Climate Skeptic

Charlie Martin is looking through some of James Hansen’s emails and found this:

[For] example, we extrapolate station measurements as much as 1200 km. This allows us to include results for the full Arctic. In 2005 this turned out to be important, as the Arctic had a large positive temperature anomaly. We thus found 2005 to be the warmest year in the record, while the British did not and initially NOAA also did not. …

So he is trumpeting this approach as an innovation?  Does he really think he has a better answer because he has extrapolated station measurement by 1200km (746 miles)?  This is roughly equivalent, in distance, to extrapolating the temperature in Fargo to Oklahoma City.  This just represents for me the kind of false precision, the over-estimation of knowledge about a process, that so characterizes climate research.  If we don’t have a thermometer near Oklahoma City then we don’t know the temperature in Oklahoma City and lets not fool ourselves that we do.

I had a call from a WaPo reporter today about modeling and modeling errors.  We talked about a lot of things, but my main point was that whether in finance or in climate, computer models typically perform what I call knowledge laundering.   These models, whether forecasting tools or global temperature models like Hansen’s, take poorly understood descriptors of a complex system in the front end and wash them through a computer model to create apparent certainty and precision.  In the financial world, people who fool themselves with their models are called bankrupt (or bailed out, I guess).  In the climate world, they are Oscar and Nobel Prize winners.

In most all of the climate models, the warming effect from feedback is actually much larger than the warming effect from CO2 alone.   That is why I have said for years that it is a waste of time to debate “greenhouse gas theory” as the real theory that matters to the proposition that climate sensitivity to CO2 is high is the theory that Earth’s temperature system is dominated by strong positive feedback.  And the largest feedback in climate models tends to be water vapor feedback, despite the fact that even the IPCC admits that such feedback is poorly understood.  To this end:

In a third paper, accepted for publication by the Journal of Theoretical and Applied Climatology, three scientists – two Australians and one American, revisit data on upper-atmospheric humidity. The three are Garth Paltridge, Albert Arking and Michael Pook, and they have found that, contrary to climate model predictions, water vapour in the upper atmosphere is acting as a brake on global warming.

Established climate models assume constant humidity at all levels in the atmosphere as the temperature rises. But, using data from weather balloons accumulated over 35 years, these researchers find this is not so. At the lower levels, it is higher than expected, dropping below normal at the higher altitudes.

This, they say, implies that “long-term water vapour feedback is negative – that it would reduce rather than amplify the response of the climate system to external forcing such as that from increasing atmospheric CO2.” This, in one fell swoop, challenges the central premise of the warmists that, once CO2 reaches a certain level, we experience runaway global warming.

Thought I would share a couple of bits of an email I got today.  The email showed a distinct lack of familiarity with the nuances of my climate position, so my guess is this may be a form letter.  I find it interesting a 17-year-old knows the term “NGO” but does not know to capitalize the first letter in a sentence (emphasis added).

hello.
this is a (hopefully) reasonable and (hopefully) well thought out message.
firstly i will say that i am 17 years old and not under the sway of any goverments/NGOs.
i believe that what you are doing with your climate skeptic blog is dangerous.
dangerous not only to yourself (in a minor way), but to my generation(in a much bigger way)….  [portion snipped out here basically talking about the writer's view of what science is beyond dispute and lecturing me on the precautionary principle]

you’ll probably think it’s rich, being lectured on ‘responsibility’ by a mere 17 year old, but hear (or read ) me out…
by publishing your blog i believe you are infringing upon successive generations’ fundamental basic human right to life.
denying climate change is fine if you just hold these veiws and keep them to yourself and don’t overtly act upon them.
it does however become infinitely more dangerous to my generation to preach these views as fact(or even air them in a serious manner).
as far as i see it, this is an issue of life and death.
the way i see it, you’re going along the ‘more likely to be death’ route, and please, if only for the sake of your children, or your children’s children, stop updating your blog.

Hmm, I will pass.  But it is nice to know that folks like Al Gore, Michael Mann, and Steve Jones have passed down their fear and loathing of debate to the next generation.    I won’t share my response, but I asked him if he would prefer that my generation, instead of handing his generation a degree or so of warming, instead handed his generation an extra billion or so people in poverty.

When asked what one thing I would want to tell laymen about catastrophic man-made global warming theory, it is the following:  That this theory is in fact a two-part theory.  Greenhouse gas theory alone only gives us incremental warming and no catastrophe.  It is a second theory that Earth’s climate is dominated by strong positive feedbacks that multiplies warming of perhaps a degree over the next century from CO2 to 3,5, or more degrees of warming.  And while it is fairly well accepted by all that CO2 will cause a bit of warming alone, this second theory is not at all settled and in fact may even the the sign of the feedback wrong.

Two stories came out this week undercutting to of the largest sources of feedback.

1.  Water Vapor Feedback

Water vapor is a highly variable gas and has long been recognized as an important player in the cocktail of greenhouse gases—carbon dioxide, methane, halocarbons, nitrous oxide, and others—that affect climate.

“Current climate models do a remarkable job on water vapor near the surface. But this is different — it’s a thin wedge of the upper atmosphere that packs a wallop from one decade to the next in a way we didn’t expect,” says Susan Solomon, NOAA senior scientist and first author of the study.

Since 2000, water vapor in the stratosphere decreased by about 10 percent. The reason for the recent decline in water vapor is unknown. The new study used calculations and models to show that the cooling from this change caused surface temperatures to increase about 25 percent more slowly than they would have otherwise, due only to the increases in carbon dioxide and other greenhouse gases.

An increase in stratospheric water vapor in the 1990s likely had the opposite effect of increasing the rate of warming observed during that time by about 30 percent, the authors found.

2.  CO2  (outgassing from oceans) Feedback

The most alarming forecasts of natural systems amplifying the human-induced greenhouse effect may be too high, according to a new report.

The study in Nature confirms that as the planet warms, oceans and forests will absorb proportionally less CO2.

It says this will increase the effects of man-made warming – but much less than recent research has suggested….

The most likely value among their estimates suggests that for every degree Celsius of warming, natural ecosystems tend to release an extra 7.7 parts per million of CO2 to the atmosphere (the full range of their estimate was between 1.7 and 21.4 parts per million).

This stands in sharp contrast to the recent estimates of positive feedback models, which suggest a release of 40 parts per million per degree; the team say with 95% certainty that value is an overestimate.

OK readers, let’s see how close you have been paying attention.  The models have over-estimated this important feedback by a factor of 5 (40 to 7.7). As I have shown time and time again, the vast majority of the warming in climate forecasts is from feedback — about 1C per century is directly from CO2, the rest is from feedback multipliers.  Have a forecast that says 5C warming in the next century, then about 4C of that is probably due to feedback.

But remember this post, where I said

…there is a very strong social cost in academia to challenging global warming, so that even when findings in certain studies seem to undercut key pieces of the argument, the researches always add something like “but of course this does not refute the basic theory of global warming” at the end of the paper.

So what do this study’s author’s say?

The authors warn, though, that their research will not reduce projections of future temperature rises.

Further, they say their concern about man-made climate change remains high.

Of course, because if this factor goes down, they will just shore up their forecasts and keep them them high with some other plug variable.  Because no one is funding scientists (or quoting them in newspapers) whose models call for just 1C of warming over the next century.

In preparing for my climate presentation in Phoenix next week, I went back and read through Lindzen & Choi, a study whose results I linked here.  The study claims to have measured feedback, and have found feedback to temperature changes in the natural climate system to be negative –opposite of the assumption of strong positive feedback in climate models.  I found this interesting, as we often do of studies that confirm our own hypotheses.

Re-reading the study, I was uncomfortable with the methodology, but figured I was missing something.  Specifically, I didn’t understand how an increase in temperature could result in a decrease in outgoing radiation, as Lindzen says is assumed in all the models.   As I have always understood it, the opposite has to be true in a stable system.   With an added forcing, temperature increases which increases outgoing radiation until the radiation budget is back in balance.  Models that assumed otherwise would have near infinite temepratures.   I assumed perhaps that Lindzen & Choi were making measurements during the time the system came back into equilibrium.

Apparently, both Luboš Motl and Roy Spencer have spotted problems as well, and they explain the issue in a more sophisticated way here and here.

But the results I have been getting from the fully coupled ocean-atmosphere (CMIP) model runs that the IPCC depends upon for their global warming predictions do NOT show what Lindzen and Choi found in the AMIP model runs. While the authors found decreases in radiation loss with short-term temperature increases, I find that the CMIP models exhibit an INCREASE in radiative loss with short term warming.

