Coyote Blog

It is possible for the theory that the climate has a high sensitivity to CO2 (ie that a doubling of CO2 concentrations will lead to global temperature increases of 2.5C or higher) to be correct while still having ten years of flat to declining surface temperatures.  That is because Earth’s great surface heat reservoir is the oceans, not the atmosphere, and so the extra heat from the greenhouse effect could be going into the oceans rather than into near-surface air.

However, it is NOT possible, as least as we (and by “we” I mean everyone, skeptics and alarmists alike) understand the climate, for CO2 to be holding a lot of extra heat and it not show up either in surface temperatures or ocean heat content.  The greenhouse effect does not turn off — its effects may be masked in the chaotic weather systems, perhaps for years, but if the climate sensitivity to CO2 is really as high as the IPCC says, there has to be new heat going somewhere.

That is why a number of folks, including Roger Pielke, have argued for years that the best way to monitor whether we are truly seeing an additional forcing or heat input to the climate is to look at ocean heat content.  Understand, changes in ocean heat content would not tell us where the heat is coming from (e.g. anthropogenic CO2 vs. solar activity).  But it is pretty much impossible for us to imagine a new heat input to the Earth’s surface, like greenhouse gas forcing from anthropogenic CO2, without observing its effect in ocean heat content.

I will turn over the story to Jo Nova, who has a good post on the new tools we have to measure ocean heat content since 2003.  In short, though, we have seen no rise in measured ocean heat content since we started measuring with technology dedicated to the task.  This means, if those who believe the climate has a high sensitivity to CO2 are right, something like 50,000 quintillion joules of energy have gone missing since 2003.  This is the “missing heat”, and though climate scientists sometimes discuss it in private, they almost never do so in public.  Ocean heat is the dinosaur bone fossil that the creationists simply don’t want to acknowledge.

Read the whole thing.  It is very simple and well-written and written.

PS- note in the chart above, the y-axis is mis-labelled a bit, it is not absolute heat content but changes in heat content from some base period.  Scientists call this the “anomaly.”  This is typical of many climate charts.

I feel the need to reproduce this email in its entirety.  Here is Phil Jones actively hoping the world will warm (an outcome he has publicly stated would be catastrophic).  The tribalism has gotten so intense that it is more important for his alarmist tribe to count coup on the skeptics than to hope for a good outcome for the Earth.

>From: Phil Jones [mailto:p.jones@uea.ac.uk]
>Sent: 05 January 2009 16:18
>To: Johns, Tim; Folland, Chris
>Cc: Smith, Doug; Johns, Tim
>Subject: Re: FW: Temperatures in 2009
>
>
>   Tim, Chris,
>     I hope you're not right about the lack of warming lasting
>   till about 2020. I'd rather hoped to see the earlier Met Office
>   press release with Doug's paper that said something like -
>   half the years to 2014 would exceed the warmest year currently on
> record, 1998!
>     Still a way to go before 2014.
>
>     I seem to be getting an email a week from skeptics saying
>   where's the warming gone. I know the warming is on the decadal
>   scale, but it would be nice to wear their smug grins away.
>
>     Chris - I presume the Met Office
> continually monitor the weather forecasts.
>    Maybe because I'm in my 50s, but the language used in the forecasts seems
>    a bit over the top re the cold. Where I've been for the last 20
> days (in Norfolk)
>    it doesn't seem to have been as cold as the forecasts.
>
>     I've just submitted a paper on the UHI for London - it is 1.6 deg
> C for the LWC.
>   It comes out to 2.6 deg C for night-time minimums. The BBC forecasts has
>   the countryside 5-6 deg C cooler than city centres on recent nights.
> The paper
>   shows the UHI hasn't got any worse since 1901 (based on St James Park
>   and Rothamsted).
>
>   Cheers
>   Phil

Is this better or worse than rooting for a bad economy to get your favorite politicians elected?  Anthony Watt has more in this same tone, showing how climate scientists were working to shift messages and invent new science to protect the warming hypothesis.

The last part about the UHI (urban heat island) study is interesting.  I don’t remember this study.  But it is interesting that he accepts a UHI of as high as 1.6C (my son and I found evening UHI in Phoenix around 4-6C, about in line with his London results).    It looks like he is trying to say that UHI should not matter to temperature measurement, since it has not changed in London since 1900  (a bias in temperature measurement that does not change does not affect the temperature anomaly, which is what tends to be important).  But the point is that many other temperature stations in the Hadley CRUT data base are in cities that are now large today but were much smaller than London in 1900 (Tucson is a great example).  In these cases, there is a changing measurement bias that can affect the anomaly, so I am not sure what Jones was trying to get at.

In the Climategate 2.0 emails, Michael Mann confirms what we already knew – there is absolutely no tolerance for dissent, even the scientifically thoughtful sort, among climate alarmists.  Writing about their mother-site, RealClimate, Mann says

 I suspect you’ve both seen the latest attack against [Keith Briffa's] Yamal work by McIntyre.    Gavin and I (having consulted also w/ Malcolm) are wondering what to make of this, and what sort of response—if any—is necessary and appropriate. So far, we’ve simply deleted  all of the attempts by McIntyre and his minions to draw attention to this at RealClimate.

Note that the knee-jerk, default action is to purge, hide, and delete criticism, even before it is understood.  They make absolutely no attempt to understand the argument, reading it just enough to know that it is critical and therefore must be deleted.  The second action is to find someone to refute it, again even before the critique is understood.  It is critical of us so it must be wrong.  QED.

Here is one of the original McIntyre posts where he outlines the problem he found in Briff’s work.  He argues that the findings in Briffa are not very robust, as substitution of a larger sample of trees (this is a tree-ring temperature reconstruction study, like the hockey stick) from the same area for Briffa’s apparently small, hand-picked sample have an astoundingly large effect on the study’s findings (the red study line below, McIntyre’s reconstruction in black).

Perhaps McIntyre was missing something (though over the 2 years since no one involved has suggested what that might be).  But the tone of the article is certainly scientific and thoughtful.   It has no resemblance to the unscientific polemic that alarmists often use as an excuse to excise skeptical comments from their web sites.

James Hansen, head of NASA’s GISS and technical adviser on An Inconvenient Truth, wrote recently

Thus there is no need to equivocate about the summer heat waves in Texas in 2011 and Moscow in 2010, which exceeded 3σ – it is nearly certain that they would not have occurred in the absence of global warming. If global warming is not slowed from its current pace, by mid-century 3σ events will be the new norm and 5σ events will be common.

This statement alone should be enough for any thoughtful person who here-to-fore has bought in to global warming hysteria out of vague respect for “science” to question their beliefs.

First, he is basically arguing that a 3σ event proves (makes it “nearly certain”) that some shift has occurred in the underlying process.  In particular, he is arguing that one single sample’s value is due to a mean shift in the system.  I don’t have a ton of experience in process control and quality, but my gut feel is that a 3σ event can be just that, a 3σ event.  One should expect a 3σ event to occur, on average, once in every 300 samples of a system with a normal distribution of outcomes.

Second, and a much bigger problem, is that Hansen is gaming the sampling process.  First, he is picking an isolated period.  Let’s say, to be generous, that this 3σ event stretched over 3 months and was unprecedented in the last century.  But there are 400 3-month periods in the last hundred years.  So he is saying in these two locations there was a 3σ temperature excursion once out of 400 samples.  Uh, ok.  Pretty much what one would expect.

Or, if you don’t like the historic approach, lets focus on just this year.  He treats Moscow and Texas like they are the only places being sampled, but in fact they are two of hundreds or even thousands of places on Earth.  Since he does not focus on any of the others, we can assume these are the only two that have so-called 3σ temperature events this summer.

It’s hard to know how large to define “Texas”  (since the high temperatures did not cover the whole state) or “Moscow” (since clearly the high temperatures likely reached beyond the suburbs of just that city).

