Since he prefers a Kim Jong Il-style commenter policy –“only those who flatter the Premier need comment” — Anthony Watts‘s site doesn’t get the pleasure of my visits much, anymore. Consequently I missed the announcement he made last week that he was “suspending” his blog, at least temporarily, until some great news came out.
Anthony Watts, June, 2010. Speaking in Gold Coast, Australia, on a tour searching to find some place on Earth not affected by global warming. (Photo: Wikipedia)
Now the great news is out. I think. Watts may have been right to suspend blogging. He should have kept the suspension longer.
Watts says NOAA‘s temperature measurement in the U.S. is way off, and that if we ignore all the cities, and if we ignore sites that show the greatest increases in temperature over the past century or so, global warming doesn’t look so bad.
Watts said he is the lead author on a new paper questioning all warming calculations:
This pre-publication draft paper, titled An area and distance weighted analysis of the impacts of station exposure on the U.S. Historical Climatology Network temperatures and temperature trends, is co-authored by Anthony Watts of California, Evan Jones of New York, Stephen McIntyre of Toronto, Canada, and Dr. John R. Christy from the Department of Atmospheric Science, University of Alabama, Huntsville, is to be submitted for publication.
Wait a minute. “Prepublication draft paper?” ” . . . to be submitted for publication?”
Yes, Dear Reader, that claxon you hear is your and my Hemingway III Solid Gold [Excrement] Detectors™ going off. It may be a false alarm, but still — isn’t this how bogus science is done, isn’t this what Robert Park warns us about? Indeed, in the Seven Warning Signs of Bogus Science, Park says to pay attention to key indicators: “1. The discoverer pitches the claim directly to the media.” It is, indeed, a press release from Watts, about a paper he hopes to get through the peer review process at some point in the future — but it has not yet been pitched to the science journals. (Yes, that’s also one of the Seven Warning Signs of Bogus History . . . one discipline at a time, please.)
What’s the rush? Oh: Tuesday, July 31, is the deadline for peer reviewed papers to be submitted to the international agency studying climate change, the Internatioinal (IPCC), for consideration and inclusion in the next report.
Same old stuff, new day. Watts has been arguing for years that NOAA’s temperature measurements err, but after the Berkeley Earth Surface Temperatures (BEST) Project determined that warming exists, even using Watts’s modified measurements and accounting for his claimed errors, some of us hoped Watts might turn to blogging about science, instead.
No, Watts turned to finding a hint of a methodology that might support his preconceived notions. He found one.
So, Watts’s big announcement is that he’s found a methdology which favors his criticisms of NOAA; so we should ignore temperature readings from cities, because cities are hot, and we should ignore temperature readings from suburbs of cities, because suburbs are warm; and if we do that, then warming in the U.S. doesn’t look so bad.
Were I allowed to ask questions at Watts’s blog, I’d ask why we should ignore warming in cities, because are they not part of the planet? Oh, well.
The Twitter version:
Watts: Ignore city temps (hot!) and ‘burbs (warm!), temps on farms don’t show so much global warming! Oops – did we say that before?
Anthony, how about you suspend your blog until you get the paper accepted at a good journal? Make sure you got the numbers right . . .
More:
- Stoat at ScienceBlog: “Watts disappoints”
- Climate Denial Crock of the Week: Warming caused by man
- Denier Denier Denier … (tamino.wordpress.com)
- Where’s the Skepticism? (tamino.wordpress.com)
- Anthony Watts Is Right Because He’s Older Than Me (desmogblog.com)
- Is the United States Actually Getting Warmer? (powerlineblog.com)
- UPDATE: (Koch-funded) Scientist changes opinion, finds warming due to humans (including Kochs)
- Shortened even more: See discussion at Rabett Run
- Stoat says the paper will likely be unpublished forever
- MediaMatters notes the rather political, unsciency nature of Watts’s paper, and reactions in its favor
Millard Fillmore's Bathtub 
These links will enable you to observe and rate stations for yourselves.
Link to Leroy (2010):
Click to access CS202_Leroy.pdf
Link to visual evidence of station siting:
http://gallery.surfacestations.org/main.php?g2_itemId=20
You will also need Google Earth. (Bing Maps “birdseye” views are also helpful.)
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There may be some value in your study, Evan, but y’all remind me a lot of creationist paleontologists, who having found a fossil under layers of stone, then work to develop a hypothesis on how so many annual layers could be put down in just a few days in a massive flood like the one Noah had — no evidence of such a flood, no evidence of shortened rock building, but an assumption that scientists got it wrong.
We do not assume. We observe.
Your response to those observations, as stated earlier, is that perhaps the poorly sited stations are accurate and the well sited stations are not.
If the well sited stations warmed more than the poorly sited stations or there was no difference between the two trends, ask yourself, would you be making that argument? It appears to me that sort of approach is more akin to what the creationist so-called “scientists” are doing than what we are doing. So you should be wary of falling into that fallacy.
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By the way, it is not necessary to “probe Watts” as to what is a well sited station and what is not. Leroy (2010) is the tool to use to for that. Just apply that method (which is approved by WMO) and you can determine for yourself whether a station is well or poorly sited.
You will find that on surfacestations.org, I have posted hundreds of “measurement views” (using the ruler feature of Google Earth) that will make station evaluation quite accessible to the independent reviewer.
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I fail to see how anything published three years ago, long before any analysis had been made using Leroy (2010), can “nail” anything.
When the final paper is published, my entire set of spreadsheets will be made available for review and as a tool for further study and inquiry. At that point, you will be able to check, personally, whether or not my findings are or are not crap.
I can now add that I have recently found that when removing TOBS-biased stations, my earlier dataset (the basis for Fall et al., 2011), shows significant differences between the well sited USHCN Tmean trends and poorly sited stations, i.e., using Leroy (1999) as opposed to Leroy (2010) even after accounting for MMTS conversion. Not as great as Leroy 2010, but still significant.
If you can look at the issue unemotionally it should be easy to perceive that if microsite and/or equipment bias is prevalent, then any homogenization method that does not account for that is going to yield seriously incorrect results.
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Sorry Evan, Atmoz nailed your crap three years ago
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You know, when we observe phenomena, we tend to look for causes. Watts assumes the cause is evil scientists, or at best, scientists who are idiots.
[citation needed]
I don’t think that’s a safe assumption — it’s not what research shows. I’m not seeing any research to establish that, in fact, “poorly-sited” weather stations are not accurate
It’s what the data shows. Better come up with a new theory, methinks.
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>> We shall see …
>Yes, we did.
Indeed we did. the greater scientific community said we needed to account for TOBS and MMTS adjustment.
So that’s exactly what I did.
It will have saved us a lot of time and trouble come peer-review time.
Funny, though, no one gave a hoot in hell about either one of those factors when it came to Fall, et al. Was that because the opponents of Watts’ hypothesis liked those results – which indicated that siting did NOT matter regarding Tmean trends? #B-)
But all of a sudden, when the followup shows siting DOES matter, those factors become of primary importance. In fact they are assumed to have invalidated our study. Without even checking. Well, I checked. And they do NOT invalidate our study, though they do affect the results, somewhat.
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If the warming trend found (or picked) by Watts et al is lower than that of the surrounding oceans then they have identified a significant UNDERREADING of the land temperture trend in the contiguous 48.
Good lord, no. SST is much lower than what we find.
But you do have to consider that the PDO will sharply increase SST in the Pacific equatorial area, because, well, that’s what PDO does. And you also must remember that we are measuring CONUS land temperature trends, only, and form 1979 – 2008, only. Not global temps.
Overall, though, SST increase is lower than what we find.
And we don’t “pick”. To the extent we exclude stations, it works heavily against our hypothesis, not for it. I have said this before, and I can demonstrate it clearly. No, I don’t cheat to prove a thesis. To the extent I do “cheat”, I cheat against myself.
And, no, I have not received one thin dime from Big Oil, or anyone else, for that matter. I rely solely on GE (with measurement capacity), NOAA/MMS, and photos taken by unpaid volunteers. I work very hard for over ten hours a day, so all of my USHCN efforts come out of the rest of my time.
There are two primary conclusions one may draw from Watts, et al., and some inference leading to other hypotheses which require further examination.
Conclusions:
— Siting matters. Microsite, especially, but also mesosite. They not only affect temperature levels, but affect trend as well.
— Equipment matters. That also heavily affects trends. That was not something we expected, but it jumps out bigtime from the data.
Those are very damn important scientific findings, in and of themselves. And they both throw a very big monkey wrench in the way NOAA/NCDC, HadCRU adjusts the raw data: Homogenization is a fatally flawed approach as it is currently conducted (I have explained the whys and wherefores previously in this thread).
Inferences:
— USHCN is regarded as a gold standard for climate networks. That means GHCN is called into serious question as well. We have not examined GHCN, so it becomes very important to do just that.
We don’t have the resources to do it, ourselves, though. Station locations are provided only to two decimal places past the degree level, so we can’t locate those stations on our own. And Google Earth does not provide resolution worldwide as it does in the US, so we can’t pick out enough of the stations “from the air”, even if precise coordinates were provided. Also, we have not the volunteers to photograph them from the ground.
— What goes up must come down. That is to say that we would hypothesize that during a cooling trend, the opposite effects would occur: namely that poorly sited stations and CRS equipment would be expected cool faster than well sited stations.
But we have not the data to determine this: there is no way I know of to precisely locate sufficient station sites prior to 1979. The coordinates are very inexact prior to GPS technology.
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Greenbelted cities may not warm faster than rural areas. Watts says greenbelted cities are not cooler at all, and that cities that do not have greenbelts, show inaccurate warming, because they warm faster than greenbelted cities. Not every city is as future-oriented, nor sustainability-biased, as Boulder, Colorado.
You know, when we observe phenomena, we tend to look for causes. Watts assumes the cause is evil scientists, or at best, scientists who are idiots.
I don’t think that’s a safe assumption — it’s not what research shows. I’m not seeing any research to establish that, in fact, “poorly-sited” weather stations are not accurate, nor to establish that, if they are inaccurate, they are all inaccurate in the same direction (which might be a stretch). You assume that because a set of stations you claim to be badly sited measure warmer temperatures, they’re wrong.
Where is the testing to see if that’s the case?
Then, when I probe Watts on what is a “poorly-sited” station, I see him spouting off claims that airports are all urban heat islands, without any serious study to see whether that is so; and assumptions that, since Watts thinks airport weather stations are wrong, there must be causes for that error that in reality do not show up. Regardless Anthony’s assumptions, the weather sensors at BWI are not at the eastern end Runway 11, and they’re closer to forest than a mass of concrete.