In fact, a radiation increase MUST exist for the climate system to be stable, at least in the long term. Even though some of the CMIP models produce a lot of global warming, all of them are still stable in this regard, with net increases in lost radiation with warming (NOTE: If analyzing the transient CMIP runs where CO2 is increased over long periods of time, one must first remove that radiative forcing in order to see the increase in radiative loss).

So, while I tend to agree with the Lindzen and Choi position that the real climate system is much less sensitive than the IPCC climate models suggest, it is not clear to me that their results actually demonstrate this.

Spencer further makes the point he has made for a couple of years now that feedback is really, really, really hard to measure, because it is so easy to confuse cause and effect.

Spencer by the way points out this admission from the Fourth IPCC report:

“A number of diagnostic tests have been proposed…but few of them have been applied to a majority of the models currently in use. Moreover, it is not yet clear which tests are critical for constraining future projections (of warming). Consequently, a set of model metrics that might be used to narrow the range of plausible climate change feedbacks and climate sensitivity has yet to be developed.”

This is kind of amazing, in effect saying “we have no idea what the feedbacks are or how to measure them, but lacking any knowlege, we are going to consistently and universally assume very high positive feedbacks with feedback factors > 0.7″

Joe Romm has gone on the record at Climate Progress on April 13, 2009 that the “median” forecast was for warming in the US by 2100 of 10-15F, or 5.5-8.3C, and he made it very clear that if he had to pick a single number, it would be the high end of that range.

On average, the 8.3C implies about 0.9C per decade of warming.  This might vary slightly by what starting point he intended (he is not very clear in the post) and I understand there is a curve so it will be below average in the early years and above in the later.

Anyway, Joe Romm is ready to put his money where his mouth is, and wants to make a 50/50 bet with any comers that warming in the next decade will be… 0.15C.  Boy, it sure is daring for a guy who is constantly in the press at a number around 0.9C per decade to commit to a number 6 times lower when he puts his money where his mouth is.   Especially when Romm has argued that warming in the last decade has been suppressed (somehow) and will pop back up soon.  Lucia has more reasons why this is a chickensh*t bet.

I deconstructed a previous gutless bet by Nate Silver here.

I am looking at some back and forth in this Flowing Data post.

Apparently an Australian Legislator named Stephen Fielding posted this chart and asked, “Is it the case that CO2 increased by 5% since 1998 whilst global temperature cooled over the same period (see Fig. 1)?  If so, why did the temperature not increase; and how can human emissions be to blame for dangerous levels of warming?”

Certainly this could sustain some interesting debate.  Climate is complex, so their might be countervailing effects to CO2, but it also should be noted that none of the models really predicted this flatness in temperatures, so it certainly could be described as “unexpected” at least among the alarmist community.

Instead, the answer that came back from Stephen Few was this (as reported by Flowing Data, I cannot find this on Few’s site):

This is a case of someone who listens only to what he wants to hear (the arguments of a few fringe organizations with agendas) and either ignores or is incapable of understanding the overwhelming weight of scientific evidence. He selected a tiny piece of data (a short period of time, with only one of many measures of temperature), misinterpreted it, and ignored the vast collection of data that contradicts his position. This fellow is either incredibly stupid or a very bad man.

Every alarmist from Al Gore to James Hansen has used this same chart in their every presentation – showing global temperatures since 1950  (or really since 1980) going up in lockstep with Co2.  This is the alarmists #1 chart.  All Fielding has done is shown data after 1998, something alarmists tend to be reluctant to do.  Sure it’s a short time period, but nothing in any alarmist prediction or IPCC report hinted that there was any possibility that for even so short a time as 15 years warming might cease  (at least not in the last IPCC report, which I have read nearly every page of).  So, by using the alarmists’ own chart and questioning a temperature trend that went unpredicted, Fielding is “either incredibly stupid or a very bad man.”  Again, the alarmist modus operandi – it is much better to smear the person in ad hominem attacks than deal with his argument.

Shouldn’t there be symmetry here?  If it is OK for every alarmist on the planet to show 1980-1995 temperature growing in lockstep with CO2 as “proof” of a relationship, isn’t it equally OK to show 1995-2010 temperature not growing in lockstep with CO2 to question the relationship?  Why is one ok but the other incredibly stupid and/or mean-spirited?   I mean graphs like this were frequent five years ago, though they have dried up recently:

For extra credit, figure out how they got most of the early 2000’s to be warmer than 1998 in this chart, since I can find no major temperature metric that matches this.  I suspect some endpoint smoothing games here.

I won’t get into arguing the “overwhelming weight of scientific evidence” statement, as I find arguments over counting scientific heads or papers to be  useless in the extreme.  But I will say that as a boy when I learned about the scientific method, there was a key step where one’s understanding of a natural phenomenon is converted into predicted behaviors, and then those predictions are tested against reality.  All Fielding is doing is testing the predictions, and finding them to be missing the mark.  Sure, one can argue that the testing period has not been long enough, so we will keep testing, but what Fielding is trying to do here, however imperfectly, is perfectly compatible with the scientific method.

I must say I am a bit confused about those “many other measures of temperature.”  Is Mr. Few suggesting that the chart would have different results in Fahrenheit?  OK, I am kidding of course.  What I am sure he means is that there are groups other than the Hadley Center that produce temperature records for the globe  (though in Mr. Fielding’s defense the Hadley Center is a perfectly acceptable source and the preferred source of much of the IPCC report).  To my knowledge, there are four major metrics (Hadley, GISS, UAH, RSS).  Of these four, at least three (I am not sure about the GISS) would show the same results.  I think the “overwhelming weight” of temperature metrics makes the same point as Mr. Fielding’s chart.

In the rest of his language, Few is pretty sloppy for someone who wants to criticize someone for sloppiness.  He says that Fielding “misinterpreted” the temperature data.  How?  Seems straight forward to me.  He also says that there is a “vast collection of data that contradicts his position.”  What position is that?  If his position is merely that Co2 has increased for 15 years and temperatures have not, well, there really is NOT a vast collection of data that contradicts that.  There may be a lot of people who have published reasons whythis set of facts does not invalidate AGW, but the facts are still the same.

By the way, I get exhausted by the accusation that skeptics are somehow simplistic and can’t understand complex systems.    I feel like my understanding is pretty nuanced. By the way, its interesting how the sides have somewhat reversed here.  When temperature was going up steadily, it was alarmists saying that things were simple and skeptics saying that climate was complex and you couldn’t necessarily make the 1:1 correlation between CO2 and temperature increases.  Now that temperature has flat lined for a while, it is alarmists screaming that skeptics are underestimating the complexity.  I tend to agree — climate is indeed really really complex, though I think if one accepts this complexity it is hard to square with the whole “settled science” thing.  Really, we have settled the science in less than 20 years on perhaps the most complex system we have ever tried to understand?

The same Flowing Data post references this post from Graham Dawson.  Most of Dawson’s “answers” to Fieldings questions are similar to Few’s, but I wanted to touch on one or two other things.

First, I like how he calls findings from the recent climate synthesis report the “government answer” as if this makes it somehow beyond dispute.  But I digress.

The surface air temperature is just one component in the climate system (ocean, atmosphere, cryosphere). There has been no material trend in surface air temperature during the last 10 years when taken in isolation, but 13 of the 14 warmest years on record have occurred since 1995. Also global heat content of  the ocean (which constitutes 85% of the total warming) has continued to rise strongly in this period, and ongoing warming of the climate system as a whole is supported by a very wide range of observations, as reported in the peer-reviewed scientific literature.

This is the kind of blithe answer that is full of inaccuracies everyone needs to be careful about.  The first sentence is true, and the second is probably close to the mark, though with a bit more uncertainty than he implies.  He is also correct that global heat content of the ocean is a huge part of warming or the lack thereof, but his next statement is not entirely correct.  Ocean heat content as measured by the new ARGO system since 2003 has been flat to down.  Longer term measures are up, but most of the warming comes at the point the old metrics were spliced to the ARGO data, a real red flag to any serious data analyst.  The cryospehere is important as well, but most metrics show little change in total sea ice area, with losses in the NH offset by gains in the SH.

While the Earth’s temperature has been warmer in the geological past than it is today, the magnitude and rate of change is unusual in a geological context. Also the current warming is unusual as past changes have been triggered by natural forcings whereas there are no known natural climate forcings, such as changes in solar irradiance, that can explain the current observed warming of the climate system. It can only be explained by the increase in greenhouse gases due to human activities.

No one on Earth has any idea if the first sentence is true — this is pure supposition on the author’s part, stated as a fact.  We are talking about temperature changes today over a fifty year (or shorter) period, and we have absolutely no way to look at changes in the “geological past” on this fine of a timescale.  I am reminded of the old ice core chart that was supposedly the smoking gun between CO2 and temperature, only to find later as we improved the time resolution that temperature increases came before Co2 increases.

