From the “we told you so” department comes this paper out of China that quantifies many of the very problems with the US and global surface temperature record we have been discussing for years: the adjustments add more warming than the global warming signal itself
A paper just published in Theoretical and Applied Climatology finds that the data homogenization techniques commonly used to adjust temperature records for moving stations and the urban heat island effect [UHI] can result in a “significant” exaggeration of warming trends in the homogenized record.
The effect of homogenization is clear and quite pronounced. What they found in China is based on how NOAA treats homogenization of the surface temperature record.
According to the authors:
“Our analysis shows that “data homogenization for [temperature] stations moved from downtowns to suburbs can lead to a significant overestimate of rising trends of surface air temperature.”
Basically what they are saying here is that the heat sink effect of all the concrete and asphalt surrounding the station swamps the diurnal variation of the station, and when it is moved away, the true diurnal variation returns, and then the homogenization methodology falsely adjusts the signal in a way that increases the trend.
You can see the heat sink swamping of the diurnal signal in the worst stations, Class 5, nearest urban centers in the graphs below. Compare urban, semi-urban, and rural for Class 5 stations, the effect of the larger UHI heat sink on the Tmax and Tmin is evident.
In Zhang et al, they study what happens when a station is moved from an urban to rural environment. An analogy in the USA would be what happened to the signal of those rooftop stations in the center of the city, such as in Columbia, SC when the station was moved to a a more rural setting.
U.S. Weather Bureau Office, Columbia SC. Circa 1915 (courtesy of the NOAA photo library)Here is the current USHCN station at the University of South Carolina:The Zhang et al paper studies a move of Huairou station in Beijing from 1960 to 2008, and the resultant increases in trend that result from the adjustments from homgenization being applied, resulting in a greater trend. They find:
The mean annual Tmin and Tmax at Huairou station drop by 1.377°C and 0.271°C respectively after homogenization. The adjustments for Tmin are larger than those for Tmax, especially in winter, and the seasonal differences of the adjustments are generally more obvious for Tmin than for Tmax.
The figures 4 and 5 from the paper are telling for the effect on trend:
Huairou station and reference data for original (dotted lines) and adjusted (solid lines) data series during 1960–2008. The solid straight lines denote linear trends
Now here is the really interesting part, they propose a mechanism for the increase in trend, via the adjustments, and illustrate it.
They conclude:
The larger effects of relocations, homogenization, and urbanization on Tmin data series than on Tmax data series in a larger extent explain the “asymmetry” in daytime and nighttime SAT trends at Huairou station, and the urban effect is also a major contributor to the DTR decline as implied in the “asymmetry” changes of the annual mean Tmin and Tmax for the homogeneityadjusted data at the station.
In my draft paper of 2012 (now nearing completion with all of the feedback/criticisms we received dealt with, thank you. It is a complete rework. ), we pointed out how much adjustments, including homogenization, added to the trend of the USCHN network in the USA. This map from the draft paper pretty much says it all: the adjusted data trend is about twice as warm as the trend of stations (compliant thermometers) that have had the least impact of siting, UHI, and moves:
The Zhang et al paper is open access, an well worth reading. Let’s hope Petersen, Karl, and Menne at NCDC (whose papers are cited as references in this new paper) read it, for they are quite stubborn in insisting that their methodology solves all the ills of the dodgy surface temperature record, when it fact it creates more unrecognized problems in addition to the ones it solves.
