess the latter response saves time and brain cells.
I’m with Jo at being concerned at the criteria they used to decide on significance for support for changes in certain parameters using particular models. This is where I’d be most sceptical. In defense of the paper, their models make predications that can be verified by observations. So time for cloud watching (best if you can tell clouds apart from chemtrails)
48
To your last point. That’s been difficult these last few days with heavy aerosol spraying over Melbourne CBD. The tell tale sign is a long aircraft trails which expands over the course of the day to fill the skies. This is due to water condensing onto the matter which is sprayed as it provides a location for droplets to stick.
If you want proof that there is stuff falling from the sky on such sunny days simply cover the sun with your hand and watch for long polymer strands lofting on down from above.
Skeptics of chemtrails will tell you that this is ballooning spiders! Hahahahahajajaja
64
Just a few questions Gee Aye, how many years do I need to read and study this stuff before I realize I’m just repeating the same old junk science with a new coat of whitewash? It isn’t even a good whitewash job. How far does it need to go before I can write it off?
101
Hi Bite Back,
You took the time to respond to GA. Good work.
He is “benign troll” but on occasion still likes to show that he wants to save the planet.
His complaint that people are “bagging models” is again incorrect.
Nobody is Bagging Models.
Models are an extraordinarily valuable tool when used according to the rules of science but when they are
used incorrectly AND with a definite intent to DEFRAUD they need to be bagged and bagged mercilessly.
Like JB, Gee refers to particular parameters and such as “possibly” being in need of change or fine tuning but that otherwise , no problem.
Sorry there are huge problems with so called Models of CO2 vs Atm Temp.
These models do not model anything; they are rubbish.
People supporting Climate Models should be lined up at the gates of every University in Australia and forced to hand back their Degrees.
KK
101
thanks KK. Obviously I need to clarify.
The problem I see in this paper is that so many parameters are being examined that (as I think Jo was stating), the chances of finding significance using mujltiple models over multiple parameters is very high, by chance. I consider this a huge blind spot in many areas in science and I am sceptical that climate scientists are dealing with it competently. The statistical methods employed don’t give me confidence that this was addressed well. In the absence of independent analysis of the model output, and of testing other valid methods of assessing multiple observations of the same data, I remain unconvinced of the main conclusions.
What are your thoughts on this?
60
Well Gee you got me.
I must confess I have not read much of the above at all but I did see diagrams about the atmospheric hot spot, relative humidity and similar situations that just do not lend themselves to modeling in the all encompassing way of climate science.
We have “models” for a system that varies over a 24 hour cycle ( the diurnal bulge) which is superimposed on a monthly cycle ( the moon) which is laid over a a constantly varying annual cycle (the sun) which is put over other longer period cycles determined by orbital mechanics and location within the galaxy.
Is Harry Trenberth the same guy who had a model showing CO2 effects on atm temperature against the backdrop of all the above factors which he deemed to be “accounted for”.
ALL of the factors listed have signals Greater than the signal from all CO2 let alone the puny man made CO2, so anyone purporting to have modeled CO2 vs Temp atm is pulling our leg.
You cannot have models where the background factors have signals millions of tomes larger then the signal being tested.
Once all of the listed factors have been quantified, only THEN will I admit that a model of COO2 could be tried.
That may occur on 2100 or nearabouts.
KK 🙂
20
Keith,
If my work was as good as these climate models I would be shown the door.
They’re building models based on the symptoms of an underlying cause which they assume without proof because they don’t know what the real underlying cause is. Then they adjust the fudge factors trying to make it work. It can’t ever succeed.
If I use “fudge factors” I better be able to justify them. I can’t tweak bad input to make it look good in the output. If any number isn’t traceable back to the problem I’m solving and based on sound research, sound engineering or sound math it won’t fly. Management looks at the result. Where is the management in climate modeling?
Climate modeling does not fly.
BB
20
Yes Bite Back
The “models” are only accepted within the Climate Science community within Universities.
An academic from any other Faculty that gave assent to the accuracy of that work would be a laughing stock.
Departments of “Climate Change” are more closely related to Philosophy Departments than any form of
science and that is why any Meteorologist or Hydrologist working on agricultural or general
engineering projects are attached to the ENGINEERING FACULTY.
KK 🙂
20
You will let us know when they are in fact verified, won’t you?
91
not my job to inform you of when something is or isn’t corroborated. And to the previous post. Yes, absolutely. If you assume a priori that something is junk then you are not much of a sceptic.
211
Gee Aye,
I think you’re a reasonable man. So here is my position.