I won’t make too much of my usual argument on the sun, except to say that the Sun has been substantially more active during the warming period of 1950-2000 than it has been in other times.  What I want to point out, though, is the core foundation of the alarmist argument, one that I have pointed out before.  It boils down to:  Past warming must be due to man because we can’t think of what else it could be.   This is amazing hubris, representing a total unwillingness to admit what we do and don’t understand.  Its almost like the ancient Greeks, attributing what they didn’t understand in the cosmos to the hijinx of various gods.

It is not the case that all GCM computer models projected a steady increase in temperature for the period 1990-2008.  Air temperatures are affected by natural variability.  Global Climate Models show this variability in the long term but are not able to predict exactly when such variations will happen. GCMs can and do simulate decade-long periods of no warming, or even slight cooling, embedded in longer-term warming trends.

But none showed zero warming, or anything even close.

Vegas casinos love the sucker bet.  Nothing makes the accountants happier than seeing someone playing the Wheel of Fortune, or betting on “12, the hard way” in craps, or taking insurance in blackjack.  While the house always maintains a slim advantage, these bets really stack the deck in the house’s favor.

And just as I don’t feel guilty for leaving Caesar’s Palace without playing the Wheel of Fortune, I don’t feel a bit of guilt for not taking this bet from Nate Silver:

1. For each day that the high temperature in your hometown is at least 1 degree Fahrenheit above average, as listed by Weather Underground, you owe me $25. For each day that it is at least 1 degree Fahrenheit below average, I owe you $25.

I presume Silver is a smart guy and knows what he is doing, because in fact this is not a bet on future warming, but on past warming.  Even without a bit of future warming, he wins this bet.  Why?

I am sitting in my hotel room, and so I don’t have time to dig into the Weather Underground’s data definitions, but my guess is that their average temperatures are based on historic data, probably about a hundred years worth on average.

Over the last 100 years the world has on average warmed about 1F.  This means that today, again on average, most locations will sit on a temperature plateau about 0.5F higher than the average.  So by structuring this bet like this, he is basically asking people  to take “red” in roulette while he takes black and zero and double zero.   He has a built in 0.5F advantage.  Even with zero future warming.

Now, the whole point of this bet may be to take money from skeptics who don’t bother to educate themselves on climate and believe Rush Limbaugh or whoever that there has never been any change in world temperatures.  Fine.  I have little patience with either side of the debate that want to be vocal without educating him or herself on the basic facts.  But to say this is a bet on future warming is BS.

The other effect that may exist here (but I am less certain of the science, commenters can help me out) is that by saying “your hometown” we put the bet into the domain of urban heat islands and temperature station siting issues.  Clearly UHI has substantially increased temperatures in many cities, but that is because average temperatures are generally computed as the average of the daily minimum and maximum.  My sense is that UHI has a much bigger effect on Tmin than Tmax – such that my son and I found a 10 degree F UHI in Phoenix in the evening, but I am not sure if we could find one, or as large of one, at the daily maximum.  Nevertheless, to the extent that such an effect exists for Tmax, most cities that have grown over the last few years will be above their averages just from the increasing UHI component.

I don’t have the contents of my computer hard drive here with me, but a better bet would be from a 10-year average of some accepted metric  (I’d prefer satellites but Hadley CRUT would be OK if we just had to use the old dinosaur surface record).  Since I accept about 1-1.2C per century, I’d insist on this trend line and would pay out above it and collect below it  (all real alarmists consider a 1.2C per century future trend to be about zero probability, so I suspect this would be acceptable).

A lot of skeptics’ websites are riled up about the EPA’s leadership decision not to forward comments by EPA staffer Alan Carlin on the Endangerment issue and global warming because these comments were not consistent with where the EPA wanted to go on this issue.   I reprinted the key EPA email here, which I thought sounded a bit creepy, and some of the findings by the CEI which raised this issue.

However, I think skeptics are getting a bit carried away.  Let’s try to avoid the exaggeration and hype of which we often accuse global warming alarmists.  This decision does not reflect well on the EPA, but let’s make sure we understand what it was and was not:

• This was not a “study” in the sense we would normally use the word.  These were comments submitted by an individual to a regulatory decision and/or a draft report.  The  authors claimed to only have 4 or 5 days to create these comments.  To this extent, they are not dissimilar to the types of comments many of us submitted to the recently released climate change synthesis report (comments, by the way, which still have not been released though the final report is out — this in my mind is a bigger scandal than how Mr. Carlin’s comments were handled).  Given this time frame, the comments are quite impressive, but nonetheless not a “study.”
• This was not an officially sanctioned study that was somehow suppressed.  In other words, I have not seen anywhere that Mr. Carlin was assigned by the agency to produce a report on anthropogenic global warming.  This does not however imply that what Mr. Carlin was doing was unauthorized.  This is a very normal activity — staffers from various departments and background submitting comments on reports and proposed regulations.  He was presumably responding to an internal call for comments by such and such date.
• I have had a number of folks write me saying that everyone is misunderstanding the key email — that it should be taken on its face — and read to mean that Mr. Carlin commented on issues outside of the scope of the study or based document he was commenting on.  An example might be submitting comments saying man is not causing global warming to a study discussing whether warming causes hurricanes.   However, his comments certainly seem relevant to Endangerment question — the background, action, and proposed finding the comments were aimed at is on the EPA website here.  Note in particular the comments in Carlin’s paper were totally relevant and on point to the content of the technical support document linked on that page.
• The fourth email cited by the CEI, saying that Mr. Carlin should cease spending any more time on global warming, is impossible to analyze without more context.  There are both sinister and perfectly harmless interpretations of such an email.  For example, I could easily imagine an employee assigned to area Y who had a hobbyist interest in area X and loved to comment on area X being asked by his supervisor to go back and do his job in area Y.  I have had situations like that in the departments I have run.

What does appear to have happened is that Mr. Carlin responded to a call for comments, submitted comments per the date and process required, and then had the organization refuse to forward those comments because they did not fit the storyline the EPA wanted to put together.  This content-based rejection of his submission does appear to violate normal EPA rules and practices and, if not, certainly violates the standards we would want such supposedly science-based regulatory bodies to follow.  But let’s not upgrade this category 2 hurricane to category 5 — this was not, as I understand it, an agency suppressing an official agency-initiated study.

I may be a cynical libertarian on this, but this strikes me more as a government issue than a global warming issue.  Government bureaucracies love consensus, even when they have to impose it.  I don’t think there is a single agency in Washington that has not done something similar — ie suppressed internal concerns and dissent when the word came down from on high what the answer was supposed to be on a certain question they were supposed to be “studying.”**  This sucks, but its what we get when we build this big blundering bureaucracy to rule us.

Anyway, Anthony Watt is doing a great job staying on top of this issue.  His latest post is here, and includes an updated version of Carlin’s comments.   Whatever the background, Carlin’s document is well worth a read.  I have mirrored the document here.

**Postscript: Here is something I have observed about certain people in both corporate and government beauracracies.  I appologize, but I don’t really have the words for this and I don’t know the language of psychology.   There is a certain type of person who comes to believe, really believe, their boss’s position on an issue.  We often chalk this up from the outside to brown-nosing or an “Eddie Haskell” effect where people fake their beliefs, but I don’t think this is always true.  I think there is some sort of human mental defense mechanism that people have a tendency to actually adopt (not just fake) the beliefs of those in power over them.  Certainly some folks resist this, and there are some issues too big or fundamental for this to work, but for many folks their mind will reshape itself to the beaucracracy around it.  It is why sometimes organizations cannot be fixed, and can only be blown up.

Update: The reasons skeptics react strongly to stuff like this is that there are just so many examples:

Over the coming days a curiously revealing event will be taking place in Copenhagen. Top of the agenda at a meeting of the Polar Bear Specialist Group (set up under the International Union for the Conservation of Nature/Species Survival Commission) will be the need to produce a suitably scary report on how polar bears are being threatened with extinction by man-made global warming….

Dr Mitchell Taylor has been researching the status and management of polar bears in Canada and around the Arctic Circle for 30 years, as both an academic and a government employee. More than once since 2006 he has made headlines by insisting that polar bear numbers, far from decreasing, are much higher than they were 30 years ago. Of the 19 different bear populations, almost all are increasing or at optimum levels, only two have for local reasons modestly declined.

Dr Taylor agrees that the Arctic has been warming over the last 30 years. But he ascribes this not to rising levels of CO2 – as is dictated by the computer models of the UN’s Intergovernmental Panel on Climate Change and believed by his PBSG colleagues – but to currents bringing warm water into the Arctic from the Pacific and the effect of winds blowing in from the Bering Sea….

