No evidence at WUWT - a DuKE, global surface temperature, and statistics

Anthony Watts has a new article on his climate conspiracy blog (archived here). It has the title: "Is There Evidence of Frantic Researchers “Adjusting” Unsuitable Data? (Now Includes July Data)". The answer is NO. Or at least none is provided by anyone. Which raises the question of why the title? You'd think he'd at least make up something to appease the mob. All he has is a mish-mash of temperature data from various sources, including lower troposphere data, and land and sea surface data (combined), and sea surface data, interspersed with gobbledegook from one of his long-winded fans. (And July must be a big deal, even though it's already October!)

The authors are listed as follows:

• Professor Robert Brown from Duke University (aka the batty duke or rgbatduke)
• Werner Brozek
• with one of Anthony's pet Anonymous Cowards known as "Just The Facts" as editor.

In regard to whoever is Just The Facts, he or she is a long time regular. Anthony doesn't like people using pseudonyms. Let me correct that. Anthony only likes deniers using pseudonyms. Any normal person who prefers to comment on climate using a pseudonym is castigated by Anthony Watts. (I think Just The Facts is the same person who also posts at WUWT as justthefactswuwt. But I cannot say for sure. It doesn't matter.)

A note on statistical significance: If you want to skip over the meaningless ramble, you can jump straight to the discussion about what statistical significance means. (Hint: a 'not statistically significant' trend doesn't mean that it hasn't warmed.)

Partial to Carbon Dioxide - Why Willis Eschenbach Wonders at WUWT

Update - I've updated the archive here, just so anyone interested can read the comment from the batty duke (rgbatduke).  See below.

Update 2 - Willis has added a new chart and now has another question - Click here to jump to it.


Wondering Willis Eschenbach is wondering again.  This time he's wondering about carbon dioxide in the sea surface and the air (archived here, latest archive here).  He used data analysed by the following team, that was collected way back in the 1950s and 60s:

Lee S. Waterman, Pieter P. Tans and Todd Aten from NOAA, Boulder, Colorado; Charles D. Keeling from Scripps Institution of Oceanography, La Jolla, California and Thomas A. Boden from the Carbon Dioxide Information Analysis Center, Oak Ridge, Tennessee.

A gigantic geochemical experiment...

The paper that Willis linked to provides an interesting piece of scientific history.  It has a quote on the front page:

"...Man, in his burning of fossil fuels and denudation of the land's surface, may be performing a gigantic geochemical experiment in which the CO2 cycle is being influenced. It is thought we may be increasing the C02 input into the atmosphere by 70% in 40 years, although it is not certain how much of this may be absorbed by the oceans. A substantial increase in C02 content in the air would trap more of the earth's radiated heat and cause a warming of temperature.

Data collected during the IGY will be needed for comparison with measurements made 15 to 25 years from now to determine whether the C02 content is changing ..."

Lill and Revelle
IGY Bulletin
October 1958

Early ocean CO2 research

What the researchers did was analyse data collected in three oceanographic expeditions between October 1957 and August 1963.  The data related to carbon dioxide in the air and the surface water. (IGY was a major international collaborative scientific effort between July 1957 and December 1958. From Wikipedia - "It marked the end of a long period during the Cold War when scientific interchange between East and West had been seriously interrupted".)

It didn't take me long to find what was probably Willis' source. The research is described by Scripps CO2 Program as:

During the late 1950's and early 1960's, Charles D. Keeling supervised the measurement of pCO2 in surface ocean waters and in the atmosphere just above on a number of seagoing expeditions mounted by Scripps Institution of Oceanography. These expeditions ("cruises"), comprising long transects in the major oceans, were chosen to map the global features of surface ocean pCO2. Data from most of these cruises are presented here for the first time in detail (in the form of hourly averages). The data had been processed soon after the cruises and presented in several research articles as averages, over geographical areas, of the difference in CO2 concentration between ocean and atmosphere (see References). This site contains data from the DOWNWIND cruise in 1957, the MONSOON cruise in 1961, and the long LUSIAD cruise in 1962 and 1963.

The wrong end of the stick

Willis took the difference between the air and sea surface CO2 data, which he mistakenly thought was parts per million by volume of CO2, and plotted it against sea surface temperature.  (He obviously didn't read the above paragraph or the paper very closely.)

Source: WUWT

Willis wrote:

To describe the situation in another way, when the water is cool, it contains less CO2 than the overlying air … but when the water is warm, it has more CO2 than the overlying air.

Say what? I gotta confess, I have little in the way of explanations or comprehension of the reason for that pattern … all suggestions welcome.

In fact, as Nick Stokes pointed out in the comments, the data Willis used wasn't the amount or parts per million by volume of CO2, it was the partial pressure of CO2 (pCO2).  So Willis' positives meant CO2 was going from the sea to the air (which is expected as water warms up) and his negatives going from air to sea, not the other way around - which was what Willis mistakenly thought. No wonder Willis was wondering why his chart was counter-intuitive.

There is more that is wrong with Willis' chart, but because his main error was so fundamental, he probably wouldn't have plotted the data that way if he had understood what the data was. So I won't go into that.

About ocean CO2

Ocean CO2 data have since been collected over the years by individual scientists or research teams.  Now there are attempts to coordinate efforts globally, as described on the Global Observing Systems Information Centre (GOSIC) website.

CO2 dissolves fairly readily in water.  Once in the water it reacts chemically and there's only a small bit that remains as CO2.  As described at GOSIC:

The CO2 and associated chemical forms are collectively known as dissolved inorganic carbon or DIC. This chemical partitioning of DIC affects the air–sea transfer of CO2 as only the unreacted CO2 fraction in the sea water affects the CO2 flux, which is determined from measurements of atmospheric and surface sea water partial pressure of CO2 (pCO2) and wind speed.

The surface ocean partial pressure of CO2, pCO2, is a critical parameter of the oceanic inorganic carbon system

1. because it determines the magnitude and direction of the exchange of CO2 between the ocean and atmosphere, and
2. because it is a good indicator for changes in the upper ocean carbon cycle.

In addition, it is an oceanic parameter that can be routinely measured with high accuracy and precision. 

The oceans are absorbing about 30% of the CO2 we are adding to the air (and the biosphere is absorbing about 25% of the extra CO2).  The amount of uptake is affected by ocean modes such as the North Atlantic Oscillation, the Pacific Decadal Oscillation and ENSO. For example, in El Nino years, the oceans absorb a about 30% more than the long term annual average (which according to this 2010 paper by Valsala and Maksyutov is estimated at around 1.5 petagrams of carbon a year).

Here's a map from CDIAC showing the mean annual net air-sea CO2 flux as measured in 2000.  Click for larger view.

