Anthony Watts of WattsUpWithThat.com and SurfaceStations.org published a 30 page white paper in 2009 with the help of the Heartland Institute titled “Is the U.S. Surface Temperature Record Reliable?” His conclusion was that the temperature record was not reliable due to problems with where thermometers are located.
If Watts were correct, this would be a major problem. If the entire US temperature record was unreliable, then conclusions drawn from the temperature record could also be similarly flawed. At a minimum, the scientific papers using the temperature record would have to be revisited. So a thorough investigation of Watts’ conclusion by scientists was warranted. And now a new peer-reviewed paper by scientists at the National Climate Data Center (NCDC) have analyzed the temperature record and found that Watts’ conclusion of a flawed temperature record runs contrary to the actual data.
Let’s start by looking a little closer at how Watts’ reached his conclusion that the US temperature data was unreliable.
According to Watt’s white paper, 89% of the surveyed temperature stations in the United States Historical Climatology Network (USHCN) do not meet new NOAA standards for proximity to heat sources, location away from shade and the crest of hills, and so on. Watts chose a station in Bainbridge, Georgia, as his main example (pictured at right). It shows that the thermometer is located about 9 feet from an air conditioning unit and in the shade rather than the desired 100 meters from any heat sources. Furthermore, the original thermometer enclosure can be seen just above “14.3′” distance indicator in a much better, but still not ideal location. Given the photographic evidence, it’s impossible to claim that the new thermometer location is ideal. As Watts points out, “the new station may report higher temperatures than the old station even if ambient temperatures remain unchanged.”
But this statement presents a problem. Watts says that the new station “may” report higher temperatures. But do we know for certain that it will? Determining what effect the AC unit and shade tree have on the temperature measurement requires an actual analysis of the temperature data from the new thermometer and location. Watts’ white paper has no such analysis. In fact, in the entire paper, Watts presents a brief analysis of only a single station’s temperature record, and it’s not this station. One station out of a total 865 stations that had been surveyed at the time of the white paper’s publication, and out of a total of 1221 USHCN stations in the continental United States, is not enough to cast doubt on the entire network no matter how bad the analysis turned out.
Watts uses words like “may” and “likely” and “could have” throughout his white paper. In fact, just about the only firm conclusion that Watts reaches is that the temperature record is unreliable. But he’s based that conclusion entirely on qualitative information known as “metadata” (information that may or may not affect the accuracy of a measurement) rather than on quantitative (mathematical) data analysis. With respect to thermometer measurements, the proximity of the thermometer to a heat source like an AC unit or an electrical transformer is metadata. So is the type of thermometer used. And the time of day that the temperature measurement was taken. And the color and composition of the thermometer enclosure. And whether or not the thermometer moved from one place to another. And so on.
The problem is that metadata is a tool to determine if there might be a problem in the real data, but it takes actual data analysis to establish if there’s a problem. And analyzing a single station (Watts used Lampasas, Texas) isn’t enough to draw any statistically valid conclusions, such as reliability or unreliablility, about any other station or about the temperature monitoring network as a whole.
Watts makes a number of other mistakes in his white paper as well. One of the larger errors is that he claims, based exclusively on qualitative metadata, that “89% of the stations surveyed produce unreliable data by NOAA’s own definition (emphasis original).” It’s not possible to make that claim without a detailed mathematical analysis of the temperature record for the supposedly unreliable stations, and Watts shows no such analysis. Watts also claims that “the reported increase in temperature during the twentieth century falls well within the margin of error of the instrument record,” but doesn’t take into account the simple techniques that can be utilized to reduce error in a measurement – techniques like averaging multiple samples, correcting for known biases in equipment, filtering, homogenization of station errors, and so on.
Watts does, however, make a couple of good recommendations in his white paper. One of them is that “a pristine dataset should be produced from the best stations and then compared to the remainder of the USHCN network to quantify the total magnitude of bias.” While this is something that Watts himself probably should have done before making a blanket declaration that the US temperature record was bad, it’s still necessary to quantitatively assess the impacts of all the metadata on real temperature measurements. And that analysis is what the NCDC team undertook in their new paper titled “On the reliability of the U.S. Surface Temperate Record”.
What the NCDC scientists found was that, contrary to Watts’ claim of unreliability, the difference between good and poor sited thermometers was small and thus the US temperature record is reliable.