Dr Taylor had obtained funding to attend this week’s meeting of the PBSG, but this was voted down by its members because of his views on global warming. The chairman, Dr Andy Derocher, a former university pupil of Dr Taylor’s, frankly explained in an email (which I was not sent by Dr Taylor) that his rejection had nothing to do with his undoubted expertise on polar bears: “it was the position you’ve taken on global warming that brought opposition”.

Dr Taylor was told that his views running “counter to human-induced climate change are extremely unhelpful”. His signing of the Manhattan Declaration – a statement by 500 scientists that the causes of climate change are not CO2 but natural, such as changes in the radiation of the sun and ocean currents – was “inconsistent with the position taken by the PBSG”.

One frequent topic on this blog is that the theory of catastrophic anthropogenic global warming actually rests on two separate, unrelated propositions.  One, that increasing CO2 in the atmosphere increases temperatures.  And two, that the Earth’s climate is dominated by positive feedbacks that multiply the warming from Co2 alone by 3x or more.  Proposition one is well-grounded, and according to the IPCC (which this report does not dispute) the warming from Co2 alone is about 1.2C per doubling of Co2 concentrations.  Proposition two is much, much iffier, which is all the more problematic since 2/3 or more of the hypothesized future warming typically comes from the feedback.

We have to do a little legwork, because this report bends over backwards to not include any actual science.  For example, as far as I can tell, it does not actually establish a range of likely climate sensitivity numbers, but we can back into them.

The report uses CO2 concentrations numbers for “do nothing” scenarios (no global warming legislation) of between 850 and 950 ppm in 2100.  These are labeled as the IPCC A2 and A1F1 scenarios.  For these scenarios, between 2000 and 2100 they show warming of 6F and 7F respectively.   Now, I need to do some conversions.  850 and 950 ppm represent about 1.25 and 1.5 doublings from 2000 levels.  The temperatures for these are 3.3C and 3.9C.  This means that the assumed sensitivity in these charts (as degrees Celsius per doubling) is around 2.6, though my guess is that there are time delays in the model and the actual number is closer to 3.  This is entirely consistent with the last IPCC report.

OK, that seems straight forward.  Except having used these IPCC numbers on pages 23-25, they quickly abandon them in favor of higher numbers.    Here for example, is a chart from page 29:

Note the map on the right, which is the end of century projection for the US.  The chart shows a range of warming of 7-11 degrees F for a time period centered on 2090  (they boxed that range on the thermometer, not me), but the chart on page 25 shows average warming in the max emissions case in 2090 to be about 7.5F against the same baseline (you have to be careful, they keep moving the baseline around on these charts).  It could be that my Mark I integrating eyeball is wrong, but that map sure looks like more than an average 7.5F increase.  It could be that the US is supposed to warm more than the world average, but the report never says so that I can find, and the US (even by the by the numbers in the report) has warmed less than the rest of the globe over the last 50 years.

The solution to this conundrum may be on page 24 when they say:

Based on scenarios that do not assume explicit climate policies to reduce greenhouse gas emissions, global average temperature is projected to rise by 2 to 11.5°F by the end of this century90 (relative to the 1980-1999 time period).

Oddly enough (well, oddly for a science document but absolutely predictably for an advocacy paper) the high end of this range, rather than the median, seems to be the number used through the rest of the report.  This 11.5F probably implies a climate sensitivity around 5 C/doubling.  Using the IPCC numaber of 1.2 for CO2 alone, means that this report is assuming that as much as 75% of the warming comes from positive feedback effects.

So, since most of the warming, and all of the catastrophe, comes from the assumption that the climate system is dominated by net positive feedback, one would assume the report would address itself to this issue.  Wrong.

I did a search for the word “feedback” in the document just to make sure I didn’t miss anything.  Here are all the references in the main document (outside of footnotes) to feedback used in this context:

• P15:  “However, the surface warming caused by human-produced increases in other greenhouse gases leads to an increase in atmospheric water vapor, since a warmer climate increases evaporation and allows the atmosphere to hold more moisture. This creates an amplifying “feedback loop,” leading to more warming.”
• P16:  “For example, it is known from long records of Earth’s climate history that under warmer conditions, carbon tends to be released, for instance, from thawing permafrost, initiating a feedback loop in which more carbon release leads to more warming which leads to further release, and so on.”
• P17:  “For example, it is known from long records of Earth’s climate history that under warmer conditions, carbon tends to be released, for instance, from thawing permafrost, initiating a feedback loop in which more carbon release leads to more warming which leads to further release, and so on.

That’s it – the entire sum text of feedbacks.  All positive, no discussion of negative feedbacks, and no discussion of the evidence how we know positive feedbacks outweight negative feedbacks.  The first one of the three is particularly disengenuous, since most serious scientists will admit that we don’t even know the sign of the water vapor feedback loop, and there is good evidence the sign is actually negative (due to albedo effects from increased cloud formation).

If frequent readers get any one message from this site, it should be that the theory of catastrophic global warming from CO2 is actually based on two parallel and largely unrelated theories:

1. That CO2 acts as a greenhouse gas and can increase global temperatures as concentrations increase
2. That the earth’s climate is dominated by strong positive feedback that multiplies the effect of #1 3,4,5 times or more.

I have always agreed with #1, and I think most folks will accept a number between 1-1.2C for a doubling of CO2 (though a few think its smaller).  #2 is where the problem with the theory is, and it is no accident that this is the area least discussed in the media.  For more, I refer you to this post and this video.  (higher resolution video here, clip #3).

In my video and past posts, I have tried to back into the feedback fraction f that models are using.  I used a fairly brute force approach and came up with numbers between 0.65 and 0.85.  It turns out I was pretty close.  Dr Richard Lindzen has this chart showing the feedback fractions f used in models, and the only surprise to me is how many use a number higher than 1 (such numbers imply runaway reactions similar to nuclear fission).

Lindzen thinks the true number is closer to -1, which is similar to the number I backed into from temperature history over the last 100 years.  This would imply that feedback actually works to reduce the net effect of greenhouse warming, from a sensitivity of 1.2 to one something like 0.6C per doubling.

I thought this article in the NY Times about the failure of models to accurately predict the progression of swine flu cases was moderately instructive.

In the waning days of April, as federal officials were declaring a public health emergency and the world seemed gripped by swine flu panic, two rival supercomputer teams made projections about the epidemic that were surprisingly similar — and surprisingly reassuring. By the end of May, they said, there would be only 2,000 to 2,500 cases in the United States.

May’s over. They were a bit off.

On May 15, the Centers for Disease Control and Prevention estimated that there were “upwards of 100,000” cases in the country, even though only 7,415 had been confirmed at that point.

The agency declines to update that estimate just yet. But Tim Germann, a computational scientist who worked on a 2006 flu forecast model at Los Alamos National Laboratory, said he imagined there were now “a few hundred thousand” cases.

We can take at least two lessons from this:

• Accurately modeling complex systems is really, really hard.  We may have hundreds of key variables, and changes in starting values or assumed correlation coefficients between these variables can make enormous differences in model results.
• Very small changes in assumptions about processes that compound or have exponential growth make enormous differences in end results.  I think most people grossly underestimate this effect.  Take a process that starts at an arbitrary value of “100″ and grows at some growth rate each period for 50 periods.    A growth rate of 1% per period yields an end value of  164.  A growth rate just 1 percentage point higher of 2% per period yields a final value of  269.    A growth rate of 3% yield a final value of 438.  In this case, if we miss the growth rate by just a couple of percentage points, we miss the end value by a factor of three!

Bringing this back to climate, we must understand that the problem of forecasting disease growth rates is grossly, incredibly more simple than forecasting future temperatures.  These guys missed the forecast my miles of a process that is orders of magnitude more amenable to forecasting than is climate.  But I am encouraged by this:

Both professors said they would use the experience to refine their models for the future.

If only climate scientists took this approach to new observations.

William DiPuccio has a really very readable and clear post on using ocean heat content to falsify current global warming model projections. He argues pretty persuasively that surface air temperature measurements are a really, really poor way to search for evidence of a man-made climate forcing from CO2.

Since the level of CO2 and other well-mixed GHG is on the rise, the overall accumulation of heat in the climate system, measured by ocean heat, should be fairly steady and uninterrupted (monotonic) according to IPCC models, provided there are no major volcanic eruptions.  According to the hypothesis, major feedbacks in the climate system are positive (i.e., amplifying), so there is no mechanism in this hypothesis that would cause a suspension or reversal of overall heat accumulation.  Indeed, any suspension or reversal would suggest that the heating caused by GHG can be overwhelmed by other human or natural processes in the climate system….

