Note: See update below, new graph added.
There’s a new paper out by Dr. Edward Long that does some interesting comparisons to NCDC’s raw data (prior to adjustments) that compares rural and urban station data, both raw and adjusted in the CONUS.
The paper is titled Contiguous U.S. Temperature Trends Using NCDC Raw and Adjusted Data for One-Per-State Rural and Urban Station Sets. In it, Dr. Edward Long states:
“The problem would seem to be the methodologies engendered in treatment for a mix of urban and rural locations; that the ‘adjustment’ protocol appears to accent to a warming effect rather than eliminate it. This, if correct, leaves serious doubt for whether the rate of increase in temperature found from the adjusted data is due to natural warming trends or warming because of another reason, such as erroneous consideration of the effects of urban warming.”
Here is the comparison of raw rural and urban data:
And here is the comparison of adjusted rural and urban data:
Note that even adjusted urban data has as much as a 0.2 offset from adjusted rural data.
Dr. Long suggests that NCDC’s adjustments eradicated the difference between rural and urban environments, thus hiding urban heating. The consequence:
“…is a five-fold increase in the rural temperature rate of increase and a slight decrease in the rate of increase of the urban temperature.”
The analysis concludes that NCDC “…has taken liberty to alter the actual rural measured values”.
Thus the adjusted rural values are a systematic increase from the raw values, more and more back into time and a decrease for the more current years. At the same time the urban temperatures were little, or not, adjusted from their raw values. The results is an implication of warming that has not occurred in nature, but indeed has occurred in urban surroundings as people gathered more into cities and cities grew in size and became more industrial in nature. So, in recognizing this aspect, one has to say there has been warming due to man, but it is an urban warming. The temperatures due to nature itself, at least within the Contiguous U. S., have increased at a non-significant rate and do not appear to have any correspondence to the presence or lack of presence of carbon dioxide.
The paper’s summary reads:
Both raw and adjusted data from the NCDC has been examined for a selected Contiguous U. S. set of rural and urban stations, 48 each or one per State. The raw data provides 0.13 and 0.79 oC/century temperature increase for the rural and urban environments. The adjusted data provides 0.64 and 0.77 oC/century respectively. The rates for the raw data appear to correspond to the historical change of rural and urban U. S. populations and indicate warming is due to urban warming. Comparison of the adjusted data for the rural set to that of the raw data shows a systematic treatment that causes the rural adjusted set’s temperature rate of increase to be 5-fold more than that of the raw data. The adjusted urban data set’s and raw urban data set’s rates of temperature increase are the same. This suggests the consequence of the NCDC’s protocol for adjusting the data is to cause historical data to take on the time-line characteristics of urban data. The consequence intended or not, is to report a false rate of temperature increase for the Contiguous U. S.
The full paper may be found here: Contiguous U.S. Temperature Trends Using NCDC Raw and Adjusted Data for One-Per-State Rural and Urban Station Sets (PDF) and is freely available for viewing and distribution.
Dr. Long also recently wrote a column for The American Thinker titled: A Pending American Temperaturegate
As he points out in that column, Joe D’Aleo and I raised similar concerns in: Surface Temperature Records: Policy Driven Deception? (PDF)
UPDATE: A reader asked why divergence started in 1960. Urban growth could be one factor, but given that the paper is about NCDC adjustments, this graph from NOAA is likely germane:
http://www.ncdc.noaa.gov/img/climate/research/ushcn/ts.ushcn_anom25_diffs_urb-raw_pg.gif
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Rural readings reflect the real natural climate variability in temperature whereas urban readings are poisoned by various sources. This is an obvious truth. There’s only one explanation why they persistently adjust the rural readings up to match the less useful urban ones instead of adjusting the urban ones to other way. That’s obvious too so I don’t need to explain it.
What matters from the perspective of AGW is the temperature trend since 1980. The fact that the adjusted rural data gives almost the same value as the urban is surprising. I think this may be another way of stating, as I have sometimes seen, that the UHI correction overcorrects for urbanization.
If the work leading to this graph is valid, it’s beautiful. It actually shows that they change together and isolates the “average” urban effect.
It happens to confirm all my expectations. For example, the urban effect is mostly occurring in the last 50 years and gives 0.6 deg C or so.
By the way, that’s exactly how much I expected to the urban contribution to the data in Prague Clementinum:
http://motls.blogspot.com/2010/02/climate-czechgate-pragues-klementinum.html
When you subtract 0.6 °C from recent temperature, to get a corresponding guess for the countryside around Prague, you will actually see that Prague has slightly cooled between 1800 and today.
Best wishes
Lubos
How robust is this methodology? Looking at the paper here’s the selection criteria for rural/urban?
“In the context of this paper, ‘rural’ means a station whose location is with no more than one dwelling in its vicinity or at the outer boundary of a small community whose population does not exceed a small multiple of a thousand residents. The second set consists of stations with ‘urban’ locations. In the context of this paper, ‘urban’ means a station at the site of a sizeable airport, an industrial area within a city, or near the center of a well-populated city with industrial activity.”
As for stations selected, they seemed to have picked 48 and one from each state. I would have expected something like one in each of the 5×5 grids that was mapped out. 5×5 grids of course are poor representations of geography and climate zones.
By inspection a few standout. On the rural side Bedford, MA (suburb) and Kingston, RI (URI main campus)
Overall, the urban selection looks like it’s in a different climate zone. For example Yosemite vs Pasadena.
An interesting study certainly does raise some methodology questions about the NCDC plot, but I think a better better study should be demanded.
Anthony, do you have any idea what the station count for the NCDC raw data? If there are more stations then this could be a sampling issue. Doesn’t seem to hurt to include more stations and especially stations in similar climate zones.
I think the author is looking at the data from the wrong perspective.
The primary fact to remember is that “global warming” is a social phenomenon, so the impacts in the lives of individual people is what really counts.
As the move of populations from rural to urban locations accelerated over the last century, then clearly the social impact of warming in urban areas has become increasingly important. It therefore is perfectly reasonable to weight temperature readings to match the number of people affected, thus giving the rural readings very low significance due the to low populations.
So you see, when you apply the proper perspective of a social scientist, it is perfectly reasonable, and only a hard scientist like a physicist would fail to see this!
Not so much a smoking gun but an exhaust trail left by an ICBM!
Wow! This will be big. (Just wanted to get in the first comment, as with Climategate.)
PS: Someone please pursue the suspicious winter icebreaking in Hudson Bay.
That is incredible! If it holds up, it blows the whole AGW theory to kingdom come. If the UK Met review of surface stations shows the same problems. it’s all over.
So, just so I’m clear:
Instead of adjusting the urban stations down to counteract the artificial heat retention in an urban setting, they instead adjusted the rural stations up. Is there anyone who can’t see how that is wrong? Is it any surprise that the “average” temperature then shows an increase?
Isn’t this what “we” have been claiming was being done all along?
A very graphical example of fraud, obvious even to a child.
Or should we call it politely “a convenient lie”?
Impostors have been denounced. No honest, self-respecting scientist or journalist can continue to insist that AGW theory is based on facts. Nevertheless, many scientists and journalists are still pushing this red herring. Why?
Money is the most powerful drug, it does wonders with the perception of reality. Especially when it’s other people’s money.
In a real world, not one in the mind of a climate alarmist, the rural area readings would not need adjusting and the urban ones would need a downward adjustment of at least 0.5-1.0 degrees C.
Almost the opposite has happened here.
So the question is clearly: With only one comparison of urban and rural temperatures per state, how representative are the figures, or is this ‘cherry picking’ like so much of the alarmist data?
If it can be demonstrated that these figures are truly representative, then the climate establishment is clearly guilty of fraud on a massive scale.
It is nothing new on this paper. Almost everybody knows that they do this kind of “trick”. Just look at part 3 of this video from Finnish TV about CRU. They are talking about exact same “trick” on Russian rural and urban station data.
part 1:
part 2:
part 3:
Sounds very convincing, but what about Roy Spencer’s recent satellite analysis?
http://wattsupwiththat.com/2010/02/20/spencer-developing-a-new-satellite-based-surface-temperature-set/
Kind of nullifies everything doesn’t it?
As for stations selected, they seemed to have picked 48 and one from each state. I would have expected something like one in each of the 5×5 grids that was mapped out. 5×5 grids of course are poor representations of geography and climate zones.
So your “correction” for allegedly poor methodology is … wait for it … a methodology you acknowledge to be poor.
The 5×5 grids are a meaningless abstraction. They should be ignored IMO.