The NCDC scientists reached this conclusion by looking at thermometer stations scattered around the continental US that were in the surfacestations.org database and broke them up into two groups, one each for good and poor thermometer siting. Then the scientists calculated the monthly temperatures at each station and compared the results of the good stations to the poor sited stations, both before and after adjusting for discontinuities (aka “homogenization”) in the records. When they did this, they discovered that, contrary to what Watts expected, the unadjusted data showed that poor sites showed cooler maximum temperatures and only slightly warmer minimum temperatures, while the adjusted data showed almost no difference whatsoever. This is shown in the image below.
Furthermore, when the scientists continued their analysis, they found that the vast majority of the difference in the unadjusted temperature came not as a result of the location of the thermometer as Watts had claimed, but rather from changes in the technology used to measure temperature (liquid-in-glass thermometers vs. electronic) and from a widespread change from taking measurements in the afternoon to taking them in the morning. In fact, these two changes represented 90% of the adjustment required for good sited temperature stations and 72% of the adjustment needed for poorly sited stations.
The fact that the two transitions mentioned above represents so much of the overall adjustment disproves another claim of Watts’, namely that the homogenization process itself transferred hot temperatures from poorly sited stations to good stations. Had Watts’ claim been correct, then the time of day adjustment would account for a much smaller percentage of the total adjustment. In fact, the data shows that time of day adjustments account for less of the adjustments made to poorly sited stations (72% vs. 90% for good sited stations), suggesting that the good stations are actually correcting the poor ones.
Watts also claimed that the transition from LiG thermometers to electronic thermometers took too long to correct and wouldn’t show up in the data. The analysis in the NCDC paper shows that this claim is also incorrect. In fact, the transition occurred mostly in the mid 1980s, and the transition is clearly visible in the maximum temperature graphs of the figure below where the “adjusted maximum” crosses the red line (0.0 degrees C).
In addition, Watts’ surfacestation.org project classified USHCN temperature stations by using criteria developed for a new generation of climate monitoring stations, known as the United States Climate Reference Network (USCRN). The USCRN stations and the criteria by which they’re gauged as “good” or “poor” are newer and significantly more restrictive than the quality criteria for the USHCN. So Watts’ use of the CRN standards for USHCN stations is something of an apples/oranges comparison. However, the USCRN has 60 months of good data that can be compared to the most recent 60 months of USHCN data. The result is a statistical correlation (r2) of 0.998 and 0.996 for the maximum and minimum monthly temperatures respectively. While this is a short period of correlation, it shows that, at least recently, the USHCN data is clearly reliable. As the NCDC scientists point out,
the value of the USCRN as a benchmark for reducing the uncertainty of history observations from the USHCN and other networks will only increase with time.
The image below visually illustrates the close correlation of the USCRN (black dashes) data to the USHCN data.
Finally, Watts claimed that if the US surface temperature record was unreliable, then by extension, the entire global surface temperature record must be similarly unreliable, since “the U.S. temperature record is widely regarded as being the most reliable of the international databases.” While Watts offered no documentary support for this statement, if we accept his logic, then the results of the NCDC paper clearly show that the international records must be reliable because as the US records have been shown to be. However, it’s certainly possible that the international databases are less reliable than the US database, and so the accuracy of Watts’ original statement is questionable at best.
Ultimately, the paper’s conclusion represents a clear rejection of Watts’ conclusions:
[O]ur analysis and the earlier study by Peterson 2006 illustrate the need for data analysis in establishing the role of station exposure characteristics on temperature trends no matter how compelling the circumstantial evidence of bias may be. In other words, photo and site surveys do not preclude the need for data analysis, and concerns over exposure must be evaluated in light of other changes in observation practice such as new instrumentation.
The NCDC scientists directly acknowledge Watts’ effort at documenting and categorizing the USHCN sites via the surfacestations.org project. And even though Watts’ conclusions in the Heartland Institute white paper cannot be supported, the work he organized and accomplished via a legion of volunteers at surfacestations.org represents a significant contribution to climate science and the surface temperature record in the United States. Unfortunately for Watts, he rushed his white paper to print before he had verified that his conclusions were justified by the measured data.
Ever since Watts and the Heartland Institute published Watts’ white paper, a large number of self-described climate disruption skeptics have been using the white paper as “proof” that that temperature records are riddled with errors. These so-called skeptics claim that the qualitative metadata about the surface stations make strong conclusions about the state of the global climate impossible. The new paper authored the NCDC scientists shows those claims to be wishful thinking. The temperature record clearly shows that the U.S. climate has warmed significantly over the last 130 years, and this paper serves as yet another proof of the robustness of that observation.
Other voices discussing this paper:
Image credits:
Journal of Geophysical Research – Atmospheres
surfacestations.org
Categories: Environment/Nature, Politics/Law/Government, Science/Technology, United States
Progressive Culture | Scholars & Rogues 
“Ever since Watts and the Heartland Institute published Watts’ white paper, a large number of self-described climate disruption skeptics have been using the white paper as “proof” that that temperature records are riddled with errors.”