There may be some value in your study, Evan, but y’all remind me a lot of creationist paleontologists, who having found a fossil under layers of stone, then work to develop a hypothesis on how so many annual layers could be put down in just a few days in a massive flood like the one Noah had — no evidence of such a flood, no evidence of shortened rock building, but an assumption that scientists got it wrong.
Can you answer Robert Park’s Seven Warning Signs of Bogus Science? http://www.quackwatch.org/01QuackeryRelatedTopics/signs.html
I think you’re squarely in the category on the first two warning signs.
And while you’re fiddling with data on a minor point, glaciers melt, cheat grass takes over the west, shellfish go extinct, coral reefs die, deserts advance, harbors flood, and Nero fiddles along with you.
Tell me that, at least, Heartland Institute isn’t funding your work, nor Exxon-Mobil, nor the “Marshall” Institute.
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Watts, when he criticizes BWI’s weather station for being too close to other runways, when it’s not close to any other runways and surrounded on three sides by forest.
Watts, when he claims the greenbelt around Boulder, Colorado — twice the size of the city itself — doesn’t cool things off there.
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> We shall see …
Yes, we did.
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The gold standard comparison is the sea surface temperature.
It has no siting or UHI issues although there may be an underestimate of the warming trend due to instrument and orbital variation factors.
But the warming trend on land must at least equal the trend in sea surface temperatures and should exceed them. If the warming trend found (or picked) by Watts et al is lower than that of the surrounding oceans then they have identified a significant UNDERREADING of the land temperture trend in the contiguous 48.
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Dagnabbit.
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Evan Jones said back on December 23, 2012 at 8:19 am:
OK, let’s grant Jones the suspension of the laws of physics to which others have tried to introduce him.
If the planet is warming at half the rate (or less) that professional science has noted to date, then the response of the cryosphere and the biosphere to the WJMC version is frighteningly more sensitive than even people such as Hansen have indicated. Given the inertia and commitment already laid into the warming of the planet, and granting WJMC their version of temperature response to increasing CO2, the future inevitably non-linear cryospheric and biospheric responses to inevitable warming are grave indeed.
In essence, if WJMC want to claim low temperature sensitivity, they are directly implying even catastrophically-sensitive cryospheric, biospheric and meteorological sensitivities than conservative mainstream science indicates. They might think that they are able to make some of the warming ‘go away’, but doing so reveals an even bigger monster to compensate.
There’s no such thing as a free lunch…
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Evan Jones said back on December 23, 2012 at 8:19 am:
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Regarding your latest on airports:
If what you were saying were relevant in the least, airport trends would match non-airport trends. But they are somewhat higher than their non-AP counterparts. Especially the poorly sited AP trends.
Well sited AP trends clock in around 6.5% higher than non-AP trends. Poorly sited AP trends are 30% higher than poorly sited non-AP trends.
Some of that may be from the HO-83 bias. But whether it is from equipment flaws or from conditions pertaining to airports themselves, AP trends are higher.
That is the bottom line. The data. The rest is handwaving. You can cite any expert you like. We cite the data.
And, to repeat (for maybe the fifth time), by far the most important factor in the exaggeration of USHCN trend is not the terrain (AP or urban). It’s the equipment and the micrositing. Both critics and supporters seem to fail to get that.
If the equipment is MMTS and it is properly sited, then the trend is a mere ~47% of the “official” adjusted trend data, be the terrain urban or whatever. And that is after a hefty upward adjustment to account for MMTS conversion. That is the point you need to be addressing.
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Trees tend to cool stuff whether they’re near cropland, or away from it, or in a city, Eli. This is something Anthony Watts doesn’t want to acknowledge.
Who said we don’t acknowledge that?
And this is why I think his exercise is little more than scientific statistical masturbation.
How does that invalidate anything? Urban sites are part of the environment and rural areas aren’t?
Both are. So ~1.5% of sites should be urban, 15% of sites should be semi-rural, 19.5% of sites should be cropland, 0.5% (at most) should be in airports, and the rest should be rural.
Rural sites can be desert, shrub, forest, etc. By no means are all near trees, but the same % should be near trees as % of land is covered with trees.
No TOBS-biased sites (until TOBS has been constant for well over 25 years). MMTS adjustments to be made (until stations have been MMTS for over 30 years).
How can anyone possibly argue against that?
The net result of that warming is ~ half the official number.
We know that greenbelts cool cities. Watts dismisses this information as invalid.
How is that relevant. If greenbelts cooled cities so much, then cities would not warm faster than than rural areas. They do.
At worst, if everything Jones and Watts claim is accurate, warming is slightly less severe in some rural areas, though the damage is more alarming then, because it’s caused by less severe warming.
Mmm, nope.
First off, that would be “at best”. As is “at best” the hole in the boat is much smaller than we thought. Not “at worst”.
Then: Warming is around half what is claimed. Two thirds, at most.
And: Not only is there no net damage from warming so far, there is net benefit. With a considerable increase in biomass, especially in the rainforests and an overall greening of the Sahel. And there will be net benefit from a further 1C of warming. So says the IPCC.
If it warms 3 to 5 degrees, all bets are off. But there would have to be powerful positive feedbacks in effect for that to be the case. But there is no empirical evidence of positive feedbacks, so far. Only negative feedbacks. This should come as no surprise. Warming would have have spun out of control eons ago if homeostasis were not the null hypothesis.
In his current paper, he argues that city temperatures are skewed, and suburban temperatures are skewed, and that if we ignore those readings, warming isn’t so bad (though, even Watts finds there is still warming beyond a natural trend).
Again, I repeat: Terrain (cities, airports, semi-rural) are the least of it. The two main spurious factors are equipment bias and microsite. NOT mesosite. Warming is “not so bad” if the micrositing is proper and the equipment is modernized — even if the site is in a city or airport.
I have pointed this out at least three times. Please acknowledge.
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This is the crap that makes me nuts dealing with anyone affiliated with Watts, Evan.
In a post complaining about BWI’s station siting, Watts said:
Here are the problems with accuracy and science in those three sentences:
1. There is no “nearby runway.” Runway 10 is out there all by itself. The nearest runway from that spot is thousands of feet away.
2. This station is at the west end of the runway, that runs in a straight line along a compass path of 100 degrees. (Add a zero to the number of the runway, you get the compass direction — this is “Runway 10,” so it’s heading in a line at 100 degrees; the other end would be “Runway 28,” since it’s exactly opposite.) In other words, if a westerly wind blew in, it wouldn’t blow over the runway to get to the weather station.
3. West of the weather station and the end of the runway is a forest. A west wind would get to the weather station through the forest.
I think this will take you to a Bing map showing the runway.
Now, I don’t deny that wind over the concrete might be warmer, especially if it traveled the length of a runway on a very warm day — but 60 degrees F is not “very warm.”
I don’t know why the guy at BWI said what he did, but a westerly wind can’t do what Watts claims it does here, not unless the forest is hotter than the runway (possible — it can get cold out there in the wind).
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Trees tend to cool stuff whether they’re near cropland, or away from it, or in a city, Eli. This is something Anthony Watts doesn’t want to acknowledge.
And this is why I think his exercise is little more than scientific statistical masturbation.
We know that greenbelts cool cities. Watts dismisses this information as invalid. See here: https://timpanogos.wordpress.com/2010/03/15/boulder-and-fort-collins-wise-city-action-prevents-global-warming/
Watts claims airports are too warm, even though some of them, like Thurgood Marshall Baltimore-Washington International are populated by forests and are quite rural even as development springs up around them (these sites are larger than major cities, and forested — opposite of UHI effect). (Except when it suits Watts to claim a heat spike skews the effect — then he’s happy with the cooler temps;
also, never mind that if the wind blows from the west, it crosses the runway perpendicularly, and so probably couldn’t gain much heat from a 30 yard concrete path).(Every time Watts goes after BWI it makes me ill. The runway he cites is Runway 10, which means it’s 100 degreesoff of North, almost north-south.or almost East-West [whew! — took a comet watch break and lost my train of thought there; sorry) — and the station is at the far west end of the runway. Consequently, the west wind he complains about here wouldn’t spend enough time running over the runway to heat up —it crosses the runway perpendicularly;it runs parallel to the runway, not across it; worse, what Watts or his minion claims as runway [in pictures at Watts’s site] isn’t a runway — it’s a taxiway/equipment storage area. Plus, its at thenorthwest end of the airport, closer to forest than any other concrete or any other building. Sheesh.)In any case, I’m not convinced that Watts can do a statistical study to show that thermometers are wrong. At worst, these temperature readings are used to corroborate warming indications from other things, measured differently — and the corroboration shows the warming, but the primary measures show more warming than the weather stations.
I’m not convinced that the warmer trend isn’t more accurate, still.
At worst, if everything Jones and Watts claim is accurate, warming is slightly less severe in some rural areas, though the damage is more alarming then, because it’s caused by less severe warming.
1. https://timpanogos.wordpress.com/2013/03/11/annals-of-global-warming-nasa-finds-amplified-greenhouse-effects-shift-northern-growing-seasons/
2. https://timpanogos.wordpress.com/2012/12/17/annals-of-global-warming-333rd-consecutive-month-above-20th-century-average-temperature/
3. https://timpanogos.wordpress.com/2011/03/26/annals-of-global-warming-records-from-mauna-loa-show-continuing-rise-in-atmospheric-co2/
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I’ll add that the great majority of non-cropland rural sites tend to be near things called “buildings” . . .
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Yes, quite.
And it is underrepresented by the USHCN.
That’s the point.
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Non cropland rural sites tend to be near things called trees and bushes which have cooling effects. Something Eli pointed out years ago
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The Twitter version:
Watts: Ignore city temps (hot!) and ‘burbs (warm!), temps on farms don’t show so much global warming! Oops – did we say that before?
Anthony, how about you suspend your blog until you get the paper accepted at a good journal? Make sure you got the numbers right . . .
My comment on the conclusion of the article:
We find that farms warm more than cities. But cropland is only 19.5% of CONUS land use, while USHCN cropland sites are over 29% of total.
So that is somewhat overrepresented.
The non-cropland rural sites are underrepresented, and those yield the lowest trends.
I think I will look at the subset results and weight them at the same rate that they represent land use, but using only MMTS-majority sensors to eliminate equipment bias. That would yield an overall “correct” result. It would include all types of terrain, including urban.