The paper:
Effect of data homogenization on estimate of temperature trend: a case of Huairou station in Beijing Municipality Theoretical and Applied Climatology February 2014, Volume 115, Issue 3-4, pp 365-373,
Lei Zhang, Guo-Yu Ren, Yu-Yu Ren, Ai-Ying Zhang, Zi-Ying Chu, Ya-Qing Zhou
Abstract
Daily minimum temperature (Tmin) and maximum temperature (Tmax) data of Huairou station in Beijing from 1960 to 2008 are examined and adjusted for inhomogeneities by applying the data of two nearby reference stations. Urban effects on the linear trends of the original and adjusted temperature series are estimated and compared. Results show that relocations of station cause obvious discontinuities in the data series, and one of the discontinuities for Tmin are highly significant when the station was moved from downtown to suburb in 1996. The daily Tmin and Tmax data are adjusted for the inhomogeneities. The mean annual Tmin and Tmax at Huairou station drop by 1.377°C and 0.271°C respectively after homogenization. The adjustments for Tmin are larger than those for Tmax, especially in winter, and the seasonal differences of the adjustments are generally more obvious for Tmin than for Tmax. Urban effects on annual mean Tmin and Tmax trends are −0.004°C/10 year and −0.035°C/10 year respectively for the original data, but they increase to 0.388°C/10 year and 0.096°C/10 year respectively for the adjusted data. The increase is more significant for the annual mean Tmin series. Urban contributions to the overall trends of annual mean Tmin and Tmax reach 100% and 28.8% respectively for the adjusted data. Our analysis shows that data homogenization for the stations moved from downtowns to suburbs can lead to a significant overestimate of rising trends of surface air temperature, and this necessitates a careful evaluation and adjustment for urban biases before the data are applied in analyses of local and regional climate change
Download the PDF (531 KB) Open Access
h/t to The Hockey Schtick
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UPDATE 1/30/14: Credit where it is due, Steve McIntyre found and graphed the physical response to station moves three years ago with this comment at Climate Audit.
Here’s another way to think about the effect.
Let’s suppose that you have a station originally in a smallish city which increases in population and that the station moves in two discrete steps to the suburbs. Let’s suppose that there is a real urbanization effect and that the “natural” landscape is uniform. When the station moves to a more remote suburb, there will be a downward step change. E.g. the following:
The Menne algorithm removes the downward steps, but, in terms of estimating “natural” temperature, the unsliced series would be a better index than concatenating the sliced segments.
This is why you dont adjust after station moves.
When a station moves its a new station.
You have to split the record.
Giss cru and ncdc have to adjust because then cannot use short records.
The approach pioneered by skeptics is to split the record.
We of course split records. A moved station is a new station.
(settles in with popcorn)
Following figure 6, you then get 3 short red trends instead of the 1 combined red trend. But each of your short trends still contains UHI, no improvement here with BEST.,
Manfred says:
“A criterium to separate UHI affected / non affected stations may then be, if the difference Tmax-Tmin remained stable or if it decreased.”
A criterium is a bicycle race on a short course. A criterion is a standard on which a judgement may be made.
From the map from your draft paper — did NOAA really ADD the increases sees in the Class 1 & 2 stations to the increases seen in the Class 3, 4, & 5 stations? To come up with an increase in temp HIGHER that either?
I think first to identify this problem was …..
http://climateaudit.org/2011/10/31/best-menne-slices/#comment-307953
Steve McIntyre…
OT Heads up.
Snowden Docs: U.S. Spied on Negotiators At 2009 Climate Summit
“WASHINGTON — The National Security Agency monitored the communications of other governments ahead of and during the 2009 United Nations climate negotiations in Copenhagen, Denmark, according to the latest document from whistleblower Edward Snowden.
The document, with portions marked “top secret,” indicates that the NSA was monitoring the communications of other countries ahead of the conference, and intended to continue doing so throughout the meeting. Posted on an internal NSA website on Dec. 7, 2009, the first day of the Copenhagen summit, it states that “analysts here at NSA, as well as our Second Party partners, will continue to provide policymakers with unique, timely, and valuable insights into key countries’ preparations and goals for the conference, as well as the deliberations within countries on climate change policies and negotiation strategies.” ”
http://www.huffingtonpost.com/2014/01/29/snowden-nsa-surveillance-_n_4681362.html
And here is the wonderful Watts, et. al., 2012!
Part 1: http://wattsupwiththat.com/2012/07/29/press-release-2/
Part2: http://wattsupwiththat.com/2012/07/31/watts-et-al-paper-2nd-discussion-thread/
WAY TO GO, ANTHONY!
