If you are worried about greenhouse gasses and global warming, then I have some Christmas advice for you. When you are done with your Christmas tree, do NOT take it to one of those "recycling" locations most towns have. The recycling process is typically chipping and mulching the trees, which just accelerates their decomposition into greenhouse gasses. If you are really concerned about catastrophic warming, you want to use your tree as a carbon sink. Have it shrink-wrapped in some sort of plastic what won't biodegrade and then landfill it -- the deeper it is buried, the better. Those folks trying to get you to "recycle" your tree are secretly in the pay of the Koch brothers and trying to trick you into ruining the environment.
Posts tagged ‘global warming’
I have observed in the past that the media will run negative pieces about legislation they favor, but only after the legislation is passed and the information is not longer useful to the debate. I suppose they do this to retroactively create a paper trail for being even-handed. So I hypothesized that we might see a December surprise once Hillary won, raising issues about her more forthrightly than they were willing to before the election.
Well, I was sortof right. We are seeing a December surprise -- the silly Russian hacking story being pushed by the Clinton campaign and the White House -- but for completely different reasons. These stories are clearly to try to de-legitimize Trump's election, either just as general battle-space preparation or more specifically ahead of the Electoral College vote.
By the way, speaking of fake news, it strikes me there is an interesting bait and switch in how this story is presented. The story itself is about the appropriation and publication of the emails of Democratic insiders. To my knowledge, no one has claimed the emails have been altered or faked, so one could argue that most of the damage is self-inflicted on Democrats -- if they had not been writing about inciting violence at Trump rallies, there would be nothing salacious to leak.
But the media shorthands all this as just "hacking" which I suspect many low information voters think refers to actually altering vote tabulations. Certainly this is the assumption that Jill Stein and all the suckers who donated to her money-hole recount effort ran with. But of course there is zero evidence of this and it is almost impossible to imagine happening in any kind of wholesale manner. But I think that some in the media and many in the Democrat camp are purposely throwing around the "hacking" term in the hopes that people will get this false impression.
Postscript: I have a new standard we should apply to any government regulatory effort aimed at a private company selling a product or service thought to be fraudulent: No private individual can be prosecuted for selling any product or service that is less of a scam than Jill Stein's recount eff0rt (which, oh wait, may get spent on something else, anything else they want). Ordinary people are being suckered into giving money to this on completely false, really absurd, principles. It infuriates me when politicians get all pious about, say, Exxon misleading the public about global warming when they sell crap like this. At least when I pay my $3 to Exxon, I get a gallon of gas that actually runs my car as promised. What will any of these donors get from Stein's effort?
This is part A of Chapter 5 of an ongoing series. Other parts of the series are here:
- Greenhouse Gas Theory
- A) Actual Temperature Data; B) Problems with the Surface Temperature Record
- Attribution of Past Warming: A) Arguments for it being Man-Made (this article); B) Natural Attribution
- Climate Models vs. Actual Temperatures
- Are We Already Seeing Climate Change
- The Lukewarmer Middle Ground
- A Low-Cost Insurance Policy
Having established that the Earth has warmed over the past century or so (though with some dispute over how much), we turn to the more interesting -- and certainly more difficult -- question of finding causes for past warming. Specifically, for the global warming debate, we would like to know how much of the warming was due to natural variations and how much was man-made. Obviously this is hard to do, because no one has two thermometers that show the temperature with and without man's influence.
I like to begin each chapter with the IPCC's official position, but this is a bit hard in this case because they use a lot of soft words rather than exact numbers. They don't say 0.5 of the 0.8C is due to man, or anything so specific. They use phrases like "much of the warming" to describe man's affect. However, it is safe to say that most advocates of catastrophic man-made global warming theory will claim that most or all of the last century's warming is due to man, and that is how we have put it in our framework below:
By the way, the "and more" is not a typo -- there are a number of folks who will argue that the world would have actually cooled without manmade CO2 and thus manmade CO2 has contributed more than the total measured warming. This actually turns out to be an important argument, since the totality of past warming is not enough to be consistent with high sensitivity, high feedback warming forecasts. But we will return to this in part C of this chapter.
Past, Mostly Abandoned Arguments for Attribution to Man
There have been and still are many different approaches to the attributions problem. In a moment, we will discuss the current preferred approach. However, it is worth reviewing two other approaches that have mostly been abandoned but which had a lot of currency in the media for some time, in part because both were in Al Gore's film An Inconvenient Truth.
Before we get into them, I want to take a step back and briefly discuss what is called paleo-climatology, which is essentially the study of past climate before the time when we had measurement instruments and systematic record-keeping for weather. Because we don't have direct measurements, say, of the temperature in the year 1352, scientists must look for some alternate measure, called a "proxy," that might be correlated with a certain climate variable and thus useful in estimating past climate metrics. For example, one might look at the width of tree rings, and hypothesize that varying widths in different years might correlate to temperature or precipitation in those years. Most proxies take advantage of such annual layering, as we have in tree rings.
One such methodology uses ice cores. Ice in certain places like Antarctica and Greenland is laid down in annual layers. By taking a core sample, characteristics of the ice can be measured at different layers and matched to approximate years. CO2 concentrations can actually be measured in air bubbles in the ice, and atmospheric temperatures at the time the ice was laid down can be estimated from certain oxygen isotope ratios in the ice. The result is that one can plot a chart going back hundreds of thousands of years that estimates atmospheric CO2 and temperature. Al Gore showed this chart in his movie, in a really cool presentation where the chart wrapped around three screens:
As Gore points out, this looks to be a smoking gun for attribution of temperature changes to CO2. From this chart, temperature and CO2 concentrations appear to be moving in lockstep. From this, CO2 doesn't seem to be a driver of temperatures, it seems to be THE driver, which is why Gore often called it the global thermostat.
But there turned out to be a problem, which is why this analysis no longer is treated as a smoking gun, at least for the attribution issue. Over time, scientists got better at taking finer and finer cuts of the ice cores, and what they found is that when they looked on a tighter scale, the temperature was rising (in the black spikes of the chart) on average 800 years before the CO2 levels (in red) rose.
This obviously throws a monkey wrench in the causality argument. Rising CO2 can hardly be the cause of rising temperatures if the CO2 levels are rising after temperatures.
It is now mostly thought that what this chart represents is the liberation of dissolved CO2 from oceans as temperatures rise. Oceans have a lot of dissolved CO2, and as the oceans get hotter, they will give up some of this CO2 to the atmosphere.
The second outdated attribution analysis we will discuss is perhaps the most famous: The Hockey Stick. Based on a research paper by Michael Mann when he was still a grad student, it was made famous in Al Gore's movie as well as numerous other press articles. It became the poster child, for a few years, of the global warming movement.
So what is it? Like the ice core chart, it is a proxy analysis attempting to reconstruct temperature history, in this case over the last 1000 years or so. Mann originally used tree rings, though in later versions he has added other proxies, such as from organic matter laid down in sediment layers.
Before the Mann hockey stick, scientists (and the IPCC) believed the temperature history of the last 1000 years looked something like this:
Generally accepted history had a warm period from about 1100-1300 called the Medieval Warm Period which was warmer than it is today, with a cold period in the 17th and 18th centuries called the "Little Ice Age". Temperature increases since the little ice age could in part be thought of as a recovery from this colder period. Strong anecdotal evidence existed from European sources supporting the existence of both the Medieval Warm Period and the Little Ice Age. For example, I have taken several history courses on the high Middle Ages and every single professor has described the warm period from 1100-1300 as creating a demographic boom which defined the era (yes, warmth was a good thing back then). In fact, many will point to the famines in the early 14th century that resulted from the end of this warm period as having weakened the population and set the stage for the Black Death.
However, this sort of natural variation before the age where man burned substantial amounts of fossil fuels created something of a problem for catastrophic man-made global warming theory. How does one convince the population of catastrophe if current warming is within the limits of natural variation? Doesn't this push the default attribution of warming towards natural factors and away from man?
The answer came from Michael Mann (now Dr. Mann but actually produced originally before he finished grad school). It has been dubbed the hockey stick for its shape:
The reconstructed temperatures are shown in blue, and gone are the Medieval Warm Period and the Little Ice Age, which Mann argued were local to Europe and not global phenomena. The story that emerged from this chart is that before industrialization, global temperatures were virtually flat, oscillating within a very narrow band of a few tenths of a degree. However, since 1900, something entirely new seems to be happening, breaking the historical pattern. From this chart, it looks like modern man has perhaps changed the climate. This shape, with the long flat historical trend and the sharp uptick at the end, is why it gets the name "hockey stick."
Oceans of ink and electrons have been spilled over the last 10+ years around the hockey stick, including a myriad of published books. In general, except for a few hard core paleoclimatologists and perhaps Dr. Mann himself, most folks have moved on from the hockey stick as a useful argument in the attribution debate. After all, even if the chart is correct, it provides only indirect evidence of the effect of man-made CO2.