According to NOAA, MMTS sensors are the best. There is peer reviewed literature explaining why MMTS is superior to CRS and yields more accurate readings. The reason given is the superior gill structure of the MMTS, and that CRS “box in” temperatures, creating an artifact at Tmax and Tmin. That’s the reason NOAA switched over from CRS to MMTS.
Unfortunately, the MMTS has to be physically cabled, so there is a problem locating them far enough away from heat sinks and waste heat. So there is a tendency to trench until you hit asphalt and then stop (it is difficult to trench through asphalt, and you have to replace it afterwards). So microsite suffers as a result.
But fortunately there are enough well sited MMTS sensors for a statistically robust sample.
Finally, I have spent at least a couple hundred hours of QC since the initial release to ensure that the results are right:
1.) Folks will be going over the results with a fine-toothed comb after publication, so it is vital to get it right.
2.) We really, really do want to get it right — just for the sake of getting it right.
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Unless your data shows warming isn’t happening, your report is just fog in the discussion.
That statement makes zero sense. Please explain why identifying the correct rate of warming and identifying a serious measurement error is “just fog in the discussion”. Why is precision “fog” and lack of precision “not fog”?
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First, “artificial” means “not real”. As in the term “artifact”, used all the time by scientists. And it does not imply dishonesty. It implies error.
Besides, in both the article and in the paper, we emphasize that it is not a result of dishonesty, but a result of the wrong criterion: Leroy (1999) vs. Leroy (2010). We, ourselves, used Leroy (1999) in Fall et al. (2011), for that matter.
But they aren’t intentionally wrong, if they’re wrong — and your data seem to show they are right.
We agree they are not intentionally wrong. It is a textbook case of confirmation bias.
But please explain how “my” (i.e., NOAA’s own) data seems to show they are right? It shows unequivocally they were dead wrong. And it also shows why and how they were dead wrong.
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“Artificial,” but not wrong. Is that correct?
“Artificial suggests an intentional lie. But they aren’t intentionally wrong, if they’re wrong — and your data seem to show they are right.
Fog. Fog isn’t good for seeing what needs to be done, and much needs to be done to stop the pollution that is doing the damage. Unless your data shows warming isn’t happening, your report is just fog in the discussion.
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Oh really? Do you honestly think we can do as much as we do to the environment and it won’t have a cost?
False dichotomy. We do not claim there is no warming. We do not claim the warming that has occurred is not partially anthropogenic. Besides, the vast bulk of the damage we do to the environment has nothing to do with warming in general or CO2 in particular.
What we claim is this: the official contiguous US temperature record exaggerates warming. And that hypothesis is strongly supported by the available data.
What if you and your side are wrong, Evan? How many people are going to have to die for your side?
That sword cuts both ways. What if the life expectancy of, say, the Chinese (just one example), was to remain at ~40 years for the foreseeable future and what if that was needless? [Note deliberate non-use of subjunctive.] That’s a whole lot of ongoing megadeath. Tens of millions of premature deaths per year in China alone.
China has chosen Life over Death, however, and it is beyond anyone’s power to change that decision.
But this is far beyond the scope of our paper; it is another discussion entirely. Or are you arguing that our study is scientifically correct but immoral?
Because your argument boils down “We don’t need a fire escape on that apartment building..it will never ever catch fire.”
Actually we are not making any argument, whatever. We are saying the recent warming trend in the US is significantly exaggerated by NOAA. Do you disagree?
Hell you guys are the same people who claimed that the Titanic was unsinkable.
Hmmm. I thought that was the “scientific consensus” . . . #B-)
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Well, yours is inaccurate:
— We did not cherrypick cooling stations to show NOAA is wrong.
— The stations we dropped averaged much, much lower trends than the ones we retained.
— We show all sets of stations, both together and in separate subsets. You want urban, urban we got. You want non-urban, non-urban we got. You want them together and not separated, well, we got that, too. Airports: “With”, “without”, “separated out”, name your poison — we got it all.
Watts’ statement, on the other hand, is merely accurate. Half of “official” US warming from 1979 – 2008 is artificial. So says the data.
Furthermore, the headline does not insult anyone, and in the paper itself he is careful to point out that we do not believe the mistake, (ghastly though it is) is intentional.
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To quote: Well, that is what the data clearly supports — even after the latest reanalysis removing TOBS and adding MMTS conversion adjustment.
Oh really? Do you honestly think we can do as much as we do to the environment and it won’t have a cost? What if you and your side are wrong, Evan? How many people are going to have to die for your side?
Because your argument boils down “We don’t need a fire escape on that apartment building..it will never ever catch fire.”
Hell you guys are the same people who claimed that the Titanic was unsinkable.
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What’s the difference, in your mind, between the two headlines?
Mine at least refers to the data and its impact. Not sure what Watts’s does other than impugn scientists.
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Shorter Anthony Watts: Ignore cities, discount all NOAA sites that show warming, and global warming doesn’t look so bad
That is the actual headline. And I do dispute that statement. Vehemently.
Evan, would you support a resolution that this headline is wildly inaccurate, too?
“New study shows half of the global warming in the USA is artificial”
Well, that is what the data clearly supports — even after the latest reanalysis removing TOBS and adding MMTS conversion adjustment.
So I would endorse a resolution that this headline is pretty much bang-on accurate.
(I would not, however, support a resolution that this headline is wildly inaccurate, seeing as how it isn’t inaccurate in the least.)
MMTS data, even after equipment adjustment (upward), and even with urbanized areas included, and even after TOBS-biased stations are removed, shows a 0.148 C/decade warming from 1979 – 2008.
Official USHCN/NCDC adjusted data clocks in at +0.315/d.
So, if anything, the headline is a slight understatement.
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Evan, would you support a resolution that this headline is wildly inaccurate, too?
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1. If what you claim is accurate, it makes little difference to policy. It may buy us a decade or two to get things right, but all your numbers show is that disasters comes a little slower than we might have feared.
Actually, it does not address policy one way or the other. 1979 – 2008 was a period of powerful natural warming covering a positive Pacific Decadal Oscillation. How much of that warming is natural, how much is anthropogenic has never been determined.
In fact, whether the warming is or is not anthropogenic is quite irrelevant to the narrow concerns of our study. There is a strong warming trend from 1979 – 2008. That allows us to examine how well vs. poorly sited stations “behave” during a warming trend. The source of the warming (natural and/or otherwise) is not important to that question, and we do not address it.
For the record, I personally believe that a significant percentage of the warming during that period is anthropogenic (CO2, soot, etc.). But my beliefs on the matter do not pertain to the results of our paper.
2. Your complaints are wholly based on modelling, and not based on actual temperature readings. Especially since “skeptics” have made many cottage businesses out of falsely claiming that warming observations are based on models, and not on actual termperature observations, were there justice in the world you and Watts would be laughed off the internet for using models instead of real data. Fortunately for you, science works on data, and not on notions of evening scores to achieve justice.
Where to begin?
First, we do not “complain”, we merely observe.
Second, our observations are definitely based on actual temperature readings. We address the trends of raw readings and of adjusted readings. It is true that we are interested not in the offset, but in the trend. However, that in no way means or implies that we are not using actual temperature readings.
Third, we have used zero models. We use only observational raw data and adjusted NOAA data that is already on the record. We “model” nothing. We present exiting data.
Fourth, “notions of evening scores”? what in the world are you talking about? We are attempting to determine whether siting matters to trend (it does) and, as it does, whether of not that is properly accounted for in the adjusted metadata (it isn’t).
And “justice”? Science, like our paper, is about “getting it right”. IIRC, neither the word (nor the concept of) “justice” appears even once in the text.
The more important BUT: If all of your claims are wholly accurate, then warming is more destructive than the models show and moving much faster than the cynics and pessimists project — so any time you may have “gained” by showing warming is not so bad as we thought, is lost when we realize the damage from that lessened warming is so much greater than we thought, and moving faster to destroy more at a lower level of heat than anyone dared fear.
The IPCC does not agree that there is net (sic) damage from the warming that has occurred so far. For that matter, the IPCC claims there will be a net environmental benefit for one degree C of further warming. Whether that much occurs or whether 3 to 4 times that amount occurs is entirely dependent on feedback.
The IPCC projects extraordinarily powerful positive feedback, but, as of yet, there is no empirical evidence whatever for that. Either those feedbacks do not pertain or else they do pertain, but the base CO2 forcing effect is incorrect: It all has to “squeeze into” the amount of warming that has occurred thus far — whether or not that amount has been exaggerated. And then there is the issue of negative feedback.
But all that is an issue that, while vitally important in the overall scientific debate, is far afield from what we address in Watts et al.
And you guys are still up in the night claiming UHI for forested areas of airports.
I have addressed this specifically and in detail already. We have examined USHCN airport sites and their trends. Those trends are a matter of record. What name you call it is less than irrelevant. You can call it UPS for all I care. It is what it is.
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It makes sense, Evan.
But:
1. If what you claim is accurate, it makes little difference to policy. It may buy us a decade or two to get things right, but all your numbers show is that disasters comes a little slower than we might have feared.
2. Your complaints are wholly based on modelling, and not based on actual temperature readings. Especially since “skeptics” have made many cottage businesses out of falsely claiming that warming observations are based on models, and not on actual termperature observations, were there justice in the world you and Watts would be laughed off the internet for using models instead of real data. Fortunately for you, science works on data, and not on notions of evening scores to achieve justice.
The more important BUT: If all of your claims are wholly accurate, then warming is more destructive than the models show and moving much faster than the cynics and pessimists project — so any time you may have “gained” by showing warming is not so bad as we thought, is lost when we realize the damage from that lessened warming is so much greater than we thought, and moving faster to destroy more at a lower level of heat than anyone dared fear.
And you guys are still up in the night claiming UHI for forested areas of airports.
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On the other hand, if you’re arguing that they DO affect trends, then you must have some indication the poorly-sited stations come up with random errors, not simply measurements warmer than others. Is that what you claim?
What I am arguing is that the statistics show much higher trends for poorly sited stations than for well sited stations. And that the error bars do not overlap — for any of our ten sample sets. We use standard error bars for the subsets and stricter error bars for the overall sets (95% confidence that if bars “touch”, the difference is not random. That would be an overall Confidence of 1 minus the square root of 5% for each data series.)
That would indicate an exceedingly low possibility that our results are the result of random error. It’s possible they are. And it’s also possible you will win the lotto.
Why do you think NOAA’s homogenizing procedure is inaccurate? Have you run the tests to show that?
NOAA describes how homogenization works. It adjusts outliers. And a large majority of well sited stations are identified as outliers because of their low trends.
The well sited station average is adjusted upward to match the poorly sited stations, not the other way around. That’s what the data tells us.