I’ve read the paper, and the analysis seems reasonable, as far as it goes, but there is bizarre logic. It seems that they do correctly derive the adjusted trend as per Fig 6, but they also do a UHI analysis based on different behaviour of Max and Min. Then they argue that adjustment overestimates the trend, as independently corrected for UHI.
But these are unrelated things, and illustrate the peril of analysing just one station. It happens that for Hairou, station moves approx compensate for UHI, but there’s no reason to expect that to happen generally.
I think BEST said there was no UHI detected in their set. But that is pretty nonsensical for several reasons
One – the idea that the rate of temp change is the same over time for rural and Urban stations makes little sense. This could only be true if the population, structures, impervious surfaces and the like stayed exactly the same in the urban area over time. There is no city in my opinion and belief that has not seen a large and significant increase in building mass and hard cover over time. And if building mass and hard cover has increased then there MUST be an increase in temperature over and above the natural warming signal.
Next – although related – if I recall the increase in temps over time is largely in overnight temps in urban areas. This too makes perfect sense – more building mass and more hard cover increases the heat sink dramatically. That increased heat sink stores and radiates that heat into the night, causing higher night time temps.
Here too however – the urban Tmin temps MUST increase over and above the natural warming signal, as the city is built out and the structural mass increases.
IF a city remained entirely statci over time – there were no changes to buildings, road, hard cover etc then it COULD be conceivable the warming in this urban city would match the trend for rural areas. Both would be subject to a static “base” and should reflect only the natural warming signal.
However, in any city that grew during the measurement period – which increased its structural mass and hard cover – there pretty much MUST be a mean temp increase in excess of the natural warming signal trend. There must be an UHI effect.
Simple common sense science says to me this must be so.
I still think it would be interesting to pair two top-notch stations – one correctly and permanently situated (an existing, long-standing station would be best), and one either robotic or moved by volunteers to honestly random locations in a 100m radius.
It should be possible to:
1) -directly- quantify some of the microsite issues
2) end up with an -apples-to-apples- thermal map (as opposed to a quick-and-dirty infrared photo)
3) start quantifying the -spatial- error
Wow … you know what really stood out last night on the LWIR satellite image with this cold air in place? The DFW metro area … all that concrete, the buildings contributing to the (drum roll please) UHI effect! … geesh …
.
So maybe the global warming has stopped because it hardly started in the first place.
There’s a lot of good stuff on HS at the moment.
Trenberth debunks himself: The oceans didn’t eat the global warming ‘missing heat’
http://hockeyschtick.blogspot.com.au/2014/01/trenberth-debunks-himself-oceans-didnt.html
NSIDC: 2013 sea ice was at record highs for the satellite era, record high winter extent & summer minimum
http://hockeyschtick.blogspot.com.au/2014/01/nsidc-2013-sea-ice-was-at-record-highs.html
“The troubling part of the whole adjustment process is that it does similar magic on historical records as well. There is no justification for manipulating 80-120 year old records.”
Come now! If you do not adjust those old records, how are you to get the alarming trend you’re looking for? Merely pumping more recent temperatures UP simply won’t get the job done. You must also push earlier temperatures DOWN.
Evan/Anthony: FWIW- thanks for the tenacity and long hours. The importance of the work you’ve done (and folks like M&M) is impossible to overstate if we’re ever to start redirecting the billions from the political beneficiaries of faux science to the truly needy of our world. Not to mention the regressively destructive effect of more expensive and less accessible energy and food.
While I’m at it- h/t to all the remarkable commentators here. It’s amazing how I slip in to catch the latest on the shenanigans of the hockey team and before long I’m waist deep in Newton’s Principia. WUWT is a reincarnation of the joys found following Silverlock’s epic jaunt through the Commonwealth of Letters- thanks very much.
JRP
REPLY — And don’t forget the volunteers. Hansen may have a bulldog, but Anthony has the “mercury monkeys”! ~ Evan
From the map from your draft paper — did NOAA really ADD the increases sees in the Class 1 & 2 stations to the increases seen in the Class 3, 4, & 5 stations? To come up with an increase in temp HIGHER that either?