Source: CDIAC Ocean CO2

It varies a fair bit, with the green parts having zero net exchange, the blue and purple bits are the ocean areas absorbing CO2 and the red bits emitting CO2.  (The year 2000 was part of an extended La Nina period.  That year saw Australia's second wettest year on record at the time, exceeded only by 1974, according to the Australian Bureau of Meteorology.)

Here's some more information from CDIAC about the differences in the CO2 absorption in different parts of the oceans.

Major source of CO2: The equatorial Pacific (14°N-14°S) is the major source for atmospheric CO2, emitting about +0.48 Pg-C/yr.

Major sink of CO2: The temperate oceans between 14° and 50° in the both hemispheres are the major sink zones with an uptake flux of -0.70 Pg-C/yr for the northern and –1.05 Pg-C/yr for the southern zone. 

Most intense CO2 sink: The high latitude North Atlantic, including the Nordic Seas and portion of the Arctic Sea, is the most intense CO2 sink area on the basis of per unit area, with a mean of –2.5 tons-C / month / km2 (1 Ton = 106 grams). This is due to the combination of the low pCO2 in seawater and high gas exchange rates. 

Lowest CO2 flux: In the ice-free zone of the Southern Ocean (50°S-62°S), the mean annual flux is small (-0.06 Pg-C/yr) because of a cancellation of the summer uptake CO2 flux with the winter release of CO2 caused by deepwater upwelling. 

Net global flux: The annual mean for the contemporary net CO2 uptake flux over the global oceans is estimated to be -1.4 ± 0.7 Pg-C/yr. Taking the pre-industrial steady state ocean source of 0.4 ± 0.2 Pg-C/yr into account, the total ocean uptake flux including the anthropogenic CO2 is estimated to be –2.0 ± 0.7 Pg-C/yr in 2000.

So - now I know a whole lot more about the absorption of carbon dioxide by the oceans.  I've always maintained that I learn a whole heap about climate science by researching the wrongs from pseudo-scientists :)

From the WUWT comments

There were some thoughtful comments (I'd say more than usual) among the usual swag of thoughtless comments in response to Wondering Willis Eschenbach's article.  Here is a smattering (archived here, latest archive here):

ronald foolishly takes the word of Wondering Willis over that of the scientists.  He's full of conspiracy ideation and says:

November 27, 2013 at 2:55 am
Can it be a agw survey? Cold water absorbes CO2 and warm water let it go by out gassing. It looks to me that someone wants to let look to work the other way to help agw.

Macha has it all back to front when he says:

November 27, 2013 at 3:23 am
Relative difference is not the same as absolute. Warmer water can absorb and hold more CO2, than cold. The rate of change I more a question of kinetics.

martin brumby is a paid up member of the Scientific Illiterati and says:

November 27, 2013 at 3:25 am
The vast majority of their dots are for sea surface temperatures greater than 20ºC.

Perhaps the cruises in oceans where this was the case were more popular with the psyentists than those trawling around oceans with temperatures below 10ºC?

Or maybe the latter group just kept warm and cosy below decks?

Nick Stokes comment prompted me to look into this.  He says (excerpt):

November 27, 2013 at 4:02 am
Willis, I don’t think the water measurement reflects concentration of CO2, and I’m sure it isn’t ppmv of water. It’s described in your link as pCO2, which would be the partial pressure of CO2 in equilibrium with the seawater.

In that case, there’s no particular expectation about variation with temperature. With no flux, it would be zero at any temperature. What it does reflect is which way CO2 is moving.

Richard Graves also has it back to front when he says:

November 27, 2013 at 4:42 am
I like to make soda water. Thinking very cold water would make bubblier soda that’s what I tried. Results not good! Then I tried water from tap around 20C. Result nice bubbly sodas. Seems the warmer water absorbs more CO2 more easily. Its been bothering me why?

François is impressed by the scientific research done 55 years ago and says:

November 27, 2013 at 4:11 am
Five years of measurements, fifty years ago, with the instruments available then. I am impressed.

Dodgy Geezer is a conspiracy theorist too and, after quoting Willis, says it's all a political plot:

November 27, 2013 at 4:39 am

…The first surprise was that I was under the impression that there was some kind of close relationship between the atmospheric CO2, and the CO2 in the surface seawater. …

Alas, Willis, you have been infected by IPCC reasoning. The idea that there are only a few big variables and they interact with each other in a simple manner is what you say when you are a political advisor hoping to persuade a politician.

“Yes, Mr Prime Minister – if you enact this law you WILL get more votes…”

In reality we have two domains here, the sea and the air. Each has a set of pressures and balances which determine the local CO2 concentration. At the point where they touch – the sea surface, they probably interact with one another. But how important that interaction is compared with their own internal driving variables… who knows?

Update

I've updated the archive (and again here) because there is a very long comment by the batty duke (rgbatduke AKA Robert G Brown.  Don't worry, I'm not outing him.  He hasn't hidden his identity at WUWT).  I have to wonder how he got and managed to hold onto a job at Duke University.  He doesn't seem to be aware that the data is from samples collected 50 years or so ago.  He says he would have brought on-boat computers and automated robots! In 1957!  And he wants the data compared to CO2 at Mauna Loa - which didn't start measuring CO2 until 1959. And despite the fact that quite a number of people mentioned it, the batty duke is also oblivious to the fact that Willis made a mistake and the data was pCO2 not ppmv CO2.

There's worse still.  From his ivory tower at Duke, the batty one writes:

...but I’d bet my sweet bippy that it also reflects the selection bias of researchers to prefer ocean cruises in the warm, sunny tropics with lots of interesting places to stop and things to see relative to cruising around the Cape of Good Hope or Tierra del Fuego or knocking around Iceland or the Bering Straits — presuming one can get in through the ice and so on. 

What a nong.  If he'd checked the paper he'd have seen from the map of the routes that voyages went from around 70S to 35N and virtually all around the globe from east to west.  They did sail around the Cape of Good Hope and while they didn't go around Tierra del Fuego, they went pretty far south in South America and right down near the Antarctic.  (How many American scientific expeditions travelled around the Bering Strait during the cold war?)

Not only that, the batty duke has no appreciation of how real live scientists do field work - and the way that so many of them risk all sorts of dangers and put up with all sorts of hardships, so idiots like the batty duke can figure out whether to bring a brolly to work or will need to put in more firebreaks or add a water tank to his comfy home in North Carolina.

Update 2

Willis has added more to his post including another chart and has another question (archived here).  This time he asks:

My main question in all of this is, how does the CO2 content of the seawater get to be up to 100 ppmv above the CO2 content of the overlying air? It seems to me that the driver must be biology … but I was born yesterday.

I came across an older paper that examined ocean CO2 in more detail, including looking at seasonal and diurnal fluctuations.  The paper stated:

These results support that the diurnal change in pCO2 measured in the present study are associated with the photosynthetic activity by photoplanktons in seawater.