I think you’re missing the point… It’s good to correct the inaccurate original paper from Watts but it seems that publishing it in the first place is the end goal since most skeptics who read it will run with it, and will not care at all about anyone’s refutation.
It’s like when Fox shows a Republican politician caught in a scandal and “accidentally” puts a “D” under their name (which has happened multiple times). Any correction that happens after the fact is lost since the original impact was the point.
That’s the way they play the game. The battleground isn’t logic with these issues, it’s emotion and fear. They understand that and that’s why they’re winning. Arguing with facts unfortunately isn’t going to help.
Hugo, I agree with you that arguing with facts against gut emotion and wishful thinking doesn’t work. But if I can make the story compelling enough, then the facts are good too. The way to do it is to make the facts relevant to everyone’s life. It’s hard, and sometimes I’m more successful than others, but it does work eventually.
I don’t write this to convince the brain dead. Nothing I write can ever reach the people who can’t see reality due to their ideological blinders, and so I don’t even try any more. I write posts like this in hope that the people who don’t know or who haven’t been convinced yet will think and connect climate science to their own lives. And if something comes along that runs counter to the prevailing scientific explanations, I report that factually too, because that’s how climate science, science in general, works.
This is education as much as reporting, and it’s effective. Slower than I’d like, to be sure, but it is effective over the long run. I know this because I’ve had someone associated with the National Post linked to a post of mine as an example of why he is now convinced that climate disruption is real and that people are the dominant cause this time around. That kind of a win gives you energy for a long, long time.
After this spurious Watts “white paper” was released, right-wing owned radio and television channels ran with it, claiming that this one paper proved that climate change and atmospheric warming was a hoax, a bogus right-wing claim which still continues to this day.
Maybe one of the climate scientists who just refuted all of Watts lies will contact Keith Olbermann’s staff and offer to talk about this on Countdown, bringing charts, pictures, whatever, to present the data so a layman will understand, to counter all the anti-global warming lies.
My major concern is that rising CO2 concentrations in the atmosphere not only will lead to more global warming and ice melting but will start a chain reaction in which the melting of ice/permafrost and increase in ocean temperatures will release huge amounts of methane into the atmosphere (with methane being 20 times more potent as a greenhouse gas than CO2), thus compounding global warming exponentially. Worst case scenario? Or actually a conservative estimate of what appears to be happening already?
Eli has been pointing out for years, that pretty much for every “hot looking station” you find a “cold looking” due to shading and other such. Giorgio Gilestro nails this
http://www.gilestro.tk/2009/lots-of-smoke-hardly-any-gun-do-climatologists-falsify-data/
It would be in the best interest of everyone to leave the politics out of this and allow the science to be done, by real scientists, not amateur pundits or science by consensus, . If you don’t have a PhD in one of the physical sciences, leave it alone….seriously.
No one in their right mind denies that climate changes on a cyclical basis, always has always will. It’s the man made postulate that needs to be subject to the rigors of the scientific method(not just statistical analysis and questionable math), leaving politics and personal agenda out of the equation. Lets prove it scientifically, and I hope to not be flamed by non scientists, liberal arts types, political types and those not trained in the physical sciences
Jeff
If I recall, you don’t have a PhD in economics or politics. I trust we’ll be hearing no more from you on these subjects, then?
Sam, although I lack your excellent credentials in media from a state school, I did get mine in Physical Chemistry, so my authority on the subject is a wee bit better than yours. You still are the most self-righteous person I’ve ever come across and you can’t even see it. I think I can speak about the science in a dispassionate manner, which I was trying to do in my response. You will remember that I did say that nobody was denying that climate has cyclical changes.. As for economics, I play with the big boys and risk my own money, not like the words you are only willing to risk. However, you are just fucking with me, showing me that your internet dick is bigger than mine. That’s OK with me, because I suspect that you really need a victory in your life, so I’ll give you this one. This is on me. Cheers, Jeff
Jeff
Keep talking, Jeff. Please – talk more, in fact. You’ve gone out of your way to insult just about everybody who isn’t, well, you. People who went to state schools are inferior. People who lack your inherently good “breeding” are inferior. And so on.
Keep talking. Every time you hit send you make an important point. But for now, the issue isn’t whether the institution that issued your degree makes you smarter than everybody else, it’s about how climate disruption deniers keep trying to derail productive policy development in service to vested corporate interests.
But no threadfucking. Keep it on point, if you would.