[The] use of surface air temperature as a metric has weak scientific support, except, perhaps, on a multi-decadal or century time-scale.  Surface temperature may not register the accumulation of heat in the climate system from year to year.  Heat sinks with high specific heat (like water and ice) can absorb (and radiate) vast amounts of heat.  Consequently the oceans and the cryosphere can significantly offset atmospheric temperature by heat transfer creating long time lags in surface temperature response time.  Moreover, heat is continually being transported in the atmosphere between the poles and the equator.  This reshuffling can create fluctuations in average global temperature caused, in part, by changes in cloud cover and water vapor, both of which can alter the earth’s radiative balance.

One statement in particular really opened my eyes, and made  me almost embarassed to have focused time on surface temperatures at all:

For any given area on the ocean’s surface, the upper 2.6m of water has the same heat capacity as the entire atmosphere above it

Wow!  So oceans have orders of magnitude more heat capacity than the atmosphere.

The whole article is a good read, but his conclusion is that estimates of ocean heat content changes appear to be way off what they should be given IPCC models:

My only concern with the analysis is that I fear the authors may be underestimating the effect of phase change (e.g. melting or evaporation).  Phase change can release or absorb enormous amounts of heat.  As a simple example, observe how long a pound of liquid water at 32.1F takes to reach room temperature.  Then observe how long a pound of ice at 31.9F takes to reach room temperature.  The latter process takes an order of magnitude more time, because it absorbs an order of magnitude more heat.

The article attached was necessarily a summary, but I am not totally convinced he has accounted for phase change sufficiently.  Both an increase in melting ice as well as an increase in evaporation would tend to cause measured accumulated heat in the oceans to be lower than expected.   He uses an estimate by James Hansen that the number is really small for ice melting (he does not discuss evaporation).  However, if folks continue to use Hansen’s estimate of this term to falsify Hansen’s forecast, expect Hansen to suddenly “discover” that he had grossly underestimated the ice melting term.

For several years, there was an absolute spate of lawsuits charging sudden acceleration of a motor vehicle — you probably saw such a story:  Some person claims they hardly touched the accelerator and the car leaped ahead at enormous speed and crashed into the house or the dog or telephone pole or whatever.  Many folks have been skeptical that cars were really subject to such positive feedback effects where small taps on the accelerator led to enormous speeds, particularly when almost all the plaintiffs in these cases turned out to be over 70 years old.  It seemed that a rational society might consider other causes than unexplained positive feedback, but there was too much money on the line to do so.

Many of you know that I consider questions around positive feedback in the climate system to be the key issue in global warming, the one that separates a nuisance from a catastrophe.  Is the Earth’s climate similar to most other complex, long-term stable natural systems in that it is dominated by negative feedback effects that tend to damp perturbations?  Or is the Earth’s climate an exception to most other physical processes, is it in fact dominated by positive feedback effects that, like the sudden acceleration in grandma’s car, apparently rockets the car forward into the house with only the lightest tap of the accelerator?

I don’t really have any new data today on feedback, but I do have a new climate forecast from a leading alarmist that highlights the importance of the feedback question.

Dr. Joseph Romm of Climate Progress wrote the other day that he believes the mean temperature increase in the “consensus view” is around 15F from pre-industrial times to the year 2100.  Mr. Romm is mainly writing, if I read him right, to say that critics are misreading what the consensus forecast is.  Far be it for me to referee among the alarmists (though 15F is substantially higher than the IPCC report “consensus”).  So I will take him at his word that 15F increase with a CO2 concentration of 860ppm is a good mean alarmist forecast for 2100.

I want to deconstruct the implications of this forecast a bit.

For simplicity, we often talk about temperature changes that result from a doubling in Co2 concentrations.  The reason we do it this way is because the relationship between CO2 concentrations and temperature increases is not linear but logarithmic.  Put simply, the temperature change from a CO2 concentration increase from 200 to 300ppm is different (in fact, larger) than the temperature change we might expect from a concentration increase of 600 to 700 ppm.   But the temperature change from 200 to 400 ppm is about the same as the temperature change from 400 to 800 ppm, because each represents a doubling.   This is utterly uncontroversial.

If we take the pre-industrial Co2 level as about 270ppm, the current CO2 level as 385ppm, and the 2100 Co2 level as 860 ppm, this means that we are about 43% through a first doubling of Co2 since pre-industrial times, and by 2100 we will have seen a full doubling (to 540ppm) plus about 60% of the way to a second doubling.  For simplicity, then, we can say Romm expects 1.6 doublings of Co2 by 2100 as compared to pre-industrial times.

So, how much temperature increase should we see with a doubling of CO2?  One might think this to be an incredibly controversial figure at the heart of the whole matter.  But not totally.  We can break the problem of temperature sensitivity to Co2 levels into two pieces – the expected first order impact, ahead of feedbacks, and then the result after second order effects and feedbacks.

What do we mean by first and second order effects?  Well, imagine a golf ball in the bottom of a bowl.  If we tap the ball, the first order effect is that it will head off at a constant velocity in the direction we tapped it.  The second order effects are the gravity and friction and the shape of the bowl, which will cause the ball to reverse directions, roll back through the middle, etc., causing it to oscillate around until it eventually loses speed to friction and settles to rest approximately back in the middle of the bowl where it started.

It turns out the the first order effects of CO2 on world temperatures are relatively uncontroversial.  The IPCC estimated that, before feedbacks, a doubling of CO2 would increase global temperatures by about 1.2C  (2.2F).   Alarmists and skeptics alike generally (but not universally) accept this number or one relatively close to it.

Applied to our increase from 270ppm pre-industrial to 860 ppm in 2100, which we said was about 1.6 doublings, this would imply a first order temperature increase of 3.5F from pre-industrial times to 2100  (actually, it would be a tad more than this, as I am interpolating a logarithmic function linearly, but it has no significant impact on our conclusions, and might increase the 3.5F estimate by a few tenths.)  Again, recognize that this math and this outcome are fairly uncontroversial.

So the question is, how do we get from 3.5F to 15F?  The answer, of course, is the second order effects or feedbacks.  And this, just so we are all clear, IS controversial.

A quick primer on feedback.  We talk of it being a secondary effect, but in fact it is a recursive process, such that there is a secondary, and a tertiary, etc. effects.

Lets imagine that there is a positive feedback that in the secondary effect increases an initial disturbance by 50%.  This means that a force F now becomes F + 50%F.  But the feedback also operates on the additional 50%F, such that the force is F+50%F+50%*50%F…. Etc, etc.  in an infinite series.  Fortunately, this series can be reduced such that the toal Gain =1/(1-f), where f is the feedback percentage in the first iteration. Note that f can and often is negative, such that the gain is actually less than 1.  This means that the net feedbacks at work damp or reduce the initial input, like the bowl in our example that kept returning our ball to the center.

Well, we don’t actually know the feedback fraction Romm is assuming, but we can derive it.  We know his gain must be 4.3 — in other words, he is saying that an initial impact of CO2 of 3.5F is multiplied 4.3x to a final net impact of 15.  So if the gain is 4.3, the feedback fraction f must be about 77%.

Does this make any sense?  My contention is that it does not.  A 77% first order feedback for a complex system is extraordinarily high  — not unprecedented, because nuclear fission is higher — but high enough that it defies nearly every intuition I have about dynamic systems.  On this assumption rests literally the whole debate.  It is simply amazing to me how little good work has been done on this question.  The government is paying people millions of dollars to find out if global warming increases acne or hurts the sex life of toads, while this key question goes unanswered.  (Here is Roy Spencer discussing why he thinks feedbacks have been overestimated to date, and a bit on feedback from Richard Lindzen).

But for those of you looking to get some sense of whether a 15F forecast makes sense, here are a couple of reality checks.

First, we have already experienced about .43 if a doubling of CO2 from pre-industrial times to today.  The same relationships and feedbacks and sensitivities that are forecast forward have to exist backwards as well.  A 15F forecast implies that we should have seen at least 4F of this increase by today.  In fact, we have seen, at most, just 1F  (and to attribute all of that to CO2, rather than, say, partially to the strong late 20th century solar cycle, is dangerous indeed).  But even assuming all of the last century’s 1F temperature increase is due to CO2, we are way, way short of the 4F we might expect.  Sure, there are issues with time delays and the possibility of some aerosol cooling to offset some of the warming, but none of these can even come close to closing a gap between 1F and 4F.  So, for a 15F temperature increase to be a correct forecast, we have to believe that nature and climate will operate fundamentally different than they have over the last 100 years.