Let’s say that the 3σ event occurred in a circular area 500km in diameter.  That is an area of 196,250 sq km each.  But the land surface area of the Earth (we will leave out the oceans for now since heat waves there don’t tend to make the headlines) is about 150 million sq km.   This means that each of these areas represent about 1/764th of the land surface area of the Earth.  Or said another way, this summer there were 764 500km diameter land areas we could sample, and 2 had 3σ events.  Again, exactly as expected.

In other words, Hansen’s that something unusual is going on in the system is that he found two 3σ events that happened once every 300 or 400 samples.  You feeling better about the science yet?

Luboš Motl has a more sophisticated discussion of the same statement, and gets into other issues with Hansen’s statement.

Postscript:  One other issue — the mean shift in temperatures over the last 30 years has been, at most, about 0.5C  (a small number compared to the Moscow temperature excursion from the norm).  Applying that new mean and the historic standard deviation, my guess is that the Moscow event would have still been a 2.5σ event.  So its not clear how an event that would have been unlikely even with global warming but slightly more unlikely without global warming tells us much of anything about changes in the underlying system, or how Hansen could possible assign blame for the even with near certainty to anthropogenic CO2.

For those who have read my climate work or seen the video, the key question in climate science revolves around the feedback effects in the climate system to Co2 warming.

Skeptics, like alarmists, generally agree that a doubling of Co2 concentrations might warm the Earth about a degree Celsius, absent any other effects.  But we can imagine all sorts of feedback effects, the most important of which are in water vapor and cloud formation.  Warming that forms more clouds might have negative feedback, as clouds offset some of the warming.  Warming that increases humidity could lead to more warming, as water vapor is a strong greenhouse gas.

The difference, then, between minor warming and catastrophe is in the feedbacks, and most importantly in clouds and water vapor.  All the research the government is funding on whether warming will cause sterility in tree frogs is tangential to this key question.

And this question is far from decided.  I won’t get into all the arguments here, but to the extent there is any consensus, it is that man’ CO2 is probably causing some warming.  Whether this is a catastrophe or a nuisance depends on feedbacks which are not well understood.

This week there has been a lot of interesting back and forth over a paper by Roy Spencer several months ago arguing that cloud feedback was negative and would serve to limit the total amount of man-made warming.  Just how central this issue is can be seen in the fuss this paper has caused, including editors forced to resign for even daring to publish such heresy, and the speed with which a counter-paper flew through peer review.

I won’t get into the depths of this, except to show two charts.  The first is from Dessler in the alarmist camp, the second is the same chart but using a different data series.  I won’t explain the axes,  just trust the relationship between these two variables is key to diagnosing the size and direction of feedback.

So we get opposite results (the slope of the regression) simply by using temperature and radiative flux data from to different agencies.  And note how thin the fit is in both — basically drawing a line through a cloud.  Neither of these likely has an R-squared higher than about .05.

So there you have it, the most important question in climate – really, the only important question associated with anthropogenic global warming.  Settled science, indeed.

Today in Forbes, I have an article bringing the layman up to speed on Henrik Svensmark and this theory of cosmic ray cloud seeding.  Since his theory helped explain some 20th century warming via natural effects rather than anthropogenic ones, he and fellow researchers have face an uphill climb even getting funding to test his hypothesis.  But today, CERN in Geneva has released study results confirming most of Svensmark’s hypothesis, though crucially, it is impossible to infer from this work how much of 20th century temperature changes can be traced to the effect (this is the same problem global warming alarmists face — CO2 greenhouse warming can be demonstrated in a lab, but its hard to figure out its actual effect in a complex climate system).

From the article:

Much of the debate revolves around the  role of the sun, and though holding opposing positions, both skeptics and alarmists have had good points in the debate.  Skeptics have argued that it is absurd to downplay the role of the sun, as it is the energy source driving the entire climate system.  Michael Mann notwithstanding, there is good evidence that unusually cold periods have been recorded in times of reduced solar activity, and that the warming of the second half of the 20th century has coincided with a series of unusually strong solar cycles.

Global warming advocates have responded, in turn, that while the sun has indeed been more active in the last half of the century, the actual percentage change in solar irradiance is tiny, and hardly seems large enough to explain measured increases in temperatures and ocean heat content.

And thus the debate stood, until a Danish scientist named Henrik Svensmark suggested something outrageous — that cosmic rays might seed cloud formation.  The implications, if true, had potentially enormous implications for the debate about natural causes of warming.

When the sun is very active, it can be thought of as pushing away cosmic rays from the Earth, reducing their incidence.  When the sun is less active, we see more cosmic rays.  This is fairly well understood.  But if Svensmark was correct, it would mean that periods of high solar output should coincide with reduced cloud formation (due to reduced cosmic race incidence), which in turn would have a warming effect on the Earth, since less sunlight would be reflected back into space before hitting the Earth.

Here was a theory, then, that would increase the theoretical impact on climate of an active sun, and better explain why solar irradiance changes might be underestimating the effect of solar output changes on climate and temperatures.

I go on to discuss the recent CERN CLOUD study and what it has apparently found.

For a while, I have criticized the practice both in climate and economics of using computer models to increase our apparent certainty about natural phenomenon.   We take shaky assumptions and guesstimates of certain constants and natural variables and plug them into computer models that produce projections with triple-decimal precision.   We then treat the output with a reverence that does not match the quality of the inputs.

I have had trouble explaining this sort of knowledge laundering and finding precisely the right words to explain it.  But this week I have been presented with an excellent example from climate science, courtesy of Roger Pielke, Sr.  This is an excerpt from a recent study trying to figure out if a high climate sensitivity to CO2 can be reconciled with the lack of ocean warming over the last 10 years (bold added).

“Observations of the sea water temperature show that the upper ocean has not warmed since 2003. This is remarkable as it is expected the ocean would store that the lion’s share of the extra heat retained by the Earth due to the increased concentrations of greenhouse gases. The observation that the upper 700 meter of the world ocean have not warmed for the last eight years gives rise to two fundamental questions:

1. What is the probability that the upper ocean does not warm for eight years as greenhouse gas concentrations continue to rise?
2. As the heat has not been not stored in the upper ocean over the last eight years, where did it go instead?

These question cannot be answered using observations alone, as the available time series are too short and the data not accurate enough. We therefore used climate model output generated in the ESSENCE project, a collaboration of KNMI and Utrecht University that generated 17 simulations of the climate with the ECHAM5/MPI-OM model to sample the natural variability of the climate system. When compared to the available observations, the model describes the ocean temperature rise and variability well.”

Pielke goes on to deconstruct the study, but just compare the two bolded statements.  First, that there is not sufficiently extensive and accurate observational data to test a hypothesis.  BUT, then we will create a model, and this model is validated against this same observational data.  Then the model is used to draw all kinds of conclusions about the problem being studied.

This is the clearest, simplest example of certainty laundering I have ever seen.  If there is not sufficient data to draw conclusions about how a system operates, then how can there be enough data to validate a computer model which, in code, just embodies a series of hypotheses about how a system operates?

A model is no different than a hypothesis embodied in code.   If I have a hypothesis that the average width of neckties in this year’s Armani collection drives stock market prices, creating a computer program that predicts stock market prices falling as ties get thinner does nothing to increase my certainty of this hypothesis  (though it may be enough to get me media attention).  The model is merely a software implementation of my original hypothesis.  In fact, the model likely has to embody even more unproven assumptions than my hypothesis, because in addition to assuming a causal relationship, it also has to be programmed with specific values for this correlation.

This is not just a climate problem.  The White House studies on the effects of the stimulus were absolutely identical.  They had a hypothesis that government deficit spending would increase total economic activity.  After they spent the money, how did they claim success?  Did they measure changes to economic activity through observational data?  No, they had a model that was programmed with the hypothesis that government spending increased job creation, ran the model, and pulled a number out that said, surprise, the stimulus created millions of jobs (despite falling employment).  And the press reported it like it was a real number.

There may be something interesting coming out in the climate front over the next few weeks from CERN.

Years ago, a researcher named Henrik Svensmark developed a hypothesis that cosmic rays can seed cloud formation, and thus when there are more cosmic rays, there may be more clouds.  This is interesting because it may act as a sort of solar amplification.

