the CEA took a conventional Keynesian-style macroeconomic model and used those set of equations to estimate the effect the stimulus should have had.  Essentially, the model offers an estimate of the policy’s effect, conditional on the model being a correct description of the world.  But notice that this exercise is not really a measurement based on what actually occurred.  Rather, the exercise is premised on the belief that the model is true, so no matter how bad the economy got, the inference is that it would have been even worse without the stimulus.  Why?  Because that is what the model says.  The validity of the model itself is never questioned.

Does this sound like climate science or what?  The same models that are used to predict future temperature increases are used to decide how much of past warming was dues to Co2 and how much was due to natural effects.  Here is the retrospective IPCC chart which assigns more than 100% of post-1950 warming to CO2 (since the blue “natural forcings” is shown to go down, see more here)

Here is the stimulus version, showing flat employment, but positing that the stimulus created jobs because employment “would have gone down without it” (sound familiar?)

This kind of retrospective look at causality has the look of science but in fact is nothing of the sort, and can be not much more than guesses laundered to look like facts.

But this may in fact be worse than guessing.  In both cases, these graphs are drawn by folks who think they know the answer (in the first case that CO2 caused all warming, in the second that the stimulus created millions of jobs).  Since in both cases the lower “without” case (either without CO2 or without stimulus) is horrendously, almost impossible to derive and totally impossible to measure, there is good reason to believe it is merely a plug, fixed in value to get the answer they want.  But if I plugged it just on the back of an envelope, everyone would call me out for it, so I plug it in an arcane model where numerous inputs can be tweaked to get different results, to avoid this kind of unwanted scrutiny.

Readers of climate sites will also recognize this criticism of Obama’s self-serving stimulus analysis

Moreover, the fact that other organizations simulating similar models come to similar conclusions is no evidence about the validity of the model’s simulations.  It only tells you the CEA staff did not commit egregious programming errors when running their computer simulations.

Sounds like the logic behind the hockey stick spaghetti graphs, no?

Again, there almost certainly is a warming trend since 1850, and some of that trend is probably due to manmade CO2, but sensitivities in most forecasts that get attention in the media are way too high.  A tenth of a degree C per decade over the next 100 years from manmade CO2 seems a reasonable planning number.

Spencer also looks at the global numbers here.

Edward Long took a selection of US measurement points from the NCDC master list and chose 48 rural and 48 urban locations (one for each of the lower-48 states).  While I would like to see a test to ensure no cherry-picking went on, his results are pretty telling:

More at Anthony Watt, who has this chart from the study:

The Reference Frame has more analysis as well.

If this data is representative of the whole data set, we see two phenomena that should not be news to readers of this site:

• Inclusion of biased urban data points may be contributing as much as 5/6 of the warming signal in the test period
• The homogenization and adjustment process, which is supposed to statistically correct for biases, seems to be correcting the wrong way, increasing clean sites to matched biased ones rather than vice versa  (something I discussed years ago here)

The homogenization process has always bothered me.  It is probably the best we can do if we don’t know which of two conflicting measurements are likely to be biased, but it makes no sense in this case, as we have a fair amount of confidence the rural location is likely better than the urban.

Let’s say you had two compasses to help you find north, but the compasses are reading incorrectly.  After some investigation, you find that one of the compasses is located next to a strong magnet, which you have good reason to believe is strongly biasing that compass’s readings.  In response, would you

1. Average the results of the two compasses and use this mean to guide you, or
2. Ignore the output of the poorly sited compass and rely solely on the other unbiased compass?

Most of us would quite rationally choose #2.

Most climate data bases go with approach #1.

Let’s remind everyone why this matters:  We are not going to eliminate past warming.  The Earth was at one of its coldest periods in 5000 years through about 1800 and it has gotten warmer since.   The reason it matter is twofold:

• The main argument for anthropogenic causes of warming is that the rise of late (particularly 1978 – 1998)  has been so steep and swift that it couldn’t be anything else.  This was always an absurd argument, because we have at least two periods in the last 150 years prior to most of our fossil fuel combustion where temperature rises were as fast and steep as 1978-1998.  But if temperatures did not rise as much as we thought, this argument is further gutted.
• High sensitivity climate models have always had trouble back-casting history.  Models that predict 5C of warming with a doubling have a difficult time replicating past warming of 0.6C for 40% of a doubling.  If the 0.6C is really 0.3C, then someone might actually raise their hand and observe that the emperor has not clothes – ie, that based on history, high sensitivity models make no sense.