There is only one answer to this paper. To show that urban stations and rural stations do not differ in the manner shown. I doubt they can actually do that, even with cherry picking.
If the AGW crowd cannot show that rural stations do not show warming correlating to CO2, then the allegation that the USA is warming due to CO2 is going to be hard to maintain. By “hard” I mean, of course, near impossible.
Steveta_uk (00:38:35) :
“the social impact of warming in urban areas has become increasingly important.”
Not a lot of glaciers in cities, no really major swamps, lakes or fish stocks either. No coral reefs or forests that I have noticed.
“thus giving the rural readings very low significance due the to low populations.”
I don’t think they grow a lot of food in cities.
So what is “significance” to an urban population?
Clearly you don’t think that it is food.
Are we going to have to call this new “significance” Human Induced Social Warming?
“That is incredible! If it holds up, it blows the whole AGW theory to kingdom come. If the UK Met review of surface stations shows the same problems. it’s all over.”
DCC – the UK Met office? Don’t hold your breath
This paper validates a belief I have held for a long time. They are “removing” UHI by apparently adjusting rural temperatures up rather than adjusting urban temperatures down. This is also easier to accomplish when you remove rural stations wholesale from the record and increasingly rely on urban stations for setting the temperature calculation for large areas.
Until this is thoroughly investigated, the current surface data should not be used. It is my personal belief that the satellite data are the only reliable temperature reading we currently have available and it goes back only to 1979.
This whole thing is just sickening. If the average citizen understood how they data have been manipulated and the extent to which they have been sold a bill of goods, there would be a run on pitchforks and torches.
Steveta_uk (00:38:35) :
We can reduce Human Induced Social Warming by installing few clean coals fired generating stations and distributing air conditioners.
We can increase Human Induced Social Warming by distributing sleeping bags and Guinness.
Social Warming, you perhaps trying to move the goal posts?
It appears from the graphs that for at least the last 5yrs the urban values were actually adjusted up. WUWT?
Steveta_uk (00:38:35) :
“I think the author is looking at the data from the wrong perspective.
The primary fact to remember is that “global warming” is a social phenomenon, so the impacts in the lives of individual people is what really counts.
As the move of populations from rural to urban locations accelerated over the last century, then clearly the social impact of warming in urban areas has become increasingly important. It therefore is perfectly reasonable to weight temperature readings to match the number of people affected, thus giving the rural readings very low significance due the to low populations.
So you see, when you apply the proper perspective of a social scientist, it is perfectly reasonable, and only a hard scientist like a physicist would fail to see this!”
————————————————————
So the social scientist’s proper perspective is to compare apples with oranges? Thanks for the tip.
I think another issue has to be considered. Rural stations are not imune to change of land use. A rural area might change from forest to corn field or from grassland to forrest. Those changes will have a huge effect on the measured temperatures.
And it’s simple math (right Pamela, not maths).
Assuming cities occupy 5% of the US land area, then adjusted combined slope should be something near:
0.13 * (100%-5%) + 0.79 * 5% = 0.163 oC/cy
When in reality only rural temperatures should be used, period, giving 0.13 oC/cy if we want to know if the globe is warming, not if cities are warming.
Another shoe drops…
I suspect the increasing trend from a rural lifestyle to urbanisation over the past few generations makes the UHI seem ‘normal’ to politicians increasingly separated from the countryside and the natural world. Couple this to the background of Marxist control-freakery that most UK New Labour politicians spring from and their adherence to AGW is no surprise. As a class, these men and women see no reason why everything in the environment can’t be controlled, when every person who has some experience of rural life knows the environment, including the climate, is supremely indifferent to Man.
As an example of the law of unexpected consequences, farmers in the Yorkshire Dales are paid by government agencies to ‘winter’ sheep rather than turning them out to forage for themselves on the high moors. As a consequence, wild birds native to the moors are in decline due to the absence of the sheep, who once dug through snow to expose grazing and thus allowed the birds access to ground-based fodder.
Climate is largely a mystery, as yet, but dishonest selection and manipulation of basic data is only useful for fooling some of the public for some of the time and will (hopefully) bite the manipulators on the backside some time soon.
“appears to accent to a”: presumably he meant, or wrote, “appears to accentuate”?
That adjustment of rural trend up to match urban trend is the exact opposite of what should have been done in any “country, continent or global temperature set”, that attempts to investigate any real temperature trends caused by CO2 or any other greenhouse gas. I am amazed at what they appear to have done! Surely the incorrectness of their adjustment was plain to see when they were doing it!
Dear Anthony,
I just had a look at the paper, it is worth reading in the original!
He lists the individual stations, do you have them in your database and can you comment on the individual quality?
Also, can you comment on his selection criteria of using “one station” of each per state? It somehow seems to overrepresent the costal area!?
However I think the two figures with the interanual trends are worthy to be included in post article about it. It is true, that the interanual trend for both sets are very similar giving the study a lot of credit!
All the best,
LoN
I’m not so sure on this one. If the adjusted graph is correct, every year since 1990 should’ve been proclaimed hotter than 1934, which still stands as the record even in their own adjusted stats.
””””’Peter of Sydney (00:16:28) :
There’s only one explanation why they persistently adjust the rural readings up to match the less useful urban ones instead of adjusting the urban ones to other way.”””””
Peter,
It is obvious. There no need to say. And it is likely to be the beginning of NCDC’s (NOAA’s) undoing.
Now we look back on the 21 Feb WUWT post by Willis Eschenbach titled “Fudged Fevers in the Frozen North”. We (at least I) were struggling with understanding why GISS/NASA made the counterintuitive temperature adjustments to Anchorage (urban) and Matanuska (rural then recently possibly urban) that they did. The explanation could simply be very similar to the “obvious” explanation of why NCDC/NOAA did the adjustments that were shown in the paper by Dr Edward Long.
First Hadley/CRU dataset has problems, now NCDC/NOAA has problems and GISS/NASA datasheet is being looked at but preliminary signals is they also have problems.
The problems increasingly appear to be intentional AGW biased manipulation of temperature datasets via their adjustment of raw data.
To all three datasets! There is some implication there that I hesitate to go to . . . . .
John
In other news, something astounding has happened: a part of the Arctic shelf broke off and the Scientist in the know said it isn’t directly linked to `climate change’.
I’m shocked, upset and, frankly rather bemused by this turn of events.
Looks like an open and shut case, which no doubt, the MSM will leave in lost luggage.
Good Job the MET office is to re-examine 160 years of global temperature records following the ‘climategate’ scandal…. but wait…
“Vicky Pope, Head of Climate Change Advice, at the Met Office, said the new global temperature analyses would not change the trend of global warming.”
…maybe not
This has always been a no brainer. Anyone with a car dashboard thermometer can do this.
In my case, I worked for years in central London at night, and at 3 a.m. in Trafalgar, the temp would be 5C, driving home westwards, it would be 3C at Heathrow, 4c at Slough, 3 at Maidenhead, 2 at Reading, and 0C at Newbury.
This same pattern was common winter or summer.
Quote from author’s American Thinker piece:
We have been repeatedly told (perhaps “lectured” is a better word) the past twenty years that global warming is occurring. With Climategate and subsequent confessions and bailouts by scientists at the CRU, Penn State, Arizona State, IPCC, et al., we are learning that little to none of the factual content in their “peer reviewed” articles is true.
The Medieval Warming Period did occur, and it was warmer than currently; the oceans are not going to flood the plains; and the Arctic Ocean may not be turning into a summer water park. Of course, the mainstream media, especially in the United States, has reported little of this news, and President Obama appears not to be well-informed. But now the global warming story grows more interesting because here in America, we may have our own little “gate.” I will call it ATG, for “American Temperaturegate.”
In case you assumed he might be a partisan observer.
I’ve said it before, the AGW concensus/conspiracy is falling apart in front of our eyes. The trouble will be the true believers – scientists and laypeople who continue believing despite the evidence and agitate for needless changes to be made.
There will be complaints that the 2 subsets of sites were cherry picked. How much extra work is needed to analyse all rural vs all urban raw data? Also look at the 10 fastest and slowest increasing rural sites and the 10 fastest and slowest increasing urban sites, contrast and compare, to see what physical characteristics likely place them in that position if they are significantly different from their cohort growth.
No smoking gun. Nothing definitive. Not global. Small study. Have to do better.
Wow, that’s an impressive fudge-factor! 🙂
Where’s good ol’ Gav to spin this one?