Changes in the sun’s output through varying solar cycles are measurable, but seem to some scientists to be too small to drive substantial temperature changes on Earth.  But a more active sun tends to blow cosmic rays away from the Earth, thus reducing their incidence.  Therefore, if a more active sun reduced cooling clouds, and a less active sun increased cooling clouds, this might explain a larger effect for the sun.

I have avoided discussing Svensmark much, since the evidence seemed thin, though several labs recently have confirmed his hypothesis, at least in the laboratory.  But Svensmark is definitely a topic among some climate skeptics.  The reason is that higher solar activity levels  in the second half of the twentieth century coincided with much of the 20th century warming that is blamed on manmade CO2.  Svensmark’s theory, if true, might force scientists to apportion more of the historic warming to natural causes, thus reducing the estimated sensitivity of the climate to man-made CO2.

But apparently the CERN lab has been undertaking a substantial study to confirm or deny Svensmark’s hypothesis.  The results have not been released, but skeptics are beginning to anticipate that CERN’s work has confirmed the hypothesis of cosmic ray cloud seeding.  Why?  Because of the dog that did not bark, or rather was told not to bark.

Via Watts Up With That:

CERN Director General Rolf-Dieter Heuer told Welt Online that the scientists should refrain from drawing conclusions from the latest experiment.

“I have asked the colleagues to present the results clearly, but not to interpret them,” reports veteran science editor Nigel Calder on his blog. Why?

Because, Heuer says, “That would go immediately into the highly political arena of the climate change debate. One has to make clear that cosmic radiation is only one of many parameters.”

Skeptics are suggesting that had CERN disproved Svensmark, and thus protected the hypothesis that CO2 is driving most current warming, they would not have hesitated to draw exactly this conclusion in public.  Only a finding considered more consistent with the skeptical position would cause them to go silent, trying to avoid the taint from the politically correct intelligentsia that would come from even partially confirming a skeptic talking point.

I have to agree that Heuer’s comments seem to telegraph the result.  I have read a ton of global warming related studies.  And every single one I have read that has ever published negative results vis a vis the hypothesis of catastrophic manmade global warming has felt obligated to put in a sentence at the end that says something like “but of course this does not in any way disprove the hypothesis of anthropogenic global warming and we fully support that hypothesis despite these results.”  The absolute fear of becoming an outcast for coming up with the “wrong” result is palpable in reading these papers, sort of like the very careful language a report in Soviet Russia might have used to even mildly criticize some aspect of the state.  Of course, no such disclaimer can be found with narrow positive results – these are always immediately extrapolated  (in fact over-extrapolated in press releases) to be the final nail in the coffin proving once and for all that man is changing the climate in dire ways.

Here is the current global warming hype process as it exists today:

1. Identify a 2 or 3 sigma weather event.  Since there are 365 days in the year and hundreds of different regions in the world, the laws of probability say that some event in the tail of the normal distribution (local high, local low, local flood, local drought, local snow, local tornado, local hurricane, etc) should be regularly occurring somewhere.
2. Play weather event all over press, closely linked as often as possible with supposition that this is due to manmade CO2.  If the connection to global warming is too outlandish to make with a straight face (e.g. cold weather) use term “climate change” or “climate disruption” instead of global warming.
3. Skeptics will point to actual data that this event is not part of a long term trend, e.g. there is no rise in tornado activity correlated with 20th century rise in temperatures so blaming one year of high tornadoes on global warming makes no sense.    Ignore this.
4. Peer reviewed literature will emerge 6-12 months later demonstrating that the event was not likely due to man-made global warming.  Ignore this as well.  Never, ever go back and revisit failed catastrophic predictions.
5. Repeat

Last year’s Russian heat wave is a classic example.  Here is an example of the hype and the tie to man-made global warming in Time.  And here, 12 months later, is the study saying that weather was just weather:

Reference
Dole, R., Hoerling, M., Perlwitz, J., Eischeid, J., Pegion, P., Zhang, T., Quan, X.-W., Xu, T. and Murray, D. 2011. Was there a basis for anticipating the 2010 Russian heat wave? Geophysical Research Letters38: 10.1029/2010GL046582.

Background
The authors write that “the 2010 summer heat wave in western Russia was extraordinary, with the region experiencing the warmest July since at least 1880 and numerous locations setting all-time maximum temperature records.” And as a result, they say that “questions of vital societal interest are whether the 2010 Russian heat wave might have been anticipated, and to what extent human-caused greenhouse gas emissions played a role.”

What was learned
The nine U.S. researchers determined that “analysis of forced model simulations indicates that neither human influences nor other slowly evolving ocean boundary conditions contributed substantially to the magnitude of the heat wave.” In fact, they say that the model simulations provided “evidence that such an intense event could be produced through natural variability alone.” Similarly, on the observation front, they state that “July surface temperatures for the region impacted by the 2010 Russian heat wave show no significant warming trend over the prior 130-year period from 1880-2009,” noting, in fact, that “a linear trend calculation yields a total temperature change over the 130 years of -0.1°C.” In addition, they indicate that “no significant difference exists between July temperatures over western Russia averaged for the last 65 years (1945-2009) versus the prior 65 years (1880-1944),” and they state that “there is also no clear indication of a trend toward increasing warm extremes.” Last of all, they say that although there was a slightly higher variability in temperature in the latter period, the increase was “not statistically significant.”

Not sure I find the computer model work comforting one way or the other but the complete lack of any observational trend seems compelling.

My article this week at Forbes.com digs into some fundamental flaws of climate models

When I looked at historic temperature and CO2 levels, it was impossible for me to see how they could be in any way consistent with the high climate sensitivities that were coming out of the IPCC models.  Even if all past warming were attributed to CO2  (a heroic acertion in and of itself) the temperature increases we have seen in the past imply a climate sensitivity closer to 1 rather than 3 or 5 or even 10  (I show this analysis in more depth in this video).

My skepticism was increased when several skeptics pointed out a problem that should have been obvious.  The ten or twelve IPCC climate models all had very different climate sensitivities — how, if they have different climate sensitivities, do they all nearly exactly model past temperatures?  If each embodies a correct model of the climate, and each has a different climate sensitivity, only one (at most) should replicate observed data.  But they all do.  It is like someone saying she has ten clocks all showing a different time but asserting that all are correct (or worse, as the IPCC does, claiming that the average must be the right time).

The answer to this paradox came in a 2007 study by climate modeler Jeffrey Kiehl.  To understand his findings, we need to understand a bit of background on aerosols.  Aerosols are man-made pollutants, mainly combustion products, that are thought to have the effect of cooling the Earth’s climate.

What Kiehl demonstrated was that these aerosols are likely the answer to my old question about how models with high sensitivities are able to accurately model historic temperatures.  When simulating history, scientists add aerosols to their high-sensitivity models in sufficient quantities to cool them to match historic temperatures.  Then, since such aerosols are much easier to eliminate as combustion products than is CO2, they assume these aerosols go away in the future, allowing their models to produce enormous amounts of future warming.

Specifically, when he looked at the climate models used by the IPCC, Kiehl found they all used very different assumptions for aerosol cooling and, most significantly, he found that each of these varying assumptions were exactly what was required to combine with that model’s unique sensitivity assumptions to reproduce historical temperatures.  In my terminology, aerosol cooling was the plug variable.

(via Popehat) one of the writers at Balloon Juice offers this test of a “reasonable” Conservative blog

1) Do you believe in evolution?

2) Do you believe that the average temperature on earth has increased over the past 30 years?