I have already posted the details of how this occurs.
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Poor siting shouldn’t affect trends, hypothetically, so long as they are consistently poorly-sited. A stopped clock is only correct twice a day, but it’s impossible to tell when. It’s accurate two seconds a day, but we don’t know when. A slow clock may keep perfect time, but shows it slow. A slow clock may be slow and still be accurate, especially to trends in time, for 86,400 seconds a day.
Which sort of measurement error are you claiming?
On the other hand, if you’re arguing that they DO affect trends, then you must have some indication the poorly-sited stations come up with random errors, not simply measurements warmer than others. Is that what you claim?
Why do you think NOAA’s homogenizing procedure is inaccurate? Have you run the tests to show that?
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You claim that ground traffic of airplanes, and construction at airports, affects temperature readings?
It would seem likely that airport expansion has an effect. And there was expansion in both construction and in air traffic from 1979 – 2008, our study period.
But that is not what I was referring to. I meant that the mere presence of an airport attracts population in the surrounding (non-airport) environment.
Unfortunately, we do not have the means to calibrate this systematically. So we cannot determine how much of the change in AP trends is from variable step change due to expansion vs. how much is a result of constant heat sink effect.
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Well, in the interest of full disclosure before anyone can get to grips with what he is claiming, Evan Jones has to lay out specifically what his criteria are for choosing stations. It is pretty clear from previous work involving the Climate Reference Network pairwise comparisons, that he and Tony are enjoying red fruit.
That is a very legitimate question.
We use the USHCN network as our base set. We drop those stations that are biased by significant changes in TOBS. This is not done in our original paper, but is done in our reanalysis based on independent review.
We drop the stations for which there is no available data (there are not a lot of these). We drop the stations that we have been unable to identify and rate. We also do our best to exclude stations that have documented moves.
If we included the stations that we have dropped, our argument would be a great deal stronger. However, we are interested in getting the right answers, so drop them we must.
We will, of course, include a full list of all the stations we dropped, and the reasons for dropping them. (And the full set of data for those stations, for purposes of comparison.)
Well, Evan, how about getting Tony to let others comment in his bathtub as a first step towards hashing this out?
He does what he does and I do what I do. You’d have to address him, directly. (I assume he will, of course, go into a great deal of detail once we have gone through peer review.)
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An aside:
We do not address the global effects of warming so far, nor do we address future projections. That is not what our paper is about.
We are concerned exclusively with accuracy of measurement.
We do have opinions on the subject, but that is not at issue in this particular discussion.
If we were to get into that we would have to discuss the issue of feedbacks. That is the critical overall issue going forward. But that is not the subject of our paper and we do not address it one way or the other. It’s another topic entirely.
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You noted that you used NASA’s categorization of airports as urban or rural — but that doesn’t change the error of claiming airports as UHIs, when they are not.
All we do is show airport trends as compared with non-airport trends. The rest is mere nomenclature.
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It results in spurious exaggeration if all the cooler stations are subtracted out, and if we know that the remaining stations are erroneously reporting warmer temperatures than those that existed.
As I have said before, the stations we exclude from our study show MUCH lower trends than the stations we include. If we were to include them, we might conclude that warming is exaggerated by a factor of as much as eight (Rural MMTS sample).
With the stations we do include, however, we find that trends are likely exaggerated by at least fifty percent, and more likely somewhat more than double.
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Evan, I’d like to wait for publication. But. But we need to act five years ago to slow and stop destructive, warming climate change.
I am not addressing policy here. Only data.
We could discuss the wider scientific issues (we all have opinions), but those are not addressed in this paper.
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2.) NOAA adjusts well sited station trends to match poorly sited station trends, not the other way around.
Why does NOAA do that? It sounds as if they have some reason to suspect that the “poorly-sited” stations know something you’re not letting on.
I believe it is an inadvertent, though serious, error in methodology. NOAA, based on Menne (2009, 2010), does not believe siting affects trends (sic). Therefore NOAA does not account for site quality when homogenizing the data.
The data from the well sited stations tends to be significantly lower. And the fact that only one in five stations is well sited means that most of the surrounding stations are poorly sited and therefore have, on average, significantly higher trends. Therefore, the well sited stations are identified as outliers and their temperatures are adjusted to “conform”.
Does NOAA call them “poorly-sited,” or is there another way to describe those stations?
They do acknowledge that they are not in conformity with CRN standards or the NWS “hundred-foot rule”. They do not believe that this affects the trends.
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So, your claim that there is station bias is based, ultimately, on your assumption that there is station bias.
My clam that there is station bias is based ultimately on:
1.) The finding that the trends from well sited stations are (very) significantly different from poorly sited stations
2.) The observation that the trend data from the well sited stations is adjusted upwards to match the trend data of the poorly sited stations.
It may well be that most of the stations you claim are poorly sited, are in fact under reporting warming. You’ve assumed that they measure warmer than the temperature actually is — but you have no data to back that claim, just an assumption that a poorly sited station, by your criteria, measures too warm.
Anything is possible, I suppose. The null hypothesis is that properly sited stations will, on average, produce proper trends. (Provided always they are free of significant TOBS bias and equipment inhomogeneity is accounted for.)
You’re really out on a limb, it seems to me.
I don’t think so. I think it is NOAA that is out on limb. A thin one.
I mean, the plants don’t pay any attention to thermometer readings, and they show warming, and have for more than a century. They cannot be biased by politics, by newspaper headlines, or by sites that are judged to be poorly-sited on some criterion.
We agree that there has been warming for over a century.
So we’re not looking to see whether warming occurs, really, since we’ve eliminated all other causes of the plant zones’ marching north into the cold. We’re looking to see how much warming there is.
Quite correct.
You claim that well-sited stations accurately measure warming — and they do show warming, right? But then you assume that poorly-sited stations show too much warming, and so you’ve looked to see if they show more warming, and they do. Have any of your assumptions here been tested? Are the “well-sited stations” accurate? How can you tell, without assuming, that the “poorly-sited stations” are inaccurate, and inaccurate consistently in one direction? Which direction?
Our null hypothesis is that the well sited stations give us correct data (subject always to constraints mentioned above). If poorly sited stations match those trends, then we would postulate that poorly sited stations are correct. If not, then we would postulate that they are incorrect.
Without putting a well-sited station, by your criteria, within a few yards of a poorly-sited station, and running them in parallel for a decade or so, how do we know those stations are not showing accurate temperatures, or temperatures below what they should be?
We would very much like to see such an experiment conducted. We do grid our data to account for distribution bias.
By the way, did you control for heat pumps versus air conditioners? Because heat pumps will put out cool air in winter, and consequently they would bias stations to the colder side.
No. We use only Leroy (2010) ratings for heat sink proximity. Nothing else.
Waste heat and heat sink effect, I believe will yield differing effects. Waste heat may even dampen a trend by overwhelming it. A heat sink, on the other hand, is dependent on the ambient surroundings. But this is merely my own belief; we do not address this experimentally in our paper.
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I said: I’m still looking for information to suggest you’re not chasing hoodoos.
Mr. Jones said:
Can you tell us why that is? Have you done research to establish a firm causal link, that the poor siting always results in a skew to warmer temperatures?
I would think that, statistically, poor siting would result in temperatures different from well-sited stations, but there should be about an equal number of stations cooler than the well-sited stations, as there are warmer. Errors in measurement sampling, if they are errors, should produce random wanderings from the accurate readings, shouldn’t they?
How many stations reported cooler temperatures, and how did you adjust for those?
Why does NOAA do that? It sounds as if they have some reason to suspect that the “poorly-sited” stations know something you’re not letting on.
Does NOAA call them “poorly-sited,” or is there another way to describe those stations?
It results in spurious exaggeration if all the cooler stations are subtracted out, and if we know that the remaining stations are erroneously reporting warmer temperatures than those that existed.
How much warmer than accurate does an air conditioning unit make a station report, if the air conditioner is 50 feet away from the thermometer? 100 feet away? Doesn’t that obtain ONLY if the exhaust from the air conditioner actually blows to the measuring device? If heat rises, why wouldn’t an exhaust stream from a residential-sized whole-building air conditioner rise above a weather station 50 feet or more away?
Evan, I’d like to wait for publication. But. But we need to act five years ago to slow and stop destructive, warming climate change. We can’t afford to wait for something that isn’t well thought-through in the science, and the more you explain, the more convinced I am that you’re not pursuing a serious problem in measurement that should delay action to save the planet. Were warming not confirmed through a half-dozen different methods of measuring global temperature averages, there might be room for doubt. I don’t see that room here.
More, it seems to me that there are a lot of links you’re assuming that have not been established in science — that “poorly-sited” stations are inherently inaccurate, that they inherently register temperatures warmer than real, and that the differences are significant when the trends they show are corroborated by all other measurements.
You noted that you used NASA’s categorization of airports as urban or rural — but that doesn’t change the error of claiming airports as UHIs, when they are not.
You might be able to establish that some weather stations produce different measurements than other weather stations. At best that would suggest an adjustment in the degree of warming, not whether there is warming, and having nothing whatsoever to do with the hard political, economic and engineering solutions we need to be pursuing, now.
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Well, in the interest of full disclosure before anyone can get to grips with what he is claiming, Evan Jones has to lay out specifically what his criteria are for choosing stations. It is pretty clear from previous work involving the Climate Reference Network pairwise comparisons, that he and Tony are enjoying red fruit.
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Well, Evan, how about getting Tony to let others comment in his bathtub as a first step towards hashing this out?
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So, your claim that there is station bias is based, ultimately, on your assumption that there is station bias.
It may well be that most of the stations you claim are poorly sited, are in fact under reporting warming. You’ve assumed that they measure warmer than the temperature actually is — but you have no data to back that claim, just an assumption that a poorly sited station, by your criteria, measures too warm.
You’re really out on a limb, it seems to me.
I mean, the plants don’t pay any attention to thermometer readings, and they show warming, and have for more than a century. They cannot be biased by politics, by newspaper headlines, or by sites that are judged to be poorly-sited on some criterion.
So we’re not looking to see whether warming occurs, really, since we’ve eliminated all other causes of the plant zones’ marching north into the cold. We’re looking to see how much warming there is.
You claim that well-sited stations accurately measure warming — and they do show warming, right? But then you assume that poorly-sited stations show too much warming, and so you’ve looked to see if they show more warming, and they do. Have any of your assumptions here been tested? Are the “well-sited stations” accurate? How can you tell, without assuming, that the “poorly-sited stations” are inaccurate, and inaccurate consistently in one direction? Which direction?