Here are a few of the critiques:
- Note that the real visual impact of the hockey stick comes from the orange data on the far right -- the blue data alone doesn't form much of a hockey stick. But the orange data is from an entirely different source, in fact an entirely different measurement technology -- the blue data is from tree rings, and the orange is form thermometers. Dr. Mann bristles at the accusation that he "grafted" one data set onto the other, but by drawing the chart this way, that is exactly what he did, at least visually. Why does this matter? Well, we have to be very careful with inflections in data that occur exactly at the point that where we change measurement technologies -- we are left with the suspicion that the change in slope is due to differences in the measurement technology, rather than in the underlying phenomenon being measured.
- In fact, well after this chart was published, we discovered that Mann and other like Keith Briffa actually truncated the tree ring temperature reconstructions (the blue line) early. Note that the blue data ends around 1950. Why? Well, it turns out that many tree ring reconstructions showed temperatures declining after 1950. Does this mean that thermometers were wrong? No, but it does provide good evidence that the trees are not accurately following current temperature increases, and so probably did not accurately portray temperatures in the past.
- If one looks at the graphs of all of Mann's individual proxy series that are averaged into this chart, astonishingly few actually look like hockey sticks. So how do they average into one? McIntyre and McKitrick in 2005 showed that Mann used some highly unusual and unprecedented-to-all-but-himself statistical methods that could create hockey sticks out of thin air. The duo fed random data into Mann's algorithm and got hockey sticks.
- At the end of the day, most of the hockey stick (again due to Mann's averaging methods) was due to samples from just a handful of bristle-cone pine trees in one spot in California, trees whose growth is likely driven by a number of non-temperature factors like precipitation levels and atmospheric CO2 fertilization. Without these few trees, most of the hockey stick disappears. In later years he added in non-tree-ring series, but the results still often relied on just a few series, including the Tiljander sediments where Mann essentially flipped the data upside down to get the results he wanted. Taking out the bristlecone pines and the abused Tiljander series made the hockey stick go away again.
There have been plenty of other efforts at proxy series that continue to show the Medieval Warm Period and Little Ice Age as we know them from the historical record
As an aside, Mann's hockey stick was always problematic for supporters of catastrophic man-made global warming theory for another reason. The hockey stick implies that the world's temperatures are, in absence of man, almost dead-flat stable. But this is hardly consistent with the basic hypothesis, discussed earlier, that the climate is dominated by strong positive feedbacks that take small temperature variations and multiply them many times. If Mann's hockey stick is correct, it could also be taken as evidence against high climate sensitivities that are demanded by the catastrophe theory.
The Current Lead Argument for Attribution of Past Warming to Man
So we are still left wondering, how do climate scientists attribute past warming to man? Well, to begin, in doing so they tend to focus on the period after 1940, when large-scale fossil fuel combustion really began in earnest. Temperatures have risen since 1940, but in fact nearly all of this rise occurred in the 20 year period from 1978 to 1998:
To be fair, and better understand the thinking at the time, let's put ourselves in the shoes of scientists around the turn of the century and throw out what we know happened after that date. Scientists then would have been looking at this picture:
Sitting in the year 2000, the recent warming rate might have looked dire .. nearly 2C per century...
Or possibly worse if we were on an accelerating course...
Scientists began to develop a hypothesis that this temperature rise was occurring too rapidly to be natural, that it had to be at least partially man-made. I have always thought this a slightly odd conclusion, since the slope from this 20-year period looks almost identical to the slope centered around the 1930's, which was very unlikely to have much human influence.
But never-the-less, the hypothesis that the 1978-1998 temperature rise was too fast to be natural gained great currency. But how does one prove it?
What scientists did was to build computer models to simulate the climate. They then ran the computer models twice. The first time they ran them with only natural factors, or at least only the natural factors they knew about or were able to model (they left a lot out, but we will get to that in time). These models were not able to produce the 1978-1998 warming rates. Then, they re-ran the models with manmade CO2, and particularly with a high climate sensitivity to CO2 based on the high feedback assumptions we discussed in an earlier chapter. With these models, they were able to recreate the 1978-1998 temperature rise. As Dr. Richard Lindzen of MIT described the process:
What was done, was to take a large number of models that could not reasonably simulate known patterns of natural behavior (such as ENSO, the Pacific Decadal Oscillation, the Atlantic Multidecadal Oscillation), claim that such models nonetheless accurately depicted natural internal climate variability, and use the fact that these models could not replicate the warming episode from the mid seventies through the mid nineties, to argue that forcing was necessary and that the forcing must have been due to man.
Another way to put this argument is "we can't think of anything natural that could be causing this warming, so by default it must be man-made. With various increases in sophistication, this remains the lead argument in favor of attribution of past warming to man.
In part B of this chapter, we will discuss what natural factors were left out of these models, and I will take my own shot at a simple attribution analysis.
This is the part B of the fourth chapter of an ongoing series. Other parts of the series are here:
- Greenhouse Gas Theory
- A) Actual Temperature Data; B) Problems with the Surface Temperature Record (this article)
- Attribution of Past Warming; A) Arguments for it being Man-Made; B) Natural Attribution
- Climate Models vs. Actual Temperatures
- Are We Already Seeing Climate Change
- The Lukewarmer Middle Ground
- A Low-Cost Insurance Policy
In part A of this chapter, we showed that the world had indeed warmed over the past 30-100 years, whether you looked at the surface temperature record or the satellite record. Using either of these metrics, though, we did not see global warming accelerating, nor did we see warming rates that were faster than predicted. In fact, we saw the opposite.
One story I left out of part A, because it did not affect the basic conclusions we drew, is the criticisms of the surface temperature record. In this part B, we will discuss some of these criticisms, and see why many skeptics believe the 0.8C warming number for the past century is exaggerated. We will also gain some insights as to why the satellite measured warming rates may be closer to the mark than rates determined by surface temperature stations.
Uncorrected Urban Biases
Years ago a guy named Steve McIntyre published a graphical portrayal of warming rates across the US. This is a common chart nowadays. Anyway, this chart (almost 10 years old) drew from temperature measurement stations whose locations are shows with the crosses on the map:
I was living in Arizona at the time and I was interested to learn that the highest warming rate was being recorded at the USHCN station in Tucson (remember, just because Arizona is hot is no reason to necessarily expect it to have high warming rates, they are two different things). At the time, Anthony Watt was just kicking off an initiative to develop quality control data for USHCN stations by having amateurs photograph the sites and upload them to a central data base. I decided I would go down to the Tucson site to experience the highest warming rate myself. This is what I found when I tracked down the station, and took this picture (which has been reproduced all over the place at this point):
That is the temperature station, around that fenced in white box (the uproar over this picture eventually caused this location to be closed). It was in the middle of a parking lot in the middle of a major university in the middle of a growing city. 100 years ago this temperature station was in the countryside, in essentially the open desert - no paving, no buildings, no cars. So we are getting the highest warming rates in the country by comparing a temperature today in an asphalt parking lot in the middle of a city to a temperature a hundred years ago in the open desert.
The problem with this is what's called the urban heat island effect. Buildings and concrete absorb heat from the sun during the day, more than would typically be absorbed by raw land in its natural state. This heat is reradiated at night, causing nights to be warmer in cities than in the areas surrounding them. If you live in a city, you will likely hear weather reports that predict colder temperatures in outlying areas, or warn of freezes in the countryside but not in the city itself.
It turns out that this urban heat island effect is easily measured -- it even makes a great science fair project!
My son and I did this project years ago, attaching a small GPS and temperature probe to a car. We then drove out of the city center into the country and back in the early evening, when the urban heat island effect should be largest. We drove out and then back to average out any effects of overall cooling during our testing. One of the trips is shown above, with around 6 degrees F of temperature change. We, and most others who have done this in other cities, found between 5 and 10 degrees of warming as one drives into a city at night.
If this effect were constant over time, it would not pose too many problems for our purposes here, because we are looking at changes in average temperatures over time, not absolute values. But the urban heat island warming of a city (and particular temperature stations) increases as the urban area grows larger. Because this urban warming is many times the global warming signal we are trying to measure, and since most temperature stations are located near growing urban locations, it introduces an important potential bias into measurement.
A number of studies have found that, in fact, we do indeed see more warming historically in thermometers located in urban areas than in those located in rural areas. Two studies in California have shown much lower warming rates at rural thermometers than at urban ones:
Anthony Watt has been working for years to do this same analysis for the entire US. In fact, the pictures taken above of the temperature station in Tucson were part of the first phase of his project to document each USHCN site used in the global warming statistics with pictures. Once he had pictures, he compared the details of the siting with a classification system scientists use to measure the quality of a temperature sites, from the best (class 1) to the worst with the most biases (class 5). He found that perhaps a third of the warming in the official NOAA numbers may come from the introduction of siting biases from bad sites. Or put another way, the warming at well-sited temperature stations was only about 2/3 in the official metric.
By the way, this is one other reason why I tend to favor the satellite measurements. Going back to the numbers we showed in part A, the satellite temperature metric had about 2/3 the trend of the surface temperature reading, or almost exactly what the surface readings would be if this siting bias were eliminated (the absolute values of the trends don't match, because they are for different time periods and different geographies).