A few semi-random thoughts:

• Count me as a yes for both
• Is the best test of the likely reasonableness of a political blog really to ask two questions about science that such a blog might never even touch?  This is not an entirely rhetorical question — just the other day I linked the data that suggested that asking your date about beer might be the best way to test their views on sex.  Sometimes odd cross-correlations exist, but I don’t think these would be my first test
• I find the Left’s obsession with evolution as a litmus test for political thought to be funny, as the theory of evolution is largely irrelevant to any political questions except fairly narrowly the question of teaching evolution in schools.   I find it funny as much of the Left does not believe in a science – micro economics (very specifically differentiated from macro) – that is also fairly old and well understood and is much more relevant to typical political blog discourse.  I had a debate on national TV a few weeks ago with a man who claimed, as many on the Left will, that raising the minimum wage will increase employment.   If we want to test blogs based on scientific questions, why wouldn’t a far more relevant question in public discourse be “do you believe demand curves slope down” or perhaps something like “do you believe breaking windows stimulates the economy?”
• The second test is not a bad test of any site writing about global warming and climate change.  I don’t know many science-based skeptics who would deny that global temperatures have likely increased over the last 30 years  (from a data base without UHI or alarmist manual adjustments or large data holes, the trend is something like 0.1C per decade).   I say “likely” because it could be argued that 0.1C is within the error bar of the measurement. Even so, this wouldn’t be my first test, even for climate sites
• I would tend to have four tests of the liberal and conservative sites I read
  • Is it interesting to read (after all, this is a freaking unpaid hobby)
  • Is the data-analysis-to-name-calling ratio fairly high
  • Are they willing to step out of team politics and question their own team from time to time
  • Do they have interesting perspectives on individual liberty.  I can plow through Marxist economic posts on progressive sites if from time to time they have a useful perspective on, say, indefinite detentions or gay marriage.  I can plow through some social Conservatism if they have useful posts on economics and fiscal policy.

This post from Nick Gillespie is sort of relevent, in which he talks about CPAC and social conservatives.  One line that struck me

A person’s choice of sexual partner in no way means he or she can’t be in favor of less spending on farm subsidies.

If I weeded out every blog that held some sort of view with which I disagree (or might even call “unreasonable”) I would be down to about 3 blogs in my reader.

I continue to be fascinated by the similarity between climate science and macro-economics.  Both study unbelievably complex multi-variable systems where we would really like to isolate the effect of one variable.  Because we only have one each of climates and economies  (we can define smaller subsets, but they are always going to be subject to boundary effects from the larger system) it is really hard to define good controlled experiments to isolate single variables.  And all of this is done in a highly charged political environment where certain groups are predisposed to believe their variable is the key element.

In this post by Russ Roberts, one could easily substitute “climate” for “economy” and “temperature” for “unemployment.”

Suppose the economy does well this year–growth is robust and unemployment falls. What is the reason for the improvement? Will it be because of the natural rebound of an economy after a downturn that has lasted longer than people thought? The impact of the stimulus finally kicking in? The psychological or real impact of extending the Bush tax cuts? The psychological or real impact of the November election results? The steady hand of Obama at the tiller? All of the above? Can any model of the economy pass the test and answer these questions?

The reason macroeconomics is not a science and not even scientific is that the question I pose above is not answerable. If the economy improves, there will be much talk about the reason. Data and evidence will be trotted out in support of the speaker’s viewpoint. But that is not science. We don’t have a way of distinguishing between those different theories or of giving them weights to measure their independent contribution.

I’m with Arnold Kling. This is a time for humility. It should be at the heart of our discipline. The people who yell the loudest and with the most certainty are the least trustworthy. And the reason for that goes back to Hayek. We can’t measure many of the things we would have to measure to have any reasonable amount of certainty about the chains of connection and causation.

I have heard it said that the only way nowadays to advance pure science is to be working on arcana like the first microsecond of the universe or behavior of the 9th dimension in string theory.   There is still room for a ton of useful work on the analysis, solution, and forecasting of complex multi-variable systems, even if it is just a Goedel-like proof of where the boundaries of our potential understanding can be drawn.

By the way, I wrote my own piece about the limits of macroeconomics here.

I obviously need to go out and buy an SUV to reverse this:

Phoenix-area temperatures could drop as low as the mid-20s early Tuesday morning, possibly breaking the record low temperature of 30 degrees set in 1911.

One aspect of the TSA debate I find hilarious as a libertarian is that we get to see yet another example of partisans switching sides on an issues based on whose team is in the White House.  Since when have Republicans had this deeply held concern about liberty and privacy vs. security against terrorism.  And now leftie Kevin Drum steps up to say that all the extract screening makes sense (to my college roommate Brink Lindsey:  Sorry, but the whole liberaltarian thing is a myth.  When in power, they seem to act just as authoritarian on social and civil rights issues as Conservatives).

Anyway, Drum is certainly not full-bore backing the TSA, but he does write

I hate the TSA screening process. Everyone hates the TSA screening process. You’d be crazy not to. It’s intrusive, annoying, and time-wasting. It treats us all like common criminals even though most of us are just ordinary schlubs trying to get on a plane and go somewhere.

But guess what? The fact that you personally are annoyed — you! an educated white-collar professional! — doesn’t mean that the process is idiotic. I’ve heard it called “security theater” so many times I’d be rich if I had a nickel for each time it popped up in my browser, but although the anti-TSA rants are often cathartic and amusing, they’ve never made much sense to me. All the crap that TSA goes through actually seems pretty clearly directed at improving the security of air travel.

The point is not, as implied by Drum, that current TSA screening isn’t protection against certain types of threats. Let’s be generous and assume that the TSA’s screening, generally concocted in a barn-door approach after someone tries a particular approach, is effective at catching the threats it is designed to catch.

The point is that nearly anyone with a room temperature IQ can think of 20 ways to attack an airplane that is not covered by the screening. If there are, say, a hundred imaginable threats, how much privacy do you want to give up to protect yourself from 35 of them?

For example, you know what is in the cargo hold below your seat? The US Mail. You know how much screening is performed on the US Mail? Zero. How hard would it be to wire up a package with a bomb and an altimeter, or perhaps just a noise sensor, and send it off airmail.  They screen the crap out of your bags and body and then throw them on the plane right next to a bunch of anonymous, unscrutinized cargo.  And that is just one example.

In 8th grade, my son won his science fair with this easy and fun project to measure the urban heat island effect around our city.  I know parents and kids alike can struggle to find a good project.  This is one that not only is interesting, but helps to prove the existence of a phenomenon that many climate alarmists work hard to deny.  Imagine a temperature measurement point in downtown Phoenix, which we found to be 7-10F hotter than the outlying areas just 30 miles away.

What did that thermometer read 100 years ago?  How much of measured global warming is due to this effect, particularly since our airport, the typical place where temperature records are based for large cities, is right in the center of town?

Anyway, we had to kluge together some stuff to make this work, but the Weather Shop now offers a simple kit. The site suggests keeping track of position in a log vs. time, which is what we did the first time and works just fine.  However, the second time through, we got fancy and also had a GPS logger.

Some scientists claim to be able to make room temperature ice (yes, I presume at 1 atm pressure).  Not sure what to make of it:

Earth’s climate is strongly influenced by the presence of particles of different shapes and origins — in the form of dust, ice and pollutants — that find their way into the lowest portion of the atmosphere, the troposphere. There, water adsorbed on the surface of these particles can freeze at higher temperatures than pure water droplets, triggering rain and snow.Researchers at Spain’s Centre d’Investigació en Nanociència i Nanotecnologia (CIN2) have studied the underlying mechanisms of water condensation in the troposphere and found a way to make artificial materials to control water condensation and trigger ice formation at room temperature. Described in the Journal of Chemical Physics, which is published by the American Institute of Physics, their work may lead to new additives for snowmaking, improved freezer systems, or new coatings that help grow ice for skating rinks.

The next step? The researchers’ goal now is to produce environmentally-friendly synthetic materials for efficiently inducing snow. “If water condenses in an ordered way, such as a hexagonal structure, on such surfaces at ambient conditions, the term ‘room temperature ice’ would be fully justified,” adds Verdaguer. “The solid phase, ice, would be produced by a surface effect rather than as a consequence of temperature. In the long term, we intend to prepare smart materials, ‘intelligent surfaces,’ that will react to water in a predefined way.”