I make no a priori assumption about it. I do compare the lack of empirical evidence to support it with the accumulating evidence that natural forces are at work. I do compare the claims of temperature rise with the actual temperatures. I do compare the claims of sea level rise with the actual rise. I do compare the claims that this or that year was the warmest on record with the actual temperature records. I do compare the claim of present alarming temperature rise with reality. I do notice that nothing unprecedented in Earth’s history is happening, not even the temperature rise since the LIA that is supposed to be the harbinger of disaster.
I also look behind the scenes at the way climate science operates and it’s not a pretty picture. Lots of dishonesty there (climate gate I and II for instance). It’s not trustworthy.
But the most important fact is that not a single bit of evidence actually connects CO2 with anything. That CO2 is doing something is the real a priori assumption in this whole thing…the monster of an elephant in the parlor. A whole body of “science” has been built on a foundation of assumption. And you call us out for “bagging” climate models.
The claim of dangerous human interference with the climate can’t support itself. The whole body of evidence against AGW can’t be overcome with some new paper claiming,
If you have a model of something it’s supposed to represent an object or phenomenon in the real world. To the extent that it behaves like what it models it’s a good model. If it’s supposed to have predictive power then it must predict accurately. This is the basic definition of a model. And climate models don’t measure up. If they get only a small piece of it right and only for some spots on earth, so what?
BB
60
That was rhetorical. On the other hand, it is the responsibility of those making some claim to actually show the evidence.
30
Hi Biter
As I said in an earlier thread: I don’t know what motivates his behaviour.
It is different and that is about all you can say.
51
Gee, you’ll take some heat here but I’ve come to love you. True, this isn’t the place or time but alas the heart knows no geography nor chronology.
20
Friday night is not the time to consummate anything in a meaningful manner. Always best to start these things sober.
20
This is OT, please pardon, but it leads back in again. I think.
Can anyone refer me to papers where the barometric pressure as measured by instruments carried aloft has been measured in the same way as (say) relative humidity, gridded globally and contoured? The angle is that the sum of the barometric pressures should remain approximately constant over time at a nominated altitude, though we all know that highs and lows move around. If the variability of barometric pessure is large, we can start to draw some inferences about the variability of measurement of humidity and temperature. This in turn might further constrain the model data.
40
Interesting point Geoff.
KK
10
Here is a model.
It is a model example of what is ‘failed’ with ‘their’ ABC’s climate alarmism.
Titled, “The zeal of the newly converted climate sceptic”, it is article highlighting a video clip of a doorstop interview of a woman ‘seeing the light’ after viewing a documentary about melting glaciers.
Huh? Cognitive dissonance anyone? Guess that ‘life change’ starts tomorrow.
But, the ‘money shot‘ is the quotes from the author, ABC enviro-editor Sara Phillips, like:
Frightened. Quivering. Just how we like the population, so we can lead them to safety with new taxes!
Not to mention the tired ole cliche’, ” Sea level rises may in fact be worse than predicted.”
Worse than predicted? When will they get a prediction right?
Then there is the links.
One to the World Bank.
Climate experts who, whilst funding & building new coal fired power stations worldwide, warns of warming of 4-6 degrees! Good reference, Sara. Investigative journalism? Not for this true believer.
Scientists from the Global Carbon Project have recrunched numbers..
* Unspun: We moved the goalposts because we were wrong, and the science is now re-settled.
“Just wait until the world’s population grows some more and all those new people have a car, a TV and air conditioning.”
Yeah. Just wait you, you … denier!
.
Only ignoramuses believe that climate stability is normal.
(h/t greenie watch for this quote)
81
Excuse me, Jo,
– “top most”(?) The word in this context is surely “topmost”. Breaking the compound word in two renders it meaningless.
00
.
I built a model the other day. It came about as a result of a decision to show my grandson how to use hand-tools. We built a widget. My grandson was happy. Total cost of our widget was one dollar. The following Sunday we took it to the local market and sold it for two dollars.
The next week, trading on lessons learned, we built two widgets, each costing a dollar. On Sunday we sold both at the local market, for two dollars each. The next week I knocked up some jigs, and we made four widgets, again for a dollar each, and again we sold them for two dollars each. Last week we made eight widgets, and once again our return doubled.
I started to wonder, with this doubling of profits each week, how long it would be before I started to make some REAL money. So I developed a little algorithm to model it.
The results were astounding. It turns out, in a bit over a year, in 64 weeks to be precise, I will be worth $18,446,744,073,709,551,615.00 which I’m sure you’ll agree is a great deal of money.
.
Now I’m not a
climate scientistcomplete idiot. I knew there would a bit more to it than that. For a start, long before I made even a tenth of that lovely money, everybody on earth would already own one of my indestructible widgets. How on earth would I convince them to buy a second one? Worse, the following week everybody would have to buy two more, and the week after that, four.Then I realised this was actually a marketing problem, and I know nothing at all about marketing, which was a bit of a worry. But then I realised there are thousands upon thousands of things I know nothing about – like the effects of clouds, fluctuating solar energy output, humidity, jetstream air currents, and Lord alone knows what else.