There is one other aspect of this chart that might have caught your eye -- if some temperature stations are showing 2 degrees of warming and some 3.2 degrees of warming, why is the total 3.2 degrees of warming. Shouldn't it be somewhere in the middle?
One explanation is that the NOAA and other bodies take the data from these stations and perform a number of data manipulation steps in addition to a straight spatial averaging. One such step is that they will use a computer process to try to correct temperature stations based on the values from neighboring stations. The folks that run these indices argue that this computational process overcomes the site bias problem. Skeptics will argue that this approach is utter madness -- why work to correct a known bad temperature point, why not just eliminate it? If you have a good compass and a bad compass, you don't somehow mathematically average the results to find north, you throw out the bad one and use the good one. In short, skeptics argue that this approach does not eliminate the error, it just spreads the error around to all the good stations, smearing the error like peanut butter. Here is an example from the GISS, using station data that has only been adjusted for Time of Observation changes (TOBS).
This is exactly what we might expect - little warming out in undeveloped nature in Grand Canyon National Park, lots of warming in a large and rapidly growing modern city (yes, the Tucson data is from our favorite temperature station we featured above). 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 currently biasing it colder by 1.5 degrees, which is a lot? One suspects the GISS is doing some sort of averaging, which is bringing the Grand Canyon and Tucson from each end closer to a mean -- they are not eliminating the urban bias from Tucson, they are just spreading it around to other stations in the region.
Temperature Adjustments and Signal-To-Noise Ratio
Nothing is less productive, to my mind, than when skeptics yell the word "fraud!" on the issue of temperature adjustments. All temperature databases include manual adjustments, even the satellite indices that many skeptics favor. As mentioned above, satellite measurements have to be adjusted for orbital decay of the satellites just as surface temperature measurements have to be adjusted for changes in the daily time of observation. We may argue that adjustment methodologies are wrong (as we did above with urban biases). We may argue that there are serious confirmation biases (nearly every single adjustment to every temperature and sea level and ocean heat database tends to cool the past and warm the present, perhaps reinforced by preconceived notions that we should be seeing a warming signal.) But I find that charges of fraud just cheapen the debate.
Even if the adjustments are all made the the best of intentions, we are still left with an enormous problem of signal to noise ratio. It turns out that the signal we are trying to measure -- warming over time -- is roughly equal to the magnitude of the manual adjustments. In other words, the raw temperature data does not show warming, only the manually adjusted data show warming. This does not mean the adjusted data is wrong, but it should make us substantially less confident that we are truly measuring the signal in all this noise of adjustment. Here are two examples, for an individual temperature station and for the entire database as a whole:
In this first example, we show the raw data (with Time of Observation adjustments only) in orange, and the final official adjusted version in blue. The adjustments triple the warming rate for the last century.
We can see something similar for the whole US, as raw temperature measurements (this time before time of observation adjustments) actually shows a declining temperature trend in the US. In this case, the entirety of the global warming signal, and more, comes from the manual adjustments. Do these adjustments (literally thousands and thousands of them) make sense when taken in whole? Does it make sense that there was some sort of warming bias in the 1920's that does not exist today? This is certainly an odd conclusion given that it implies a bias exactly opposite of the urban heat island effect.
We could go into much more detail, but this gives one an idea of why skeptics prefer the satellite measurements to the surface temperature record. Rather than endlessly working to try to get these public agencies to release their adjustment details and methodology for third party validation to the public that pays them (an ongoing task that still has not been entirely successful), skeptics have simply moved on to a better approach where the adjustments (to a few satellites) are much easier to manage.
Ultimately, both approaches for seeking a global warming signal are a bit daft. Why? Because, according to the IPCC, of all the extra warming absorbed by the surface of the Earth from the greenhouse effect, only about 1% goes into the atmosphere:
Basically, water has a MUCH higher heat carrying capacity than air, and over 90% of any warming should be going into oceans. We are just starting to get some new tools for measuring the changes to ocean heat content, though the task is hard because we are talking about changes in the thousandths of a degree in the deep oceans.
After this brief digression into the surface temperature records, it is now time to get back to our main line of discussion. In the next chapter, we will begin to address the all-important attribution question: Of the warming we have seen in the past, how much is man-made?
Last month I outlined my position on global warming to a fabulous audience at the Athenaeum at Claremont-McKenna College. In doing so, I had a chance to substantially update my presentation materials. I realized that it had been years since I had posted this presentation as anything but a video, and so I embark over the next several weeks to lay my position out in a multi-part written series.
Table of Contents (updated as new chapters are added)
- Introduction (this article)
- Greenhouse Gas Theory
- A) Actual Temperature Data; B) Problems with the Surface Temperature Record
- Attribution of Past Warming; A) Arguments for it being Man-Made; B) Natural Attribution
- Climate Models vs. Actual Temperatures
- Are We Already Seeing Climate Change
- The Lukewarmer Middle Ground
- A Low-Cost Insurance Policy
I suppose the first question I need to answer is: why should you bother reading this? We are told the the science is "settled" and that there is a 97% consensus among scientists on .... something. Aren't you the reader just giving excess credence to someone who is "anti-science" just by reading this?
Well, this notion that the "debate is over" is one of those statements that is both true and not true. There is something approaching scientific consensus for certain parts of anthropogenic global warming theory -- for example, the fact that CO2 is a greenhouse gas and that concentrations of it in the atmosphere have a warming effect on the Earth is pretty much undisputed in all but the furthest reaches of the scientific community.
But it turns out that other propositions that are important to the debate on man-made global warming are far less understood scientifically, and the near certainty on a few issues (like the existence of the greenhouse gas effect) is often used to mask real questions about these other propositions. So before we go any further , it is critical for us to get very clear what exact proposition we are discussing.
At this point I have to tell a story from over thirty years ago when I saw Ayn Rand speak at Northeastern University (it's hard to imagine any university today actually allowing Rand on campus, but that is another story). In the Q&A period at the end, a woman asked Rand, "Why don't you believe in housewives?" and Rand answered, in a very snarky fashion, "I did not know housewives were a matter of belief." What the woman likely meant to ask was "Why don't you believe that being a housewife is a valid occupation for a woman?" But Rand was a bear for precision in language and was not going to agree or disagree with a poorly worded proposition.
I am always reminded of this story when someone calls me a climate denier. I want to respond, in Rand's Russian accent, "I did not know that climate was a matter of belief?"
But rather than being snarky here, let's try to reword the "climate denier" label and see if we can get to a proposition with which I can agree or disagree.
Am I, perhaps, a "climate change denier?" Well, no. I don't know anyone who is. The world has had warm periods and ice ages. The climate changes.
OK, am I a "man-made climate change denier?" No again. I know very few people, except perhaps for a few skeptics of the talkshow host variety, that totally deny any impact of man's actions on climate. Every prominent skeptic I can think of acknowledges multiple vectors of impact by man on climate, from greenhouse gas emissions to land use.
If you have to slap a label on me, I am a "catastrophic man-made climate change denier." I deny the catastrophe. Really, I would prefer "catastrophic man-made global warming denier" because there is no mechanism by which man's CO2 emissions can affect climate except through the intermediate step of warming. The name change from "global warming" to "climate change" was, to my mind, less about science and more about a marketing effort to deal with the fact the temperatures had plateaued over the last 10-20 years and to allow activists to point to tail of the distribution weather events and call them man-made. But we get ahead of ourselves. We will discuss all of this in later sections.
In this series I will therefore be discussing what I will call the "Catastrophic Man-Made Global Warming Theory." There are a lot of moving parts to this theory, so I will use the following framework as a structure for my discussion.
This framework follows the work of the UN IPCC, an international panel that meets every 5 years or so to summarize the state of climate science in general and catastrophic man-made global warming in particular. While I will obviously disagree with the IPCC canon from time to time, I will try to always point out when I do so. However, I don't think any climate scientists would argue with the framework I am using here to describe their theory.
The first thing you will see, and perhaps the most important single point you should take away from this discussion, is that the core theory of catastrophic man-made global warming is actually a two part theory. In part one, which is essentially greenhouse gas theory, a doubling of CO2 warms the Earth by a bit over 1 degree Celsius. But there is a second part of the theory, a theory that is entirely unrelated to greenhouse gas theory. That theory states that the Earth's climate systems are dominated by positive feedbacks which multiply the initial warming from CO2 by 3- 5 times or more.
It is this two-part theory that causes me, and many other skeptics, the most frustration in the climate debate. For when advocates say the science is "settled," they really mean that greenhouse gas theory is pretty well accepted. But this is only one part of a two-part theory, and in fact the catastrophe actually comes from the second theory, the theory that the climate is dominated by positive feedbacks, and this second theory is far from settled. But again, I get ahead of myself, we will cover this all in great depth in later sections.
No theory in science has any meaning until it is confirmed by observations, so the bottom half of our framework deals with observational evidence for the theory. The IPCC claims that the Earth has warmed about 0.8C over the last century, and that [much/substantial/most/all/more than 100%] of this warming is due to man. The IPCC and many scientists have played with the wording of the amount of warming attributable to man over the years, and rather than deal with that complexity here, we will wait until we get to that section. But it is fair to say that IPCC canon is that man's contribution to the warming is probably not less than half and could be more than 100%.