From what little I've read so far (and it's a huge subject area of which I haven't scraped but a fraction of the surface) the seasonal variation is driven by temperature but this varies by location.  There are other factors that play an important role including upwelling / downwelling water (vertical mixing) and wind. There is also spatial variation that is driven by biological factors (which themselves vary with the season) and which combine with the effect of sea surface temperature.

Willis has simply plotted pCO2 vs sea surface temperature.  He hasn't plotted by space (lat/long) or season.  In his plot where the sea surface temperature is above 25 degrees and more particularly so when it gets closer to 30 degrees, pCO2 (ocean surface) is generally above the average atmospheric CO2 pressure.  But I don't think that tells much.

What I don't understand is why Willis goes and plots all this stuff with no apparent particular aim in mind without doing any reading.  You'd think being chided by Roy Spencer would have taught him a lesson.

---

L.S. Waterman, P.P. Tans, T. Aten, C.D. Keeling, and T.A. Boden, Quasi-simultaneous CO2 Measurements in the Atmosphere and Surface Ocean Waters from Scripps Institution of Oceanography DOWNWIND, MONSOON, and LUSIAD Expeditions, 1957-1963, draft report, 38 pages, 1996.

Boring climate or short term memory loss at WUWT? Extreme weather in 2013

I have neither the time nor the interest in picking up every single wrong in rgbatduke's article from yesterday (archived here). I'll just post a short list as a starter.

rgbatduke is bored with the climate, complaining that there hasn't been anything unusual happening.  I already pulled him up on his mistakes (intentional or otherwise) relating to global temperatures for September (and June).  This time I'll pick him up for his claim about boring climate, which Anthony Watts, supposed weather watcher and owner of WUWT, used as the headline when he elevated rgbatduke's comment:

‘Let’s face it. The climate has never been more boring.’

Here's a list of just a few of the extreme weather events this year that our boring climate has delivered, which wasn't so boring for many people and utterly devastating for some:

• Fires in Tasmania - January 2013
• Australia's (hottest) Angry Summer
• Oklahoma EF5 tornado May 2013
• Alberta flood (June 2013)
• Catastrophic fire in Arizona July 2013
• Record heat waves in China July August 2013
• Extreme longest drought in Colorado August 2013
• Colorado flood September 2013
• Yosemite fire August 2013
• Australia's hottest 12 consecutive months (again) September 2013
• Drought in USA
• NSW unseasonal devastating spring bushfires September and October 2013
• Super cyclone Phailin hits India October 2013

Not to mention the as yet little discussed Queensland drought

That's just off the top of my head.  You can tell rgbatduke about other non-boring weather in the comments if you like.

Climate is weather

To pre-empt anyone trotting out the obvious, that "weather is not climate" and that it is difficult, but not impossible, to attribute any individual weather event to global warming, let me point out:

Climate is weather

As the weather changes so does the climate.  And the climate is changing.  It's been changing almost everywhere:

Source: IPCC AR5 WG1 Fig ST.2 page TS-82

I'm not claiming all the above are "caused by" global warming.  But I will claim that all weather is affected by global warming.  It has to be.  I will also argue that many of the above-listed events, perhaps all of them, would not have been as extreme if not for global warming.  Some might not have occurred in a cooler world.  And it's still early days...

Rgbatduke is bored at WUWT and reduced to getting it all wrong. Ho hum!

I've added a few more catchy comments! (see below)

---

I suppose it's because he was so bored that he decided to write such a silly comment at WUWT.  Anthony Watts must have been bored too, because he raised rgbatduke's comment to article status.

rgbatduke teaches physics at Duke.  It's easy to tell he knows precious little about climate science.

His comment was very, very long. rgbatduke doesn't believe in pithy and concise.  He doesn't believe in checking facts either. Here is just one little paragraph of many.  Count the wrongs!  (Archived here - updated.)

Let’s face it. The climate has never been more boring. Even the weather blogs trying to toe the party line and promote public panic — I mean “awareness” — of global warming are reduced to reporting one of GISS’s excessive spikes as being “the fourth warmest September on record” while quietly neglecting the fact that in HADCRUT4, RSS and UAH it was nothing of the sort and while even more quietly neglecting the fact that if one goes back a few months the report might have been that June was the fourth coldest in 20 years. Reduced to reporting a carefully cherry-picked fourth warmest event? Ho hum.

GISTemp - Hottest September on record

The fourth warmest September recorded at GISTemp?  Wrong! Actually, at 0.74°C above the 1951-80 mean, it's the equal hottest September on record, with that in 2005.

Data Source: NASA

HadCRUT equal third hottest September on record

I wouldn't say HadCRUT4  was "nothing of the sort".  It came fairly close with September registering as equal third hottest on record at 0.534 above the 1961-90 mean, just pipped at the post by 2005 and 2009.

Data Source: HadCRU

UAH fourth hottest September on record

UAH was next, with September 2013 coming in fourth hottest after 2009, 2010 and 2012.

Data Source: UAH

RSS ninth hottest September on record

The only one where rgbatduke could argue he was right with his "nothing like" comment was RSS, although this September still scraped into the top ten and was the ninth hottest in the record:

Data Source: RSS

It's 112 (or 172) months since the fourth coldest June in twenty years

As for rgbatduke claiming that:

while even more quietly neglecting the fact that if one goes back a few months the report might have been that June was the fourth coldest in 20 years

Well, you'd have to go back 112 months in GISTemp to find the fourth coldest June in 20 years.  It was back in June 2004, with June 1999 equal third coldest with June 1994.  Or if you went by HadCRUT, you'd go back 172 months to June 1999 - just in case you think I'm cherry picking :)

Data Source: NASA

Looks as if rgbatduke is the one who is "reduced to getting it all wrong? Ho hum."  He didn't even bother to check the data, let alone pick cherries!

1,252 months since the coldest June on record

Anonymous in the comments pointed out that rgbatduke cherry-picked 20 years for the coldest June.  If you look at the entire instrumental record, it's 1,252 months (GISTemp) or 1,228 months (HadCRUT) since the coldest June on record.  It's 184 months since the hottest June on record.  1998 was a very hot year!

From the WUWT comments

The comments demonstrate again that WUWT-ers don't have a skeptical bone in their body as long as they can read what they want to believe.  The comments are mostly (boring) content-free adoration from the illiterati - archived here - updated here.

Jim Cripwell says:

November 4, 2013 at 10:09 am
Thank you for writing so well, what I have been trying to say for months.

leon0112 says:

November 4, 2013 at 10:15 am
Dr. Brown,
This is a great article. AR5 includes known ****. It should be cleansed.
Thank you for your well done peer review of AR5.