I remember some work on how water boiling could be suppressed by polishing surfaces where bubbles form (watch a pot of water boiling, the bubbles appear on the pan surfaces).  I presume this may be a related effect.

One of the geekier conversations I used to get drawn into (up there along with arguing about favorite Serenity episodes, lamenting the demise of Omni magazine, and coming to blows over D&D rules interpretations) was over the relative merits of various sorting algorithms.  Flowing Data has some links to some interesting visualization approaches to sorting algorithms.  This one is for quicksort (colors start out random on the left and must be sorted into Roy G Biv order).

In college I did a project on solving traveling-salesman-type problems with an algorithm called simulated annealing.  Many approaches to the traveling salesman problem pick a random path and then randomly switch pairs of routings on the path, and then stick with the alternative that gives the best score (in this case the shortest path).   Rinse, repeat a zillion times.  The problem is this approach can get stuck in, or converge on, a local optima that are not as good as the single grand optimum for the problem.

In simulated annealing, the algorithm is allowed to sometimes jump to a worse (ie longer) path, which lets it jump out of local minima.  The amount of the backwards jump that is allowed is slowly reduced over time as the algorithm runs.  It is called simulated annealing because this is very similar to the annealing process in metals, where temperature is decreased slowly to, initially, allow the metal molecules to jump to higher energy states so that the whole can settle into a more homogeneous structure.

Anyway, we tried to show how the algorithm proceeded to a solution over time and the visualizations looked a little like this.

I couldn’t care less what happens to my body after I die and I am done using it.  So the following, which I suppose is intended to freak me out, simply leaves me amazed yet again at green thinking

Undertakers in Belgium plan to eschew traditional burials and cremations and start dissolving corpses instead.

The move is intended to tackle a lack of burial space and environmental concerns as 573lbs of carbon dioxide are released by each cremated corpse.

Under the process, known as resomation, bodies are treated in a steel chamber with potassium hydroxide at high pressure and a temperature of 180c (350f).

The raised pressure and temperature means the body reaches a similar end point as in standard cremation — just bones left to be crushed up — in two to three hours.

My first thought on reading this was “Soylent Green is People!”

My second is to wonder how a torched body creates 573 pounds of CO2.  12 pounds of carbon combusts to 44 pounds (approx) of Co2.  This means that to combust to 573 pounds of Co2, the human body must have 156 pounds of carbon.  WTF?   But carbon in 18% of human body weight, which means that to produce 573 pounds of CO2, the human body would have to weigh 867 pounds.   One might be able to get this number by including the cremation fuel in the equation (though this is a generous interpretation since this is not how the article is written), but since it is usually gas used for cremation it would take a hell of a lot of gas given its low carbon content.

My third thought is what does any of this have to do with CO2 reduction

• The process occurs at 350F.  You mean no fossil fuels are used to get the chamber up to 350F.  What, are they using solar mirrors?
• The process occurs at high pressure.  This takes energy
• The end product is a carb0n rich soup that they pour down the drain or pour on their garden.  I have a clue for you, all oxidation is not combustion.  That carbon dumped in your garden or in your compost heap will still become CO2 even without seeing aflame.

Do you remember the State Science Institute report on Rearden Metal?  If you were like me, you thought that this ridiculous report was an exaggeration, a literary device to make a point.  But as in so much of Atlas Shrugged, I am finding that it was no exaggeration at all.

Check out this real life example of “science.”  From the real state science folks at the Interagency Working Group on Climate Change and Health.

There are potential impacts on cancer both directly from climate change and indirectly from climate change mitigation strategies. Climate change will result in higher ambient temperatures that may
increase the transfer of volatile and semi-volatile compounds from water and wastewater into the atmosphere, and alter the distribution of contaminants to places more distant from the sources, changing subsequent human exposures. Climate change is also expected to increase heavy precipitation and flooding events, which may increase the chance of toxic contamination leaks from storage facilities or runoff into water from land containing toxic pollutants. Very little is
known about how such transfers will affect people’s exposure to these chemicals—some of which are known carcinogens—and its ultimate impact on incidence of cancer.  More research is needed to determine the likelihood of this type of contamination, the geographical areas and populations most likely to be impacted, and the health outcomes that could result.

Although the exact mechanisms of cancer in humans and animals are not completely understood for all cancers, factors in cancerdevelopment include pathogens, environmental contaminants, age, and genetics. Given the challenges of understanding the causes of cancer, the links between climate change and cancer are a mixture of fact and supposition, and research is needed to fill in the gaps in what we know.

One possible direct impact of climate change on cancer may be through increases in exposure to toxic chemicals that are known or suspected to cause cancer following heavy rainfall and by
increased volatilization of chemicals under conditions of increased temperature. In the case of heavy rainfall or flooding, there may be an increase in leaching of toxic chemicals and heavy metals
from storage sites and increased contamination of water with runoff containing persistent chemicals that are already in the environment. Marine animals, including mammals, also may suffer
direct effects of cancer linked to sustained or chronic exposure to chemical contaminants in the marine environment, and thereby serve as indicators of similar risks to humans.64 Climate impact
studies on such model cancer populations may provide added dimensions to our understanding of the human impacts.

Remember, the point of this all is not science, but funding.  This is basically a glossy budget presentation, probably cranked out by some grad students over some beers, tasked to come up with scary but marginally plausible links between health issues and climate change.   Obama has said that climate is really, really important to him.  He has frozen a lot of agency budgets, and told them new money is only for programs that supports his major initiatives, like climate change.  So, every agency says that their every problem is due to climate change, just as every agency under Bush said that they were critical to fighting terrorism.  This document is the NIH salvo to get climate change money, not actual science.

I stole this post title from Ayn Rand, but it seems appropriate to this story by James Delingpole.  Apparently James Hansen, leader of NASA’s GISS, which does most of its climate research, wants to turn back the clock on industrialized civilization.    A new book by Keith Farnish writes:

The only way to prevent global ecological collapse and thus ensure the survival of humanity is to rid the world of Industrial Civilization.

And continues:

I’m rarely afraid of stating the truth, but some truths are far harder to give than others; one of them is that people will die in huge numbers when civilization collapses. Step outside of civilization and you stand a pretty good chance of surviving the inevitable; stay inside and when the crash happens there may be nothing at all you can do to save yourself. The speed and intensity of the crash will depend an awful lot on the number of people who are caught up in it: greater numbers of people have more structural needs – such as food production, power generation and healthcare – which need to be provided by the collapsing civilization; greater numbers of people create more social tension and more opportunity for extremism and violence; greater numbers of people create more sewage, more waste, more bodies – all of which cause further illness and death.

I wonder what Mr. Farnish thinks the average life expectancy was before the industrial revolution, or even “civilization?”  But my intention here is not to shoot fish in Mr. Farnish’s barrel.  What is interesting is who approached Farnish and offered, unsolicited, to blurb his book:  James Hansen.  Here is Hansen’s endorsement:

Keith Farnish has it right: time has practically run out, and the ’system’ is the problem. Governments are under the thumb of fossil fuel special interests – they will not look after our and the planet’s well-being until we force them to do so, and that is going to require enormous effort.

Does anyone believe that a person who believes this wouldn’t misrepresent the science or fudge his temperature metrics to support his cause.  If he expects civilization to crash, why do we expect him to operate by the rules of civilized society?

It is not uncommon for certain shady dealing to go on for years, with a small group of critics but never really breaking out into the media.  We skeptics have been criticizing climate scientists for years for various problems with their temperature indexes and historical temperature reconstructions, but never really got traction until the CRU emails were made public, and then there has been a real firestorm of media attention.  Criticisms that never got much traction before are now being actively investigated.

I am hoping that we have a similar situation with Sheriff Joe Arpaio and County Attorney Andrew Thomas.  The story is so wacky it simply defies easy description, but Arpaio and Thomas have been pursuing a number of corruption probes against their bosses in the County government.  All well and good, except for the funny fact that the targets of the probes all seem to be historic critics of Arpaio and Thomas, who have brought out their biggest guns for the one Democrat on the County Council (Arpaio and Thomas are both Republicans).