Finally, on the right of our framework, this man-made warming has the potential to cause all sorts of changes -- to weather patterns, to animal species, to disease vectors -- you name it. Pick any possible negative effect -- more hurricanes, more tornadoes, more heat waves, more snow, less snow, lower crop yields, more malaria, more rain, less rain, more terrorism, rising sea levels, displaced persons, more acne, etc. etc. -- and someone has been quoted in the media claiming the link to warming. When something bad happened in Medieval Europe, it was typically blamed on Jews or marginalized women (via witchcraft accusations). Today, global warming is the new all-purpose target of blame.
Over many installments and several weeks, I hope to walk through this framework and discuss the state of the science (for those who can't wait, I wrote a much shorter overview here several years ago). We will discuss parts of the science that are well-grounded -- such as man-made warming from greenhouse gas theory and the fact that the Earth has warmed over the last century. We will discuss parts of the science I consider exaggerated -- such as the claim of large positive feedback multipliers of future warming and attribution of all past warming to man. And we will discuss parts of the theory which, despite constant repetition in the press, have absolutely no evidence behind them whatsoever -- such as the claim that we are already seeing negative effects from warming such as more hurricanes and tornadoes.
There was some debate a while back around about a temperature chart some Conservative groups were passing around.
Obviously, on this scale, global warming does not look too scary. The question is, is this scale at all relevant? I could re-scale the 1929 stock market drop to a chart that goes from Dow 0 to, say, Dow 100,000 and the drop would hardly be noticeable. That re-scaling wouldn't change the fact that the 1929 stock market crash was incredibly meaningful and had large impacts on the economy. Kevin Drum wrote about the temperature chart above,
This is so phenomenally stupid that I figured it had to be a joke of some kind.
Mother Jones has banned me from commenting on Drum's site, so I could not participate in the conversation over this chart. But I thought about it for a while, and I think the chart's author perhaps has a point but pulled it off poorly. I am going to take another shot at it.
First, I always show the historic temperature anomaly on the zoomed in scale that you are used to seeing, e.g. (as usual, click to enlarge)
The problem with this chart is that it is utterly without context just as much as the previous chart. Is 0.8C a lot or a little? Going back to our stock market analogy, it's a bit like showing the recent daily fluctuations of the Dow on a scale from 16,300 to 16,350. The variations will look huge, much larger than either their percentage variation or their meaningfulness to all but the most panicky investors.
So I have started including the chart below as well. Note that it is in Fahrenheit (vs. the anomaly chart above in Celsius) because US audiences have a better intuition for Fahrenheit, and is only for the US vs. the global chart above. It shows the range of variation in US monthly averages, with the orange being the monthly average daily maximum temperature across the US, the dark blue showing the monthly average daily minimum temperature, and the green the monthly mean. The dotted line is the long-term linear trend
Note that these are the US averages -- the full range of daily maximums and minimums for the US as a whole would be wider and the full range of individual location temperatures would be wider still. A couple of observations:
- It is always dangerous to eyeball charts, but you should be able to see what is well known to climate scientists (and not just some skeptic fever dream) -- that much of the increase over the last 30 years (and even 100 years) of average temperatures has come not from higher daytime highs but from higher nighttime minimum temperatures. This is one reason skeptics often roll their eyes as attribution of 15 degree summer daytime record heat waves to global warming, since the majority of the global warming signal can actually be found with winter and nighttime temperatures.
- The other reason skeptics roll their eyes at attribution of 15 degree heat waves to 1 degree long term trends is that this one degree trend is trivial compared to the natural variation found in intra-day temperatures, between seasons, or even across years. It is for this context that I think this view of temperature trends is useful as a supplement to traditional anomaly charts (in my standard presentation, I show this chart scale once and the standard anomaly chart scale further up about 30 times, so that utility has limits).
Using a helicopter and a large tank of heated water to deice a windmill so it can continue to reduce fossil fuel use and global warming. (source)
Virtually every study done points to the fact the immigrants, even illegal immigrants, are less prone to crime than American citizens. That is why immigration opponents must rely on repetition of lurid single examples to try to make their case, a bit like global warming advocates point to individual heat waves as a substitute for having any warming show up in the recent global temperature metrics.
With few exceptions, immigrants are less crime prone than natives or have no effect on crime rates. As described below, the research is fairly one-sided.
There are two broad types of studies that investigate immigrant criminality. The first type uses Census and American Community Survey (ACS) data from the institutionalized population and broadly concludes that immigrants are less crime prone than the native-born population. It is important to note that immigrants convicted of crimes serve their sentences before being deported with few exceptions.
However, there are some potential problems with Census-based studies that could lead to inaccurate results. That’s where the second type of study comes in. The second type is a macro level analysis to judge the impact of immigration on crime rates, generally finding that increased immigration does not increase crime and sometimes even causes crime rates to fall.
Butcher and Piehl examine the incarceration rates for men aged 18-40 in the 1980, 1990, and 2000 Censuses. In each year, immigrants are less likely to be incarcerated than natives with the gap widening each decade. By 2000, immigrants have incarceration rates that are one-fifth those of the native-born
There is a lot more at the link.
First, let's start with the Guardian headline:
Exxon knew of climate change in 1981, email says – but it funded deniers for 27 more years
So now let's look at the email, in full, which is the sole source for the Guardian headline. I challenge you, no matter how much you squint, to find a basis for the Guardian's statement. Basically the email says that Exxon knew of the concern about global warming in 1981, but did not necessarily agree with it. Hardly the tobacco-lawyer cover-up the Guardian is trying to make it sound like. I will reprint the email in full because I actually think it is a pretty sober view of how good corporations think about these issues, and it accurately reflects the Exxon I knew from 3 years as a mechanical / safety engineer in a refinery.
I will add that you can see the media denial that a lukewarmer position even exists (which I complained about most recently here) in full action in this Guardian article. Exxon's position as described in the Guardian's source looks pretty close to the lukewarmer position to me -- that man made global warming exists but is being exaggerated. But to the Guardian, and many others, there is only full-blown acceptance of the most absurd exaggerated climate change forecasts or you are a denier. Anyway, here is the email in full:
Corporations are interested in environmental impacts only to the extent that they affect profits, either current or future. They may take what appears to be altruistic positions to improve their public image, but the assumption underlying those actions is that they will increase future profits. ExxonMobil is an interesting case in point.
Exxon first got interested in climate change in 1981 because it was seeking to develop the Natuna gas field off Indonesia. This is an immense reserve of natural gas, but it is 70% CO2. That CO2 would have to be separated to make the natural gas usable. Natural gas often contains CO2 and the technology for removing CO2 is well known. In 1981 (and now) the usual practice was to vent the CO2 to the atmosphere. When I first learned about the project in 1989, the projections were that if Natuna were developed and its CO2 vented to the atmosphere, it would be the largest point source of CO2 in the world and account for about 1% of projected global CO2 emissions. I’m sure that it would still be the largest point source of CO2, but since CO2 emissions have grown faster than projected in 1989, it would probably account for a smaller fraction of global CO2 emissions.
The alternative to venting CO2 to the atmosphere is to inject it into ground. This technology was also well known, since the oil industry had been injecting limited quantities of CO2 to enhance oil recovery. There were many questions about whether the CO2 would remain in the ground, some of which have been answered by Statoil’s now almost 20 years of experience injecting CO2 in the North Sea. Statoil did this because the Norwegian government placed a tax on vented CO2. It was cheaper for Statoil to inject CO2 than pay the tax. Of course, Statoil has touted how much CO2 it has prevented from being emitted.
In the 1980s, Exxon needed to understand the potential for concerns about climate change to lead to regulation that would affect Natuna and other potential projects. They were well ahead of the rest of industry in this awareness. Other companies, such as Mobil, only became aware of the issue in 1988, when it first became a political issue. Natural resource companies – oil, coal, minerals – have to make investments that have lifetimes of 50-100 years. Whatever their public stance, internally they make very careful assessments of the potential for regulation, including the scientific basis for those regulations. Exxon NEVER denied the potential for humans to impact the climate system. It did question – legitimately, in my opinion – the validity of some of the science.
Political battles need to personify the enemy. This is why liberals spend so much time vilifying the Koch brothers – who are hardly the only big money supporters of conservative ideas. In climate change, the first villain was a man named Donald Pearlman, who was a lobbyist for Saudi Arabia and Kuwait. (In another life, he was instrumental in getting the U.S. Holocaust Museum funded and built.) Pearlman’s usefulness as a villain ended when he died of lung cancer – he was a heavy smoker to the end.
Then the villain was the Global Climate Coalition (GCC), a trade organization of energy producers and large energy users. I was involved in GCC for a while, unsuccessfully trying to get them to recognize scientific reality. (That effort got me on to the front page of the New York Times, but that’s another story.) Environmental group pressure was successful in putting GCC out of business, but they also lost their villain. They needed one which wouldn’t die and wouldn’t go out of business. Exxon, and after its merger with Mobil ExxonMobil, fit the bill, especially under its former CEO, Lee Raymond, who was vocally opposed to climate change regulation. ExxonMobil’s current CEO, Rex Tillerson, has taken a much softer line, but ExxonMobil has not lost its position as the personification of corporate, and especially climate change, evil. It is the only company mentioned in Alyssa’s e-mail, even though, in my opinion, it is far more ethical that many other large corporations.