“Well, if it is but a myth, and the global scientific community is involved in some sort of conspiracy, why is it then that around the globe sea levels are more than six inches higher than they were 100 years ago?

“This isn’t an opinion – it is a fact.”

He added: “And, ladies and gentlemen please be in no doubt that the evidence of long-term and potentially irreversible changes to our world is utterly overwhelming.”

Here is the deal with sea levels.  Yes, they were rising in 2009.  And they were rising in 2000.  And they were rising in 1950.  And they were rising in 1900.  And they were rising in 1850.   In fact, sea levels have been rising (due to thermal expansion of water and perhaps some melting land ice**) since the end of the little ice age  (and longer, see WUWT)

In fact, I would argue that this extended sea level rise helps disprove, rather than prove, the strong anthropogenic hypothesis.   The influence of manmade CO2 had to be small from 1850 to 1900 or even 1950.  Therefore, for the 1950-2000 sea level rise to be due to man, it means the natural warming had to stop at the exact same moment that anthropogenic effects took over.  Occam’s Razor says a better answer is that the end of the little ice age around 1800 has led to a general recovery of temperatures ever since.  We see the exact same pattern in glaciers melting

So many people are obsessed over whether or not current temperatures are the highest in the last 100o years or not, they forget that the temperatures in the little ice age were in fact lower than at any time in perhaps the last 5000 years.  It was very cold.

Postscript: By the way, I love the carbon footprint for me, but not for thee angle of the Prince Charles story:

Charles spoke after arriving in Manchester by Royal Train pulled by a coal-fired steam locomotive, named the Tornado, which was rebuilt from a 1948 design.

** Footnote: We know glaciers around the world have retreated since 1850, as shown above, but 90% of the world’s land ice is in Antarctica and we don’t fully understand what has happened there.  Some climatologists believe that warming weather actually increases the ice pack in Antarctica because it never will cause much melting but it increases  snowfall.

The paper was based on a test of a widely-used climate model on the mid-Pleiocene warm period, 3 million years ago, when the Earth warmed in response to natural processes. Cores drilled from ocean sediment provide some evidence for atmospheric carbon levels and temperature at the time.

The team found that at that era, although CO2 levels were close to today’s 388 parts per million by volume, global temperature was 3 C° (5.5 F°) warmer than today. The paper assumes – without evidence – that the difference can only be fully explained by the long-term loss of ice sheets and changes in vegetation that caused the Earth’s surface to absorb more solar radiation. One of the authors said that today’s CO2 concentration of 388 ppmv might already be too high to prevent more than 2 C° (3.5 F°) of warming compared with pre-industrial times – the limit agreed as an aspiration by the recent Copenhagen accord.

The authors are concluding that there is therefore another 3C of warming we should see over time due to our current CO2 levels that has just not showed up yet because slow-response-time feedbacks like ice melting / albedo changes haven’t fully come into play.

I presume you see the problem.  This conclusion can only be drawn if either

1.  We know the value of every other climate forcing that was in play 3 million years ago, and know them to be identical to their values today, such that the only changed variable in the temperature system between then and now is CO2.  Of course, this is absurd — we can’t possibly know all the other forcings from 3 million years ago (we argue about what they are today) and there is a very low probability they were all of the same value as today to set up a nice controlled experiment.  – OR -

2.  We assume that the only major driver of climate, the one that dominates and makes all others irrelevant, is CO2.  This is not only not proven, it is not even reasonably true.

These guys, as is so often the case in climate, are assuming their conclusion.  “If we assume that CO2 is the primary driver of climate, then sensitivity of the climate to CO2 is high.”  Duh.