Both these men have  a history of indifference to civil liberties.   When Arpaio is not busy arresting folks for breathing while Mexican (he once managed to make a crime sweep through the 99% Anglo neighborhood of Fountain Hills and arrest 75% Mexicans), he likes to haul folks off to jail whose only crime is speaking out against the Sheriff .   He arrested (with Thomas’s help) newspaper reporters and editors who wrote critically of him.  This is a man who in his paranoia invented an assassination plot (against himself, of course) and got the city to spend $500,000 protecting him.  If his deputies want to see a defense attorney’s working papers, they just take them.  If he can’t get a judge to release computer records, he has his posse storm into the County computer center and take it over at gunpoint.

Most recently, Thomas and Arpaio wanted a judge who has handed them a number of court losses removed from a certain case.  To make that happen, Arpaio and Thomas bizarrely charged the judge and numerous other county employees in a giant RICO case, a case attorneys are still laughing about because it was so transparent and shoddy.  When that didn’t work, he charged the judge with felony bribery, apparently on the interesting theory that getting a new, updated court house building was effectively a bribe to the judges working there.

It gets much weirder even than this, with Arpaio’s stealing documents from a defense counsel in court (caught on video) with this same judge holding Arpaio’s deputy in contempt for the action and then the sheriff’s deputies essentially going on strike at court, refusing to bring in prisoners.

But after years of fawning, positive publicity as “Americas Toughest Sheriff,” the dam may finally be breaking.  When the AZ Republic finally covers it, you know the situation has to be bad:

Hundreds of attorneys gathered on the courthouse steps in downtown Phoenix to protest Thomas and Arpaio’s public campaign against public corruption.

LOL, I have a picture of these guys with suits and holding placards.  Anyway, this was a real blow:

And, in a scathing letter to The Arizona Republic, the Yavapai County attorney

, who previously handled some of Thomas’ cases against county officials, blasted the prosecutor and sheriff as “a threat to the entire criminal-justice system.”

Oops, so much for the respect of your peers.  Shelia Polk, the Yavapai County attorney (that is a neighboring county) handled the investigations into some of Arpaio and Thomas’s early charges against our County officials, so she knows the details of the story.  And she is a Republican, the same party as Arpaio and Thomas:

In her letter, Polk wrote that although Maricopa County isn’t her jurisdiction, she can’t sit by and watch the abuses from a distance anymore.

“I am conservative and passionately believe in limited government, not the totalitarianism that is spreading before my eyes,” she wrote. “The actions of Arpaio and Thomas are a disservice to the hundreds of dedicated men and women who work in their offices and a threat to the entire criminal-justice system.”

Polk had stayed out of the legal drama in Maricopa County, and her remarks offer the first insight from an outside law-enforcement official who has some knowledge of the cases Arpaio and Thomas have lodged against county officials.

Arpaio’s response was predictable:

Hendershott spoke on behalf of Arpaio. Hendershott said that Polk’s office repeatedly failed to issue subpoenas the Sheriff’s Office needed.

“It seemed clear to us that this case was being deliberately stalled,” he said. “We basically let her know that her work product was ineffective.”

This is a constant refrain from the sheriff – anyone who seeks to impose any limit on his power is therefore evil and conspiring to thwart his will.  It comes up time and time again – he simply does not react well when denied a subpoena, or a search warrant, or access to certain information.  If they are not rubber stamping Sheriff Joe’s requests, then they must be corrupt.  If he had been honest, his RICO charges would have simply read “they didn’t give me what I want.”  But there is a reason these third parties are part of the process, and you can see it in Polk’s letter:

Polk said she worked with the Sheriff’s Office on the cases for the next six months, then returned the cases to the Maricopa County Attorney’s Office.

In Polk’s letter, she wrote that she was “happy to remove myself from the cases and from contact with Sheriff Arpaio. My discomfort grew daily and my role in restraining potential abuses of power increasingly more difficult.”

First, let’s settle something.  The world has warmed since 1850.  While there always is an error bar on nearly every statement about nature, I think there is little point in questioning this past warming.  There is ice core data that suggests that the little ice age, which ended some time in the very early 19th century, was perhaps the coldest period, or one of the two or three coldest periods, in the last 5000 years (ie in nearly the entire span of human civilization).  Temperatures are inevitably warming from this low point.(*1)

So, if the point is not to deny warming altogether, what is the point in discussions of Climategate of picking over and trying to audit historical temperature records like the Hadley CRUT3 or NASA’s GISStemp?  Skeptics often argue that much of the warming is due to bogus manual adjustments in the temperature records and biases such as urban warming.  Alarmists argue that the metrics may understate warming because of masking by manmade anthropogenic cooling agents (e.g. sulfate aerosols).  Why bother?  Why does it matter if past warming is 0.6C or 0.8C or 0.3C?  There are at least two reasons.

1.  The slope of recent temperature increases is used as evidence for the anthropogenic theory.

We know greenhouse gasses like CO2 have a warming effect in the lab.  And we know that overall they warm planets because otherwise ours would be colder.  But how much does an incremental amount of CO2 (a relatively weak greenhouse gas) warm the Earth?  A lot or a little?  Is the sensitivity of the climate to CO2 high or low?

Every time I try to express this, it sounds so ridiculous that people think I must have it wrong.  But the main argument supporting a high climate sensitivity to CO2 is that scientists claim to have looked at past warming, particularly from 1950-2000, and they can’t think of any natural cause that could behind it, which leaves CO2 by process of elimination.  Yeah, I know this seems crazy – one wants to ask if this is really a test for CO2 sensitivity or of scientists’ understanding and imagination, but there you have it.

Now, they don’t always say it this directly.  What they actually say is that they ran their climate models and their climate models could not produce the warming from 1950-2000 with natural forcings alone, but could reproduce this warming with forcings from CO2.  But since the climate models are not handed down from the gods, but programmed by the scientists themselves to represent their own understanding of the climate system, in effect this is just a different way of saying what I said in the previous paragraph.   The climate models perform the function of scientific money laundering, taking an imperfect knowledge on the front end and somehow converting that into settled science at the output.

Now, there are a lot of ways to criticize this approach.  The models tend to leave out multi-decadal ocean cycles and don’t really understand cloud formation well.  Further, the period from 1957-2008, which supposedly can only be explained by non-natural forcings, has almost the exact same temperature profile and increase as the time from 1895-1946, which of necessity must be mostly “natural.”  I go into this more here, among other places.

But you can see that the amount of warming matters to this argument.  The more the warming falls into a documented natural range of temperature variation, the harder it is to portray it as requiring man-made forcings to explain.  This is also the exact same reason alarmist scientists work so hard to eliminate the Medieval Warm Period and little ice age from the temperature record.  Again, the goal is to show that natural variation is in a very narrow range, and deviations from this narrow range must therefore be man-made. (*2)

This is the sort of unified field theory of everything we are seeing in the CRU emails.   We see scientists using every trick they can find to lower or smooth out temperatures numbers before 1950, and adjust numbers after 1950 upwards.  Every single trick and programming adjustment all tended to have this effect, whether it be in proxy studies or in the instrumental record.  And all the efforts to prevent scrutiny, ignore FOIA’s, and throw out raw data have been to avoid third party replication of the statistical methods and adjustments they used to achieve these ends.

As an aside, I think it is incorrect to picture this as a SPECTRE-like cabal scheming to do evil.   These guys really, really believed they had the right answer, and these adjustments were made to tease out what they just knew the right answer to be.  This is why we are only going to see confused looks from any of these guys – they really, really believed they were doing God’s work.  They are never going to understand what they did wrong.  Which doesn’t make it any less bad science, but just emphasizes that we are never going to get data without spin until total sunlight is brought to this process

2.  It is already really hard to justify the huge sensitivities in alarmist forecasts based on past warming — if past warming is lower, forecasts look even more absurd.