Lon Hocker misses the big errors and nitpicks little ones and says:

November 4, 2013 at 10:33 am
Great Article. A couple of details, though:
“it will no longer be possible to conceal this fact even from ignorant politicians by 2000 if there is no statistically significant warming by that time.” Did you mean 2020?
“if CAGW is a true hypothesis, them maybe — just maybe —” Should be “then” not “them”

UK Marcus says:

November 4, 2013 at 10:58 am
Thank you Dr. Brown for your elegant and concise summary.
Sometimes Masterly Inactivity is a sensible course of action. When so much is known and so little is changing wrt climate, for some people to try to persuade us that we must immediately alter our way of life is willfully to ignore the facts. We require disinterested science and honest political leadership, not endless propaganda. I’m not holding my breath…
In the meantime, thank goodness for Anthony, WUWT and the world-wide community of commentators here.

lurker, passing through laughing says:

November 4, 2013 at 11:09 am
Yes. CO2 is a trivial player in the climate, if we are to judge by actual evidence.

I had to update the archive because I couldn't pass up this comment from markstoval, who can't believe there is a real person on WUWT who knows even a little bit about climate science.  Or maybe he's amazed that anyone would stand up to richardscourtney.  He says:

November 4, 2013 at 1:18 pm
I have been reading comments here for a long time. I have made only a few comments myself but have read many. There is this one name, “Steven Mosher”, that shows up a lot and I am beginning to think it is a parody account. Does anyone know if this is a real fellow and not a regular playing games just to keep the comments section lively?
TIA, Mark

Here are a couple more

taxed has figured out what causes climate extremes and ice ages, they are caused by stable weather!:

November 4, 2013 at 1:02 pm
l don’t think we should be so quick we welcome boring weather.
Because its when the weather does become stable with little in the way of change over the longer term, is just when you do get extremes in climate.
lts what causes deserts to form, and l also think its what causes ice ages to form when the weather gets locked into a certain pattern

Walt The Physicist accepts without question whatever nonsense and pseudoscience rants he reads at WUWT, but doesn't accept real science.  He fancies himself as a ladies' man too and says:

November 4, 2013 at 12:54 pm

“This really is shocking. Shockingly bad science, shockingly dishonest political manipulation of policy makers on the part of scientists who participated in the creation of AR5 and permitted their names to give the report its weight.”

====================================================================
It is shocking indeed. As I am scientist, frequently laymen and more frequently laywomen ask me at the parties of what is the reason for highly educated scientists and academics to commit such fraud. I have no answer. It would be interesting to know what Dr. Brown as well as this blog participants think. Is this necessity of producing research funding and vain of awards and prizes that drives Mann, Schmidt, Hansen, Caldeira and multitudes others from Center for Climate Risk Management (CLIMA), Center for Solutions to Weather and Climate Risk, Department of Global Ecology, Climate Change Research Center, Climate System Research Center, etc.? Is this dishonesty unique to the climate science, or similar situations are prevailing in all sciences – the proponents of an idea “choke” all competition and the idea finally becomes a dogma supported by fraudulent “science”?

Denier weirdness: The batty duke has gone to pot...

As if a potty peer isn't enough, now Anthony Watts of WUWT is giving space to a batty DuKE**.

Credit: Torben Hansen

Dr. Robert G. Brown, Duke University (elevated from a comment) AKA rgbatduke is today arguing that the greenhouse effect isn't real because marijuana is thought to have medicinal properties.  Or something like that.

If you can't follow his argument, then you're not inhaling deeply enough.  Pass the joint.



**DuKE - a collective noun eg A DuKE of deniers TM Lotharsson.

In the WUWT comments

Nylo says:

August 22, 2013 at 8:10 am  Stephen Abbott says: August 22, 2013 at 7:59 am Anyone who thinks pot was made illegal because two newspaper publishers didn’t want better that better paper from hemp to come onto the market is smoking something.

It’s not THE reason. It’s just how it all started, the original impulse. Similarly, IPCC started because of Margaret Thatcher’s desire to criminalise coal to deal with a domestic problem involving miners strikes. The reason why CO2 is now officially a Devil’s product is not because of the UK miners. That’s just how everything started rolling.

Rud Istvan says:

August 22, 2013 at 8:33 am   As fun as RGB’s post is to read, it is 1/3 truth and 2/3 urban legend living on the Internet on sites advocating legalization. That is the main way it resembles CAGW. A half hour of fact checking easily shows this assessment is directionally correct.

Personally, I think it detracts from the very important and sometimes personal points Dr. curry made about motived climate science reasoning, and the resulting ‘monopolization’ and then ‘corruption’ of some of the underlying essential data, as Anthony’s crowd sourced project has proven. Fighting bad science using bad analogies to motivated urban legends is bad technique.

curryja says:

August 22, 2013 at 8:38 am  Robert, thank you for your hysterically clever post

A Battle of the DuKEs: Climate science deniers are getting all tied up in knots

Rgbatduke (aka Robert G Brown of Duke University aka the DuKE), Monckton, Spencer & Christy and now Willis Eschenbach and WM Briggs having a right old ding-dong battle.  It's another battle of the DuKEs.

Here is where it started, here is a continuation, and then WM Briggs "statistician to the stars" dealt a blow to deniers by saying what Professor Brown wrote was complete and utter nonsense.

This is the latest (h/t Nick Stokes).

"Wondering" Willis Eschenbach told WM Briggs what he thought of his tearing down of Professor Brown's rant.  This is part of what Willis wrote:

I know you’re a great statistician, and you’re one of my heroes … but with all respect, you’ve left out a couple of important priors in your rant ….

1. You assume that the results of the climate model are better than random chance.

2. You assume that the mean of the climate models is better than the individual models.

3. You assume that the climate models are “physics-based”.

As far as I know, none of these has ever been shown to be true for climate models. If they have, please provide citations.

As a result, taking an average of climate models is much like taking an average of gypsy fortunetellers … and surely you would not argue that the average and standard deviation of their forecasts is meaningful.

(Odd that Wondering Willis doesn't know that "climate models" are based on physics - or at least the ones I believe he's referring to are.)

Robert G Brown is embarrassingly wrong...wronger than televised wrestling

Here are some excerpts from WM Briggs' response to Willis.  This is about as big a slap down as one climate science denier (WM Briggs) can give to two others (Willis and the DuKE) and probably bigger than a science denier would give to a scientist (my bold):

1. Do ensemble models make statistical sense in theory?

Yes. Brown said no and wanted to slap somebody, God knows who, for believing they did and for creating a version of an ensemble forecast. He called such practice “horrendous.” Brown is wrong. What he said was false. As in not right. As is not even close to being right. As is severely, embarrassingly wrong. As in wrong in such a way that not one of his statistical statements could be repaired. As in just plain wrong. In other words, and to be precise, Brown is wrong. He has no idea of which he speaks. The passage you quote from him is wronger than Joe Biden’s hair plugs. It is wronger than Napoleon marching on Moscow. It is wronger than televised wrestling....

...3. A model does not have to explain the physics to be good.

Stop and re-read that before continuing.

Poor Wondering Willis.  He probably won't know what hit him.