Thank you Dr Long, this awful AGW scam needs very fast closure. The politics need to be stopped dead in their tracks.
The world has enough trouble with out a doomsday scenario. The rational among us can then pursue the perpetrators of this fraud.
When did Dr. Long start reading WUWT and CA? The findings come as no surprise to regulars on this blog.
Anyhoo, Dr. Long’s work can actually be peer reviewed, which is more than can me said for all of those pal reviewed charts that show “WAGTD real soon now.”
I think there is a real problem with his methodology that needs to be overcome. Given the disparity in size between the states (Texas is 174 times the size of Rhode Island) there must be a better way to represent the whole US than to select one rural and one urban station per state. Also Dr Long will be open to attack on the same grounds as Mann, in that he is using a very selective data set. Given that, I suspect his hypothesis is correct, that the algoreithms have adjusted rural temperatures upwards as a novel way of dealing with the UHI, enabling their advocates to argue that Anthony’s findings are false, as rural temperatures apparently rise as fast as urban ones, and neatly dispose of the obviously real UHI effect in similar style to the MWP.
Bang.
So others don’t have to calculate or question the missing factor:
(from: A Pending American Temperaturegate)
Using from the last decade of the 19th century to 2006 from NCDC and reverse-engineering to the “rural+urban” temperature rates implied, you get that they are using 59% as the percent of land covered by cities if using raw data and 50% as the percent of land covered by cities if using adjusted data. This is assuming that city temperature slopes would linearly revert back to the rural rate if all cities didn’t exist at all.
Raw:
Urban = 59%
0.11 * (100%-Urban) + 0.72 * Urban = 0.47 oC/cy
Adjusted:
Urban = 50%
0.58 * (100%-Urban) + 0.72 * Urban = 0.65 oC/cy
Don’t buy it. There is more open, rural land in the U.S. than 41% or 50%, your pick.
Steveta_uk (00:38:35) :
But I really don’t care if it’s a few degrees hotter on your patio, surrounded by streets, houses, your house, your air conditioner, and fences; I care answering the question if the entire globe is getting warmer or not. So far the answer to me is no. When I sit on my patio I’m smart enough to know why it is a few degrees hotter, because it is surrounded by streets, houses, my house, my air conditioner, and fences. Seems you are so worried about your personal square yard that surrounds and follows you around that you would decimate the economies of the world to make it the right temperature in your backyard. You can live in your perspective of a social scientist if you want to, sorry, not me.
I’d like to see this carried out on all Anthony’s surveyed sites, limited to the CN 1 & 2 quality stations; that’ll avoid accusations of cherry picking.
Good work though. I’m still astonished at how dishonest the crimatologists have been; so brazen.
Has to be done to match their climate model predictions I suppose. Blatant fraud really.
Hee HAw, Catlin expedition 2010 soon underway. http://bushynews.com/?p=201
Having looked at 4 Northern Calif. and 2 Southern Oregon rural stations as compared to 2 Northern Calif. urban stations going back beyond 1900, I agree with the findings of this paper.
It’s an exhaustive task to sift through the mountain of data for just one site, which is how they have gotten away with such shennanigans for so long.
If you haven’t spent time there, I highly recommend you visit NCDC’s original document archives.
But it is not “peer-reveived”
The argument against this paper will be a political one: It is not peer- or pal-rewieved, not done by ‘real’ scientists, not published in a “leading scientific” publisher’s house.
Is there somewhere a ranking of publishers? Those with misconducts in publishing (CRU-mails)? Those which demand access to all data and software of all papers? Those which do not? Those which collaborate in hiding declines? ……..
When I first looked at the two graphs I completely missed their significance. It seemed that the second graph showed that they had done a good job. The adjustments had almost eliminated the difference between rural and urban.
But then I realised the awful truth. They had adjusted the rural values *up* to almost match the urban values!
This is so bad that it only leaves one question. Was this due to sheer incompetence? Or fraud? Either way, whoever is responsible should be held to account. Hopefully we won’t have to wait too long….
Chris
Instead of adjusting the urban stations down to counteract the artificial heat retention in an urban setting, they instead adjusted the rural stations up.
And it appears they ignore the disparity in total area between urban and rural environments, too. There’s a reason the term “Urban Heat Island” was coined…
Wow…that graph says everything…
http://www.foxnews.com/scitech/2010/02/26/climate-scientists-january-hottest/
Climate Scientists: January Was ‘Hottest’ Ever
Reuters
Despite images of Europe crippled by a deep freeze and parts of the United States blasted by blizzards, the pace of global warming continues unabated, climate scientists claimed Thursday.
“January, according to satellite (data), was the hottest January we’ve ever seen,” said Nicholls of Monash University’s School of Geography and Environmental Science in Melbourne.
Which is the kind of lunacy that makes millions want to spit nails. It did NOT happen, this amazing hottest ever, in the real world. Perhaps it truly exists in the mind seized with fever.
To a non expert such as myself the raw unajusted urban data looks to coincide with the increase and economical availablity and popularity of inexpensive residential and apartment size air conditioning units. Not?
“NUSA DUA, Feb 26 (AFP) – The United Nations will review its Nobel prize-winning climate panel, whose credibility has been tarnished by errors in a key report on global warming, a spokesman said on Friday.
…
UN Environment Programme spokesman Nick Nuttall said at an international environmental meeting on the Indonesian resort island of Bali that an independent body would be set up to “review and strengthen” the IPCC.”
http://www.mysinchew.com/node/35629
Ahhh, The Divergence Problem and very neatly outlined. A very nice correlation, but I am uneasy about only one station set per state. 48 does not seem very many for the continental US, and perhaps using the WUWT surveyed set, a second paper could be written. I fear that the AGW team will shout about – “Cherry Picking”.
” The fact that the adjusted rural data gives almost the same value as the urban is surprising. I think this may be another way of stating, as I have sometimes seen, that the UHI correction overcorrects for urbanization.”
The trick is that their “correction” isn’t reducing the UHI.. it’s applying the UHI EVERYWHERE! Look at the absolute temp of the recent data of the adjusted graphs.
Yes, this homoginizes the readings so you can compare them, and eliminates the UHI… when comparing Urban vs Rural… but what it does NOT allow you to do is compare past rural readings (less UHI) to later rural readings (more UHI.)
Think about it this way… for a rural station they’re pretending that:
RTEMP1950 + UHI = RTEMP1990 + UHI
That is to say that if no warming was happening, 1950 and 1990 would be the same because UHI cancels out.
What they’re neglecting is that UHI has dramatically different values in 1950 and 1990. It’s not a constant, so they don’t balance out the equation. For all intents and purposes, UHI adjustment in1950 was 0, but the UHI adjustment in 1990 was around .5 degrees C in the adjusted data.
RTEMP1950 + 0 = RTEMP1990 +.5
This causes the equality comparison to no longer be remotely true.
RTEMP1950
Very important work. One thing puzzles me. Look at Figure 11showing the difference between raw and adjusted rural temperatures. It says the raw temperatures were moved downwards by about 2 degrees in the beginning of the period, and upwards by 0,5 degrees at the end. This agrees with the previous figures as far as the late period is concerned, but hardly the early part.
You cannot be too suspicious these days. I hope I am wrong.
Irrespective of the obvious pollution of the urban data by UHI, note also that both the raw data shows that the 1930s and 1940s were warmer than the 1990s.
Robinson (02:03:16) :
Robinson – the BBC new website also carried this news but, amazingly did not spin it with any reference to AGW.
What they did day however, was the fact that the cooling effect of the ‘berg, blocking super-cold bottom water flow and hence heat conveyor belt sea currents may cause several harsh winters ahead of us. This primes the current cooling argument to be parried by the “global warming caused the calving and now the world is cooling”
Heads we win, Tails you lose.
“Also Dr Long will be open to attack on the same grounds as Mann, in that he is using a very selective data set.”
There’s one difference… the goal of Dr. Long’s analysis was to disprove a thesis. By showing that the algorithm generates incorrect results in one case, you prove that it isn’t trustworthy and can not be relied upon for any cases.
John Hooper (02:08:19) :
“In case you assumed he might be a partisan observer.”
b.poli (02:54:07) :
“The argument against this paper will be a political one:”
Partisan? Political?
How about “Witness for the Prosecution”.
—
Edward R. Long is a physicist who retired from NASA where he led NASA’s Advanced Materials Program[…] He also provides technical consultant support to members of the Commonwealth of Virginia’s legislative bodies.