Having spent twenty years working for Exxon and ten working for Mobil, I know that much of that ethical behavior comes from a business calculation that it is cheaper in the long run to be ethical than unethical. Safety is the clearest example of this. ExxonMobil knows all too well the cost of poor safety practices. The Exxon Valdez is the most public, but far from the only, example of the high cost of unsafe operations. The value of good environmental practices are more subtle, but a facility that does a good job of controlling emission and waste is a well run facility, that is probably maximizing profit. All major companies will tell you that they are trying to minimize their internal CO2 emissions. Mostly, they are doing this by improving energy efficiency and reducing cost. The same is true for internal recycling, again a practice most companies follow. Its just good engineering.
One of my critiques of global warming alarmists is that they are trying to use a type of observation bias to leave folks with the impression that weather is becoming more severe. By hyping on every tail-of-the-distribution weather event in the media, they leave the impression that such events are becoming more frequent, when in fact they are just being reported more loudly and more frequently. I dealt with this phenomenon in depth in an older Fortune article, where I made an analogy to the famous "summer of the shark"
...let’s take a step back to 2001 and the “Summer of the Shark.” The media hysteria began in early July, when a young boy was bitten by a shark on a beach in Florida. Subsequent attacks received breathless media coverage, up to and including near-nightly footage from TV helicopters of swimming sharks. Until the 9/11 attacks, sharks were the third biggest story of the year as measured by the time dedicated to it on the three major broadcast networks’ news shows.
Through this coverage, Americans were left with a strong impression that something unusual was happening — that an unprecedented number of shark attacks were occurring in that year, and the media dedicated endless coverage to speculation by various “experts” as to the cause of this sharp increase in attacks.
Except there was one problem — there was no sharp increase in attacks. In the year 2001, five people died in 76 shark attacks. However, just a year earlier, 12 people had died in 85 attacks. The data showed that 2001 actually was a down year for shark attacks.
Yesterday I was stuck on a stationary bike in my health club with some Fox News show on the TV. Not sure I know whose show it was (O'Reilly? Hannity?) but the gist of the segment seemed to be that a recent murder by an illegal immigrant in San Francisco should be taken as proof positive of the Trump contention that such immigrants are all murderers and rapists. The show then proceeded to show a couple of other nominally parallel cases.
Yawn. It would be intriguing to flood an hour-long episode with stories of legal American citizens committing heinous crimes. One wonders if folks would walk away wondering if there was something wrong with those Americans.
One could pick any group of human beings and do a thirty-minute segment showing all the bad things members of that group had done. What this does not prove in the least is whether that group has any particular predilection towards doing bad things, or specifically in the case of Mexican immigrants, whether they commit crimes at a higher rate than any other group in this country. In fact, everything I read says that they do not, which likely explains why immigration opponents use this technique, just as climate alarmists try to flood the airwaves with bad weather stories because the actual trend data for temperatures does not tell the story they want to tell.
Man has almost certainly warmed the world by some tenths of a degree C with his CO2, though much of this warming has hit night-time lows rather than daily highs. Anyway, while future temperature rise forecasts are often grossly exaggerated by absurdly high assumptions of positive feedback, there is at least a kernel of fact in there that CO2 is likely warming the world somewhat.
However, the popular "science" on climate change is often awful, positing, for example, that hurricanes are being increased by man right in the midst of the longest hurricane drought we have seen in the US for a hundred years.
Inevitably, the recent severe California droughts have been blamed on manmade CO2. As a hopefully useful adjunct to this debate, I have annotated a recent chart from the San Jose Mercury News on the history of California droughts to reflect the popular global warming / climate change narrative. You be the judge of the reasonableness:
A while back I wrote a long post on topics like climate change, vaccinations, and GMO foods where I discussed the systematic problems many in the political-media complex have in evaluating risks in a reasoned manner.
I didn't have any idea who the "Food Babe" was but from this article she sure seems to be yet another example. If you want to see an absolute classic of food babe "thinking", check out this article on flying. Seriously, I seldom insist you go read something but it is relatively short and you will find yourself laughing, I guarantee it.
Postscript: I had someone tell me the other day that I was inconsistent. I was on the side of science (being pro-vaccination) but against science (being pro-fossil fuel use). I have heard this or something like it come up in the vaccination debate a number of times, so a few thoughts:
- The commenter is assuming their conclusion. Most people don't actually look at the science, so saying you are for or against science is their way of saying you are right or wrong.
- The Luddites are indeed taking a consistent position here, and both "Food babe" and RFK Jr. represent that position -- they ascribe large, unproveable risks to mundane manmade items and totally discount the benefits of these items. This includes vaccines, fossil fuels, GMO foods, cell phones, etc.
- I am actually with the science on global warming, it is just what the science says is not well-portrayed in the media. The famous 97% of scientists actually agreed with two propositions: That the world has warmed over the last century and that man has contributed to that warming. The science is pretty clear on these propositions and I agree with them. What I disagree with is that temperature sensitivity to a doubling of CO2 concentrations is catastrophic, on the order of 4 or 5C or higher, as many alarmist believe, driven by absurdly high assumptions of positive feedback in the climate system. But the science is very much in dispute about these feedback assumptions and thus on the amount of warming we should expect in the future -- in fact the estimates in scientific papers and the IPCC keep declining each year heading steadily for my position of 1.5C. Also, I dispute that things like recent hurricanes and the California drought can be tied to manmade CO2, and in fact the NOAA and many others have denied that these can be linked. In being skeptical of all these crazy links to global warming (e.g. Obama claims global warming caused his daughter's asthma attack), I am totally with science. Scientists are not linking these things, talking heads in the media are.
I refuse to assume (contrary to the modern practice) that someone who disagrees with me is either stupid or ill-intentioned or both [OK, I did call people idiots here -- sorry, I was ranting]. Intelligent people of goodwill can disagree with each other, and the world would be a better place if more people embraced that simple notion.
Anyway, I won't blame lack of intelligence or bad motivations for the following statement from Bill Maher. He seems to be a smart guy who is honestly motivated by what he says motivates him. But this statement is just so ignorant and provably false that it must be the result of living in a very powerful echo chamber where no voices other than ones that agree with him are allowed.
HBO’s Bill Maher complained that comparing climate change skepticism to vaccine skepticism was unfair to vaccine skeptics before attacking GMOs on Friday’s “Real Time.”
“The analogy that I see all the time is that if you ask any questions [about vaccines], you are the same thing as a global warming denier. I think this is a very bad analogy, because I don’t think all science is alike. I think climate science is rather straightforward because you’re dealing with the earth, it’s a rock…climate scientists, from the very beginning, have pretty much said the same thing, and their predictions have pretty much come true. It’s atmospherics, and it’s geology, and chemistry. That’s not true of the medical industry. I mean, they’ve had to retract a million things because the human body is infinitely more mysterious” he stated.
Climate science is astoundingly complex with thousands or millions of variables interacting chaotically. Separating cause and effect is a nightmare, because controlled experiments are impossible. It is stupendously laughable that he could think this task somehow straightforward, or easier than running a double-blind medical study (By the way, this is one reason for the retractions in medicine vs. climate -- medical studies are straightforward enough they can be easily replicated... or not, and thus retracted. Proving cause and effect in climate is so hard that studies may be of low quality, but they are also hard to absolutely disprove).
It is funny of course that he would also say that all of climate scientists predictions have come true. Pretty much none have come true. They expected rapidly rising temperatures and they have in fact risen only modestly, if at all, over the last 20 years or so. They expected more hurricanes and there have been fewer. They called for more tornadoes and there have been fewer. The only reason any have been right at all is that climate scientists have separately forecasts opposite occurrences (e.g. more snow / less snow) so someone has to be right, though this state of affairs hardly argues for the certainty of climate predictions.
By the way, the assumption that Bill Maher is an intelligent person of goodwill who simply disagrees with me on things like climate and vaccines and GMO's is apparently not one he is willing to make himself about his critics. e.g.:
Weekly Standard Senior Writer John McCormack then pointed out that there are legitimate scientists, such as Dr. Richard Lindzen, who are skeptical of man-made climate change theories, but that there were no serious vaccine-skeptic professors, to which Maher rebutted “the ones who are skeptics [on climate change], usually are paid off by the oil industry.”
I will point out to you that the Left's positions on climate, vaccines, and GMO's have many things in common, as I wrote in a long article on evaluating risks here.
Post-modernism is many things and its exact meaning is subject to argument, but I think most would agree that it explicitly rejects things like formalism and realism in favor of socially constructed narratives. In that sense, what I mean by "post-modern science" is not necessarily a rejection of scientific evidence, but a prioritization where support for the favored narrative is more important than the details of scientific evidence. We have seen this for quite a while in climate science, where alarmists, when they talk among themselves, discuss how it is more important for them to support the narrative (catastrophic global warming and, tied with this, an increasing strain of anti-capitalism ala Naomi Klein) than to be true to the facts all the time. As a result, many climate scientists would argue (and have) that accurately expressing the uncertainties in their analysis or documenting counter-veiling evidence is wrong, because it dilutes the narrative.