June 4, 2003 Briffa to Cook 1054748574
On June 4, 2003, Briffa, apparently acting as editor (presumably for Holocene), contacted his friend Ed Cook of Lamont-Doherty in the U.S. who was acting as a reviewer telling him that “confidentially” he needed a “hard and if required extensive case for rejecting”, in the process advising Cook of the identity and recommendation of the other reviewer. There are obviously many issues involved in the following as an editor instruction:

From: Keith Briffa
To: Edward Cook
Subject: Re: Review- confidential REALLY URGENT
Date: Wed Jun 4 13:42:54 2003

I am really sorry but I have to nag about that review – Confidentially I now need a hard and if required extensive case for rejecting - to support Dave Stahle’s and really as soon as you can. Please
Keith

Cook to Briffa, June 4, 2003
In a reply the same day, Cook told Briffa about a review for Journal of Agricultural, Biological, and Environmental Sciences of a paper which, if not rejected, could “really do some damage”. Cook goes on to say that it is an “ugly” paper to review because it is “rather mathematical” and it “won’t be easy to dismiss out of hand as the math appears to be correct theoretically”. Here is the complete email:

Hi Keith,
Okay, today. Promise! Now something to ask from you. Actually somewhat important too. I got a paper to review (submitted to the Journal of Agricultural, Biological, and Environmental Sciences), written by a Korean guy and someone from Berkeley, that claims that the method of reconstruction that we use in dendroclimatology (reverse regression) is wrong, biased, lousy, horrible, etc. They use your Tornetrask recon as the main whipping boy. I have a file that you gave me in 1993 that comes from your 1992 paper. Below is part of that file. Is this the right one? Also, is it possible to resurrect the column headings? I would like to play with it in an effort to refute their claims. If published as is, this paper could really do some damage. It is also an ugly paper to review because it is rather mathematical, with a lot of Box-Jenkins stuff in it. It won’t be easy to dismiss out of hand as the math appears to be correct theoretically, but it suffers from the classic problem of pointing out theoretical deficiencies, without showing that their improved inverse regression method is actually better in a practical sense. So they do lots of monte carlo stuff that shows the superiority of their method and the deficiencies of our way of doing things, but NEVER actually show how their method would change the Tornetrask reconstruction from what you produced. Your assistance here is greatly appreciated. Otherwise, I will let Tornetrask sink into the melting permafrost of northern Sweden (just kidding of course).
Cheers,
Ed

A couple of observations

1. For guys who supposedly represent the consensus science of tens of thousands of scientists, these guys sure have a bunker mentality
2. I would love an explanation of how math can have theoretical deficiencies but be better in a practical sense.  In the practical sense of … giving the answer one wants?
3. The general whitewash answer to all the FOIA obstructionism is that these are scientists doing important work not to be bothered by nutcases trying to waste their time.  But here is exactly the hypocrisy:  The email author says that some third party’s study is deficient because he can’t demonstrate how his mathematical approach might change the answer the hockey team is getting.  But no third party can do this because the hockey team won’t release the data needed for replication.  This kind of data – to check the mathematical methodologies behind the hockey stick regressions – is exactly what Steve McIntyre et al have been trying to get.  Ed Cook is explaining here, effectively, why release of this data is indeed important
4. At the very same time these guys are saying to the world not to listen to critics because they are not peer-reviewed, they are working as hard as they can back-channel to keep their critics out of peer-reviewed literature they control.
5. For years I have said that one problem with the hockey team is not just that the team is insular, but he reviewers of their work are the same guys doing the work.  And now we see that these same guys are asked to review the critics of their work.

Only 25 months after a similar chart was shown on this site (and here).

Note: Box, et al in 2009 claim to have found from 1-1.5C of warming since around 1900 when this chart leaves off.  It is very, very , very dangerous to splice data sets together, but one probably has to add a degree or so to the tail of the chart to bring it up to date, putting current warming about at the Medieval level but below earlier Holocene temperatures.

Gavin [Schmidt],

In your opinion, what percentage of global warming is due to human causes vs. natural causes?