—
Commonwealth of Virginia v. U.S. Environmental Protection Agency — Petition for Reconsideration of Endangerment & Cause (U.S. Court of Appeals District of Columbia)
—
Make no mistake, this will likely be to most “peer-reviewed” climate paper of all time.
Warning: People using default excel colours usually have little skill in data processing.
CodeTech (00:55:46) :
This can’t be true. They can’t be that stupid. Doesn’t fig.11 show they actually adjusted rural down for most of the period? Why??
I had better start putting my house in Norwich… 1 mile from UEA on sale. Hope Phil Jones and Keith Briffa have already got theirs on the market!
http://www.timesonline.co.uk/tol/news/environment/article7041857.ece
This is a shell game, folks.
Step 1: adjust the rural raw data up to match the UHI.
Step 2: carefully word the illusion that rural data matches urban data.
Step 3: apply a uniform adjustment to urban data to give the impression that there’s something wrong with all instruments.
Step 4: drop the rural stations
Step 5: smile for the camera
No one will ever know.
I’ve seen a slicker version called 3 card Molly. To the uninitiated, it looks easy to find the red card that has a corner eared. Study the game long enough and you will see multiple layers of illusion.
As I have said before on previous Temperature Analysis posts, whenever someone independent of NCDC, NASA, CRU, Hadley, UK Met Office, IPCC, WWF carries out the analysis of temperature history they find these kinds of Errors.
Those involved in keeping and presenting “official” records can no longer be trusted and I am sorry to say that I include Dr Spencer and the Satallite results in that group as well. When “Calculated” temperatures do not appear to reflect our reallity something must be wrong. When the NH is seeing record breaking Cold spells and Satellites are saying it is record breaking high temperatures it does not make sense.
I understand that the higher atmosphere may differ to the Land temperature, but not the Satellite Surface temperature, they do not even agree with Sea temperatures measured by other means.
Interesting. This appears to replicate thee methodology of that Father and Son team featured on WUWT.
Also illuminating.
I now understand AGW.
It is evident that urban areas reflect the true state of climate change and that rural temperature data is subject to a natural heat sink effect (due to insufficient people?).
Hence the rural data has been rightly and legitimately adjusted for RHS (Rural Heat Sink) which would otherwise skew the data and suggest that what we are seeeing is natural climate vaiation.
As with global chilling, we must conclude that RHS is concealing the true and full extent of AGW.
(By the way, how much of this RHS effect is due to rural areas having insufficient A/C units? – or people?)
Denis Hopkins (03:55:02) :
I am ashamed to be British when they can peddle such cr*p in our name.
I was just looking at the GISS Station Data page and I noticed something that I had not noticed before… You can download the raw data. It defaults to the “homogenized” data. Is that a new feature? Or did I just miss it the dozen or so previous times I’ve downloaded GISS data?
BBk It is possible, though unlikely, that a cherry-picked selection of records might give the above picture without foul play in the GISS adjustments. I don’t believe this to be the case for a moment, but I think Dr Long has to go a little further to bury them once and for all. It is pretty important, as it kicks away the second leg of the AGW stool, after the death of dendro, and leaves the GCMs swinging in the wind.
Denis
Did you notice that in the paper version an imaginative sub-editor placed the article opposite a picture of snowbound motorists?
If the first graph correctly shows the UHI effects in urban vs rural stations, why does it begin in around 1965?
Just puzzled why it wasn’t showing up earlier or why it happens all at once.
This paper by Dr. Long is a good example of how distorted the mindset of the Warmers can be when they call it a “social phenomenon”. My cell-mate at work believes that reality is a reflection of each person’s own life experiences. Based on that, there is no absolute truth since no two lives are the same.
Steveta_uk’s comment “The primary fact to remember is that “global warming” is a social phenomenon, so the impacts in the lives of individual people is what really counts.” shows the same mindset which really isn’t science at all–it’s each individual’s opinion on climate, the weather, and temperature.
Temperature should never be a function of the observer’s mindset or adjusted by some frivolous fudge factor to support some social/political agenda. The relative warming we can measure in urban areas is simply a localized human artifact.
The crime comes when trusted repositories yield to the bogus social agenda of “Global Warming” and make unwarranted adjustments. (It really wasn’t due to CO2 after all, was it–you just thought since your city was a bit warmer it HAD to be warmer everywhere else, right?)
The term “Global Warming” should be changed to “City Warming”. And of that, folks, there is no doubt. But “Global Warming” isn’t a valid scientific term and Steveta_uk just told us why.
Smack!
The paper is perfect! It doesnt claim to measure global temperatures.It measureas and proves the fraudulent AlGor(E)itms in the homgenisation calculation of temperatures. Its like finding the bloody knive in the pocket of the suspect standing only a block away from the victem, and he left traces “carbon foootprints” behind to where he was confronted.
A number sseem concerned about the alleged “cherry picking” and why not all rural data.
As I understand it, infl;uenced by the father and son experiment, the purpose was to investigate or highlight the UHI effect.
That meant picking sizeable urban communities, the bigger the fewere, and paring them with a nearby rural area such that both could be said to be subject to the same ecternal natural climate influence.
Adding addittional rural areas does not help if they cannot be said to share the same natural climate.
Kilted made me laugh (I assume Kilter was being intentionally humerous):
QUOTE:
No smoking gun. Nothing definitive. Not global. Small study. Have to do better.
UNQUOTE
Re: Steveta_uk (00:38:35)
This is not a worry about what we feel when we go outside. It’s about the prospect of killing millions of poor folk by spending resources on a daft quest, rather than dealing with issues we really know about, like poverty, lack of clean water, deforeststion etc etc. And destroying Western economies by an unecessary rush away from fossil fuel energy (yes, we should evolve away, but not destroy ourselves in the process).
Greenies may not care, but decline and fall of USA and Europe is something I’d rather avoid, thankyou.
Please GET REAL.
Steveta_uk (00:38:35) said:
I think the author is looking at the data from the wrong perspective…..
Look at a satellite picture of the earth. What makes up the vast majority of the earth’s land surface; urban or rural/natural regions? If you really believe that we should adjust the latter to match the former then it explains why so many climate scientists are fooled into believing their own falsehoods. It would be like measuring the temperature of a sick patient by placing the thermometer on a cigarette the patient happens to be smoking in his mouth, and then use the reading to represent the temperature of the patient. Might as well just measure the temperature of active volcanoes to represent the global mean temperature as that would make Al Gore very happy.
I am pretty sure the post from Steveta_uk about how it makes sense from the perspective of a social scientist is ironic (and a quite funny satire ).
If not….well, then it is even more funny 😉
Anthony, Is the GISS and NCDC code that they use to make their adjustments available? I believe that the CRU code is definitly not available, is that true?
OT sorry but Rajendra Pachauri and the IPCC is to face an independent international inquiry into his organisations performance.
http://www.telegraph.co.uk/earth/environment/climatechange/7316758/IPCC-chief-Rajendra-Pachauri-to-face-independent-inquiry.html
Anthony
Good work here, and Long’s findings support the work you have put in to expose the bias and exaggeration of the information from the AGW camp.
The IPCC has a rice-bowl charter and runs a classic rice-bowl mission. It’s amazing how easily scientifically-trained people are converted to the new religion and morph into rice-bowl scientists. That is a consequence of their need to attract funding:
http://www.herkinderkin.com/2010/02/climate-change-rice-bowl-science/
It is important to note, however, that the AGW theory is not weakened by any of this. It fails because it is based on argument from ignorance. Even if the rate of climate changed actually matched the predictions of climate models, it still would not provide any evidence that the reason for the chage was AGW. Ptolemy was wrong about the geocentric universe, yet his model provided accurate astronomical predictions.
This pretty much goes back to Jones Et Al 1990, where they determined UHI was negligible, and confirmed by subsequent papers like Peterson 2003. This was necessary because the assertion is counter-intuitive.
The widespread inclusion of external thermometers in cars over the last 5-10 years has given the lie to this, at least on an anecdotal level.
John Hooper suggested that Spencer’s satelite comparison nullifies this, but Spencer concludes that his work is at an early stage and UHI may still be contaminating both temperature series.
A more interesting question to me is whether you should correct for UHI. Those towns and cities are there and they have changed their local climate. The cumulative effect of that and other land use changes and the knock on effects (like Kilimanjaro) pretty much is the climate change experienced to-date. However, adjusting rural stations up to match is clearly wrong.
It is worth remembering also that this is the basic data that CRU and GISS take on, then perform their own series of manipulations to. CRU claim there is no statistically significant UHI to correct, GISS claim they correct for it but either don’t, or where they do they usually go the wrong way.