Without putting a well-sited station, by your criteria, within a few yards of a poorly-sited station, and running them in parallel for a decade or so, how do we know those stations are not showing accurate temperatures, or temperatures below what they should be?
By the way, did you control for heat pumps versus air conditioners? Because heat pumps will put out cool air in winter, and consequently they would bias stations to the colder side.
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What makes you think that the warming shown by poorly-sited stations is not accurate?
The fact that poorly sited station trends do not (anywhere near) match those of well sited stations. It’s really as simple as that.
Where is the study that shows poor siting provides inaccurately-measured warming, ghost-warming in your claim?
Ours does appear to be the first . . .
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Leaving aside Watts’s bizarre claims that warming ended more than a decade ago, so that you should have plenty of cooling to check your trends (which, I gather, you don’t, actually),
No good. First of all, ten years is not long enough. And even more important, a flat trend is of no use to such a study. During a flat trend, well and poorly sited stations will behave much the same.
In order to determine what would happen to poor vs. well sited stations during a cooling trend, you need an actual cooling trend. A null trend won’t do.
I’m still looking for information to suggest you’re not chasing hoodoos.
Our results are what our results are. It’s as simple as that:
1.) Well sited stations warm slower than poorly sited stations.
2.) NOAA adjusts well sited station trends to match poorly sited station trends, not the other way around.
3.) This results in a significant (spurious) exaggeration of USHCN trends from 1979 – 2008.
When we are published, we’ll release all data and methods and you can search for any errors, yourself.
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What do you claim the headline should be, then? “Watts says all climate scientists are evil, in a conspiracy, and otherwise wrong — but warming occurs as they say, anyway?”
How about “Watts says poorly sited stations have higher trends and therefore exaggerate official warming trend statistics. We respectfully disagree,” (followed by reasons).
Seeing as how we never accuse anyone of dishonesty or other immorality and never once use the word (or refer to) conspiracy.
We just think they’re wrong; that’s all. And we think we’re right. When we publish, I will personally make sure all my data and methods in a clear and understandable manner so our results can be replicated or disputed.
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Leaving aside Watts’s bizarre claims that warming ended more than a decade ago, so that you should have plenty of cooling to check your trends (which, I gather, you don’t, actually), I’m still looking for information to suggest you’re not chasing hoodoos.
What makes you think that the warming shown by poorly-sited stations is not accurate? Where is the study that shows poor siting provides inaccurately-measured warming, ghost-warming in your claim?
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Even if you threw out all the other considerations, those two factors have an overwhelming effect on the trends.
No study shows that. If your study isn’t done yet, how can it show that? Using Watts’s data, BEST determined warming numbers are very close to those reported to and passed along by IPCC. Watts has repeatedly challenged those numbers and attacked the scientists behind them — but I don’t see any validated study that supports Watts’s position.
Quite right; no study shows that. We are the first. And we demonstrate it quite clearly.
It’s true that BEST used my data (from the earlier Watts study), data that I — personally — compiled. So I should know a thing or two about it …
That data was based on the Leroy (1999) classification system. It accounts for distance between sensor and heat sink. But it does NOT account for the SIZE of the heat sink! We had a running joke during our Fall et al. adventures: “All Class 4 stations are equal — but some Class 4 stations are more equal than others.”
Leroy, himself, realized the inadequacy of his rating system. In Leroy (2010), he revised his system to take into account both the distance from sensor to heat sink, but the % of area near the sensor covered by the heat sink.
The fact that two (now three) years on no one bothered to reclassify the USHCN using Leroy (2010) is another study in confirmation bias. They liked the (i.e., my) old Leroy (1999) results just fine!
And, actually, I did not expect to get different results when I tackled the USHCN using Leroy (2010). When I did so and ran the numbers, I practically fell out of my chair. (Alright, so I did fall out of my chair.)
And the rest is Climate History … Lukewarmers of the world, unite! And huddle together for warmth.
P.S., In Fall et al., we did not consider TOBS and MMTS conversion — I will rerun those numbers using our Leroy (1999) ratings with our non-TOBS-biased station set and see if anything unexpected pops up.
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That differs from IPCC-used measurements, how?
IPCC (and NOAA) use metadata that adjusts, GOOD station trends UPWARD to match bad stations trends. Rather than adjusting BAD station trends DOWNWARD to match good station trends.
Yes, that’s what they do. Yes, really.
I think this is largely due to “homogenization”: There are many more badly sited stations than well sited stations. The algorithm therefore identifies the well sited stations as “outliers” and “deals with them appropriately”. (This is a godawful but honest error — and a textbook case of confirmation bias.
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“TIME AS A VARIABLE”
Badly phrased on my part. The study, as best I can tell, doesn’t appear to track trends over time. Assuming every station on Earth to be skewed to produce inaccurate readings, reality is that even a badly-sited station will offer accurate trends over time.
Plus, your study appears to assume that stations poorly sited (by your definitions) never offered valuable readings of even trends.
I’ve worked studies in which we discovered a key measuring device to be calibrated incorrectly, or some process truncated. Frequently, if measurements have been careful enough, and if calibration of the instrument doesn’t wobble over time, corrections to data can be made that make the data accurate.
I don’t see this study even thinking of using data that might reveal a lot.
We ONLY deal with “time as a variable”.
The ENTIRE POINT of the Watts study is NOT to show that a bad site IS WARMER. The entire point of our study is to determine whether or not poor stations WARM FASTER OVER TIME.
We don’t “find” that a good site IS less warm than a bad site. Others have found that. already. It’s uncontroversial, and old hat, at that.
But we find that good sites WARM SLOWER OVER TIME than bad sites.
No only DO we consider “time as a variable”, but we consider ONLY “time as a variable” and NOTHING ELSE.
We exclusively compare the 30-year trends of good sites with the 30-year trends [SIC!] of bad sites. And, yes, the trends of bad sites DO “wobble over time”. The wobble UPWARDS.
Badly sited station are not only WARMER, they WARM FASTER.
It is for that reason — and for that reason alone — that badly sited stations are NOT useful for determining temperature trends.
I cannot emphasize this more strongly. It’s the whole dang point of our study.
BTW, I would therefore speculate that a poorly sited station will cool faster during a cooling trend, as the microsite effect “undoes” itself. But that is only hypothesis, not observation. Yet it is indisputable that poorly sited stations warm faster during a warming trend — we have directly observed that.
Glad we cleared THAT up!
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TOBS AND MMTS CONVERSION
I’m pretty sure that, with some time, I could decode that and put it into English.
Probably.
Could you do that for us? What is TOBS bias, what is MMTS conversion, and most important, why should anyone care?
I would be happy to answer that.
The greatest objections to Watts et al. (2012) was that we did not take this into account. In our revised station set, we have done so.
TOBS is an overall cooling bias. It legitimately warrants an upward adjustment. It occurs because the time of observation for many stations was changed from evening to morning. Now, the way USHCN temperature is currently measured, you take the highest (Tmax) and the lowest (Tmin) temperature in a given 24 hour period and average them (resulting in Tmean) for that day.
That works okay (not perfect, but close enough). But there is one problem: it doesn’t matter WHEN the max and min temperatures occur during that 24-hour period. If observation time is too near maximum temp. time (~3:00 PM), it is likely to “carry over” on very hot days to the next day, which can be much cooler. So on a very hot day at 2:59, Tmax occurs, and then the next day’s Tmax is at 3:01 — even though 23+ hours later it is much cooler!
That adds a warming bias to the readings. But it only affects the READING — not the TREND. Unless . . .
Unless, of course, you change observation times to, say, 6:00 AM. Now your station is showing a much lower reading. Because instead of Tmax “carrying over”, it is now Tmin which is “:carrying over”. So there’s a step change to the cooler for readings.
So, for 15 years of your 30-year study period, your station is reading too hot. And then for the next 15 years, your station is reading too cool. And that has a MAJOR effect on the trendline.
So you must either “adjust” for this discrepancy (using rather dubious means) or you must drop the station entirely. We choose to avoid the can-o’-worms rush and simply drop the station when TOBS is changed from morning to evening or vice versa.
Dropping these stations works against our results, but the TOBS criticism is fair play and we therefore drop those stations. We are, after all (and above all) interested in getting the right answer.
MMTS conversion is somewhat the same logical proposition. MMTS readings are lower than Stevenson Screen (i.e., CRS) readings. So when you convert to MMTS, there is a step change. And that step change affects the trend — obviously. So one must add that amount to the trend (modified by R^2) in order to offset this bias.
Doing so also works against our premise, but, as I say, getting the right answer is all that matters. So our revised paper does so.
Interestingly, removing TOBS bias actually increases the trend differences between well and poorly sited stations, BUT it somewhat decreases the differences between well sited raw data and the adjusted data.
I hope that answers your question. If you have any more qestions about TOBS or MMTS, I will, of course, try to answer you.
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Next:
URBAN SITES
You’ve assumed that no one else noted the geographic concentration of measuring stations, and that no one bothered to correct for the geography.
Actually, we make no assumptions whatsoever. We merely note that urban sites are overrepresented in proportion to the area they actually cover.
NOAA does (through the secondary effects of homogenization) adjust the trends of badly sited urban stations downward. However, they also adjust the trends of well sited urban stations upward.
For sites not affected by TOBS, well sited urban stations warmed at ~0.25 C/decade from 1979 – 2008, while poorly sited sites warmed at ~.037 C/decade. (If you include TOBS biased stations, of course, those trends for both well and poorly sited stations would be significantly lower.)
Both well and poorly sited urban station sets are adjusted to ~0.31per decade. And urban sites are the only subset of stations where poorly sited stations are adjusted significantly downward.
Once again, microsite is king. The difference in warming trend between well and poorly sited urban stations is staggering.
That is the sum of our assumptions. And they are not even assumptions — they are strictly observations.
Yes, some urban sites need to be included. But only at the same percentage of urbanized land cover.
You mention later on that there is warming in all sectors. Well, from 1979 to 2008, anyway. We agree. But, when it comes to global warming, Size Matters. And so does the Motion of the Ocean. (And when it comes to “adjustments”, If You Shake It More Than Three Times, You’re Playing With It … )
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Okay, I’ll address your points one by one. Certainly they are all legitimate questions and they deserve answers.
First:
AIRPORTS
Overall, airports do not represent a significant percentage of area. Urbanized areas cover a much larger percentage.
Having said that, airports are their own unique microenvironment. They do not affect the overall average by a whole lot, but they do have an effect. Since the area covered by airports is a much smaller percentage than the percentage of USHCN airport stations, they skew the results by that proportion.