The rigorous statistics of "it looks like"...

Now let's go back to WM Brigg's point 2. He wrote (my bold):

2. Are the ensemble climate models good? As I said originally, not for long-range predictions, but yes for very short-range ones. If Brown wants to claim long-range models are poor, even useless, then I am his brother. But if he wants to say that they do not make statistical sense, then I am his enemy. Being “good” and making “statistical sense” are different and no power in Heaven or on Earth can make them the same.

I tried to find where WM Briggs said anything about "long range predictions vs short range predictions" in his original article and its updates.  About the closest I could find was this:

TWO Are the ensemble models used in climate forecasts any good? They don’t seem to be; not for longer-range predictions (and don’t forget that ensembles can have just one member). Some climate model forecasts—those for a few months ahead—seem to have skill, i.e. they are good. Why deny the obvious? The multi-year ones look like they’re too hot.

Well, that's weird.  WM Briggs argues at length based on "statistics" but then dismisses climate models because "it looks like they're too hot".  That doesn't sound to rigourous an assessment, does it.  And he talks about climate model forecasts of  "a few months ahead".  I don't know of any such climate model forecasts.  Climate models by definition model climate, not a few months of weather.

The "short-termism" of climate science denial

This is how WM Briggs is wrong.  He said that ensemble climate models are good for short range predictions.  But climate models model climate, not "short range predictions".  Climate is long range, not short range.  Climate models do not make any claim of being "right" in the short term.  That is, the noise of weather dominates in the short term.  In the short term, the noise masks the signal.  What the models are designed for is to help understand what the various elements of the earth system will be like over coming decades to centuries, not over the coming days, weeks or months.  As noted on realclimate.org:

Short term (15 years or less) trends in global temperature are not usefully predictable as a function of current forcings. 

Fifteen years or less!  Not "a few months', not even "a few years".  It would be fair to say there is more difference between models and model runs on a daily or weekly basis than there is on a longer term basis.  This is an extract from the full comment from the article on RealClimate.org (my bold):

In interpreting this information, please note the following (mostly repeated from previous years):

• Short term (15 years or less) trends in global temperature are not usefully predictable as a function of current forcings. This means you can’t use such short periods to ‘prove’ that global warming has or hasn’t stopped, or that we are really cooling despite this being the warmest decade in centuries. We discussed this more extensively here.
• The CMIP3 model simulations were an ‘ensemble of opportunity’ and vary substantially among themselves with the forcings imposed, the magnitude of the internal variability and of course, the sensitivity. Thus while they do span a large range of possible situations, the average of these simulations is not ‘truth’.
• The model simulations use observed forcings up until 2000 (or 2003 in a couple of cases) and use a business-as-usual scenario subsequently (A1B). The models are not tuned to temperature trends pre-2000.
• Differences between the temperature anomaly products is related to: different selections of input data, different methods for assessing urban heating effects, and (most important) different methodologies for estimating temperatures in data-poor regions like the Arctic. GISTEMP assumes that the Arctic is warming as fast as the stations around the Arctic, while HadCRUT4 and NCDC assume the Arctic is warming as fast as the global mean. The former assumption is more in line with the sea ice results and independent measures from buoys and the reanalysis products.
• Model-data comparisons are best when the metric being compared is calculated the same way in both the models and data. In the comparisons here, that isn’t quite true (mainly related to spatial coverage), and so this adds a little extra structural uncertainty to any conclusions one might draw.

There is a paper by Santer et al (often misquoted by deniers) in which it is found that to determine a change in climate based solely on trends in global surface temperature generally requires multiple decades, not months or years.  In their analysis, a period of 32 years yielded a clear signal over the noise.  In the abstract they maintain you need at least 17 years.  This is from the paper's conclusion (my bold):

The clear message from our signal-to-noise analysis is that multi-decadal records are required for identifying human effects on tropospheric temperature. Minimal warming over a single decade does not disprove the existence of a slowly-evolving anthropogenic warming signal.

From what I have read, all current climate models project these (among other things) over the longer term to varying degrees depending on the emissions scenario:

• Average global surface temperature will rise
• Sea level will continue to increase
• Ice will continue to melt - including Arctic sea ice and the worlds glaciers and ice sheets.

You can see this in the latest annual update on realclimate.org, which looks at the extent to which models are getting it right.  

For example, here are the projections from the IPCC AR4 report, that shows the models are intended to project climate, not short term weather, looking ahead one hundred years or so:

Source: IPCC AR4 WGI

And looking ahead several centuries to a millenium:

Source: IPCC AR4 WGI

Climate science deniers ignore what is "right" about the models.  They all show surface temperature continuing to rise, for example.  And they estimate the expected rise within a specified range for explicit scenarios of future emissions.  They can provide explicit estimates of climate sensitivity and transient climate response - within a range.

(And just in case there is anyone who thinks the world has stopped warming, check this out before you go making as big a fool of yourself as the DuKE, WM Briggs and Wondering Willis.)  

Denier models are very short term and embarrassingly wrong

Denier "models" on the other hand, tend to the short term and "project" weird and silly stuff like this, from David Archibald.  His "model" projects that before seven years is out, by 2020, the average surface temperature will have dropped below the lowest temperature in the entire Holocene:

Why deniers deny science...

It's enlightening watching the deniers fight it out among themselves.  They all bring their own "wrong" to the table.  One thing many of them have in common is embodied in this comment from DAV on WM Brigg's blog (my bold):

Policymakers are relying on these models to represent the RANGE of possible future climates that are consistent with known physics and chemistry.

To do what, exactly? Are they making preparations or just looking for a revenue source?

The thing many climate science deniers have in common is an unwillingness to accept that the deleterious affects of climate change carry a cost.  That will apply regardless of whether we do nothing or do something beforehand (like shifting to clean energy) or wait till after the damage is done (like paying flood levies to repair broken infrastructure).

PS We can add Judith Curry to the list of deniers promoting the DuKE from Duke's rubbish.  She aligns herself with the denialiati every chance she gets.  (No link from me this time.  I can't usually be bothered with Curry tripe, with some exceptions like here and here and here and here.)

PPS (23 June 2013)  Looks as if WM Briggs is trying to backtrack from his comment about short term climate models by saying he meant the models used for weather forecasting and seasonal outlooks.  I know they are called "climate" models too, although they model weather, not climate.  And they are constantly updated with real data through data assimilation unlike the climate models rgbatduke was writing about.  So this "fervent, ill-educated activist" is sticking to her guns.  WM Briggs was wrong, plain and simple in what he said.  His article was in relation to IPCC models, which are a somewhat different beast, used for a different purpose and having different features.  The climate models being discussed here are built to learn about climate not to forecast weather.