Collection and quality control of the temperature data obviously needs to be put in the hands of people who are not “climate” scientists.
One per state leaves allot of room for error in choosing stations and in geographical weighting. Interesting but needs to be taken allot further before even discussing conclusions, IMO.
re: Steveta_uk Turn your satire detectors on people
I also interpreted the comment from Steveta_uk as irony. It does not surprise me however that so many people took him seriously. Irony is not practiced much in the US and in my experience people from that country don’t really get this form of humour.
Re: Steveta_uk comment…
I think his comment was tongue in cheek, and not meant seriously.
If you read the paper, you can see that station selection of the rural sites was from an evenly spaced grid.
NCDC and USHCN have always made access to the raw data as minimally transparent as possible.
Perhaps Judith would care to comment on these developments and similar problems being laid bare all over the world. If she is really angry that her own research has been affected by these lies, she can explain what these new data have done to her own and others research results.
Wow. People have talked about ‘smoking guns’ and massaged figures and I’ve never been particularly convinced. This looks to be smoking and gun-like though – now you see hockeystick, now you don’t. As a layman I sometimes find it difficult to interpret some of the complex data posted here, but I can see the significance of the graphs and exactly what has been done to the data here plain as day, as should most educated people. Everyone, everywhere needs to see this.
Is the terrestrial record now of any relevance to the issue? We now have satellite data.
There is clearly a lot of doubt about terrestrial measurements, and you have got to wonder why they are given any weight by either camp in the satellite age.
Having said that, I am a little concerned that no-one seems to seriously question the satellite data. I personally found the “warmest January in the northern hemisphere on record” measurement outrageous. I am sure there must be a “mistake” somewhere.
Peter Dunford (04:45:15) :
Re: Steveta_uk comment…
I think his comment was tongue in cheek, and not meant seriously.
————
Reply:
I dunno, Peter… I know people that have that mindset.
Steveta_uk (00:38:35) :
“I think the author is looking at the data from the wrong perspective.
The primary fact to remember is that “global warming” is a social phenomenon, so the impacts in the lives of individual people is what really counts.
As the move of populations from rural to urban locations accelerated over the last century, then clearly the social impact of warming in urban areas has become increasingly important. It therefore is perfectly reasonable to weight temperature readings to match the number of people affected, thus giving the rural readings very low significance due the to low populations.
So you see, when you apply the proper perspective of a social scientist, it is perfectly reasonable, and only a hard scientist like a physicist would fail to see this!”
————————————————————
So the social scientist’s proper perspective is to compare apples with oranges? Thanks for the tip.
They are station graphs off raw data plotted you pair of AGW trolls
It s a debate in science. It’s not sociology or bullshit. It’s science
What happened in 1965, when curves began diverging?
Steveta_uk was definitely being ironic, funny and clever too.
Dr Long’s article in American Thinker is well written.
Again, where oh where is the MSM in the UK.
The Y axis should surely read “temperature anomaly” and not just “temperature”? And we should know what the baseline is.
However – a stunning piece of analysis. You made the case.
Carrick (00:20:36) :
What matters from the perspective of AGW is the temperature trend since 1980. The fact that the adjusted rural data gives almost the same value as the urban is surprising. I think this may be another way of stating, as I have sometimes seen, that the UHI correction overcorrects for urbanization.
What really matters, if this research is confirmed, is that it confirms that the entire edifice of the AGW movement is a sham and that the community of climate change researchers is corrupt! I had taken Dr. Curry’s post as a sign of hope. After reading what Carrick has to say, I see no hope. This will run it’s course with the AGW movement continuing to destroy its remaining credibility. I hope the movement does not destroy the credibility of all science and return us all to the dark ages.
Retract or let Pamela Gray whip me
I chose both.
Please someone answer this simple question, why compare urban with rural, why not just use rural which for he most part are pristine.
“Vicky Pope, Head of Climate Change Advice, at the Met Office, said the new global temperature analyses would not change the trend of global warming.”
I’ve got to give her that, she’s right. Their team is measuring temperature, temperature anomolies and caculating a trend. It can’t change the trend of global warming – it will remain what it is entirely independently of whether it is measured by the Met Office. Perhaps she means that it won’t change the calculated trend of global warming which isn’t the same thing at all. You might say that it is a little premature for her to make that forecast, but we know that the Met Office is well-known for the quality of its long term forecasts.
Given that Steveta ends with an obvious ! it’s seems astonishing that anyone would fail to get the satire. Are we Americans just thicker? Hard to say. But
my experience with blogs indicates that satire is quite often taken seriously. Perhaps we just have to many commenters who still live in their mums’ basements?
Re: Steveta_uk comment…
I took steveta’s comment to be sarcasm, but you never know nowadays! 😉
But deep down he has a point. A lot of our concerns are anthropocentric. You should loook at the psychrometric envelope and see how the relationship between temperature, relative humidity and air velocity all make us comfortable or not. Adjusting one will compensate for the others being extreme.
The temperature on a tropical beach is the same as the jungle but the beach has less moisture in the air and more air speed so on the beach we are ‘in the envelope’.
Measuring air temperature alone might be the wrong metric for AGW?? Just a thought.
cheers David
If a handful of trees on the Yamal peninsula were considered sufficient to calculate global temperature trends, I can’t see the argument against using 50 odd sites for just the continental US.
and now we have a hockey stick too!
In Dallas the temperature is taken at the DFW airport which was a cow pasture in 1977.
A small city of 30,000 has grown up along with runways and buildings etc so that even with excellent surface station placement the UHI effect is undeniable.
I compared it to a site 15 miles away with no change in population density and there was no warming in later years.
I live in a suburb of Dallas and DFW is usually 3 to 4 degrees warmer than my back yard.
As far as the “social” temperature” I actually had someone make the argument to me, my jaw dropped and I was almost speechless. Then I laughed.
AleaJactaEst (03:31:54) :
Robinson (02:03:16) :
Robinson – the BBC new website also carried this news but, amazingly did not spin it with any reference to AGW.
What they did day however, was the fact that the cooling effect of the ‘berg, blocking super-cold bottom water flow and hence heat conveyor belt sea currents may cause several harsh winters ahead of us. This primes the current cooling argument to be parried by the “global warming caused the calving and now the world is cooling”
Heads we win, Tails you lose.
The BBC story did talk about the conveyor belt and may cause winters earlier today, however, they have now changed the story, which no longer mentions cold winters, but does talk about the iceberg causing food shortages for pengiuns, which will have to travel much further for food.
Interesting results: is exposure of the “adjustments” at last the start of sanity?
Its never been clear to me why ” global warming” has to be demonstrated by analysing thousands of places. Or why measuring stations which changed position or context (e.g. through urbanisation) are included in any analyses, as the information is obviously confounded, and misleading. “Correction” of such data does not help, as it is not creating observed data, but irrelevant garbage determined by its creator.
Has anyone analysed only the raw data of “non-changing stations”? (Without cherry picking) . Whats the result?
Congratulations on this post, Anthony
Me I aint no boofhead Boffin.
I would separate rural stations even further out from town stations.
I would start from white water out. I would take my pure white water stations as base line.
But I aint a boffin. I would say this is land temp nat. I would say this is my baseline.
I would say this is ambient temp and then I would measure out. In sampling of this nature mathematically, your base line must be one of two things, normal or abnormal you dont get to pick mathematically or statistically arbitrary points.
Your base line for measurement must be pure.
In a question of ambient temperature, your baseline must be ambient temperature. Mathematically and Logically you have no choice.
I’ll bet if you changed that rural, raw data to a 13mo, instead of a 13yr it would match the Satellite data for the U.S. pretty well.
Oh, I get it. Steveta_uk is calling us all physicists.
How does one get the source code of the NCDC software to open in Windows?
I want to see how they are inventing this data (only in climate science is this tolerated) , as well as how they actually “adjust” the numbers.
David (02:37:32) :
I think there is a real problem with his methodology that needs to be overcome. Given the disparity in size between the states (Texas is 174 times the size of Rhode Island) there must be a better way to represent the whole US than to select one rural and one urban station per state.
No matter where rural, urban pairs are compared with each other the outcome is invariably the same, little or no warming trend at rural sites, it might be 10 degrees warmer in one place than it is in another but the trend is the same.
This research better be solid – the AGW machine is wounded but not dead, and they will be coming after it.
Just a quick note. Still analyzing Canadian station data, but I have found something interesting.