It might be reasonable to include airports as 1% of USHCN stations. But 6% is way over the mark.
You say:
But most large airports in the U.S — with just a tiny handful of exceptions — are quite rural, even forest preserves and wildlife preserves, and not huge blocks of concrete that cause urban heat island effects.
However:
39% of USCHN airport sites are urban. 33% are semi-urban. Only 28% are rural. (We use NASA ratings to determine which are urban, suburban, and rural.)
One or two more points:
– Airports attract urbanization. This results in worsening mesosite over time. The result of that on 30-year trends is obvious.
– Nearly all airports use ASOS equipment (that is to say hygrotherm sensors). There is a known and significant problem with those sensors (the HO-83 equipment bias). Most of the HO-83 sensors have since been replaced, but that has occurred mostly after our study period. So the correction does not show up between 1979 and 2008, our study period. And the temperature records of those defective sensors remain as part of the official record.
– The overall skew for US temperature trends from airports is not huge. But the proportion of USHCN airports sites is, as I have mentioned, ~6%. GHCN, however (i.e., globally) has a much higher percentage of airport sites. I have not tabulated them as I have done for USHCN, but I have read that nearly half of GHCN sites are in airports. Therefore much of the GHCN sites are unrepresentative of global mesosite.
– Airport trends (and we are talking trends here, are adjusted sharply upwards by NOAA.
– Poorly sited airport station trends have almost no adjustment. But well sited airport trends are adjusted upwards by over a third. Almost no airports suffer from TOBS bias (I’ll discuss TOBS bias later) and only one or two use MMTS sensors. So the adjustment of the well sited stations is remarkable, to say the least. And no adjustment whatever is applied to offset HO-83 equipment bias.
– And, finally, airports are the least of the problem with the USHCN. The good vs. poor microsite issue dwarfs it. And, of course, well sited airports stations warm at a much slower rate than poorly sited airport stations over our study period of 1979 – 2008 (+0.22 C/decade vs. +0.35C/d).
And, to repeat (loudly) AIRPORTS ARE THE LEAST OF THE PROBLEM with the US temperature record. Yes, they are a problem, but they are dwarfed by other USHCN problems.
I’ll deal with each issue you adduce in a separate post.
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You’ve assumed that no one else noted the geographic concentration of measuring stations, and that no one bothered to correct for the geography.
I don’t think that’s accurate. It’s not fair to say that increased temperatures measured at three airports in Chicago then skew the readings for the entire state of Illinois.
In calculating worldwide average temperature, it is inaccurate to claim that all measurements have looked only at the existence of a measuring station and then assumed it to be correct, and then averaged that measurement in across any territory. NASA and several other agencies have spent years looking at temperatures in continents, in broad geographic regions, in smaller politically-bounded regions, in cities and towns, and in rural areas and wilderness.
We find warming in all places, and that finding is not skewed because there are more weather stations in cities in the U.S. than there are in the northern territories of Canada. Consequently, claiming that urban heat islands skew the readings is a bit off the mark. If there is an urban heat island effect — and the meteorologists for three different airlines have assured me there is such a thing — that heat is real. Measuring it is quite straightforward, and doing anything to moderate those readings skews the overall averages downward.
But, as you say, even with that downward skew, warming is still obvious.
Hmmmm.
I’m pretty sure that, with some time, I could decode that and put it into English.
Could you do that for us? What is TOBS bias, what is MMTS conversion, and most important, why should anyone care?
Badly phrased on my part. The study, as best I can tell, doesn’t appear to track trends over time. Assuming every station on Earth to be skewed to produce inaccurate readings, reality is that even a badly-sited station will offer accurate trends over time.
Plus, your study appears to assume that stations poorly sited (by your definitions) never offered valuable readings of even trends.
I’ve worked studies in which we discovered a key measuring device to be calibrated incorrectly, or some process truncated. Frequently, if measurements have been careful enough, and if calibration of the instrument doesn’t wobble over time, corrections to data can be made that make the data accurate.
I don’t see this study even thinking of using data that might reveal a lot.
That differs from IPCC-used measurements, how?
I think that’s a problem. Heat produced from any source is still heat, for purposes of climate change measurement. Urban heat islands are real, and the heat they produce is real. Pilots must make adjustments for the warmer air for dozens or hundreds of miles downwind, and then usually the excess heat mixes well enough with the rest of the air that it’s just a nominal warming, and not a dramatic, air ripple-creating thing.
It appears to me that this study pretends all that heat goes away, and shouldn’t be measured. That’s not what happens in reality, but that’s the result you’re striving toward. So if you identify a heat island, you dismiss the measures, and that heat isn’t accounted for until it’s moderated a good distance downwind, though the heat is real and is a real contributor to global warming.
It appears to me you discount or dismiss one very real source of heat.
I haven’t found any discussion which removes my concern here. Watts has argued that airports are, themselves, urban heat islands. His example on the blog was Thurgood Marshall/BWI.
But most large airports in the U.S — with just a tiny handful of exceptions — are quite rural, even forest preserves and wildlife preserves, and not huge blocks of concrete that cause urban heat island effects. Have you got a study that shows airports generate a heat island effect?
And if so, how can you dismiss that heat? It would be real.
I think ultimately Watts just counts airports incorrectly. At BWI he pretends a terminal generates more heat than the cooling from the closer forest. He assumes the entire airport is concrete, when most of it is meadow at worst, and there are hundreds or thousands of acres of forest.
See my earlier comment here. I think it’s difficult to find airports which meet Watts’s assumptions. I think he’s miscategorized many, many airports, therefore, and has discounted accurate readings because of his erroneous assumption.
No study shows that. If your study isn’t done yet, how can it show that? Using Watts’s data, BEST determined warming numbers are very close to those reported to and passed along by IPCC. Watts has repeatedly challenged those numbers and attacked the scientists behind them — but I don’t see any validated study that supports Watts’s position.
I don’t think we should throw out accurate considerations, like the miscategorizing of airport stations.
What do you claim the headline should be, then? “Watts says all climate scientists are evil, in a conspiracy, and otherwise wrong — but warming occurs as they say, anyway?”
Watts proposes to discount urban measurements, without adequate justification that I have found, and diddle the data on other sites to adjust them for a measurement error he claims to have found, that also hasn’t been verified by others — in order to dispute the data he claims are wildly wrong — but not significantly wrong enough to change any conclusion in any other study?
That doesn’t make sense.
Actual temperature readings are quite the last pieces of the puzzle. As I noted earlier, our other climate change measurement tools, perhaps most notably the plant zone charts from USDA, clearly show warming occurring nationwide; other measures show warming occurring worldwide. IPCC’s famous hockey stick chart, now more than ten years later, does appear to be inaccurate, but because it understates both the amount of warming, and the rapidity of warming.
In short, though you may claim that the sky is pink, and that, with your filters on your lenses, you can find pink light wavelengths, when I look out the window, the sky is blue.
Warming occurs anyway. It’s been going much longer and much more significantly that it should have for any natural cycle we know of. It’s time for action.
We’re on a sinking boat. Instead of heading for the lifeboats and breaking out the personal flotation devices, Watts not only quibbles with the arrangement of deck chairs, he says the chair count is wrong, and they are the wrong color. Even were he correct, his claims are distractions at best, and dangerous delusions at worst.
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Thank you for your response, Mr. Darrell.
I’d like to make a few things clear, as main co-author of Watts et al.:
First, the stations we exclude average — very — much cooler trends than the stations we included. We most emphatically did NOT “exclude the stations that are warming”. Quite the opposite.
Second, cities do indeed create heat (and a higher warming trend). But urban terrain is maybe 2% of US land cover and 9% of USHCN sites are urban. So the issue is that of proportionate effect.
Third, we did not exclude cities. We merely show the averages with and without cities (as well as urban trends, themselves). Same for Airports. We do not exclude them, we merely show the trends with and without as well as the airport trends themselves.
Even when including cities and airports, our results are still extremely robust.
Fourth, we have accounted for both TOBS bias and for MMTS conversion. TOBS-biased stations are dropped and MMTS adjustment is applied as consistent with Menne et al. (2009 & 2009).
Fifth: Semi-urban (semi-rural?) sites are a little bit skewed, but not very much. We will probably include them with rural stations when we submit for peer review.
Watts appears not to consider time as a variable, nor does he suggest any magic trash can for all that UHI heat to be taken from the surface of the planet.
Not sure what you mean by “time as a variable”. We use the 1979 – 2008 period as our basis. We do this because it is a 30-year period covering a positive PDO, and also coincides with the advent of satellite LT measurements. Our measurements for each station are exclusively the 30-year trend. We are not interested in how warm or cool a station is — we are exclusively interested in whether it cooled or warmed (and by how much) over the 30-year study period.
And we are not addressing what happens to waste heat. We merely note the trend differences (and similarities) in varying environments. We fully agree there was significant (genuine) warming over the study period. Our study merely considers how much of that warming is real and how much is due to poor siting.
And the biggest factor is not urban, airport, or any other kind of generalized terrain. Mesosite does matter somewhat, but two factors are FAR more important:
1.) Equipment type (i.e., MMTS vs. CRS), and
2.) Microsite: the immediate environment of the station.
Those two factors strongly affect trends no matter what the terrain (urban, airport, or whatever). Poorly sited airport of urban stations have much higher trends than well sited urban or airport stations. And CRS stations average much higher trends that MMTS — after accounting for the step change of equipment conversion.
Even if you threw out all the other considerations, those two factors have an overwhelming effect on the trends.
Therefore, I strongly dispute that you have accurately summed up the paper in your headline.
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You claim that ground traffic of airplanes, and construction at airports, affects temperature readings?
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Thanks, Eli. It’s always useful, I’ve learned, to test hypotheses to see whether they work out. The hypothesis that temperatures have been recorded incorrectly for 150 years always seemed a bit extreme, to me.
Mr. Jones notes that, contrary to expectations, airports are cooler than nearby cities, something that would not obtain were there a true, skewing Urban Heat Island effect from the airports alone.
Reality is that landscape, especially in great quantity, can affect temperature readings. Denver’s temps are affected by having the Rocky Mountains covering 200 miles to the west, for example; even the smaller Appalachians affect weather and temperature downwind. Having a concrete plain in a forest could be expected to affect temperature readings at Dulles International — but I still think there is not a good argument to be made that the readings are inaccurate because of that effect, especially if the comparison is over time, to measure changes in average.
Watts at one point tried to argue problems in Boulder, home of much climate measuring. Boulder’s temperatures are affected partly by the massive greenbelt around the city, an area roughly equal to the size of the city itself. I don’t think Watts took kindly to my suggestions.