A DuKE** goes to town at WUWT

A physics lecturer from Duke University, rgbatduke (see DuKE** below) aka Robert G Brown, has been writing for Anthony Watts on WUWT about how he, a humble physics teacher, knows more about climate science and climate modelling than anyone else in the world.  It doesn't seem to bother him that he has never published anything more than a blog article on the topic.  I commented earlier that he was not familiar with the IPCC reports and this little lecture he's giving to climate specialists plainly illustrates he's not, and that he knows probably less than nothing about climate or climate models.

Spaghetti graphs

Here is some of what he wrote initially:

This is reflected in the graphs Monckton publishes above, where the AR5 trend line is the average over all of these models and in spite of the number of contributors the variance of the models is huge. It is also clearly evident if one publishes a “spaghetti graph” of the individual model projections (as Roy Spencer recently did in another thread) — it looks like the frayed end of a rope, not like a coherent spread around some physics supported result.

My comment - those frayed ends of rope represent the noise in the climate.  It's caused by weather as well as differences between the models.  Weather has the properties of chaos.  Climate is all about boundaries that mark expected weather ranges and extremes.  Climate change is all about trends.  I don't think there are any spaghetti charts in the IPCC report, but I could be wrong.

Mean, standard deviation and variance

Now back to rgbatduke.  Take note of the bold section, we'll come back to that later:

Note the implicit swindle in this graph — by forming a mean and standard deviation over model projections and then using the mean as a “most likely” projection and the variance as representative of the range of the error, one is treating the differences between the models as if they are uncorrelated random variates causing >deviation around a true mean!.

Say what?...

...What I’m trying to say is that the variance and mean of the “ensemble” of models is completely meaningless, statistically because the inputs do not possess the most basic properties required for a meaningful interpretation. They are not independent, their differences are not based on a random distribution of errors, there is no reason whatsoever to believe that the errors or differences are unbiased (given that the only way humans can generate unbiased anything is through the use of e.g. dice or other objectively random instruments).

The DuKE doesn't like chaos - too messy

You'll probably groan reading this next bit.  Rgbatduke seems to want a nice, neat straight line chart with no chaotic properties.  Look at how he proposed to get it:

...First of all, we could stop pretending that “ensemble” mean and variance have any meaning whatsoever bynot computing them. Why compute a number that has no meaning? Second, we could take the actual climate record from some “epoch starting point” — one that does not matter in the long run, and we’ll have to continue the comparison for the long run because in any short run from any starting point noise of a variety of sorts will obscure systematic errors — and we can just compare reality to the models. We can then sort out the models by putting (say) all but the top five or so into a “failed” bin and stop including them in any sort of analysis or policy decisioning whatsoever unless or until they start to actually agree with reality.

Modellers - pick the winners then sit around and wait for 30 years or so ...  

Then real scientists might contemplate sitting down with those five winners and meditate upon what makes them winners — what makes them come out the closest to reality — and see if they could figure out ways of making them work even better. For example, if they are egregiously high and diverging from the empirical data, one might consider adding previously omitted physics, semi-empirical or heuristic corrections, or adjusting input parameters to improve the fit.

Then comes the hard part. Waiting. ...So one has to wait and see if one’s model, adjusted and improved to better fit the past up to the present, actually has any predictive value....

My comment: I can't really see all the scientists sitting around for thirty years fiddling their thumbs while they wait to see how well their top five winners worked out.  Whether they actually had any predictive value.

...It would take me, in my comparative ignorance, around five minutes to throw out all but the best 10% of the GCMs (which are still diverging from the empirical data, but arguably are well within the expected fluctuation range on the DATA side), sort the remainder into top-half models that should probably be kept around and possibly improved, and bottom half models whose continued use I would defund as a waste of time. That wouldn’t make them actually disappear, of course, only mothball them. If the future climate ever magically popped back up to agree with them, it is a matter of a few seconds to retrieve them from the archives and put them back into use.

It's warmed by magic

The above is more evidence that he's talking through his hat.  But there's more.  He's now attributing the warming "since the LIA" to magic from the look of things - no forcing required.  Is climate just a bouncing ball?

Of course if one does this, the GCM predicted climate sensitivity plunges from the totally statistically fraudulent 2.5 C/century to a far more plausible and still possibly wrong ~1 C/century, which — surprise — more or less continues the post-LIA warming trend with a small possible anthropogenic contribution. This large a change would bring out pitchforks and torches as people realize just how badly they’ve been used by a small group of scientists and politicians, how much they are the victims of indefensible abuse of statistics to average in the terrible with the merely poor as if they are all equally likely to be true with randomly distributed differences.

Compare what the DuKE** wrote with what really happens

Sorry, got a bit carried away with his nonsense.  Let's get back to basics.  What rgbatduke is saying up front is that the IPCC reports "a mean and standard deviation over model projections and then using the mean as a “most likely” projection and the variance as representative of the range of the error."

We saw in my previous article that the mean is not necessarily presented as the "most likely" projection.


In the comments, here is what he changed it to, sans links:

Second, to address Nick Stokes in particular (again) and put it on the record in this discussion as well, the AR4 Summary for Policy Makers doesexactly what I discuss above. Figure 1.4 in the unpublished AR5 appears poised to do exactly the same thing once again, turn an average of ensemble results, and standard deviations of the ensemble average into explicit predictions for policy makers regarding probable ranges of warming under various emission scenarios.

We've already seen that he's wrong about the AR4 Summary for Policy Makers.  I posted the chart in my previous article, but if you want to check for yourself, go here.  The model ensemble means are shown but the "best estimate" for each scenario at 2100 is not the model mean.  And the ranges aren't simple standard deviations or variance. As for "poised to do" - well AR5 isn't out yet.  However, the caption to figure 11.33 in the draft was provided at WUWT and once again it shows rgbatduke is wrong, it demonstrates that standard deviations of the ensemble average are NOT used for predictions at all, let alone explicit predictions.

This is not a matter of discussion about whether it is Monckton who is at fault for computing an R-value or p-value from the mish-mosh of climate results and comparing the result to the actual climate — this is, actually, wrong and yes, it is wrong for the same reasons I discuss above, because there is no reason to think that the central limit theorem and by inheritance the error function or other normal-derived estimates of probability will have the slightest relevance to any of the climate models, let alone all of them together. One can at best take any given GCM run and compare it to the actual data, or take an ensemble of Monte Carlo inputs and develop many runs and look at the spread of results and compare THAT to the actual data.

Does he seriously think that climate modellers don't hindcast?  Don't refine the models?

Here is the most relevant chart from IPCC AR4 Working Group I:

Figure 10.4. Multi-model means of surface warming (relative to 1980–1999) for the scenarios A2, A1B and B1, shown as continuations of the 20th-century simulation. Values beyond 2100 are for the stabilisation scenarios (see Section 10.7). Linear trends from the corresponding control runs have been removed from these time series. Lines show the multi-model means, shading denotes the ±1 standard deviation range of individual model annual means. Discontinuities between different periods have no physical meaning and are caused by the fact that the number of models that have run a given scenario is different for each period and scenario, as indicated by the coloured numbers given for each period and scenario at the bottom of the panel. For the same reason, uncertainty across scenarios should not be interpreted from this figure (see Section 10.5.4.6 for uncertainty estimates).