Second, alarmists have been peddling a second analysis, called the Mann hockey stick, which is so contradictory to these assumptions of strong positive feedback that it is amazing to me no one has called them on the carpet for it.  In brief, Mann, in an effort to show that 20th century temperature increases are unprecedented and therefore more likely to be due to mankind, created an analysis quoted all over the place (particularly by Al Gore) that says that from the year 1000 to about 1850, the Earth’s temperature was incredibly, unbelievably stable.  He shows that the Earth’s temperature trend in this 800 year period never moves more than a few tenths of a degree C.  Even during the Maunder minimum, where we know the sun was unusually quiet, global temperatures were dead stable.

This is simply IMPOSSIBLE in a high-feedback environment.  There is no way a system dominated by the very high levels of positive feedback assumed in Romm’s and other forecasts could possibly be so rock-stable in the face of large changes in external forcings (such as the output of the sun during the Maunder minimum).  Every time Mann and others try to sell the hockey stick, they are putting a dagger in teh heart of high-positive-feedback driven forecasts (which is a category of forecasts that includes probably every single forecast you have seen in the media).

For a more complete explanation of these feedback issues, see my video here.

I have been meaning to link to this post for a while, but the Reference Frame, along with Roy Spencer, makes a valuable point I have also made for some time — the warming effect from man’s CO2 is not going to be zero.  The article cites approximately the same number I have used in my work and that was used by the IPCC:  absent feedback and other second order effects, the earth should likely warm about 1.2C from a doubling of CO2.

The bare value (neglecting rain, effects on other parts of the atmosphere etc.) can be calculated for the CO2 greenhouse effect from well-known laws of physics: it gives 1.2 °C per CO2 doubling from 280 ppm (year 1800) to 560 ppm (year 2109, see below). The feedbacks may amplify or reduce this value and they are influenced by lots of unknown complex atmospheric effects as well as by biases, prejudices, and black magic introduced by the researchers.

A warming in the next century of 0.6 degrees, or about the same warming we have seen in the last century, is a very different prospect, demanding different levels of investment, than typical forecasts of 5-10 degrees or more of warming from various alarmists.

How we get from a modest climate sensitivity of 1.2 degrees to catastrophic forecasts is explained in this video:

I have written for quite a while that the most important issue in evaluating catastrophic global warming forecasts is feedback.  Specifically, is the climate dominated by positive feedbacks, such that small CO2-induced changes in temperatures are multiplied many times, or even hit a tipping point where temperatures run away?  Or is the long-term stable system of climate more likely dominated by flat to negative feedback, as are most natural physical systems?  My view has always been that the earth will warm at most a degree for a doubling of CO2 over the next century, and may warm less if feedbacks turn out to be negative.

I am optimistic that this feedback issue may finally be seeing the light of day.  Here is Professor William Happer of Princeton in US Senate testimony:

There is little argument in the scientific community that a direct effect of doubling the CO2 concentration will be a small increase of the earth’s temperature — on the order of one degree. Additional increments of CO2 will cause relatively less direct warming because we already have so much CO2 in the atmosphere that it has blocked most of the infrared radiation that it can. It is like putting an additional ski hat on your head when you already have a nice warm one below it, but your are only wearing a windbreaker. To really get warmer, you need to add a warmer jacket. The IPCC thinks that this extra jacket is water vapor and clouds.

Since most of the greenhouse effect for the earth is due to water vapor and clouds, added CO2 must substantially increase water’s contribution to lead to the frightening scenarios that are bandied about. The buzz word here is that there is “positive feedback.” With each passing year, experimental observations further undermine the claim of a large positive feedback from water. In fact, observations suggest that the feedback is close to zero and may even be negative. That is, water vapor and clouds may actually diminish the already small global warming expected from CO2, not amplify it. The evidence here comes from satellite measurements of infrared radiation escaping from the earth into outer space, from measurements of sunlight reflected from clouds and from measurements of the temperature the earth’s surface or of the troposphere, the roughly 10 km thick layer of the atmosphere above the earth’s surface that is filled with churning air and clouds, heated from below at the earth’s surface, and cooled at the top by radiation into space.

When the IPCC gets to a forecast of 3-5C warming over the next century (in which CO2 concentrations are expected to roughly double), it is in two parts.  As professor Happer relates, only about 1C of this is directly from the first order effects of more Co2.  This assumption of 1C warming for a doubling of Co2 is relatively stable across both scientists and time, except that the IPCC actually reduced this number a bit between their 3rd and 4th reports.

They get from 1C to 3C-5C with feedback.  Here is how feedback works.

Lets say the world warms 1 degree.  Lets also assume that the only feedback is melting ice and albedo, and that for every degree of warming, the lower albedo from melted ice reflecting less sunlight back into space adds another 0.1 degree of warming.  But this 0.1 degree extra warming would in turn melt a bit more ice, which would result in 0.01 degree 3rd order warming.  So the warming from an initial 1 degree with such 10% feedback would be 1+0.1+0.01+0.001 …. etc.   This infinite series can be calculated as   dT * (1/(1-g))  where dT is the initial first order temperature change (in this case 1C) and g is the percentage that is fed back (in this case 10%).  So a 10% feedback results in a gain or multiplier of the initial temperature effect of 1.11 (more here).

So how do we get a multiplier of 3-5 in order to back into the IPCC forecasts?  Well, using our feedback formula backwards and solving for g, we get feedback percents of 67% for a 3 multiplier and 80% for a 5 multiplier.  These are VERY high feedbacks for any natural physical system short of nuclear fission, and this issue is the main (but by no means only) reason many of us are skeptical of catastrophic forecasts.

[By the way, to answer past criticisms, I know that the models do not use this simplistic feedback methodology in their algorithms.  But no matter how complex the details are modeled, the bottom line is that somewhere in the assumptions underlying these models, a feedback percent of 67-80% is implicit]

For those paying attention, there is no reason that feedback should apply in the future but not in the past.  Since the pre-industrial times, it is thought we have increased atmospheric Co2 by 43%.  So, we should have seen, in the past, 43% of the temperature rise from a doubling, or 43% of 3-5C, which is 1.3C-2.2C.  In fact, this underestimates what we should have seen historically since we just did a linear interpolation.  But Co2 to temperature is a logarithmic diminishing return relationship, meaning we should see faster warming with earlier increases than with later increases.  Never-the-less, despite heroic attempts to posit some offsetting cooling effect which is masking this warming, few people believe we have seen any such historic warming, and the measured warming is more like 0.6C.  And some of this is likely due to the fact that the solar activity was at a peak in the late 20th century, rather than just Co2.

I have a video discussing these topics in more depth:

This is the bait and switch of climate alarmism.  When pushed into the corner, they quickly yell “this is all settled science,”  when in fact the only part that is fairly well agreed upon is the 1C of first order warming from a doubling.  The majority of the warming, the amount that converts the forecast from nuisance to catastrophe, comes from feedback which is very poorly understood and not at all subject to any sort of consensus.

I have often written warming about the difficulty of modeling complex systems.  My mechanical engineering degree was focused on the behavior and modeling of dynamic systems.  Since then, I have spent years doing financial, business, and economic modeling.  And all that experienced has taught me humility, as well as given me a good knowledge of where modelers tend to cheat.

Al Gore has argued that we should trust long-term models, because Wall Street has used such models successfully for years  (I am not sure he has been using this argument lately, lol).  I was immediately skeptical of this statement.  First, Wall Street almost never makes 100-year bets based on models (they may be investing in 30-year securities, but the bets they are making are much shorter term).  Second, my understanding of Wall Street history is that lower Manhattan is littered with the carcasses of traders who bankrupted themselves following the hot model of the moment.  It is ever so easy to create a correlation model that seems to back-cast well.  But no one has ever created one that holds up well going forward.

A reader sent me this article about the Gaussian copula, apparently the algorithm that underlay the correlation models Wall Streeters used to assess mortgage security and derivative risk.

Wall Streeters have the exact same problem that climate modelers have.  There is a single output variable they both care about (security price for traders, global temperature for modelers).  This variable’s value changes in a staggeringly complex system full of millions of variables with various levels of cross-correlation.  The modelers challenge is to look at the historical data, and to try to tease out correlation factors between their output variable and all the other input variables in an environment where they are all changing.

The problem is compounded because some of the input variables move on really long cycles, and some move on short cycles.  Some of these move in such long cycles that we may not even recognize the cycle at all.  In the end, this tripped up the financial modelers — all of their models derived correlation factors from a long and relatively unbroken period of home price appreciation.  Thus, when this cycle started to change, all the models fell apart.