The best way to illustrate this is with a few charts from my most recent climate presentation and video.  We usually see warming forecasts by year.  But the real relationship is between warming and CO2 concentration (this relationship is called climate sensitivity).   One can graph forecasts at various levels:

The blue line corresponds to the IPCC no-feedback formula that I think originally goes back to Michael Mann, and yields about 1-1.2C of warming for greenhouse gas warming from CO2 before feedback effects.  The middle two lines correspond to the IPCC mid and high forecasts, and the top line corresponds to more alarmist forecasts from folks like Joe Romm who predict as much as 8-10C of warming by 2100 (when we will be at 650-800ppm CO2 per the IPCC).  By the way, the IPCC does not publish the lines above the blue line, so I have taken the formula they give for the blue line and scaled it to meet their end points.  I think this is reasonable.

A couple of things – all climate models assume net positive feedback, what skeptics consider the key flaw in catastrophic global warming theory.  In fact, most of the catastrophe comes not from global warming theory, but by this second theory that the Earth’s temperature system is dominated by very high positive feedback.  I illustrate this here.  The blue line is from CO2 greenhouse gas warming.  Everything above it is from the multiplier effects of assumed feedbacks.

I won’t go into the feedback issue much now – search my site for positive feedback or else watch my video for much more.  Suffice it to say that skeptics consider the feedback issue the key failure point in catastrophic forecasts.

Anyway, beyond arguing about feedbacks, there is another way to test these forecasts.   Relationships that hold for CO2 and warming in the future must hold in the past (same Earth).  So lets just project these lines backwards to the CO2 level in the late 19th century.

Can you see the issue?  When projected back to pre-industrial CO2 levels, these future forecasts imply that we should have seen 2,3,4 or more degrees of warming over the last century, and even the flawed surface temperature records we are discussing with a number of upwards biases and questionable adjustments only shows about 0.6C.

Sure, there are some time delay issues, probably 10-15 years, as well as some potential anthropogenic cooling from aerosols, but none of this closes these tremendous gaps.  Even with an exaggerated temperature history, only the no feedback 1C per century case is really validated by history.  And, if one assumes the actual warming is less than 0.6C, and only a part of that is from anthropogenic CO2, then the actual warming forecast justified is one of negative feedback, showing less than 1C per century warming from manmade CO2 — which is EXACTLY the case that most skeptics make.

Those who control the past control the future. Those who control the present control the past.- George Orwell

Footnotes:

(1) More than once I have contemplated how much the fact that the invention of the thermometer occurred at perhaps the coldest point in human memory (early 17th century)  has contributed to the perceptions of current warm weather being unusual.

(2) For those who are on the ball, perhaps you can spot an amazing disconnect here.  Scientists claim that the natural variation of temperatures is in a very narrow band, that they never move even 0.2C per decade by natural means.  But they also say that the Earth’s temperature system is dominated by positive feedback, meaning that very very small changes in forcings are magnified many fold in to large temperature changes.  I won’t go in to it in depth from a systems perspective, but trust me that “high stability in a narrow range” and “dominated by high positive feedback” are not very compatible descriptions of a system.

We see all kinds of alarmist spin being attempted on the CRU emails.  For those who are interested, this is best layman’s article I have found to discuss the now-famous Michael Mann “trick,” what it is, and the obfuscation in the CRU’s response.

I have at least one experience with the core alarmist community responding where I pointed out an error.  The responses I got in that case are very similar to the ones today for the CRU – basically the responses either are tangential to the basic point or try to retroactively change the alarmists original assertions.  They are responses that stand up only if the questioner is unwilling or unable to do the smallest amount of verification work (in other words, they work with most of the media).

The series of posts began with this image from the recent US government climate assessment.  Its point was to provide electric grid outages as a proxy measurement variable for severe weather, the point being that severe weather must have increased.

I thought this chart smelled funny

This chart screams one thing at me:  Basis change.  Somehow, the basis for the data is changing in the period.  Either reporting has been increased, or definitions have changed, or there is something about the grid that makes it more sensitive to weather, or whatever  (this is a problem in tornado charts, as improving detection technologies seem to create an upward incidence trend in smaller tornadoes where one probably does not exist).   But there is NO WAY the weather is changing this fast, and readers should treat this whole report as a pile of garbage if it is written by people who uncritically accept this chart.

So I called the owner of the data set at the EIA

He said that there may be an underlying upward trend out there (particularly in thunderstorms) but that most of the increase in this chart is from improvements in data gathering.  In 1997, the EIA (and Makins himself) took over the compilation of this data, which had previously been haphazard, and made a big push to get all utilities to report as required.  They made a second change and push for reporting in 2001, and again in 2007/2008.  He told me that most of this slope is due to better reporting, and not necessarily any underlying trend.   In fact, he said there still is some under-reporting by smaller utilities he wants to improve so that the graph will likely go higher in the future….

At the end of the day, this disturbance data is not a good proxy for severe weather.

The author of that section of the report, Evan Mills, responded and then I dealt with his response here.  Here is just one example of the BS we have to slog through every time we criticize even a tangential analysis like this.  See the links for his whole response, but he says in part:

As noted in the caption to the figure on page 58 of our report (shown above)—which was masked in the blogger’s critique [ed.  actually it was not masked- the source I got the chart from had left off the caption]—we expressly state a quite different finding than that imputed by the blogger, noting with care that we do not attribute these events to anthropogenic climate change, but do consider the grid vulnerable to extreme weather today and increasingly so as climate change progresses, i.e.:

“Although the figure does not demonstrate a cause-effect relationship between climate change and grid disruption, it does suggest that weather and climate extremes often have important effects on grid disruptions.”

The associated text in the report states the following, citing a major peer-reviewed federal study on the energy sector’s vulnerability to climate change:

“The electricity grid is also vulnerable to climate change effects, from temperature changes to severe weather events.”

This was pretty amazing – citing his chart’s caption but hoping that somehow I or other readers would miss the very first line of the caption which he fails to quote:

To Dr. Mills’ point that I misinterpreted him — if all he wanted to say was that the electrical grid could be disturbed by weather or was vulnerable to climate change, fine.  I mean, duh.  If there are more tornadoes knocking about, more electrical lines will come down.  But if that was Dr. Mills ONLY point, then why did he write (emphasis added):

The number of incidents caused by extreme weather has increased tenfold since 1992.  The portion of all events that are caused by weather-related phenomena has more than tripled from about 20 percent in the early 1990s to about 65 percent in recent years.  The weather-related events are more severe…

He is saying flat out that the grid IS being disturbed 10x more often and more severely by weather.  It doesn’t even say “reported” incidents or “may have” — it is quite definitive.  So which one of us is trying to create a straw man?   It is these statements that I previously claimed the data did not support, and I stand by my analysis on that.

I deconstructed a lot of the rest of his longer post, and you can follow it all, but the bottom line is that if a you are drawing a trend line between two points, and you have much more data missing from the begginning end point than the end, your trend is going to be SNAFU’d.  Period.  No point in arguing about it.  See the chart below.  It represents the situation at hand.  The red is the reported data.  The blue is the unreported data, which declines as a percentage of the total due to a push for better data reporting by the database owners.  My point was simply that the red trend line was meaningless.  Its amazing to me that even accepting the basics of this picture, Dr. Mills wants to fight that conclusion.

I am reminded by one of the now-famous quotes from the CRU emails

I really wish I could be more positive about the Kyrgyzstan material, but I swear I pulled every trick out of my sleeve trying to milk something out of that. I don’t think it’d be productive to try and juggle the chronology statistics any more than I already have – they just are what they are…

Yep, sometimes the measured results from nature are what they are.  Well, I actually that most of the time they are what they are, but not in climate apparently.  Never give up a flawed analysis that yields the “right” answer without a fight.  I concluded:

Look Dr. Mills, I don’t have an axe to grind here.  This is one chart out of bazillions making a minor point.  But the data set you are using is garbage, so why do you stand by it with such tenacity?  Can’t anyone just admit “you know, on thinking about it, there are way to many problems with this data set to declare a trend exists.