So, I made my first assumption – that all the stuff that I didn’t know anything about would have both positive and negative effects on my model, and that these would invariably cancel each other out, and so they could be safely ignored.
.
That only left me with one problem: as near as I could tell, there simply weren’t enough of the raw materials I would need to build that many widgets. In fact I’d need at least three times as much raw materials as there were known reserves on all of the earth.
That was a bit of a worry until I remembered that supply of raw materials can always be expanded. It just means supply companies have to go out and find new sources. The very act of me making and selling my widgets would create new demand and have a positive forcing effect of the supply of these materials.
Since it fit my model perfectly, I decided this positive forcing would be a factor of around 3.3.
.
My model is now perfect.
It gives the answer I want – that I will be filthy rich in less than a year and a half’s time – every time I run it.
Anybody want to buy shares in my widget company? JB? GA? MattyB? Ross James? Silly filly? Cat?
190
In the old Ottoman Empire, the Shah would grant wishes to his favourite servants. One such servant was his chess tutor, as chess was very popular in the old empire.
When the Shah offered a wish to his tutor, his tutor said “My Shah is very generous. May I impose on him to give me some grain to make bread so as my wife doesn’t have to go searching for grain every day?’
Shah: Of course, how much do you want?
Tutor: My Shah is very generous, and since we both love chess, all I want is the equivalent of one grain on the first square of the chess board, two grains on the second square, four grains on the third, eight grains on the fourth and so on.
Shah: Come come my man, surely you mean bushells and not grains?
Tutor: My Shah is very generous, but just grains will suffice.
Shah: Your wish is granted. (granted wishes are law)
There wasn’t enough grain in all the silos in the whole empire.
100
BH that’s an oldie but a goody, I must have heard that one about 40 years ago.
Think my old man told me.
50
An excellent analogy.
30
MV,
Take your plan to your PM. She should instantly see the value of it and will probably buy you out for more money than you ever dreamed of. 😉
00
The general fallback business plan in IT startups these days is to have a web site promoting the virtues of your vapourware that looks so convincing that Google decides to buy your company for 10 million bucks just to get rid of you from the market.
You sell, but now its being run by Google who have slightly different ideas on how it should run, so you chuck a “loss of creative control” artistic temper tanty, quit, cash in your stock options, never have to deliver anything you advertised, and retire comfortably to the north coast.
And yes, if it was that easy, everyone would be doing it!
00
Ha, good one. But strangely, you can increase your market hugely by building a widget that breaks and needs spare parts. Indeed, if you start your plan with parts in mind, you might well prosper in practise, not just in fun.
I remember the press release from Epson printers when they announced a drastic lowering of the price of the printers themselves, and an intention to make their gains from the sale of inks and papers. Echoes of Eastman, who said he could give free cameras to all people and make a fortune from the film.
Maybe this is an oblique explanation why climate models fail so often and need regular talkfests like Doha. It’s built into them.
10
Copernicus started a roll which lasted a few hundred years. The essence of was that “reason rules” OK?
Now we have a new scientific method, F*@# reason, the models rule.
If we go back to the Copernican/Feynman view of things then our tertiary education system would collapse because a) there would be no funding and b)
nofew employees capable of reason.30
You are describing Renaissance culture – of which we are the heirs.
The primary counterrevolution to the Renaissance culture are the “Progressives” whose Orwellian name hides their ideological thrust to return us to a Neo-Feudal society of Aristocrats, Thugs and Serfs where superstition and dogma rules instead of reason.
60
It’s funny, MV. My treasury modelling shows that that’s exactly the amount of money needed for a carbon neutral, sustainable future. Perhaps we need to crank up the MV widget economy to bypass the bankers and fully fund the end of civilisation process ourselves. And all in a little over one year – miraculous.
By George, I think you’ve done it, sir! I’m in awe of your ingenuity. Who said these models weren’t useful?
40
.
Stuff civilisation – and a carbon neutral future.
I’m getting me one of these.
.
And a Ferrari.
50
.
Oh, and at least a dozen of these so me and my drinking buddies can hoon up and down Pumicestone Passage.
40
OT – Alan Jones discusses wind power with Dr Alan Watts.
http://www.2gb.com/audioplayer/6345
00
My last model predicted blades of grass in Julia’s mouth. So rich now I tear up all my mail.
00
My last model predicted blades of grass in Julia’s mouth. So loaded now I tear up all my mail
00
[…] http://joannenova.com.au/2012/12/fasulo-and-trenberth-find-spurious-success-make-headlines-but-still… […]
00