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FWIW the last comment was in response to Rob at the bottom.
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There is an old Atmoz post (since disappeared with his blog) that shows that as far as trends go that is not true. Fortunately Eli blogged about that and used Atmoz’ figures
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What makes airports non-typical? Again, I wonder why you assume that the information they show is incorrect. How do you make that determination?
Second, since you assume rural stations are correct, can you explain why you make that assumption? Is it not possible they are wrong, too, or instead of, urban stations?
And why do you assume any of these readings are incorrect?
You’re making a logical leap that because a station does not meet certain criteria, readings are incorrect. Where is the research that indicates the presence of an air conditioner within X distance units of a thermometer, any reading will be in error?
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The usual problem with airports, with regard to the cities nearby, is that they tend to run cooler than the cities, no?
They are cooler than urban (those that are not actually urban), but they warm faster than rural stations. So their trends, on average, are higher. I would say urban influence is stronger than airport influence. But AP influence is considerable.
Since airport environments are non-typical, AP records should not be part of USHCN.
We will release data on all the APs, all the non-APs, and many other selections.
We use the NASA ratings to determine urban / semi-urban / rural stations.
Bear in mind that the paper is one of statistical analysis of the presence of nearby heat sinks on USHCN trends. We speculate as to what the reasons for our findings are, but the current paper is about the findings, not the reasons for the findings.
The conclusion is twofold: First: The well sited, modernized rural stations show well under half the warming as the poorly sited stations. Therefore, siting matters. Second: Instead of adjusting the poor stations downward to match the well sited stations, the well sited stations are adjusted upwards to match the poorly sited stations. Therefore, the adjustment procedure is called into serious question.
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Well, I grew up next to LAX (a few miles south, but within earshot when the winds were right) and it sits right in the middle of an urban area. Three sides is city to the north, south and east. To the west is an area which sits under the runways and has been de-urbanized. It is kind of cool to cruise through the abandoned housing developments, only the foundations remain and the old concrete streets are slowly being taken back by the dunes.
But the prevailing winds at LAX are from the west off of the water and it is frequently fog shrouded in the mornings. I strongly doubt that UHI has caused any trend there even if UHI is inflating temps compared to the surrounding area — something I strongly doubt.
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Which affects temperature readings on the ground indirectly, through increased CO2 emissions and contrail-caused cloud formation, miles up and miles away from the airport weather stations.
Bullfeathers. I ask again, please name those airports affected by urbanization. Of the good candidates, O’Hare should stand out — but O’Hare remains a forested island in suburban development. JFK, Newark, LaGuardia, Boston, are not urbanized. Key problems with those airports involve abutting wildlife refuges and the birds that fly through jet paths.
Can you point to an airport where we might expect inaccurate temperatures from encroaching urbanization? Don’t generalize — name it.
And for everyone you might be able to name (I’m straining only because a few of the bigger urban airports I haven’t got direct experience with), I’ll name three more that are non-urban oases.
The hard reality is that airports probably capture extremely accurate temperature readings for their areas. They frequently differ from the centers of the cities they serve, but not by being warmer, nor by inaccurately showing local, ambient temperatures.
Name the station, please. You generalize, assuming that there are warming effects never evidenced, assuming misplaced stations where even Anthony Watts’s records don’t show them.
As I noted, accurate weather readings are essential to airports, because accuracy is critical to air safety and scheduling. Airlines invest hundreds of millions of dollars, if not billions — and you say they err?
I’ll need something more than your word on that error. Please show some.
Urban temperatures are real. Heat generated from cities is not magically dissipated from the planet. You assume that all heat is not equal, and you assume that there is error in these readings that I can’t find. Again, please offer some evidence, and not assumption.
Please explain why a well-sited MMTS at an airport is not accurate. (Part of my difficulty is your use of baffling and fogging acronyms; I’m about an expert at airports and scientific measurement, but not on jargon. I also suspect you may be confusing yourself with jargon.)
Denver International is about 10% the size of Rhode Island. Airports that you claim to be insignificant are huge chunks of land, often forested and wild. Your claim that these lands are insignificant is completely contrary to evidence.
O’Hare is big enough that you should see a cooling effect from the forests. So is Thurgood Marshall/BWI. Dulles is not yet urbanized, and should offer cooler temperatures.
Let’s do some comparisons. Do you think Manhattan Island is significant? It’s just over 14,000 acres. Do you think that a weather station placed in the heart of Central Park would offer temperatures similar to, say, Times Square, a few blocks away? Central Park is 843 acres, or about 6% of Manhattan.
==> Hartsfield serving Atlanta is 4,700 acres. That’s more than a third the size of Manhattan, more than five times the size of Central Park.
==> Dulles International is 11,830 acres, effectively the size of Manhattan. Take a look at some of the environmental studies, on the wetlands and forests of the area, and you start to get an idea that it is neither insignificant, nor urbanized. (This applies to almost all large, urban airports.) That these lands are large enough to require the environmental impact assessments under NEPA, or a Finding of No Significant Impact (FONSI), alone completely refutes any claim that they are insignificant lands.
==> LAX is on 3,400 acres, in the heart of Los Angeles, four times the size of Central Park; not insignificant. Is it affected by urban heat, or does it influence urban heat? Of course, LAX is near the water, and there is a wildlife refuge protecting threatened and endangered wild species there. I’m getting less convinced of your “aiports are urbanized, and therefore giving inaccurately high temperature readings” argument.
==> DFW has 18,076 acres, larger than all of Manhattan Island. A small fraction of the total land is covered in concrete. The airport is mostly undeveloped, but some of the development includes large agricultural fields where cotton and other crops are grown. Not exactly an Urban Heat Island. DFW is not the nation’s largest airport in total land.
==> Denver International (DIA) is 32,000 acres, more than twice the size of Manhattan Island.
Airports are both significant land masses in the U.S., and not urban. Your arguments against accuracy of the airport weather stations suffers from at least two completely erroneous assumptions.
The usual problem with airports, with regard to the cities nearby, is that they tend to run cooler than the cities, no?
In any case, you’ve got to provide some evidence that there is Urban Heat affecting those airports, before we can even begin to grant credence to a claim that their weather stations are inaccurate as a result. You should note that LAX, SFO, SEA-TAC and other airports on the West Coast are upwind of urban areas, and so would not get the heated air from those cities; same with O’Hare. DIA and DFW are located well north of the urban areas they serve; Dulles is north and west, affected by heat from the Washington, D.C. area only in extremely rare cases.
Where do you guys get these wild ideas of yours? The geography of the airports argues against your claims of inaccuracy.
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Oddly enough, the Airports decided to go with a cheaper model that has had all kinds of problems and a (miserable) 1.5C MoE. But the main point is that airports usually attract bad mesosite. They are bad-mesosite magnets. And over the 30-year period of the study, air traffic has been greatly increased and urbanization has encroached on airports, and many of the airports have had ongoing construction. The net effect (plus the HO-80 equipment glitch) is an artificial warming not matched by non-AP stations.
It is important for an airport to have the correct local temperature, and the ASOS systems do that adequately. But the local temperature itself is affected by encroachment of urban development.
A well sited MMTS is going to be far more reliable than most ASOS equipment located in an airport.
Airports comprise almost zero in terms of percentage of total land coverage. Yet over 5% of USHCN stations are located in Airports. So if airports do not accurately reflect nearby rural conditions, they should not be included as USHCN stations. Not that temperature in airports is not important; it is.
We will include data for samples that include: All Stations, Airports Only, Airports Excluded (etc.) So one can observe the trend differences between the AP- only and the AP-Excluded samples.
We do the same for urban and rural. We have 10 specific samples.
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Stakes are higher in the airline industry. Accurate measurement is more important. These stations are more likely to be staffed by professionals who take more care about the measurements.
Maybe these numbers are simply more accurate, and more reflective of reality.
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I think I can say with some assurance that these effects are not caused by birds, animals, oceans and winds watching Al Gore’s movie. To nature, warming is not politics, and it’s not caused by allegedly inaccurate readings of temperature.
If we’re not measuring warming accurately, would accurate measurements change any of the effects of warming? I don’t see that happening.
If we were to grant, for the sake of argument, that you’re right that stations are sited badly, and warming is reduced (by a tiny amount) when measured accurately, how does that change anything?
Okay, I will answer this. There has definitely been warming from 1979 – 2008, our period study. I don’t know anyone who disputes this. The question is how much?
What Watts et al finds is that poorly sited stations not only show higher readings, but those readings increase at a significantly faster rate over time than the well sited stations in the same region.
We can also clearly demonstrate that instead of adjusting the trend data of the poorly sited stations downward, the trends of the well sited stations are adjusted upward to match the trends of the poorly sited stations.
Equipment homogeneity is also an issue: The MMTS conversion touches on a number of factors. It narrows the gap between well sited stations and final-adjusted data by 0.14 per decade (which Matches Menne 2009 and 2010).
Another point: We have dropped the seriously TOBS-biased stations from our ratings. That is not dropping warming stations, that is dropping overwhelmingly cooling stations (of all classes).
But — granting that we are right — it is not some minor amount. It is something on the order of doubled, or even worse. If warming is being exaggerated by that much, it raises serious questions, not about warming, but about the rate of warming.
As for UHI, if you want to be truly accurate, you would have to weight urban sites at 1/5 the amount as rural. You would also need to weight semi-urban sites at 1/3 the rate of rural. That would correctly measure the amount of heat added by mesosite.
Yes, we know Airports are cooler than Non-Airport stations. But, for a number of reasons, they warm faster than non-AP sites. It’s simply an observation, though there appear to be a number of reasons that would wxplain this phenomenon.
I hope this clarifies our position.
I have to go, now, but feel free to press specific questions I did not cover, and I will do my best to answer.
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Thanks for dropping by Mr. Jones. As a general rule we don’t censor opinions here as Mr. Watts does. It’s rare we get anyone to step out of that bubble to discuss.
You wrote:
Weather and warming are not measured democratically. There is no electoral college in meteorology, and no “51% + 1” rule. Yes, there are more weather stations where people are. That does not mean that all stations are lumped together when trying to figure out whether there is warming. Warming is measured geographically, too — and those measures show warming. For example, the Department of Agriculture’s growing zone mapping projects, which are concerned more with the rural and undeveloped zones of the nation, also show warming. You assume people who study warming don’t know that and don’t account for it. I don’t know why you assume that.
Take a look at this plant zone map from 2006 and 2008.