Here the comparison again:

rgbatduke version 1 he talks of the variance and the mean of the ensemble:

the variance and mean of the “ensemble” of models is completely meaningless, statistically

rgbatduke version 2, so now he shifts to looser terminology, talking average not mean, but talks of standard deviation of the ensemble average

an average of ensemble results, and standard deviations of the ensemble average into explicit predictions

What the IPCC actually did previously (link)

Lines show the multi-model means, shading denotes the ±1 standard deviation range of individual model annual means.

So - the IPCC figures don't show what rgbatduke said they do.  The IPCC projections show multi-model means with the +/-1 standard deviation range of individual model annual means, NOT as rgbatduke wrote, standard deviation of the ensemble average.  

Moreover the report cautions against using the above chart to interpret uncertainty.  WGI has a separate section discussing and quantifying uncertainty / likely ranges and a box discussing equilibrium climate sensitivity (where they use the mode as the best estimate).  In addition there is a section describing the projected global temperature with probability ranges, which are not a simple standard deviation or variance from the mean. There is a very complicated box diagram showing the mean, the likely ranges and the ranges using different models and different approaches to uncertainty.  If rgbatduke had bothered to glance at the IPCC report he might have seen that.  

I don't usually nitpick like this, but rgbatduke is so vocal and rude in his pronouncements that I figure he deserves it.

Means are more accurate, biases cancel out, means reduce noise

More from the IPCC:

Following the TAR, means across the multi-model ensemble are used to illustrate representative changes. Means are able to simulate the contemporary climate more accurately than individual models, due to biases tending to compensate each other (Phillips and Gleckler, 2006). It is anticipated that this holds for changes in climate also (Chapter 9). ...The use of means has the additional advantage of reducing the ‘noise’ associated with internal or unforced variability in the simulations. Models are equally weighted here, but other options are noted in Section 10.5.

Now I don't know if they will be taking the same approach in AR5.  There has been more work on models and projections since 2007.  For example in this 2010 paper, Knutti et al write:

An average of models compares better to observations than a single model, but the correlation between biases among CMIP3 GCMs makes the averaging less effective at canceling errors than one would assume. For present-day surface temperature, for example, a large fraction of the biases would remain even for an infinite number of models of the same quality. Extreme biases tend to disappear less quickly than smaller biases. Thus, models are dependent and share biases, and the assumption of independence made in some studies is likely to lead to overconfidence, if the uncertainty is measured by the standard error of the ensemble means (inversely proportional to the square root of the ensemble size). Quantitative methods to combine models and to estimate uncertainty are still in their infancy....

...The overconfidence achieved by improper weighting may well be more damaging than the loss of information by equal weighting or no aggregation at all. As long as there is no consensus on how to properly produce probabilistic projections, the published methods should be used to explore the consequences arising from different specifications of uncertainty....

...However, there is some danger of not sampling the extreme ends of the plausible range with a few cases...

There will be hell to pay

I don't think any climate scientist will be quivering in her high-heeled shoes after reading this little rant from rgbatduke.  Or maybe she will, from laughter.

I make this point to put the writers of the Summary for Policy Makers for AR5 that if they repeat the egregious error made in AR4 and make any claims whatsoever for the predictive power of the spaghetti snarl of GCM computations, if they use the terms “mean and standard deviation” of an ensemble of GCM predictions, if they attempt to transform those terms into some sort of statement of probability of various future outcomes for the climate based on the collective behavior of the GCMs, there will be hell to pay, because GCM results are not iid samples drawn from a fixed distribution, thereby fail to satisfy the elementary axioms of statistics and render both mean behavior and standard deviation of mean behavior over the “space” of perturbations of model types and input data utterly meaningless as far as having any sort of theory-supported predictive force in the real world. Literally meaningless. Without meaning.

So 'literally meaningless' = 'without meaning'.  Luckily he translates that for us or we'd never have been able to figure out what he meant. Wait, there's more:

If any of the individuals who helped to actually write this summary would like to come forward and explain in detail how they derived the probability ranges that make it so easy for the policy makers to understand how likely to certain it is that we are en route to catastrophe, they should feel free to do so.

Why call for "individuals" on a crappy blog like WUWT?  What climate modeller is going to visit there or read his pontificating.  Far better to go and look for himself.  Maybe he could start with the IPCC report, and read the notation under the charts that show uncertainty.  Or he could visit HotWhopper because I've added the links to the papers themselves:

The 5 to 95% ranges (vertical lines) and medians (circles) are shown from probabilistic methods (Wigley and Raper, 2001; Stott and Kettleborough, 2002; Knutti et al., 2003; Furrer et al., 2007; Harris et al., 2006; Stott et al., 2006b).

And a couple more since then to get him started, and it looks as if there are more papers focusing on regional projections, not just global projections now.

Knutti et al (2010) Challenges in Combining Projections from Multiple Climate Models (that I quoted from above).

Mikhail A. Semenov, Pierre Stratonovitch (2010) Use of multi-model ensembles from global climate models for assessment of climate change impacts

CMIP5 portal

Suggestions for rbgatduke

My article probably has some errors too.  Please excuse me, I'm not a climate scientist or a climate modeller.  I'm going to quit here though I feel I should double check what I've written, I'll let people do that in the comments if they want to.  For a little snark blog I've spent way too much time on this :D   But if you think this article is long, you should see all the bits of rbgatdukes two rants that I didn't include - here and here.

For now, I'll just make some final suggestions for the DuKE from Duke.

1. Learn how to do a literature search

Someone ought to show rgbatduke where the library is and maybe a kind librarian will show him how to use one of the various scholarly search engines.  If he still has trouble he could always ask someone to show him how to use Google Scholar like non-academic bloggers do.

2. Read the latest IPCC report

There are good sections on climate, weather, climate models and all sorts of related information that might help him avoid looking like a goose next time he lectures specialists outside his own field.

3. Read, read, read and observe

Read up on climate science wherever he can.  Tell him to visit realclimate.org and read the archives.  Suggest he not pipe up with a comment until he learns something about climate or with his style and attitude he'll be given short shrift and his comments confined to the bore hole.  If he finds realclimate too sciency, suggest skepticalscience.com.  There is a heap of information that even a physics teacher might understand.  And loads of references if they aren't beyond his capability.

4. Stick to teaching physics

If he finds the above too much to cope with, politely suggest that he stick to teaching physics and leave the research to the experts.

Footnote:

WM Briggs has written some stuff about rgbatduke's rant.  I don't think Dr Brown will be too pleased.  h/t Nick Stokes.