It’s from the old paper. My updated map still shows a ~60% exaggeration of the surface record, but not the 100% you see there. Rural MMTS shows >100% exaggeration. Poor sites are now about equal to the adjusted version.
When we publish, I’ll explain all the hows, whys, and wherefores. A tale worthy of Willis.
Mosh —
Yes. New location = New station; that’s exactly how I see it.
And, yes, you were right about TOBS. I confess it.
In fact, rather than screwing around with TOBS adjustment, I say New TOBS ought to = New Station.
Bernie, if I did not have to read so many urban legends in the past I would not bother pointing out the liberal arts majors, some of which get taken way too seriously.
Station 1 shows no trend for 10 years. Station 1 is moved, now is called station 2. The next 10 years station 2 (now a “new” station) shows upward trend for 10 years. So what. It means nothing.
How can anyone consider that good metrological (as in measurement science) practice? It would get laughed out of any A2LA lab audit.
If machined hole in a block of aluminum is measured with appropriate NIST traceable instruments in a lab environment at 70F, was found to be undersize according to the drawing tolerance, then move it back out to the machine shop where it was made and it measures in tolerance, does that mean the diameter is actually within tolerance? Well no it does not.
There’s a reason why we have standards for measurement, but there seems to be no standards applicable to climate “science”; it’s made up as it goes along. I find the notion of homogenization of temperature data ludicrous. The process should be left to dairy farmers where it belongs.
A metrologist would have a field day in a question and answer session about how temperature data is collected and reported. No PhD required. Why? Because before you take measurements, you must first understand what it is you are measuring, the instrumentation used to take the measurements and the environmental effects of what is being measured. That’s just for starters. I find so called scientists with no metrological background quite sloppy in their methodology, no offense. Measurement equipment and the data collected by them in the wrong hands can be a dangerous thing.
It seems WUWT had a metrologist guest poster some time back. He explained it quite well I thought.
Well gee, there might be hope after all
http://www.nist.gov/mml/aerosol_metrology_for_climate_workshop.cfm
Alas, even NIST has been poisoned; not surprising considering our dear POTUS has determined that no “deniers” will work in his administration. At least no more than 3% anyway.
http://www.nist.gov/iaao/upload/1-1-HSemerjian-NIST.pdf
Hey! I’m a liberal arts major!
Even worse, I have a graduate degree in Occupy Wall Street from an Ivy League University, no less.
Tonight in 20 minutes (10 PM Pacific, 1 AM Eastern), Coast to Coast AM radio will be interviewing:
Space historian Robert Zimmerman will discuss the fraud and dishonesty which has permeated the sciences of climate and environmental studies including how scientists at NASA and NOAA have consistently manipulated the temperature records.
You know this is a good-news-bad-news story for Warmers:
Good News: it explains the “pause” in Global warming (warming paused when NOAA stopped adding an offset.)
Bad News: When you remove the offending offsets, the whole 20th century is part of the pause.
Thanks Evan,
I thought I was alone.
REPLY — I haven’t done the forensics on the murder weapon, but I have done an autopsy on the mangled corpse. Ick.
Does this paper (not to mention Anthony’s) up the ante a bit for Warmists? I wonder how long it will be before there is a criminal investigation into deliberate manipulation of global economies through intentional doctoring of scientific data, for the enrichment of a few people (such a former vice-presidents) while contributing to the near-meltdown of the western economic foundations?
Ah the Chinese throwing some light on the sneaky revisions of temperature and station locations – when I read the title I wondered what the master of weird twisted logic would have to say in defence of the heatwave “milkshake” of smeared Desert temperature averaging that turns mild Australian summers into “angry summers”, didn’t have long to wait!!
Nick Stokes says:
January 29, 2014 at 7:58 pm
“I’ve read the paper, and the analysis seems reasonable, as far as it goes, but there is bizarre logic”.
What the!!!!
Now that is a bibful of dribbled doubt from the master of the bizarre excuses!!
I agree with our host!!