2 Arctic stations show an increase in the summer temps as well as an increase in the winter temps. The Arctic is warming over all and the range is also narrowing. Now before the Warmists jump up and down with joy, the max temps are all below 25C. While the drop in summer temps seen in the lower lattitude are all above 30C. Why is this important?
Because in the summer months the Arctic can never be hotter than the lower lattitudes. Thus the Arctic trend and the lower lattitude trends are converging to a single temp. It’s 27C by 2016 when the two meet.
This begs the question, then what?
MODS! TYPO in 3rd paragraph of article, 3rd line:
DavidM — someone has to prove to me that there is a “global” temperature gradient, first. Then we can discuss trends, sample density, and finally speculate on cause and effect relationships.
Apologies if this question has already been answered by regular commenters, or is plain dumb: Has the UHI effect been assumed to be stable, or has it been measured to be more pronounced in winter months / colder areas? Could it be reasonable to expect that an urban increase in heat output from buildings in winter could outweigh the contribution from air conditioning units / warm tarmac etc. in summer months? If this is the case then in cooler weather, NCDC would have more temperature ‘headroom’ in urban areas as compared to rural to influence their adjustments (particularly if performed arbitrarily by software that might assume the UHI is stable), thus helping to iron out cooler temperatures in the adjusted data in cooler months and contribute to a warming bias in the data. Is there any validity in this? Just interested, thanks 🙂
OVERHEARD AT REALCLIMATE: “How on earth did this get published? M&M and Watts are behind this. Get Pachauri on the phone… He’s what?… when?… Oh crap, hold all my calls!”
I’m extremely surprised that something like this hasn’t been done before. This would seem to be an obvious step given the issue of the UHI effect. Or maybe I shouldn’t be surprised. Maybe it this investigation HAS been performed, but the results have been hidden inside “censored” directories that haven’t been discovered.
Seriously, though, no one has ever done this until now!?!?
I work near Philadelphia and live further away in a more rural area. My car has an air termperature guage and I always like comparing the temperature along my way home. My home is always 5-10F cooler than my work area, in all four seasons. In the summer with the windows down you can actually feel it getting cooler as you drive away from the city.
Another favorite pastime: My local hometown paper carries the diary of a local guy born in the 1840′. He wrote on this day in 1902 it was 52F and raining and he thought it wasn’t all that strange. Today it’s 25F and we are having a blizzard with high winds. For the past 5 years of comparing his diary with the current temperture I get the impression it was warmer back then. Someday I’m going to plot his temps versus the current temps to see the actual correlation.
This is not a smoking gun.Its the bullet itself.
And we realize the Curry-talk is a smokescreen.
Now the question is; The data flowchart…..
NCDC raw (no AGW) -> NCDC fudge (AGW) -> CRU ??
In that case ; Did CRU know?
It’s global weirding all right.
My thoughts on this study, for anyone who is interested:
http://strata-sphere.com/blog/index.php/archives/12882
Sorry, I think I have missed something.
Why is the rural data adjusted at all?
Wow. I have two hopes: there’s a group of scientists somewhere doing a full-tilt analysis like this on all the stations, and someone from Sen. James Inhofe’s staff is reading this blog to gather ammunition for his investigation.
Primary questions: what is the justification for ‘adjusting’ temperatures from rural stations upward? What phenomena is causing those stations to read a COOLER temperature than reality? Virtually everything Man does results in artifically warmer temperatures including deforestation, land development, and roads. Please list those things which would result in an artificial cooling temperature, keeping in mind that some things such as site relocation and equipment changes could cause cooling OR warming artifacts so those things should come close to averaging out.
This is remarkable IF it is true. Guys like Gavin Schmidt at Realclimate will be highly skeptical, not least because SPPI is hardly non-partisan, and because the use of one pair of sites per state gives a big skew in data density towards all those little states on the east coast of the USA. Also, how adjacent are the rural/urban “pairs”? Finally the explanation accompanying the graphics on Page 13 is obscure, to say the least – I know what he means, but I’m pretty sure he says the exact opposite.
This work urgently needs to be checked and replicated -“climate skeptic audited” if you like. Because if it’s true it will be evidence of outright fraud.
Grumbler (05:26:58) :
Re: Steveta_uk comment…
I took steveta’s comment to be sarcasm, but you never know nowadays! 😉
—————-
I thought the last line was a giveaway myself, but included it just in case any of our colonial friends didn’t get the joke. Apparently, some still didn’t. So it goes…
surely even the UN realises it needs to put some of its vast resources into a rebuttal of this and Anthony’s paper. The silence is deafening. I suppose that if they concede any of this a chain reaction starts, with assumptions on peer-reviewed literature being discredited. Is there any way of identifying all of the papers that would be discredited? Is there any precedent for this? It could be quite amusing to have a web page with all of the AGW papers on one side and the same rebuttal on another.
Mr. Watts…. it looks like Tamino is challenging you to a throw down.
http://tamino.wordpress.com/2010/02/26/thanks/#respond
BBk said: “The trick is that their “correction” isn’t reducing the UHI.. it’s applying the UHI EVERYWHERE! Look at the absolute temp of the recent data of the adjusted graphs.
I think you are correct with this. Halfway down the NCDC/NOAA details of the adjustments it says this:
Application of the Station History Adjustment Procedure (yellow line) resulted in an average increase in US temperatures, especially from 1950 to 1980. During this time, many sites were relocated from city locations to airports and from roof tops to grassy areas. This often resulted in cooler readings than were observed at the previous sites. When adjustments were applied to correct for these artificial changes, average US temperature anomalies were cooler in the first half of the 20th century and effectively warmed throughout the later half.
http://www.ncdc.noaa.gov/oa/climate/research/ushcn/ushcn.html
Urban stations are moved to ‘rural’ areas and the temperatures go down. If I have understood this passage correctly those cooler temperatures are adjusted upwards to maintain the continuity of the station record. This exports UHI to ‘rurals’ sites. There is then nothing to prevent exported UHI from infecting the entire set through the homogenization process.
I cannot also see why earlier temps should be adjusted downwards and more recent ones adjusted upwards. Unless… They know an urban station is running hot. They know a station removed from a UHI bubble will run cooler than before. A bit of cognative dissonance and you could justify the pre-move adjustments downwards (as it was running too hot) and the post-move adjustments upwards (as it is now running cool). Logically they should only do the former.
A general question regarding satellite data. How can we discern between actual temperature changes and simply getting more coverage and more accurate at recording? Before satellites we relied on surface stations, sea surface records and weather balloons. Accuracy has been improving since the 1850s and so too has coverage.
Could the general hump in temps in the middle of the 20th century be a result of more complete coverage than ever before, or since (until satellites) due to WWII activities putting people and equipment in more places to make more observations? ie it wasn’t actually appreciably warmer but our observations were better and more numerous.
It bothers me that the urban/rural alignment is so close pre-1960. Yes, I can imagine the trend separation accelerating over the entire period as urbanisation increased, but there were quite a few sizeable cities (certainly from a UHI perspective) in this country prior to 1960 that I’d expect to see *some* separation –what’s shown here is practically overlaying each other.
Peter Dunford,
I’m of the mindset that UHI should not be corrected for – cities are hotter than countryside, no reason not to show them as little red dots on the maps. I just wish we were in a scientific climate where that could be done without someone saying “ZOMG look that’s CO2!!!1!!ELEVEN!!”
John Holland,
I’m pretty sure I’ve corrected you on this more than once without acknowledgement – Dr. Spencer was not testing UHI, the accuracy of the “adjusted” record, etc – he was *only* testing station drop out. You are reading more into it than what was said.
And for those who are worried about cherry picking or holding up to RC or Tamino’s standard, the guy who posted “witness for the prosecution” earlier had it right. If support for the Endangerment challenge is the aim, there is no need to “disprove AGW”. Demonstrating to a judge or jury that the IPCC link to CO2 (which is the basis of the EPA Endangerment) was unreliable from a burden of evidence standpoint – which by itself this is probably adequate to do – could get the EPA finding thrown out.
Think about the sampling method used in the GHCN v2_mean database. Of the 130-odd stations for the U.S., 92% are airports. In other words, the U.S. sample is urban. This is an undisputed fact. However, only a very small percentage of land in the U.S. is actually urban. (If anyone can find an estimate of the percentage, please post it.) This is yet another undisputed fact.
The scientists who created the GHCN made the decision to over-sample the urban areas and to under-sample the rural areas in the U.S. This decision was most certainly not accidental. And it was not due to lack of data from rural stations.