Li’s copula function was used to price hundreds of billions of dollars’ worth of CDOs filled with mortgages. And because the copula function used CDS prices to calculate correlation, it was forced to confine itself to looking at the period of time when those credit default swaps had been in existence: less than a decade, a period when house prices soared. Naturally, default correlations were very low in those years. But when the mortgage boom ended abruptly and home values started falling across the country, correlations soared.

I never criticize people for trying to do an analysis with the data they have.  If they have only 10 years of data, that’s as far as they can run the analysis.  However, it is then important that they recognize that their analysis is based on data that may be way too short to measure longer term trends.

As is typical when models go wrong, early problems in the model did not cause users to revisit their assumptions:

His method was adopted by everybody from bond investors and Wall Street banks to ratings agencies and regulators. And it became so deeply entrenched—and was making people so much money—that warnings about its limitations were largely ignored.

Then the model fell apart. Cracks started appearing early on, when financial markets began behaving in ways that users of Li’s formula hadn’t expected. The cracks became full-fledged canyons in 2008—when ruptures in the financial system’s foundation swallowed up trillions of dollars and put the survival of the global banking system in serious peril.

A couple of lessons I draw out for climate models:

1. Limited data availability can limit measurement of long-term cycles.  This is particularly true in climate, where cycles can last hundreds and even thousands of years, but good reliable data on world temperatures is only available for our 30 years and any data at all for about 150 years.  Interestingly, there is good evidence that many of the symptoms we attribute to man-made global warming are actually part of climate cycles that go back long before man burned fossil fuels in earnest.  For example, sea levels have been rising since the last ice age, and glaciers have been retreating since the late 18th century.
2. The fact that models hindcast well has absolutely no predictive power as to whether they will forecast well
3. Trying to paper over deviations between model forecasts and actuals, as climate scientists have been doing for the last 10 years, without revisiting the basic assumptions of the model can be fatal.

A Final Irony

Do you like irony?  In the last couple of months, I have been discovering I like it less than I thought.  But here is a bit of irony for you anyway.  The first paragraph of Obama’s new budget read like this:

This crisis is neither the result of a normal turn of the business cycle nor an accident of history, we arrived at this point as a result of an era of profound irresponsibility that engulfed both private and public institutions from some of our largest companies’ executive suites to the seats of power in Washington, D.C.

As people start to deconstruct last year’s financial crisis, most of them are coming to the conclusion that the #1 bit of “irresponsibility” was the blind investment of trillions of dollars based on solely on the output of correlation-based computer models, and continuing to do so even after cracks appeared in the models.

The irony?  Obama’s budget includes nearly $700 billion in new taxes (via a cap-and-trade system) based solely on … correlation-based computer climate models that predict rapidly rising temperatures from CO2.  Climate models in which a number of cracks have appeared, but which are being ignored.

Postscript: When I used this comparison the other day, a friend of mine fired back that the Wall Street guys were just MBA’s, but the climate guys were “scientists” and thus presumably less likely to err.  I responded that I didn’t know if one group or the other was more capable (though I do know that Wall Street employs a hell of a lot of top-notch PhD’s).  But I did know that the financial consequences for Wall Street traders having the wrong model was severe, while the impact on climate modelers of being wrong was about zero.  So, from an incentives standpoint, I know who I would more likely bet on to try to get it right.

I have always been suspicious of climate models, in part because I spent some time in college trying to model chaotic dynamic systems, and in part because I have a substantial amount of experience with financial modeling.   There are a number of common traps one can fall into when modeling any system, and it appears to me that climate modelers are falling into most of them.

So a while back (before I even created this site) I was suspicious of this chart from the IPCC.  In this chart, the red is the “backcasting” of temperature history using climate models, the black line is the highly smoothed actuals, while the blue is a guess from the models as to what temperatures would have looked like without manmade forcings, particularly CO2.

As I wrote at the time:

I cannot prove this, but I am willing to make a bet based on my long, long history of modeling (computers, not fashion).  My guess is that the blue band, representing climate without man-made effects, was not based on any real science but was instead a plug.  In other words, they took their models and actual temperatures and then said “what would the climate without man have to look like for our models to be correct.”  There are at least four reasons I strongly suspect this to be true:

1. Every computer modeler in history has tried this trick to make their models of the future seem more credible.  I don’t think the climate guys are immune.
2. There is no way their models, with our current state of knowledge about the climate, match reality that well.
3. The first time they ran their models vs. history, they did not match at all.  This current close match is the result of a bunch of tweaking that has little impact on the model’s predictive ability but forces it to match history better.  For example, early runs had the forecast run right up from the 1940 peak to temperatures way above what we see today.
4. The blue line totally ignores any of our other understandings about the changing climate, including the changing intensity of the sun.  It is conveniently exactly what is necessary to make the pink line match history.  In fact, against all evidence, note the blue band falls over the century.  This is because the models were pushing the temperature up faster than we have seen it rise historically, so the modelers needed a negative plug to make the numbers look nice.

As you can see, the blue band, supposedly sans mankind, shows a steadily declining temperature. This never made much sense to me, given that, almost however you measure it, solar activity over the last half of the decade was stronger than the first half, but they show the natural forcings to be exactly opposite from what we might expect from this chart of solar activity as measured by sunspots (red is smoothed sunspot numbers, green is Hadley CRUT3 temperature).

By the way, there is a bit of a story behind this chart.  It was actually submitted by a commenter to this site of the more alarmist persuasion  (without the PDO bands), to try to debunk the link between temperature and the sun  (silly rabbit – the earth’ s temperature is not driven by the sun, but by parts per million changes in atmospheric gas concentrations!).  While the sun still is not the only factor driving the mercilessly complex climate, clearly solar activity in red was higher in the latter half of the century when temperatures in green were rising.  Which is at least as tight as the relation between CO2 and the same warming.

Anyway, why does any of this matter?  Skeptics have argued for quite some time that climate models assume too high of a sensitivity of temperature to CO2 — in other words, while most of us agree that Co2 increases can affect temperatures somewhat, the models assume temperature to be very sensitive to CO2, in large part because the models assume that the world’s climate is dominated by positive feedback.

One way to demonstrate that these models may be exaggerated is to plot their predictions backwards.  A relationship between Co2 and temperature that exists in the future should hold in the past, adjusting for time delays  (in fact, the relationship should be more sensitive in the past, since sensitivity is a logarithmic diminishing-return curve).  But projecting the modelled sensitivities backwards (with a 15-year lag) result in ridiculously high predicted historic temperature increases that we simply have never seen.  I discuss this in some depth in my 10 minute video here, but the key chart is this one:

You can see the video to get a full explanation, but in short, models that include high net positive climate feedbacks have to produce historical warming numbers that far exceed measured results.  Even if we assign every bit of 20th century warming to man-made causes, this still only implies 1C of warming over the next century.

So the only way to fix this is with what modelers call a plug.  Create some new variable, in this case “the hypothetical temperature changes without manmade CO2,” and plug it in.  By making this number very negative in the past, but flat to positive in the future, one can have a forecast that rises slowly in the past but rapidly in the future.

Now, I can’t prove that this is what was done.  In fact, I am perfectly willing to believe that modelers can spin a plausible story with enough jargon to put off most layman, as to how they created this “non-man” line and why it has been decreasing over the last half of the century.   I have a number of reasons to disbelieve any such posturing:

1. The last IPCC report spent about a thousand pages on developing the the “with Co2″ forecasts.  They spent about half a page discussing the “without Co2″ case.  These is about zero scientific discussion of how this forecast is created, or what the key elements are that drive it
2. The IPCC report freely admits their understanding of cooling factors is “low”
3. The resulting forecasts is WAY to good.  We will see this again in a moment.  But with such a chaotic system, your first reaction to anyone who shows you a back-cast that nicely overlays history almost exactly should be “bullshit.”  Its not possible, except with tuning and plugs
4. The sun was almost undeniably stronger in the second half of the 20th century than the first half.  So what is the countervailing factor that overcomes both the sun and CO2?

The IPCC does not really say what is making the blue line go down, it just goes down (because, as we can see now, it has to to make their hypothesis work).  Today, the main answer to the question of what might be offsetting warming  is “aerosols,” particularly sulfur and carbon compounds that are man-made pollutants (true pollutants) from burning fossil fuels.  The hypothesis is that these aerosols reflect sunlight back to space and cool the earth  (by the way, the blue line above in the IPCC report is explicitly only non-anthropogenic effects, so at the time it went down due to natural effects – the manmade aerosol thing is a newer straw to grasp).

But black carbon and aerosols have some properties that create some problems with this argument, once you dig into it.  First, there are situations where they are as likely to warm as to cool.  For example, one reason the Arctic has been melting faster in the summer of late is likely due to black carbon from Chinese coal plants that land on the ice and warm it faster.