---

**DuKE = collective noun for a group of deniers

Anthony Watts attacks Christy, Spencer and Monckton

How Anthony Watts and rgbatduke attempt to expose the chicanery of Christy, Spencer and Monckton

Anthony Watts puts up an article slamming the chart of Roy Spencer and John Christie and Christopher Monckton's charts all in a few words.  All his commenters agree they are nonsense.  They've run out of arguments against "warmists" so now they are attacking each other.  Good to see.

Here's the slam from rgbatduke:

This is reflected in the graphs Monckton publishes above (Sou: see below), where the AR5 trend line is the average over all of these models and in spite of the number of contributors the variance of the models is huge. It is also clearly evident if one publishes a “spaghetti graph” of the individual model projections (as Roy Spencer recently did in another thread) — it looks like the frayed end of a rope, not like a coherent spread around some physics supported result.

Note the implicit swindle in this graph (Sou: he is referring to Monckton's chart as shown below) — by forming a mean and standard deviation over model projections and then using the mean as a “most likely” projection and the variance as representative of the range of the error, one (Sou: ie Monckton) is treating the differences between the models as if they are uncorrelated random variates causing >deviation around a true mean!.

Say what?

I kind of like they way rgbatduke wishes climate behaved the way a single particle behaves in a laboratory-controlled physics experiment.  If only.  (By the way, I'm not twisting this in any way.  rgbatduke is referring directly to the workings of Christy, Spencer and Monckton.  He may think he's criticising the IPCC but they are not IPCC charts.  It's not the IPCC that used the data that way.  It's only Christy, Spencer and Monckton who did the charts and calculations in the way they did.)

The rest of his article reads as if it's written by a person (maybe a physicist) who doesn't know anything about climate science.  rgbatduke says as much, admitting his "comparative ignorance".  It comes across as the logical fallacy of personal incredulity.


Anyway, here are some reactions:

Ian W says:
June 18, 2013 at 5:24 pm  An excellent post – it would be assisted if it had Viscount Monckton’s and Roy Spencer’s graphs displayed with references.

mark says:
June 18, 2013 at 5:43 pm damn. just damn.

Chuck Nolan says:
June 18, 2013 at 6:02 pm I believe you’re correct. I’m not smart enough to know if what you are saying is true, but I like your logic.  Posting this on WUWT tells me you are not afraid of critique. Everyone knows nobody gets away with bad science or math here.

Abe says:
June 18, 2013 at 6:04 pm WINNER!!!!!  The vast majority of what you said went WAY over my head, but the notion of averaging models for stats as if they were actual data being totally wrong I totally agree.

Rob Ricket says:
June 18, 2013 at 8:03 pm  What a brilliant application of scientific logic in exposing the futility of attempting to prognosticate the future with inadequate tools. It takes a measure of moral courage to expose fellow academics as morally bankrupt infants bumbling about in a dank universe of deception. Bravo!

Jeef says:
June 18, 2013 at 7:32 pm  That. Is. Brilliant.  Thank you.

Only a couple of people seemed to understand what rgbatduke wrote.  

Once again, Nick Stokes asks some pertinent questions (my bold):
June 18, 2013 at 6:22 pm  As I said on the other thread, what is lacking here is a proper reference. Who does this? Where? “Whoever it was that assembled the graph” is actually Lord Monckton. But I don’t think even that graph has most of these sins, and certainly the AR5 graph cited with it does not. Where in the AR5 do they make use of ‘the variance and mean of the “ensemble” of models’?

Monckton pops in and thanks Nick Stokes for being gracious and coming to his defense.  

No, that's not what he does.  Monckton calls Nick Stokes a liar and a troll and and then goes on to say he did exactly what Nick Stokes and rgbatduke said he did. He writes: "in my own graph I merely represented the interval of projections encompassed by the spaghetti graph and added a line to represent the IPCC’s central projection."  That's precisely what rgbatduke was referring to when he originally wrote in reference to Monckton's chart, of the:

"implicit swindle in this graph — by forming a mean and standard deviation over model projections and then using the mean as a “most likely” projection and the variance as representative of the range of the error, one is treating the differences between the models as if they are uncorrelated random variates causing >deviation around a true mean!"

Monckton somehow "forgets" to mention the variance he shows on his chart (see below).

Monckton also admits to using a confidential draft AR5 chart, which if he was an expert reviewer he pledged to keep confidential.  The AR5 chart itself has errors AFAIK and the public version will no doubt be different.

Monckton shows his lack of moral fibre and his lack of grace.  His behaviour shows he is not an upright citizen, an honest man of his word or a gentleman.  Monckton is a bombastic ignorant fool who has lost his entertainment value.  I've noticed that some people who are in the wrong are incapable of admitting it, and have a tendency to get very aggro.  As if they think it will fool anyone but other fools.  Monckton also has a very compartmentalised brain. It holds his lies and truths in different compartments but he can spout either or both at the same time, usually mixed with his misplaced self-righteous venom.

A final mention to Tsk Tsk who observes the strawman (my bold):

June 18, 2013 at 7:01 pm  Brown raises a potentially valid point about the statistical analysis of the ensemble, but his carbon atom comparison risks venturing into strawman territory. If he’s claiming that much of the variance amongst the models is driven by the actual sophistication of the physics that each incorporates, then he should provide a bit more evidence to support that conclusion.

Here are the charts prepared by Christy, Spencer and Monckton that so offended rgbatduke, all the WUWT deniers and Anthony Watts, but which they are only now saying so.

Spencer and Christy's Spaghetti

Monckton's Swindle

Here are my previous articles on:

• Spencer and Christy's exercise
• Monckton's diatribe

Here is a figure from the 2007 IPCC report - Summary for Policy Makers. The left panel is emission scenarios, the right panel shows multi-model means of surface temperature for different scenarios. The bars at the right show the "best estimate" surface temperature and likely range for 2090-2099.  The best estimate is not the same as the model means you'll notice. Click to enlarge.

Figure SPM.5. Left Panel: Global GHG emissions (in GtCO2-eq) in the absence of climate policies: six illustrative SRES marker scenarios (coloured lines) and the 80th percentile range of recent scenarios published since SRES (post-SRES) (gray shaded area). Dashed lines show the full range of post-SRES scenarios. The emissions include CO2, CH4, N2O and F-gases. Right Panel: Solid lines are multi-model global averages of surface warming for scenarios A2, A1B and B1, shown as continuations of the 20th-century simulations. These projections also take into account emissions of short-lived GHGs and aerosols. The pink line is not a scenario, but is for Atmosphere-Ocean General Circulation Model (AOGCM) simulations where atmospheric concentrations are held constant at year 2000 values. The bars at the right of the figure indicate the best estimate (solid line within each bar) and the likely range assessed for the six SRES marker scenarios at 2090-2099. All temperatures are relative to the period 1980-1999. {Figures 3.1 and 3.2}