[Response: Over the last 40 or so years, natural drivers would have caused cooling, and so the warming there has been (and some) is caused by a combination of human drivers and some degree of internal variability. I would judge the maximum amplitude of the internal variability to be roughly 0.1 deg C over that time period, and so given the warming of ~0.5 deg C, I'd say somewhere between 80 to 120% of the warming. Slightly larger range if you want a large range for the internal stuff. - gavin]

This is a complete bluff.  There is no way he or anyone else knows this.  I could reverse his numbers and say 0-20% for CO2 and have just as much justification (actually more, see below).  We have devised no good way to parse the temperature changes into any reliable division between various drivers given the complexity of climate.  The only way climate scientists claim to do it is with their highly flawed temperature models, which is a fit of hubris that is unfathomable.

But, beyond the fact that he simply can’t know the answer, his guess here is just awful.  It does not reality check at all.   Here are a few pointers:

1.  Over the last 40 years, or at least over the portion from 1975-1995 when we saw most of the temperature increase, the sun was at its most active this century, as measured by sunspot numbers.  The PDO, which has close links to temperature, was in its warm cycle.  We likely were continuing to see long-term cyclical recovery from the little ice age.  And anthropogenic land use changes were increasing both urban and rural temperatures.  But he claims that the net effect of non-CO2 factors would have been negative?  This is roughly equivalent to Obama’s jobs claims numbers, saying that he saved jobs that would otherwise have been lost.  It’s appeal is that it makes a useful political point while being impossible to prove.

2.  Hansen is basically repeating the IPCC position that there could be no possible natural explanation for the the 0.2C per decade temperature increases from 1975-2000  — ie that such a pace of temperature increase has to be due to CO2 alone (80-120% in my mind equates to CO2 alone).  But world temperatures increased from 1910 to 1940 by 0.2C per decade, in a period almost certainly only minimally influenced by CO2  (see below).  So natural effects can cause warming in the 1930’s but not in the 1980’s because, why?

I often use this chart with audiences:

3.  I am positive that Hansen would argue that natural effects are currently (and temporarily) canceling out some of the warming.  He would say this as a way to deflect criticism that the world has stopped warming over the last decade (something the CRU emails admit they don’t understand, though they won’t admit this publicly**).  But Hansen et al. think we should be seeing 0.2C a decade or more in CO2 warming that is apparently being overcome by natural effects.  So natural effects have enough variability to cancel out 0.2C of warming but not enough to cause 0.2C of warming?  Huh?

This is sort of a special theme this week on this blog, as the topic keeps coming up.  In short, climate scientists need the climate to be alternately sensitive and insensitive, unstable and stable, driven by nature and not driven by nature, all depending on the period they are trying to explain.   All these wildly contradictory assumptions are required to try to keep the hypothesis of very high sensitivities to CO2 alive.

Here, by the way, was my attempt to explain the last 100 years of temperature with a cyclical wave plus a small linear trend:

Not bad, huh?  Here is a similar analysis using a linear trend plus the PDO

My answer seems at least as plausible as Gavin’s.  Here is where I did this analysis in more depth. If I really had an official climate scientist decoder ring, I would blame the gap between measured temperatures and my simplified model in orange during the 1980’s on aerosols.  I don’t know how much if any they affect the climate, but neither do climate scientists and that does not stop them from using it as the universal model plug to improve historic correlations.

By the way, for reference, here is the sunspot cycle:

Here is the world temperature graph overlayed with the PDO

And finally here is some evidence (from ice core analysis) that we may just still be recovering from a period that could well have been the coldest period in the last 5000 years  (notice the regular millennial trend as well).

But CO2 explains 80-120% of the warming?  The time is hopefully coming when smart people stop taking such statements on faith and demand proof.

**Postscript-  Last year I attended a fantastic series of lectures and discussions at ASU called the Origins Conference.  One thing that I observed there was the scientists, in talking about things like the origins of the universe, were quick to admit where they didn’t understand things — in fact they sort of were gleeful about it, like something that they didn’t understand was a new toy under the Christmas tree.  And for real scientists, I suppose it is.  This is not at all what we see in the CRU emails.

Similarly, climate alarmists assume that some sort of natural phenomenon is hiding or masking warming for the last decade.  Given their forecasts, this has to be a pretty muscular phenomenon, but at the same time they have to argue that natural factors are not muscular enough to have cause much or any of the temperature increases in the 1980s and 1990s.

The ability to handle cognitive dissonance is important in climate science.