This whole topic is a hed herring. There is no such thing as the “US climate”. There is only one climate here – Earth’s whole climate. Further the land is only 25% of the Earth’s surface and the area populated by humans (which most temperature stations are clustered near) is only 15% of the Earth’s surface. The greenhouse effect only has a significant influence on night time temperatures, and so does the UHI effect. The argument that GISS (etc) are uncontaminated by UHI because temperatures are recorded at mid-morning is a totally sound argument – but it also removes the ability to measure any significant greenhouse influence at all at urban stations (whether the site meets USCRN requirements or not).
There is only one accurate measurement of Earth’s whole average surface temperature (weather satellites) and the sad fact is we only have 30 years of data from that source – which in climatic terms is three 10-year data points.
Would you, as a scientist familiar with statistics and data analysis, make confident recommendations based on only 3 data points? Because as an amateur the only recommendation I would make is that “more research is needed”.
The oft-repeated “skeptical” claim that the world has cooled for the last 10 years is indeed as statistically unsound as the claim made by warmists that there is overwhelming evidence of AGW. There is insufficient reliable data to work with in both cases. Whether it is over 10 years or 10000 years, the world has a warming or cooling trend depending on where you cherry-pick your endpoints. According to John Brignell, fitting a line to any non-linear signal is only valid if you are trying to remove a linear bias from that signal. In essence the true signal is infinite but the line slope can only be calculated from a finite subset, so any fitted line is inherently cherry picked. Accordingly, fitting any line to any Earth temperature series for the purpose of showing a trend is disingenuous regardless of the time frame. (And you won’t see that written in the newspapers!)
The null hypothesis (of natural warming) is still the winner so far. That’s not to say it’s the truth, but that there is not yet a scientific way to arrive at any other conclusion.
One line of argument I would accept if data supported it would be the argument that human activity has changed the operation of the climate system so much that all pre-industrial evidence is null and void and that the rules are different now. That would be a big claim demanding big evidence that has not been observed.
Instead we are left with many contrary facts. Rates of CO2 increase have been higher in the distant past than today. CO2 concentrations have been naturally 10 times higher than today. Most 20th century warming occurred before most 20th century industrialisation had occurred. Further, the cycle in incident sun power of ~7% (ie +/-3.5% of average) over each year causes an asymmetric response between the NH and SH that is enough to explain most temperature changes. (see http://www.palisad.com/co2/slides/siframes.html )
No observations require us to venture further than natural phenomena to explain the recent temperature history.
I hate being wrong, so where is the credible evidence that says otherwise?
As for the assertion that us plebs should just leave the PhDs to do their jobs, in the present situation I have to disagree. It is the pre-emptive politicisation of climate research for the purpose of imposing fraudulent carbon taxation schemes that has led to the public getting involved. The sequence of claim and counterclaim has always happened in scientific circles, just not with as much publicity as this issue has received. Furthermore, everyone both can and should apply the scientific method – regardless of whether they have a PhD. Science is for everyone.
Andrew,
Lots of mostly off-topic misinformation there. Allow me to clean it up some.
First, there certainly such a thing as “US climate” just as there’s “UK climate” and “global climate” and “North rim of the Grand Canyon climate.” Climate is defined as the average weather (temperature, wind, precipitation) in a particular area. The area can be defined as large or as small as you like, although there are standards. Look up any map of global climatic regions, for example, or if you prefer, the USDA plant hardiness regions – they represent differing types of climate within the US.
Second, it’s my understanding that greenhouse warming works equally at night and during the day, but that during the day other effects may dominate (effects that would be minimized by taking temperature measurements in the morning, such as cloudiness). If you have a paper that says otherwise, I’d love to read it – the conclusions of this paper, however, support my statement:
Third, greenhouse effect forcings are not like cloud effects – they are persistant and are widely spatially distributed (CO2 is well-mixed globally, in fact, while methane is well-mixed on a hemispherical basis). So they affect all temperature stations more or less equally, regardless of what time of day the temperature measurements are taking.
Fourth, you might have had a point about the satellite record if it were the only record we had. In fact, however, we have 30 years of data that correlates pretty well with the surface temperature record. The first image below shows a scatter plot of the three main surface temperature records with the RSS satellite dataset, the second with the UAH satellite data, using monthly data from January 1979 to September 2009.