I think this is the context in which Naomi Oreskes' recent NY Times article should be read. It is telling she uses the issue of secondhand tobacco smoke as an example, because that is one of the best examples I can think of when we let the narrative and our preferred social policy (e.g. banning smoking) to trump the actual scientific evidence. The work used to justify second hand smoke bans is some of the worst science I can think of, and this is what she is holding up as the example she wants to emulate in climate. I have had arguments on second hand smoke where I point out the weakness and in some cases the absurdity of the evidence. When cornered, defenders of bans will say, "well, its something we should do anyway." That is post-modern science -- narrative over rigid adherence to facts.
If you want post-modern science in a nutshell, think of the term "fake but accurate". It is one of the most post-modern phrases I can imagine. It means that certain data, or an analysis, or experiment was somehow wrong or corrupted or failed typical standards of scientific rigor, but was none-the-less "accurate". How can that be? Because accuracy is not defined as logical conformance to observations. It has been redefined as "consistent with the narrative." She actually argues that our standard of evidence should be reduced for things we already "know". But know do we "know" it if we have not checked the evidence? Because for Oreskes, and probably for an unfortunately large portion of modern academia, we "know" things because they are part of the narrative constructed by these self-same academic elites.
Some random highlights:
- I watched a 20 minute presentation in which a woman from LA parks talked repeatedly about the urban heat island being a result of global warming
- I just saw that California State Parks, which is constantly short of money and has perhaps a billion dollars in unfunded maintenance needs, just spent millions of dollars to remove a road from a beachfront park based solely (they claimed) based on projections that 55 inches of sea level rise would cause the road to be a problem. Sea level has been rising 3-4mm a year for over 150 years and even the IPCC, based on old much higher temperature increase forecasts, predicted about a foot of rise.
- One presenter said that a 3-5C temperature rise over the next century represent the low end of reasonable forecasts. Most studies of later are showing a climate sensitivity of 1.5-2.0 C (I still predict 1C) with warming over the rest of the century of about 1C, or about what we saw last century
- I watched them brag for half an hour about spending tons of extra money on make LEED certified buildings. As written here any number of times, most LEED savings come through BS gaming of the rules, like putting in dedicated electric vehicle parking sites (that do not even need a charger to get credit). In a brief moment of honesty, the architect presenting admitted that most of the LEED score for one building came from using used rather than new furniture in the building.
- They said that LEED buildings were not any more efficient than most other commercial buildings getting built, just a matter of whether you wanted to pay for LEED certification -- it was stated that the certification was mostly for the plaque. Which I suppose is fine for private businesses looking for PR, but why are cash-strapped public agencies doing it?
I suppose one could argue that there is some change in reporting rates, since rape is well-know to be an under-reported crime. However, I would struggle to argue that under-reporting rates are going up (which is what it would take to be the prime driver of the trend above). If anything, my guess is that reporting rates are rising such that the chart above actually understates the improvement.
PS- Folks commenting on this post saying that by reporting a declining trend I demonstrate that I don't care about rape or don't treat it seriously are idiots. I have lived through dozens of data-free media scares and witch hunts -- global cooling, global warming, the great pre-school sexual abuse witch hunt, about 20 different narcotics related scares (vodka tampons, anyone?). Data is useful. In this case, knowing there is improvement means we can look for what is driving the improvement and do more of it (though Kevin Drum would likely attribute it to unleaded gasoline).
"Trend that is not a trend" is an occasional feature on this blog. I could probably write three stories a day on this topic if I wished. The media is filled with stories of supposed trends based on single data points or anecdotes rather than, you know, actual trend data. More stories of this type are here. It is not unusual to find that the trend data often support a trend in the opposite direction as claimed by media articles. I have a related category I have started of trends extrapolated from single data points.
The BBC has decided not to every talk to climate skeptics again, in part based on the "evidence" of computer modelling
Climate change skeptics are being banned from BBC News, according to a new report, for fear of misinforming people and to create more of a "balance" when discussing man-made climate change.
The latest casualty is Nigel Lawson, former London chancellor and climate change skeptic, who has just recently been barred from appearing on BBC. Lord Lawson, who has written about climate change, said the corporation is silencing the debate on global warming since he discussed the topic on its Radio 4 Today program in February.
This skeptic accuses "Stalinist" BBC of succumbing to pressure from those with renewable energy interests, like the Green Party, in an editorial for the Daily Mail.
He appeared on February 13 debating with scientist Sir Brian Hoskins, chairman of the Grantham Institute for Climate Change at Imperial College, London, to discuss recent flooding that supposedly was linked to man-made climate change.
Despite the fact that the two intellectuals had a "thoroughly civilized discussion," BBC was "overwhelmed by a well-organized deluge of complaints" following the program. Naysayers harped on the fact that Lawson was not a scientist and said he had no business voicing his opinion on the subject.
Among the objections, including one from Green Party politician Chit Chong, were that Lawson's views were not supported by evidence from computer modeling.
I see this all the time. A lot of things astound me in the climate debate, but perhaps the most astounding has been to be accused of being "anti-science" by people who have such a poor grasp of the scientific process.
Computer models and their output are not evidence of anything. Computer models are extremely useful when we have hypotheses about complex, multi-variable systems. It may not be immediately obvious how to test these hypotheses, so computer models can take these hypothesized formulas and generate predicted values of measurable variables that can then be used to compare to actual physical observations.
This is no different (except in speed and scale) from a person in the 18th century sitting down with Newton's gravitational equations and grinding out five years of predicted positions for Venus (in fact, the original meaning of the word "computer" was a human being who ground out numbers in just his way). That person and his calculations are the exact equivalent of today's computer models. We wouldn't say that those lists of predictions for Venus were "evidence" that Newton was correct. We would use these predictions and compare them to actual measurements of Venus's position over the next five years. If they matched, we would consider that match to be the real evidence that Newton may be correct.
So it is not the existence of the models or their output that are evidence that catastrophic man-made global warming theory is correct. It would be evidence that the output of these predictive models actually match what plays out in reality. Which is why skeptics think the fact that the divergence between climate model temperature forecasts and actual temperatures is important, but we will leave that topic for other days.
The other problem with models
The other problem with computer models, besides the fact that they are not and cannot constitute evidence in and of themselves, is that their results are often sensitive to small changes in tuning or setting of variables, and that these decisions about tuning are often totally opaque to outsiders.
I did computer modelling for years, though of markets and economics rather than climate. But the techniques are substantially the same. And the pitfalls.
Confession time. In my very early days as a consultant, I did something I am not proud of. I was responsible for a complex market model based on a lot of market research and customer service data. Less than a day before the big presentation, and with all the charts and conclusions made, I found a mistake that skewed the results. In later years I would have the moral courage and confidence to cry foul and halt the process, but at the time I ended up tweaking a few key variables to make the model continue to spit out results consistent with our conclusion. It is embarrassing enough I have trouble writing this for public consumption 25 years later.
But it was so easy. A few tweaks to assumptions and I could get the answer I wanted. And no one would ever know. Someone could stare at the model for an hour and not recognize the tuning.
Robert Caprara has similar thoughts in the WSJ (probably behind a paywall) Hat tip to a reader
The computer model was huge—it analyzed every river, sewer treatment plant and drinking-water intake (the places in rivers where municipalities draw their water) in the country. I'll spare you the details, but the model showed huge gains from the program as water quality improved dramatically. By the late 1980s, however, any gains from upgrading sewer treatments would be offset by the additional pollution load coming from people who moved from on-site septic tanks to public sewers, which dump the waste into rivers. Basically the model said we had hit the point of diminishing returns.
When I presented the results to the EPA official in charge, he said that I should go back and "sharpen my pencil." I did. I reviewed assumptions, tweaked coefficients and recalibrated data. But when I reran everything the numbers didn't change much. At our next meeting he told me to run the numbers again.
After three iterations I finally blurted out, "What number are you looking for?" He didn't miss a beat: He told me that he needed to show $2 billion of benefits to get the program renewed. I finally turned enough knobs to get the answer he wanted, and everyone was happy...
I realized that my work for the EPA wasn't that of a scientist, at least in the popular imagination of what a scientist does. It was more like that of a lawyer. My job, as a modeler, was to build the best case for my client's position. The opposition will build its best case for the counter argument and ultimately the truth should prevail.
If opponents don't like what I did with the coefficients, then they should challenge them. And during my decade as an environmental consultant, I was often hired to do just that to someone else's model. But there is no denying that anyone who makes a living building computer models likely does so for the cause of advocacy, not the search for truth.
Stop calling me and other skeptics "climate deniers". No one denies that there is a climate. It is a stupid phrase.
I am willing, even at the risk of the obvious parallel that is being drawn to the Holocaust deniers, to accept the "denier" label, but it has to be attached to a proposition I actually deny, or that can even be denied.