It appears that the major divergence started in the early to mid 60’s. Why is that time frame significant? That is a major clue to what’s going on. If you can isolate that to just urban growth, station moves or other changes we’ve got it nailed. I’m thinking airports (jet age) and station moves.
Once you’ve nailed the reason for the divergence you can then see how valid the “adjustments” really are.
This looks like a code glitch in the string used to adjust Urban to Rural to control for UHI. We all know that the code is a tangled mess. But with the above graphs, someone like our EMSmith could hunt down the code string by searching for certain parameters that would be limited to the years the discrepancy occurs in the graphs. Is the entire code available and is it in searchable format?
By the way, an interesting piece of trivia, anyone ever see the code for Windows? That is the mother of all tangled messes.
Senator Boxer and the EPA’s Lisa Jackson this week said they did not rely on the IPCC for the endangerment finding about CO2, but instead looked to the US.
Where can they look, now?
The raw rural data shows no drift in temperature over the whole period. Sure, you can put a line through all of those points and it will have a slight positive gradient, but that depends on where you put the endpoints of the line.
The data has an undulation, the amplitude and duration of that undulation is perhaps an interesting feature in that data. But to measure a “linear drift” in the temperature you will need to measure for several cycles of the undulation. I.e. the dataset needs to be at least 3 to 4 times as long before you can start talking about a trend – especially one as small as 0.13C/century.
I any case, what is all the fuss about? I mean, are you kidding? 0.13C/Century. Is that a joke? Am I supposed to be worried about 0.13C/Century? When I look at the temperature record, that is not significant.
Even if there was a 0.79C/century increase, the system is an equilibrium system – it will not continue to go in the same direction because other processes will provide an opposite and balancing force. Why can’t people understand this simple facet of well designed non linear systems?
I am surprised that they have not forced us to shift to mC so that they can say “130 mC’s”, becuase 130 is a bigger number than 0.13 and sounds much more siugnificant.
kzb (04:58:59) :
Is the terrestrial record now of any relevance to the issue? We now have satellite data.
There is clearly a lot of doubt about terrestrial measurements, and you have got to wonder why they are given any weight by either camp in the satellite age.
Having said that, I am a little concerned that no-one seems to seriously question the satellite data. I personally found the “warmest January in the northern hemisphere on record” measurement outrageous. I am sure there must be a “mistake” somewhere.
————————
I’ve been wondering what exactly is the basis for claiming that this past November and January were the warmest ever. Judging from comments by Australians at WUWT, this summer has not been anything exceptional. I have not heard anything about Africa or S. America (nor could I find any reports of exceptional weather in several minutes of doing a search online), but did see reports about abnormally cold weather in northern India in December, which carried on into mid-January. China and N.E. Asia have been in a deep-freeze, as has Northern Europe. The US has been experiencing an unusually cold winter, but Eastern Canada has been around or slightly above average with lower than normal snowfall. Is this claim based on SSTs and satellite data, or is there also some excessive warmth documented at a sufficient number of surface stations that would justify listing the past two months as the hottest on record? Can the satellite data be trusted?
Roger Pielke, Sr has documented the warming bias in the NCDC records, and how NCDC director Tom Karl has actively surpressed that information.
http://wattsupwiththat.com/2009/08/13/pielke-sr-on-warm-bias-in-the-surface-temperature-trend/
This is the same Tom Karl selected by Obama to head a new climate organization. When will the MSM ever report the deviousness and deception?
This, if confirmed, is going to have major implications, not only for AGW crowd, but for some people on “our side” as well, for example Spencer and Christy. Their satellite record show the warming of 0.22 degrees C per decade since 1979 for the USA 48. If this paper is correct, the rural stations in the USA 48 would have at least 3 times lower warming rate than that of UAH! What confidence we can have in the UAH data set after that? I suppose that rural trend is as close as possible to the real climatic trend. It is somewhat ironic and very worrisome in the same time, that UAH satellite data, allegedly free of any non-climatic bias, are much, much closer to the USA urban and rural-adjusted data, than to the real, unadjusted rural record!
Even with extra stations being used in the north-eastern part of the United States, this is an interesting study. I think that possibly even the rural stations in the north east show some UHI, just because population density is higher. (just a guess of course)
Here, researchers, your daily portion of freshly adjusted data, go write your papers. What do you want? Unadjusted data? Do you even know how complicated it was to get it adjusted right? We are doing this for you. How do you think would you detect an anthropogenic signal in that noisy trendless mess of unadjusted time series? So, now shut up and analyze the fine data, we have hidden a correlation in there and the first one of you who finds it and gets it peer-reviewed gets an extra grant.
My questions are these:
1. Are the effects seen in this paper the results of homogenization?
2. Do we know the algorithm used by the NCDC to produce the adjusted data?
3. The NCDC makes the assumption that stations at similar latitude bands have the same climate, is this confirmed across their grids?
It appears that homogenization within the grid was used by the NCDC as a method to produce an average. While this may be appropriate in some instances, any method of averaging must be performed with the utmost care. While urban areas may represent a significant number of stations, their weight as far as surface area represented within the grid should be proportionally small. If this is not corrected for in the NCDC correction algorithm it will result in the effects seen here.
If we do not know what methods are used at the NCDC how can we even evaluate their efficacy? The graphs presented show that there are issues with this system that need to be explained. To adjust data in this way is fraught with hazards, and should only be done to correct known offsets from an individual measuring device. This appears to be a very wide paintbrush saying that it is warmer at this station just because it is hot downtown at the airport. This is contrary to experience and measurements.
So according to the NCDC a station to the west of Chicago will have the same temperature as one buried in the middle of downtown? Or from a station on the other side of Lake Michigan? This seems highly improbable. These assumptions are part of the issue here, and the NCDC should have to prove that they are correct. However, personal experience and measurements know that this is not true.
In summary, this paper calls into question the methodology of the NCDC averaging method. Given the ability of computers today to manipulate data why are we using such coarse grids? Why are not looking at the area represented by each station as part of a sample of the grid? To give a station embedded in a city with less than 1% of the represented grid area characteristics the same weight at a rural station that represents the other 99% (an approximate analogy) would obviously skew the results. Also the unsupported assumptions made further add to the poor results of this product.
This is just a first start in the path of true science of replication of results, that I was taught many years ago. Hopefully the NCDC will respond appropriately and perform some self assessment of the methods used.
JonesII (05:06:33) :
What happened in 1965, when curves began diverging?
————————-
Much larger cities with growing population increasing the heat-island effect as one approaches the centre. Widespread introduction of air-conditioning to commercial and domestic applications. I experienced pre-air-conditioned life in Philadelphia as a child: life changed considerably as air-conditioning became wide-spread and those a/c units do emit a lot of heat. Also, the rise of 2-car families in the 1970s, and the subsequent increase in the number of automobiles more recently. Larger cities mean longer commutes – cars do emit heat. The use of more electronic technology, including microwaves and computers, which were absent in the 1960s. All of these would contribute to warming.
I think most of you are missing the point here. Who cares if the rural was adjusted up and the urban left to follow UHI?
Remember, it is the “anomoly” that matters to this GW argument. So, as has been seen for the past 12 years or so, the vaunted “anomoly” has flattened out.
Why? Because all the crappy temp stations that are by runways or air conditioning units, etc. have now come to stasis within their enviroment!
The GW crowd can keep on saying that the last decade was the warmist all they want, cause for the next decade, the temperature “anomoly” is going to be flat, then the next, then the next……, the graphs for the next thousand years will go back to being a hockey stick handle. 🙂
They have skewered themselves upon their own corrections!
I don’t know about you, but all I see is the beauty of this irony!
Mooloo (01:17:01) :
As for stations selected, they seemed to have picked 48 and one from each state. I would have expected something like one in each of the 5×5 grids that was mapped out. 5×5 grids of course are poor representations of geography and climate zones.
So your “correction” for allegedly poor methodology is … wait for it … a methodology you acknowledge to be poor.
The 5×5 grids are a meaningless abstraction. They should be ignored IMO.
There is only one answer to this paper. To show that urban stations and rural stations do not differ in the manner shown. I doubt they can actually do that, even with cherry picking.
If the AGW crowd cannot show that rural stations do not show warming correlating to CO2, then the allegation that the USA is warming due to CO2 is going to be hard to maintain. By “hard” I mean, of course, near impossible.
>>>>>
The one per state sampling is idiotic methodology – like temperatures have anything to do with political entities and imaginary lines drawn in the sand. At least, with 5×5 grids, there is near uniform coverage of area. It’s an abstraction and a somewhat bad one, but it’s not meaningless in trying to compute average temperate.