Fifth, I can’t help but wonder how much data you require in order to draw conclusions about whether the climate is warming and if human activity is the cause this time. Do you care to explain what you do need? Because I can show, with data, that a) scientists know CO2 is a greenhouse gas, b) CO2 concentrations have increased dramatically since pre-industrial times and are still increasing, c) that human activity is responsible for the increase, d) that there are multiple, independent sources of inquiry that have determined a range for “climate sensitivity” and that the climate feedback is positive instead of negative, e) that concentrations of other greenhouse gases are increasing, f) that human activity is responsible for, depending on the gas, between 50% and 100% of the various increases. If that’s not enough, fine – what more do you need?
Sixth, what you describe with respect to linear trends is somewhat true, but also somewhat false. It’s called endpoint sensitivity, and it’s a well known function of linear trends. The problem with linear trends, however, isn’t so much in the trend or the sensitivity of the trend to end points, but how you use the trend. For example, if I state up-front that I’m intentionally making my analysis conservative by choosing an unreasonably bad endpoint, then the trend analysis probably bounds one end or another. If you read this comment, you’ll find an example of what I mean.
Ultimately, though, linear trends are a useful tool if used properly. The question is whether any given linear trend is being used and presented correctly or not. In my experience, the trends I see generated by climate disruption deniers such as Joe D’Aleo, Lord Monckton, and Fred Singer are usually cherry-picked to support a claim that is not mathematically or scientifically valid. Trends produced by climate scientists are generally better quality if for no other reason than the scientists tend to explain the limitations and caveats of the trends.
It’s instructive to note, however, that the conclusions that climate disruption is real is not reliant on simple linear trends and linear correlations – they’ve been analyzed using statistically robust methods and found to still be accurate.
Seventh, I’ve not seen any evidence anywhere that rates of change of CO2 have been higher in the past. Do you have a reference for that claim?
Eigth, you’re claim about temperature rise is incorrect. If you look at the last century’s surface temperature record (pictured below), you find that the temperature anomaly was about 0.8 C lower than today back at the turn of the century, it went up until the 1940s (about +0.4C), dropped again until then 1970s (about -0.1C), and then rose again to the turn of the century (about +0.5C). That says that no more than 50% was “before” industrialization, not “most.”
And finally, there are a huge number of flaws in that .ppt file, enough that debunking it would be worth a post all of its own. One is the “CO2 is plant food” argument, which is only true in a world where there’s enough other nutrients to feed plant growth (and there isn’t – see this paper). Another is “CO2 follows warming,” which is based on a logical fallacy that I addressed in detail here.
Regarding the “CO2 follows warming” argument….
In his most excellent lecture at the 2009 AGU fall meeting, Dr Richard Alley debunked the “CO2 follows warming” talking-point with this analogy (paraphrasing here):
“Interest lags debt. How do we know that interest adds to debt?”
Dr. Alley’s lecture can be viewed here: http://www.agu.org/meetings/fm09/lectures/lecture_videos/A23A.shtml
The “CO2 lags warming” debunking can be found about 36 minutes (IIRC) into the video.
AKA as Chicken hatch from eggs therefore chickens cannot lay eggs.
I thought I had a reference, but then when I checked it again the guy said no such thing. I don’t think I made this one up, but I can’t remember where I saw it. I’d have to agree the fallacy of predictions from history makes any such data irrelevent, but if we do not base models on ancient history then we have even less of a basis to conclude AGW than if we do. Othwerwise we’d have to wait another 30 years to get more accurate data.
The closest I can get is Vostok CO2 analyis. The samples are CO2 integrated across 1000 years or more, so it is not possible to conclude that CO2 has never risen as quickly as it is today. Perhaps it rose as quickly, on many occasions, but never stayed high for long enough to produce a bump in a 1000 year slice. Again a lack of data.
Out of interest if you draw a straight line from the last in that series to the modern CO2 (an imaginary 2000 year slice) it would be a 4ppm/century change, and there’s plenty of samples in the Vostok data which are as high as that or in some cases higher. Not a good enough basis to draw conclusions, but interesting.
As for the rest of your responses… you’ve given me a lot of reading to do!
Your page of “myths debunked” is also remarkable for how many strawmen it contains and just how much it shows that the skeptics and the warmers actually agree on nearly everything. Plus I found the parts about 13Carbon and the recent increasing ocean CO2 very interesting. I hadn’t heard of those from the skeptic camp – as one might expect I guess.
It’s really just that last link in the argument of showing how much warming CO2 causes at today’s levels that is the main point of contention.
“… keep trying to derail productive policy development in service to vested corporate interests.”
man, did you hit the nail.
http://network.nationalpost.com/np/blogs/fpcomment/archive/2009/05/30/lawrence-solomon-enron-s-other-secret.aspx
http://www.jpmorgan.com/pages/jpmorgan/news/climatecare
http://www.jpmorganclimatecare.com/