As help in doing so, here are a few reminders (these would also apply to many mainstream skeptics -- I am not an outlier)
- I don't deny that climate changes over time -- who could? So I am not a climate change denier
- I don't deny that the Earth has warmed over the last century (something like 0.7C). So I am not a global warming denier
- I don't deny that man's CO2 has some incremental effect on warming, and perhaps climate change (in fact, man effects climate with many more of his activities other than just CO2 -- land use, with cities on the one hand and irrigated agriculture on the other, has measurable effects on the climate). So I am not a man-made climate change or man-made global warming denier.
What I deny is the catastrophe -- the proposition that man-made global warming** will cause catastrophic climate changes whose adverse affects will outweigh both the benefits of warming as well as the costs of mitigation. I believe that warming forecasts have been substantially exaggerated (in part due to positive feedback assumptions) and that tales of current climate change trends are greatly exaggerated and based more on noting individual outlier events and not through real data on trends (see hurricanes, for example).
Though it loses some of this nuance, I would probably accept "man-made climate catastrophe denier" as a title.
** Postscript -- as a reminder, there is absolutely no science that CO2 can change the climate except through the intermediate step of warming. If you believe it is possible for CO2 to change the climate without there being warming (in the air, in the oceans, somewhere), then you have no right to call anyone else anti-science and you should go review your subject before you continue to embarrass yourself and your allies.
You know that relative of yours, who last Thanksgiving called you anti-science because you had not fully bought into global warming alarm?
Well, it appears that the reason we keep getting called "anti-science" is because climate scientists have a really funny idea of what exactly "science" is.
Apparently, a number of folks have been trying for years to get articles published in peer reviewed journals comparing the IPCC temperature models to actual measurements, and in the process highlighting the divergence of the two. And they keep getting rejected.
Now, the publisher of Environmental Research Letters has explained why. Apparently, in climate science it is "an error" to attempt to compare computer temperature forecasts with the temperatures that actually occurred. In fact, he says that trying to do so "is harmful as it opens the door for oversimplified claims of 'errors' and worse from the climate sceptics media side". Apparently, the purpose of scientific inquiry is to win media wars, and not necessarily to discover truth.
Here is something everyone in climate should remember: The output of models merely represents a hypothesis. When we have complicated hypotheses in complicated systems, and where such hypotheses may encompass many interrelated assumptions, computer models are an important tool for playing out, computationally, what results those hypotheses might translate to in the physical world. It is no different than if Newton had had a computer and took his equation Gmm/R^2 and used the computer to project future orbits for the Earth and other planets (which he and others did, but by hand). But these projections would have no value until they were checked against actual observations. That is how we knew we liked Newton's models better than Ptolemy's -- because they checked out better against actual measurements.
But climate scientists are trying to create some kind of weird world where model results have some sort of independent reality, where in fact the model results should be trusted over measurements when the two diverge. If this is science -- which it is not -- but if it were, then I would be anti-science.
As early as 2009 (and many other more prominent skeptics were discussing it much earlier) I reported on why measuring ocean heat content was a potentially much better measure of greenhouse gas changes to the Earth rather than measuring surface air temperatures. Roger Pielke, in particular, has been arguing this for as long as I can remember.
The simplest explanation for why this is true is that greenhouse gasses increase the energy added to the surface of the Earth, so that is what we would really like to measure, that extra energy. But in fact the vast, vast majority of the heat retention capacity of the Earth's surface is in the oceans, not in the air. Air temperatures may be more immediately sensitive to changes in heat flux, but they are also sensitive to a lot of other noise that tends to mask long-term signals. The best analog I can think of is to imagine that you have two assets, a checking account and your investment portfolio. Looking at surface air temperatures to measure long-term changes in surface heat content is a bit like trying to infer long-term changes in your net worth by looking only at your checking account, whose balance is very volatile, vs. looking at the changing size of your investment portfolio.
Apparently, the alarmists are coming around to this point
Has global warming come to a halt? For the last decade or so the average global surface temperature has been stabilising at around 0.5°C above the long-term average. Can we all relax and assume global warming isn't going to be so bad after all?
Unfortunately not. Instead we appear to be measuring the wrong thing. Doug McNeall and Matthew Palmer, both from the Met Office Hadley Centre in Exeter, have analysed climate simulations and shown that both ocean heat content and net radiation (at the top of the atmosphere) continue to rise, while surface temperature goes in fits and starts. "In my view net radiation is the most fundamental measure of global warming since it directly represents the accumulation of excess solar energy in the Earth system," says Palmer, whose findings are published in the journal Environmental Research Letters.
First, of course, we welcome past ocean heat content deniers to the club. But second, those betting on ocean heat content to save their bacon and keep alarmism alive should consider why skeptics latched onto the metric with such passion. In fact, ocean heat content may be rising more than surface air temperatures, but it has been rising MUCH less than would be predicted from high-sensitivity climate models.
Yesterday I was interviewed for a student radio show, I believe from the USC Annenberg school. I have no quarrel with the staff I worked with, they were all friendly and intelligent.
What depressed me though, as I went through my usual bullet points describing the "lukewarmer" position that is increasingly common among skeptics, was that most of what I said seemed to be new to the interviewer. It was amazing to see that someone presumably well-exposed to the climate debate would actually not have any real idea what one of the two positions really entailed (see here and here for what I outlined). This gets me back to the notion I wrote about a while ago about people relying on their allies to tell them everything they need to know about their opponent's position, without ever actually listening to the opponents.
This topic comes up in the blogosphere from time to time, often framed as being able to pass an ideological Touring test. Can, say, a Republican write a defense of the minimum wage that a reader of the Daily Kos would accept, or will it just come out sounding like a straw man? I feel like I could do it pretty well, despite being a libertarian opposed to the minimum wage. For example:
There is a substantial power imbalance between minimum wage workers and employers, such that employers are able to pay such workers far less than their labor is worth, and far less than they would be willing to pay if they had to. The minimum wage corrects this power imbalance and prevents employers from unfairly exploiting this power imbalance. It forces employers to pay employees something closer to a living wage, though at $7.25 an hour the minimum wage is still too low to be humane and needs to be raised. When companies pay below a living wage, they not only exploit workers but taxpayers as well, since they are accepting a form of corporate welfare when taxpayers (through food stamps and Medicare and the like) help sustain their underpaid workers.
Opponents of the minimum wage will sometimes argue that higher minimum wages reduce employment. However, since in most cases employers of low-skilled workers are paying workers less than they are willing and able to pay, raising the minimum wage has little effect on employment. Studies of the fast food industry by Card and Walker demonstrated that raising the minimum wage had little effect on employment levels. And any loss of employment from higher minimum wages would be more than offset by the Keynesian stimulative effect to the economy as a whole of increasing wages among lower income workers, who tend to consume nearly 100% of incremental income.
Despite the fact that I disagree with this position, I feel I understand it pretty well -- far better, I would say, than most global warming alarmists or even media members bother to try to understand the skeptic position. (I must say that looking back over my argument, it strikes me as more cogent and persuasive than most of the stuff on Daily Kos, so to pass a true Turing test I might have to make it a bit more incoherent).
Back in my consulting days at McKinsey & Company, we had this tradition (in hindsight I would call it almost an affectation) of giving interviewees business cases** to discuss and solve in our job interviews. If I were running a news outlet, I would require interviewees to take an ideological Touring test - take an issue and give me the argument for each side in the way that each side would present it.
This, by the way, is probably why Paul Krugman is my least favorite person in journalism. He knows very well that his opponents have a fairly thoughtful and (to them) well intention-ed argument but pretends to his readers that no such position exists. Which is ironic because in some sense Krugman started the dialog on ideological Turing tests, arguing that liberals can do it easily for conservative positions but conservatives fail at it for liberal positions.
** Want an example? Many of these cases were just strategic choices in some of our consulting work. But some were more generic, meant to test how one might break down and attack a problem. One I used from time to time was, "what is the size of the window glass market in Mexico?" Most applicants were ready for this kind of BS, but I do treasure the look on a few faces of students who had not been warned about such questions. The point of course was to think it through out loud, ie "well there are different sectors, like buildings and autos. Each would have both a new and replacement market. Within buildings there is residential and commercial. Taking one of these, the new residential market would be driven by new home construction times some factor representing windows per house. One might need to understand if Mexican houses used pre-manufactured windows or constructed them from components on the building site." etc. etc.
Matt Ridley has another very good editorial in the WSJ that again does a great job of outlining what I think of as the core skeptic position. Read the whole thing, but a few excerpts:
The United Nations' Intergovernmental Panel on Climate Change will shortly publish the second part of its latest report, on the likely impact of climate change. Government representatives are meeting with scientists in Japan to sex up—sorry, rewrite—a summary of the scientists' accounts of storms, droughts and diseases to come. But the actual report, known as AR5-WGII, is less frightening than its predecessor seven years ago.
The 2007 report was riddled with errors about Himalayan glaciers, the Amazon rain forest, African agriculture, water shortages and other matters, all of which erred in the direction of alarm. This led to a critical appraisal of the report-writing process from a council of national science academies, some of whose recommendations were simply ignored.