The other issue with aerosols is that they disperse quickly.  Co2 mixes fairly evenly worldwide and remains in the atmosphere for years.  Many combustion aerosols only remain in the air for days, and so they tend to be concentrated regionally.   Perhaps 10-20% of the earth’s surface might at any one time have a decent concentration of man-made aerosols.  But for that to drive a, say, half degree cooling effect that offsets CO2 warming, that would mean that cooling in these aerosol-affected areas would have to be 2.5-5.0C in magnitude.  If this were the case, we would see those colored global warming maps with cooling in industrial aerosol-rich areas and warming in the rest of the world, but we just don’t see that.  In fact, the vast, vast majority of man-made aerosols can be found in the northern hemisphere, but it is the northern hemisphere that is warming much faster than the southern hemisphere.  If aerosols were really offsetting half or more of the warming, we should see the opposite, with a toasty south and a cool north.

All of this is a long, long intro to a guest post on WUWT by Bill Illis.  He digs into one of the major climate models, GISS model E, and looks at the back-casts from this model.  What he finds mirrors a lot of what we discussed above:

Blue is the GISS actual temperature measurement.  Red is the model’s hind-cast of temperatures.  You can see that they are remarkably, amazingly, staggeringly close.  There are chaotic systems we have been modelling for hundreds of years (e.g. the economy) where we have never approached the accuracy this relative infant of a science seems to achieve.

That red forecasts in the middle is made up of a GHG component, shown in orange, plus a negative “everything else” component, shown in brown.  Is this starting to seem familiar?  Does the brown line smell suspiciously to anyone else like a “plug?”  Here are some random thoughts inspired by this chart:

1. As with any surface temperature measurement system, the GISS system is full of errors and biases and gaps.  Some of these their proprietors would acknowledge, and such have been pointed out by outsiders.  Never-the-less, the GISS metric is likely to have an error of at least a couple tenths of a degree.  Which means the climate model here is perfectly fitting itself to data that isn’t even likely correct.  It is fitting closer to the GISS temperature number than the GISS temperature number likely fits to the actual world temperature anomaly, if such a thing could be measured directly.  Since the Hadley Center or the satellite guys at UAH and RSS get different temperature histories for the last 30-100 years, it is interesting that the GISS model exactly matches the GISS measurement but not these others.  Does that make anyone suspicious?  When the GISS makes yet another correction of its historical data, will the model move with it?
2. As mentioned before, the sum total of time spent over the last 10 years trying to carefully assess the forcings from other natural and man-made effects and how they vary year-to-year is minuscule compared to the time spent looking at CO2.  I don’t think we have enough knowledge to draw the Co2 line on this chart, but we CERTAINLY don’t have knowledge to draw the “all other” line (with monthly resolution, no less!).
3. Looking back over history, it appears the model is never off by more than 0.4C in any month, and never goes more than about 10 months before re-intersecting the “actual” line.  Does it bother anyone else that this level of precision is several times higher than the model has when run forward?  Almost immediately, the model is more than 0.4C off, and goes years without intercepting reality.

I have written a number of times about the “global warming accelerating” meme.  The evidence is nearly irrefutable that over the last 10 years, for whatever reason, the pace of global warming has decelerated (click below to enlarge)

This is simply a fact, though of course it does not necessarily “prove” that the theory of catastrophic anthropogenic global warming is incorrect.  Current results continue to be fairly consistent with my personal theory, that man-made CO2 may add 0.5-1C to global temperatures over the next century (below alarmist estimates), but that this warming may be swamped at times by natural climactic fluctuations that alarmists tend to under-estimate.

Anyway, in this context, I keep seeing stuff like this headline in the WaPo

Scientists:  Pace of Climate change Exceeds Estimates

This headline seems to clearly imply that the measured pace of actual climate change is exceeding previous predictions and forecasts.   This seems odd since we know that temperatures have flattened recently.  Well, here is the actual text:

The pace of global warming is likely to be much faster than recent predictions, because industrial greenhouse gas emissions have increased more quickly than expected and higher temperatures are triggering self-reinforcing feedback mechanisms in global ecosystems, scientists said Saturday.

“We are basically looking now at a future climate that’s beyond anything we’ve considered seriously in climate model simulations,” Christopher Field, founding director of the Carnegie Institution’s Department of Global Ecology at Stanford University, said at the annual meeting of the American Association for the Advancement of Science.

So in fact, based on the first two paragraphs, in true major media tradition, the headline is a total lie.  In fact, the correct headline is:

“Scientists Have Raised Their Forecasts for Future Warming”

Right?  I mean, this is all the story is saying, is that based on increased CO2 production, climate scientists think their forecasts of warming should be raised.  This is not surprising, because their models assume a direct positive relationship between CO2 and temperature.

The other half of the statement, that “higher temperatures are triggering self-reinforcing feedback mechanisms in global ecosystems” is a gross exaggeration of the state of scientific knowledge.  In fact, there is very little good understanding of climate feedback as a whole.  While we may understand individual pieces – ie this particular piece is a positive feedback – we have no clue as to how the whole thing adds up.  (see my video here for more discussion of feedback)

In fact, I have always argued that the climate models’ assumptions of strong positive feedback (they assume really, really high levels) is totally unrealistic for a long-term stable system.  In fact, if we are really seeing runaway feedbacks triggered after the less than one degree of warming we have had over the last century, it boggles the mind how the Earth has staggered through the last 5 billion years without a climate runaway.

All this article is saying is “we are raising our feedback assumptions higher than even the ridiculously high assumptions we were already using.”  There is absolutely no new confirmatory evidence here.

But this creates a problem for alarmists

For you see, their forecasts have consistently demonstrated themselves to be too high.  You can see above how Hansen’s forecast to Congress 20 years ago has played out (and the Hansen A case was actually based on a CO2 growth forecast that has turned out to be too low).  Lucia, who tends to be scrupulously fair about such things, shows the more recent IPCC models just dancing on the edge of being more than 2 standard deviations higher than actual measured results.

But here is the problem:  The creators of these models are now saying that actual CO2 production, which is the key input to their model, is far exceeding their predictions.  So, presumably, if they re-ran their predictions using actual CO2 data, they would get even higher temperature forecasts. Further, they are saying that the feedback multiplier in their models should be higher as well.  But the forecasts of their models are already high vs. observations — this will even cause them to diverge further from actual measurements.

So here is the real disconnect of the model:  If you tell me that modelers underestimated the key input (CO2) in their models,  and have so far overestimated the key output (Temperature), I would have said the conclusion to this article is that climate sensitivity must be lower than what was embedded in the models.  But they are saying exactly the opposite.  How is this possible?

Postscript: I hope readers understand this, but it is worth saying because clearly reporters do not understand this:  There is no way that climate change from CO2 can be accelerating if global warming is not accelerating.  There is no mechanism I have ever heard by which CO2 can change the climate without the intermediate step of raising temperatures.  Co2–>temperature increase–>changes in the climate.

Update: Chart originally said 1998 forecast.  Has been corrected to 1988.

Update#2: I am really tired of having to re-explain the choice of using Hansen’s “A” forecast, but I will do it again.  Hansen had forecasts A, B, C, with A being based on more CO2 than B, and B with more CO2 than C.  At the time, Hansen said he thought the A case was extreme.  This is then used by his apologists to say that I am somehow corrupting Hansen’s intent or taking him out of context by using the A case, because Hansen himself at the time said the A case was probably high.

But the only difference between A, B, and C were not the model assumptions of climate sensitivity or any other variable — they only differed in the amount of Co2 growth and the number of volcano eruptions (which have a cooling effect via aerosols).  We can go back and decide for ourselves which case turned out to be the most or least conservative.   As it turns out, all three cases UNDERESTIMATED the amount of CO2 man produced in the last 20 years.  So, we should not really use any of these lines as representative, but Scenario A is by far the closest.  The other two are way, way below our actual CO2 history.

The people arguing to use, say, the C scenario for comparison are being disingenuous.  The C scenario, while closer to reality in its temperature forecast, was based on an assumption of a freeze in Co2 production levels, something that obviously did not occur.

Arnold Kling via Cafe Hayek on macro-economic modelling:

We badly want macroeconometrics to work.  If it did, we could resolve bitter theoretical disputes with evidence.  We could achieve better forecasting and control of the economy.  Unfortunately, the world is not set up to enable macroeconometrics to work.  Instead, all macroeconometric models are basically simulation models that use data for calibration purposes.  People judge these models based on their priors for how the economy works.  Imposing priors related to rational expectations does not change the fact that macroeconometrics provides no empirical information to anyone except those who happen to share all of the priors of the model-builder.