Notice that it shows warming over broad expanses of non-urban areas, especially in the American Midwest, in agricultural regions. Our experience since then has been disastrous drought, invasive species speeded by warming, and disastrous changes in precipitation and weather patterns connected to warming. Notice that it also shows areas where cooling occurred. When your complaints are accounted for, geographically, we still see warming over the broad expanse of the U.S. — and similar studies worldwide show similar results over oceans and other continents.
The Urban Heat Island effect from Wichita, Kansas, doesn’t skew reality for the rest of Kansas.
Mr. Jones said:
Unintentional comedy? The 34,000 acres of Denver International Airport, on the largely undeveloped plains, is not urban, not a heat island, and probably has accurate temperature and precipitation readings for its non-urban area — and is about 2.5 times the size of Manhattan Island. On one hand you claim Manhattan is over-represented, then you turn around and say airports representing much larger chunks of real estate, occupy no area at all. Perhaps you’re exaggerating for effect, but the effect is to suggest you don’t account for simple physics or geography. Airports are huge, almost-always non-urban chunks of land. (I’d love to see your list of exceptions. Meigs Field in Chicago? Midway? Austin-Hobby? Dallas Love? Burbank? I’ll see those and raise you Austin-Bergstrom, DFW, Hartsfield, SEATAC, Dulles, JFK, O’Hare, Cincinnati, SFO . . . you’re assuming a trend the wrong way.)
Anthony Watts assumes airports are all urban heat islands, when in reality most commercial airports and most others are non-concrete — that is, non-urban — relatively wild areas. Thurgood Marshall/Baltimore-Washington International employs a forester to care for thousands of acres of forest, for example. (Hmmm. Did I ever post the analysis of Anthony Watts’s manifold errors about BWI?) Watts assumes, without evidence, BWI is an urbanized area with no forest at all. One of the larger, funnier problems we used to have at O’Hare was culling the deer herd that lived in the forest there, because they were prone to run onto runways when crowded by their deer colleagues (I haven’t worked O’Hare in a couple of decades, but they haven’t done away with any of their forest; whether the deer are still there, I don’t know). Watts assumes no forest, and no deer, at O’Hare. He assumes JFK isn’t on the water. He assumes DFW and DIA are not on the prairies.
Most of our major airports are similarly un-urbanized. While there is a lot of concrete at those places, volume-wise, much of that concrete is concentrated underground, to bear the weight of aircraft. Consequently, our larger airports are neither accurately portrayed as urban, nor as insignificant chunks of land. While jet engines generate a lot of heat, Watts has not made the case that the average airport generates heat like a city does.
You claim airport measurements inaccurate because airports are urban and small. You need to make a case that weather measurements are inaccurate, but you can’t do that from assumptions that are completely in error. I think you should start over, using real data on airports and urban heat effects. Anthony takes great delight in finding weather stations that are, by his photographic measurement, too close to pavement or air conditioners (he doesn’t account for heat pumps, I’ve noticed). That’s not the same thing as saying they are inaccurate.
Then there is the larger issue: Watts (and you, I presume) assume that heat from Urban Heat Islands is illusory, and should not count toward global warming. I’m not sure why he makes that assumption, but the heat from cities is very real. In my airline days, I spent a little time with the meteorologists there who had two big problems from UHI. The heat changed the nature of the air over cities, which changes the way an aircraft flies in that air. Small issue for most broadcast meteorologists, perhaps, but big issue for passenger comfort and aircraft safety. Second, UHI changes the weather, particularly in August and particularly with regard to thunderstorms, the bane of commercial flying.
For climate change issues, we should worry about how that heat gets distributed. Watts rather assumes it just disappears. Reality is that it’s heat, and heat doesn’t disappear. Heat generated by Urban Heat Islands is real, and it changes climate downwind, wholly apart from the additional greenhouse gases emitted. Watts doesn’t account for any of that.
Jones said:
Hard studies on that issue haven’t borne up that hypothesis. Even the Berkelely study, using Watts’s data, didn’t support Watts’s hypothesis.
I think that’s at best slicing the air, and at worst, total baloney. I noted the plant zone maps earlier. I first encountered climate change as an issue working on air pollution issues in the 1970s. What we observed then was botanical and zoological changes prompted by something, though we didn’t know what. We used to laugh in classrooms about the dangers of cleaning up particulate pollution and leaving the “invisible” greenhouse gases flowing, thereby frustrating the global cooling and, perhaps, ice age that, by the 1970s, was overdue.
Climate change was observed, and we have been working to find a cause for 60 years now. Almost all potential causes have been systematically eliminated by hard science, leaving our then-laughable greenhouse gas hypothesis as the one that is still standing. As Sherlock Holmes noted, once you eliminate all the things that are impossible, what remains, however improbable, is the truth.
So, if it’s not global warming that causes the climate change that accompanies global warming, what is it?
I’m not happy with the cricket chirp coming when we ask the causes question from y’all.
I don’t know that urban sites and poorly sited rural stations are warmer, and from by too-brief foray in science and longer foray in science policy, my Hemingway [Excrement] Detector starts screaming whenever someone says “everybody knows” about stuff that hasn’t mustered judicial note, or nursery rhyme. Heck, this is Millard Fillmore’s Bathtub — everybody knows that Millard Fillmore was the first president to put a bathtub in the White House. What everybody knows is wrong in that case — and I suspect, it’s wrong in your example, too.
That leads to trouble. It’s not what we don’t know that gets us into trouble, but what we know that ain’t so. You seem to know a lot that isn’t so — that airports are urban heat islands, that urban heat is different from other heat and magically disappears, that the geographically-weighted observations of climate by USDA over the past 150 years are all wrong, that CO2 magically stops behaving like CO2 for political purposes, that most scientists are wrong and refuse to admit error; Watts goes on with a number of other things everybody knows, that are not so (do you subscribe, too?) — that Rachel Carson was a fraud, that DDT is harmless and magically cures tropical diseases, etc., etc.
At least you admit that there are warmer temperature readings. Those are physical phenomena. Excuse me if I doubt your claim that they are not real.
Well, thank heaven for your dealing with those conversions. Excuse me if, again, I fear you’re dealing with acronymitis, and not with climate change.
See, here’s the problem, Evan: Earth shows effects of climate change, of warming. Almost all the world’s significant glaciers are melting. Birds change their migration paths. Crops won’t grow where they used to grow, due to heat, and now grow where it was previously too cold. Exotic species spread rampantly causing chaos in wild lands and cultivation, as if warming were paving the path for their spread. Reindeer and caribou migrations change; fish breeding and migration have changed. Ocean currents change, as if global warming is causing them to adjust. Droughts looking exactly like global warming-caused droughts wrack most of the U.S., and much of the rest of the world — punctuated by disastrous, unseasonal floods in the same places, just as if the climate were warming.
In my time in botany, I learned that plants do not read newspapers, nor do they read reports from the UN. Wild animals, birds and big ungulates, at least, also don’t read the news magazines. Ocean currents and clouds cannot read those reports, nor understand radio and television broadcasts.
I think I can say with some assurance that these effects are not caused by birds, animals, oceans and winds watching Al Gore’s movie. To nature, warming is not politics, and it’s not caused by allegedly inaccurate readings of temperature.
If we’re not measuring warming accurately, would accurate measurements change any of the effects of warming? I don’t see that happening.
If we were to grant, for the sake of argument, that you’re right that stations are sited badly, and warming is reduced (by a tiny amount) when measured accurately, how does that change anything?
Those last two paragraphs are important questions to me. I’m happy you stopped by; I hope you’ll stick around to explain your position.
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Sigh. A couple of points:
First, Urban sites make up 10% of the USHCN. But Urban area is well under 2% of US surface area. Semi-Urban sites are overrepresented by over double, as well.
Airport sites make up 6% of the USHCN (with some overlap with Urban). Airports are, well, 0% of US surface area.
Therefore Urban (and Airport) sites have a disproportional, spurious effect on the climate record. However, the effect of poorly sited rural stations on the trends is far greater.
Second point. If you exclude the poorly sited stations (i.e., those not in compliance with NOAA’s own standards), yes you get a much lower trend. The stations that are well sited have much lower trends. To quote the president, “That was the POINT.”
And time is not a variable? Huh? We deal strictly with trends per decade over a defined 30-year period:
Everybody knows urban sites and poorly sited rural stations ARE warmer. That is not an area of controversy. Both sides of the debate fully agree on this. The question we address is whether they WARM FASTER. Our findings are that they definitely do warm faster.
Finally, in our updated draft, we have fully dealt with both TOBS bias and MMTS conversion, which were legitimate criticisms of the original draft. And the premise still holds.
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Cities generate heat. We can’t claim to accurately measure temperatures if we artificially declare that temperatures in cities don’t count.
Watts has been laboring under an odd delusion that the Urban Heat Island Effect, a well documented weather phenomenon, doesn’t involve real heat, that somehow the heat is illusionary. I suppose the storms caused by urban heat islands (UHIs) are also illusionary, as is the rain that falls? His argument is more than just that there is a skew downwind of UHIs, but that the temperature readings, when averaged in with all other readings, skew world temperatures. That issue has been checked a hundred different ways a thousand times each way, and found to be no problem. UHI readings are not skewing temperature readings in Greenland, nor in the Sahara, in the Amazon Rain Forest, nor many other areas where temperatures are found to be rising and causing trouble.
Watts has a special category for airports, his claiming against evidence and common sense that the forest around Thurgood Marshall Baltimore-Washington Airport is the equivalent of a UHI, because runways are made of concrete. Since so many weather stations are at airports, Watts argues these stations are all skewed, also.
In his current paper, he argues that city temperatures are skewed, and suburban temperatures are skewed, and that if we ignore those readings, warming isn’t so bad (though, even Watts finds there is still warming beyond a natural trend).
Heat is heat. If a particular temperature measurement station is badly placed, if it remains badly placed for a decade or three or four or five, its recordings are still accurate with regard to the trending rising temperatures over time.
Watts appears not to consider time as a variable, nor does he suggest any magic trash can for all that UHI heat to be taken from the surface of the planet.
I think I’ve fairly summarized his paper in the headline — can you show any place it errs?
Seems you’re defending Watts’s paper, and you don’t understand it. Did you read it?
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If you place a thermometer next to an industrial sized air conditioner, a large concrete building, and on top of asphalt it will be artificially warmer then the true ambiant air temperature. Are you saying this is not true? We shall see what the greater scientific community thinks of this draft since EVERYONE, not just a few editors will be able to tear it apart. Seems like you are tearing it apart and you don’t even understand it.
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