Others, however, hit home. According to leaks, this time the full report is much more cautious and vague about worsening cyclones, changes in rainfall, climate-change refugees, and the overall cost of global warming.
It puts the overall cost at less than 2% of GDP for a 2.5 degrees Centigrade (or 4.5 degrees Fahrenheit) temperature increase during this century. This is vastly less than the much heralded prediction of Lord Stern, who said climate change would cost 5%-20% of world GDP in his influential 2006 report for the British government.
It is certainly a strange branch of science where major reports omit a conclusion because that conclusion is not what they wanted to see
The IPCC's September 2013 report abandoned any attempt to estimate the most likely "sensitivity" of the climate to a doubling of atmospheric carbon dioxide. The explanation, buried in a technical summary not published until January, is that "estimates derived from observed climate change tend to best fit the observed surface and ocean warming for [sensitivity] values in the lower part of the likely range." Translation: The data suggest we probably face less warming than the models indicate, but we would rather not say so.
Readers of this site will recognize this statement
None of this contradicts basic physics. Doubling carbon dioxide cannot on its own generate more than about 1.1C (2F) of warming, however long it takes. All the putative warming above that level would come from amplifying factors, chiefly related to water vapor and clouds. The net effect of these factors is the subject of contentious debate.
I have reluctantly accepted the lukewarmer title, though I think it is a bit lame.
In climate science, the real debate has never been between "deniers" and the rest, but between "lukewarmers," who think man-made climate change is real but fairly harmless, and those who think the future is alarming. Scientists like Judith Curry of the Georgia Institute of Technology and Richard Lindzen of MIT have moved steadily toward lukewarm views in recent years.
When I make presentations, I like to start with the following (because it gets everyone's attention): "Yes, I am a denier. But to say 'denier', implies that one is denying some specific proposition. What is that proposition? It can't be 'global warming' because propositions need verbs, otherwise it is like saying one denies weather. I don't deny that the world has warmed over the last century. I don't deny that natural factors play a role in this (though many alarmists seem to). I don't even deny that man has contributed incrementally to this warming. What I deny is the catastrophe. Specifically, I deny that man's CO2 will warm the Earth enough to create a catastrophe. I define "catastrophe" as an outcome where the costs of immediately reducing CO2 output with the associated loss in economic growth would be substantially less than the cost of future adaption and abatement. "
I have not been blogging climate much because none of the debates ever change. So here are some quick updates
- 67% to 90% of all warming in climate forecasts still from assumptions of strong positive feedback in the climate system, rather than from CO2 warming per se (ie models still assuming about 1 degree in CO2 warming is multiplied 3-10 times by positive feedbacks)
- Studies are still mixed about the direction of feedbacks, with as many showing negative as positive feedback. No study that I have seen supports positive feedbacks as large as those used in many climate models
- As a result, climate models are systematically exaggerating warming (from Roy Spenser, click to enlarge). Note that the conformance through 1998 is nothing to get excited about -- most models were rewritten after that date and likely had plugs and adjustments to force the historical match.
- To defend the forecasts, modellers are increasingly blaming natural effects like solar cycles on the miss, natural effects that the same modellers insisted were inherently trivial contributions when skeptics used them to explain part of the temperature rise from 1978-1998.
- By the way, 1978-1998 is still the only period since 1940 when temperatures actually rose, such that increasingly all catastrophic forecasts rely on extrapolations from this one 20-year period. Seriously, look for yourself.
- Alarmists are still blaming every two or three sigma weather pattern on CO2 on global warming (polar vortex, sigh).
- Even when weather is moderate, media hyping of weather events has everyone convinced weather is more extreme, when it is not. (effect explained in context of Summer of the Shark)
- My temperature forecast from 2007 still is doing well. Back in '07 I regressed temperature history to a linear trend plus a sine wave.
This is hilarious. Apparently the polar vortex proves whatever hypothesis you are trying to prove, either cooling or warming:
Scientists have found other indications of global cooling. For one thing there has been anoticeable expansion of the great belt of dry, high-altitude polar winds —the so-calledcircumpolar vortex—that sweep from west to east around the top and bottom of the world.
And guess what Time is saying this week? Yup:
But not only does the cold spell not disprove climate change, it may well be that global warming could be making the occasional bout of extreme cold weather in the U.S. even more likely. Right now much of the U.S. is in the grip of a polar vortex, which is pretty much what it sounds like: a whirlwind of extremely cold, extremely dense air that forms near the poles. Usually the fast winds in the vortex—which can top 100 mph (161 k/h)—keep that cold air locked up in the Arctic. But when the winds weaken, the vortex can begin to wobble like a drunk on his fourth martini, and the Arctic air can escape and spill southward, bringing Arctic weather with it. In this case, nearly the entire polar vortex has tumbled southward, leading to record-breaking cold.
If You Don't Like People Saying That Climate Science is Absurd, Stop Publishing Absurd Un-Scientific Charts
Kevin Drum can't believe the folks at the National Review are still calling global warming science a "myth". As is usual for global warming supporters, he wraps himself in the mantle of science while implying that those who don't toe the line on the declared consensus are somehow anti-science.
Readers will know that as a lukewarmer, I have as little patience with outright CO2 warming deniers as I do with those declaring a catastrophe (for my views read this and this). But if you are going to simply be thunderstruck that some people don't trust climate scientists, then don't post a chart that is a great example of why people think that a lot of global warming science is garbage. Here is Drum's chart:
The problem is that his chart is a splice of multiple data series with very different time resolutions. The series up to about 1850 has data points taken at best every 50 years and likely at 100-200 year or more intervals. It is smoothed so that temperature shifts less than 200 years or so in length won't show up and are smoothed out.
In contrast, the data series after 1850 has data sampled every day or even hour. It has a sampling interval 6 orders of magnitude (over a million times) more frequent. It by definition is smoothed on a time scale substantially shorter than the rest of the data.
In addition, these two data sets use entirely different measurement techniques. The modern data comes from thermometers and satellites, measurement approaches that we understand fairly well. The earlier data comes from some sort of proxy analysis (ice cores, tree rings, sediments, etc.) While we know these proxies generally change with temperature, there are still a lot of questions as to their accuracy and, perhaps more importantly for us here, whether they vary linearly or have any sort of attenuation of the peaks. For example, recent warming has not shown up as strongly in tree ring proxies, raising the question of whether they may also be missing rapid temperature changes or peaks in earlier data for which we don't have thermometers to back-check them (this is an oft-discussed problem called proxy divergence).
The problem is not the accuracy of the data for the last 100 years, though we could quibble this it is perhaps exaggerated by a few tenths of a degree. The problem is with the historic data and using it as a valid comparison to recent data. Even a 100 year increase of about a degree would, in the data series before 1850, be at most a single data point. If the sampling is on 200 year intervals, there is a 50-50 chance a 100 year spike would be missed entirely in the historic data. And even if it were in the data as a single data point, it would be smoothed out at this data scale.
Do you really think that there was never a 100-year period in those last 10,000 years where the temperatures varied by more than 0.1F, as implied by this chart? This chart has a data set that is smoothed to signals no finer than about 200 years and compares it to recent data with no such filter. It is like comparing the annualized GDP increase for the last quarter to the average annual GDP increase for the entire 19th century. It is easy to demonstrate how silly this is. If you cut the chart off at say 1950, before much anthropogenic effect will have occurred, it would still look like this, with an anomalous spike at the right (just a bit shorter). If you believe this analysis, you have to believe that there is an unprecedented spike at the end even without anthropogenic effects.
There are several other issues with this chart that makes it laughably bad for someone to use in the context of arguing that he is the true defender of scientific integrity
- The grey range band is if anything an even bigger scientific absurdity than the main data line. Are they really trying to argue that there were no years, or decades, or even whole centuries that never deviated from a 0.7F baseline anomaly by more than 0.3F for the entire 4000 year period from 7500 years ago to 3500 years ago? I will bet just about anything that the error bars on this analysis should be more than 0.3F, much less the range of variability around the mean. Any natural scientist worth his or her salt would laugh this out of the room. It is absurd. But here it is presented as climate science in the exact same article that the author expresses dismay that anyone would distrust climate science.
- A more minor point, but one that disguises the sampling frequency problem a bit, is that the last dark brown shaded area on the right that is labelled "the last 100 years" is actually at least 300 years wide. Based on the scale, a hundred years should be about one dot on the x axis. This means that 100 years is less than the width of the red line, and the last 60 years or the real anthropogenic period is less than half the width of the red line. We are talking about a temperature change whose duration is half the width of the red line, which hopefully gives you some idea why I say the data sampling and smoothing processes would disguise any past periods similar to the most recent one.
Update: Kevin Drum posted a defense of this chart on Twitter. Here it is: "It was published in Science." Well folks, there is climate debate in a nutshell. An 1000-word dissection of what appears to be wrong with a particular analysis retorted by a five-word appeal to authority.
Update #2: I have explained the issue with a parallel flawed analysis from politics where Drum is more likely to see the flaws.