When someone starts to shout “but its in the peer-reviewed literature” as an argument-ender to me, I usually respond that peer review is not the finish line, meaning that the science of some particular point is settled.  It is merely the starting point, where now a proposition is in the public domain and can be checked and verified and replicated and criticized and potentially disproved or modified.

The CRU scandal should, in my mind, be taken exactly the same way.  Unlike what more fire-breathing skeptics have been saying, this is not the final nail in the coffin of catastrophic man-made global warming theory.  It is merely a starting point, a chance to finally move government funded data and computer code into the public domain where it has always belonged, and start tearing it down or confirming it.

To this end, I would like to share a post from year ago, showing the kind of contortions that skeptics have been going through for years to demonstrate that there appear to be problems in  key data models — contortions and questions that could have been answered in hours rather than years if the climate scientists hadn’t been so afraid of scrutiny and kept their inner workings secret.  This post is from July, 2007.  It is not one of my most core complaints with global warming alarmists, as I think the Earth has indeed warmed over the last 150 years, though perhaps by less than the current metrics say.  But I think some folks are confused why simple averages of global temperatures can be subject to hijinx.  The answer is that the averages are not simple:

A few posts back, I showed how nearly 85% of the reported warming in the US over the last century is actually due to adjustments and added fudge-factors by scientists rather than actual measured higher temperatures.  I want to discuss some further analysis Steve McIntyre has done on these adjustments, but first I want to offer a brief analogy.

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.  However, Steve McIntyre shows us a situation involving two temperature stations in the USHCN network in which government researchers apparently have gone with solution #1.  Here is the situation:

He compares the USHCN station at the Grand Canyon (which appears to be a good rural setting) with the Tucson USHCN station I documented here, located in a parking lot in the center of a rapidly growing million person city.   Unsurprisingly, the Tucson data shows lots of warming and the Grand Canyon data shows none.  So how might you correct Tucson and the Grand Canyon data, assuming they should be seeing about the same amount of warming?  Would you

average them, effectively adjusting the two temperature readings

towards each other, or would you assume the Grand Canyon data is cleaner

with fewer biases and adjust Tucson only?   Is there anyone who would not choose the second option, as with the compasses?

The GISS data set, created by the Goddard Center of NASA, takes the USHCN data set and somehow uses nearby stations to correct for anomalous stations.  I say somehow, because, incredibly, these government scientists, whose research is funded by taxpayers and is being used to make major policy decisions, refuse to release their algorithms or methodology details publicly. They keep it all secret!  Their adjustments are a big black box that none of us are allowed to look into  (and remember, these adjustments account for the vast majority of reported warming in the last century).

We can, however, reverse engineer some of these adjustments, and McIntyre does.  What he finds is that the GISS appears to be averaging the good and bad compass, rather than throwing out or adjusting only the biased reading.  You can see this below.  First, here are the USHCN data for these two stations with only the Time of Observation adjustment made (more on what these adjustments are in this article).

As I said above, no real surprise – little warming out in undeveloped nature, lots of warming in a large and rapidly growing modern city.  Now, here is the same data after the GISS has adjusted it:

You can see that Tucson has been adjusted down a degree or two, but Grand Canyon has been adjusted up a degree or two (with the earlier mid-century spike adjusted down).  OK, so it makes sense that Tucson has been adjusted down, though there is a very good argument to be made that it should be been adjusted down more, say by at least 3 degrees**.  But why does the Grand Canyon need to be adjusted up by about a degree and a half?  What is biasing it colder by 1.5 degrees, which is a lot?  The answer:  Nothing.  The explanation:  Obviously, the GISS is doing some sort of averaging, which is bringing the Grand Canyon and Tucson from each end closer to a mean.

This is clearly wrong, like averaging the two compasses.  You don’t average a measurement known to be of good quality with one known to be biased.  The Grand Canyon should be held about the same, and Tucson adjusted down even more toward it, or else thrown out.  Lets look at two cases.  In one, we will use the GISS approach to combine these two stations– this adds 1.5 degrees to GC and subtracts 1.5 degrees from Tucson.  In the second, we will take an approach that applies all the adjustment to just the biases (Tucson station) — this would add 0 degrees to GC and subtract 3 degrees from Tucson.  The first approach, used by the GISS, results in a mean warming in these two stations that is 1.5 degrees higher than the more logical second approach. No wonder the GISS produces the highest historical global warming estimates of any source!  Steve McIntyre has much more.

** I got to three degrees by applying all of the adjustments for GC and Tucson to Tucson.  Here is another way to get to about this amount.   We know from studies that urban heat islands can add 8-10 degrees to nighttime urban temperatures over surrounding undeveloped land.  Assuming no daytime effect, which is conservative, we might conclude that 8-10 degrees at night adds about 3 degrees to the entire 24-hour average.

Postscript: Steve McIntyre comments (bold added):

These adjustments are supposed to adjust for station moves – the procedure is described in Karl and Williams 1988 [check], but, like so many climate recipes, is a complicated statistical procedure that is not based on statistical procedures known off the island. (That’s not to say that the procedures are necessarily wrong, just that the properties of the procedure are not known to statistical civilization.) When I see this particular outcome of the Karl methodology, my mpression is that, net of the pea moving under the thimble, the Grand Canyon values are being blended up and the Tucson values are being blended down. So that while the methodology purports to adjust for station moves, I’m not convinced that the methodology can successfully estimate ex post the impact of numerous station moves and my guess is that it ends up constructing a kind of blended average.

LOL.  McIntyre, by the way, is the same gentleman who helped call foul on the Mann hockey stick for bad statistical procedure.

From Christopher Booker at the Telegraph via Anthony Watts

There are three threads in particular in the leaked documents which have sent a shock wave through informed observers across the world. Perhaps the most obvious, as lucidly put together by Willis Eschenbach (see McIntyre’s blog Climate Audit and Anthony Watt’s blog Watts Up With That), is the highly disturbing series of emails which show how Dr Jones and his colleagues have for years been discussing the devious tactics whereby they could avoid releasing their data to outsiders under freedom of information laws.

They have come up with every possible excuse for concealing the background data on which their findings and temperature records were based.

This in itself has become a major scandal, not least Dr Jones’s refusal to release the basic data from which the CRU derives its hugely influential temperature record, which culminated last summer in his startling claim that much of the data from all over the world had simply got “lost”. Most incriminating of all are the emails in which scientists are advised to delete large chunks of data, which, when this is done after receipt of a freedom of information request, is a criminal offence.

But the question which inevitably arises from this systematic refusal to release their data is – what is it that these scientists seem so anxious to hide? The second and most shocking revelation of the leaked documents is how they show the scientists trying to manipulate data through their tortuous computer programmes, always to point in only the one desired direction – to lower past temperatures and to “adjust” recent temperatures upwards, in order to convey the impression of an accelerated warming. This comes up so often (not least in the documents relating to computer data in the Harry Read Me file) that it becomes the most disturbing single element of the entire story. This is what Mr McIntyre caught Dr Hansen doing with his GISS temperature record last year (after which Hansen was forced to revise his record), and two further shocking examples have now come to light from Australia and New Zealand.

In each of these countries it has been possible for local scientists to compare the official temperature record with the original data on which it was supposedly based. In each case it is clear that the same trick has been played – to turn an essentially flat temperature chart into a graph which shows temperatures steadily rising. And in each case this manipulation was carried out under the influence of the CRU.

What is tragically evident from the Harry Read Me file is the picture it gives of the CRU scientists hopelessly at sea with the complex computer programmes they had devised to contort their data in the approved direction, more than once expressing their own desperation at how difficult it was to get the desired results.

The third shocking revelation of these documents is the ruthless way in which these academics have been determined to silence any expert questioning of the findings they have arrived at by such dubious methods – not just by refusing to disclose their basic data but by discrediting and freezing out any scientific journal which dares to publish their critics’ work. It seems they are prepared to stop at nothing to stifle scientific debate in this way, not least by ensuring that no dissenting research should find its way into the pages of IPCC reports.