When doing science, it is not what your opposing intellectual team can show, but the robustness of the science of your own side. Everyone gets held to a high scientific standard, right? The AGW crowd has some of the shoddiest methodology in science, but stooping below their level makes it hard to mount a credible critique and replace their unfounded conclusions with yours.
Small sample size, 48, is also a problem in the paper, but the results are a bit too strong to be coincidental. One thing that might be explored is the difference between the urbanization of the early 20th century and the urbanization of the late 20th century. There’s a remarkable difference in UHI which suggests that something special about the late 20th century that created a large UHI.
I am shocked at how many have failed to realize that Steveta_uk’s comment was sarcasm.
Get a sense of humor, people.
I could never understand how UHI was minimized. If you look at New York City as an example.
Area, including water 468.9 sq mi ( 2,590,000 sq m)
Power used (2008) 54,869 GW-hr (http://www.nyc.gov/html/planyc2030/downloads/pdf/progress_2008_energy.pdf)
Watts/sq m = 2,416 total. The Mayor says 80 percent is used by buildings and therefore 100 percent ends up as heat loss.
So the forcing is 1,933 W/Sq M
The file also remarks that the city has seen a 23 percent increase in the last 10 years, which is close to the increase showing up in the charts.
I understand that many in the AGW community have rejected UHI as having an effect. Is there any reasoning behind why this could not be? The physics behind it would seem to make sense; more buildings, concrete, people = increase in heat. What is the AGW reasoning why this mechanism would not work? That, to me, would be a very interesting scientific explanation.
Remember its an anomoly chart, taken from different means. The author had to choose a reference year for zero. he seems to have chosen 1960. That would answer a few “where was UHI before 1960” questions.
I had my hopes up on this paper, but took a quick look at a couple of example stations. I can’t say the entire paper is suspect based on this small sampling, but when I find two without trying it leads me to question it. I looked at Beatrice NE and Bedford MA because I’m at least a bit familiar with both areas.
Beatrice 1N, Nebraska is classified as “urban”. However, Beatrice is a isolated town (not part of a larger urban area) of about 12,000 and the station is sited at or very near the airport a half mile from the north edge of town. This is a typical small-town airport with no commercial service – from airnav.com, <30 flights per day, ~25 of them general aviation (think Cessna). If there was any UHI effect on the record, I think it would be very weak. If it's anything, it's a rural station.
Bedford, MA is classified as "rural" and while it is in a more lightly developed area near a park and the relatively open areas north of Hanscom AFB, I would classify it more closely as "urban", or remove it from the candidate list as not being clearly either one. This area has a lot of trees, but a lot of houses and asphalt too. It made the criteria probably because the surrounding towns (Lexington, Bedford, etc) are indeed small but they abut one another in typical New England suburbia.
New Bedford, MA is solidly urban, so I guess you could say one is more urban than the other. The question here is whether (not New) Bedford is rural enough.
I think the author was honestly making an attempt to objectively come up with a list of "rural" vs "urban", but I don't think his classification criteria was good enough. A few hours of recon by Google Maps would be necessary to verify the classification of the other stations.
It'd be interesting to see a similar analysis on a better/broader/more r-word list of stations. Agree that the CRN rating might be a better classification criteria.
Why did it start in 1965? I remember the migration to the cities. The Great Society” benefits were available in cities, Suburbs built up near cities, not in rural areas. Small farms were left vacant and converted to pastureland. Many small communities dwindled away with the young people going to the cities.
Only an occasional small town actually grew in population. I think the “urban” curve mirrors that chabge.
Steve Goddard (04:46:49) :
If you read the paper, you can see that station selection of the rural sites was from an evenly spaced grid.
NCDC and USHCN have always made access to the raw data as minimally transparent as possible.
>>>>
This statement is not true. There’s a station list of all 48 rural and 48 urban temperature sites used for the analysis and it’s clearly one from each state instead of one from each grid. By that method, there’s 10 stations in one single grid in New England, and the large western states are under represented.
There IS a map showing station densities of NCDC in the grid, but that’s part of NCDC’s methodology – not of Long’s.
Steveta_uk (00:38:35) :
I also noticed if you turn the graph upside down it appears to be leveling. This might explain the divergence in the Southern Hemisphere.
It may be already written previously,
but may we say?
NCDC-Gate?
Just as we thought: raw rural data shows no increase since 1940. Urban shows a one degree rise, presumably due to heat island effects, siting issues etc.
Key question: what percentage of the earth is urban right now? Shouldn’t the warming formula on land be:
x*urban warming + (1-x)*rural warming where x is the % of urban land mass.
Am I being naif here??
MB (06:58:14) :
The raw rural data shows no drift in temperature over the whole period. Sure, you can put a line through all of those points and it will have a slight positive gradient, but that depends on where you put the endpoints of the line.
The data has an undulation, the amplitude and duration of that undulation is perhaps an interesting feature in that data. But to measure a “linear drift” in the temperature you will need to measure for several cycles of the undulation. I.e. the dataset needs to be at least 3 to 4 times as long before you can start talking about a trend – especially one as small as 0.13C/century.
I any case, what is all the fuss about? I mean, are you kidding? 0.13C/Century. Is that a joke? Am I supposed to be worried about 0.13C/Century? When I look at the temperature record, that is not significant.
>>>>>
It is said that the US isn’t experiencing much warming, but the rest of the world is. Not that you should believe them on that claim. The 0.13 C trend in the US isn’t the thrust of the paper since it cannot be applied globally, but it is interesting in seeing how UHI is being handled.
Also the only reason for removing UHI is to eliminate human land use and heat pollution effects so scientists can blame carbon dioxide as the cause. If we’re just talking about how humans can change the climate then UHI should not be eliminated as it captures the effects of human infrastructure. The scientists will have to model the temperature gradients surrounding a city and really know what UHI is all about instead of their current feigned ignorance.
John Hooper (01:15:12) :
Sounds very convincing, but what about Roy Spencer’s recent satellite analysis?
http://wattsupwiththat.com/2010/02/20/spencer-developing-a-new-satellite-based-surface-temperature-set/
Kind of nullifies everything doesn’t it?
Lastly satellites are making daily life unbearable for all “settled” De la belle epoque scientists. There are only three solutions left:
One: To destroy all those inconvenient satellites at once.
Two: To surrender to facts.
Three:To keep on repeating the mantra how “surprising and unexplainable” is reality for their “flintstones’ universe” model.
@bushy (02:47:50) :
re. Hee HAw, Catlin expedition 2010 soon underway.
——————
I told it already to my father,
“Daddy, food supply on it’s way.”
Best Regards
Ice Bear Junior
Ah! Ha! Mann made warming found! and it’s worse then we thought. CO2 has been found NOT to be the cause! Only computers could be the cause of this warming, as nothing else could be the cause of this. The warming follows the progression and density of computer use. ;?)
Interesting that the upslope of the urban wrt the rural stations starts around 1965, rather than post-war. Studying potential explanations for that might prove interesting.
Jason Lewis (06:05:32) :
Yes it has been done & reported before on here.
I fail to see why this is more revealing than this graph, known for years, and obviously ludicrous when the only adjustment should be down to compensate for UHI.
http://i42.tinypic.com/2luqma8.jpg
Exactly why the raw data is not used. There is absolutely no significant temperature change over the indicated period. All within the norm.
Richard Lawson (00:46:42) :
Not so much a smoking gun but an exhaust trail left by an ICBM!
***********************************************
Yes, that would be the International Climate Bullcrap Machine.
I suppose it is way late to make mention of this but Robinson @ 2:03:16 links to a part of the Arctic shelf broke off which is a report about Antarctica. I don’t see that anyone corrected this – most readers here will mentally substitute one for the other as the size, shape, and context indicate. But words matter and when the wrong one is used it frequently molders, muddles, muddies, scrambles, confounds, or confuses the meaning.
It seems Dr. Spencer used more and different “thermometers” but similar methodologies. So it should not be surprising that his results are similar to CRU’s.
“Similar to the Jones methodology, I then averaged all station month anomalies in 5 deg. grid squares, and then area-weighted those grids having good data over the Northern Hemisphere. I also recomputed the Jones NH anomalies for the same base period for a more apples-to-apples comparison.”
…
“Of course, an increasing urban heat island effect could still be contaminating both datasets, resulting in a spurious warming trend. Also, when I include years before 1986 in the analysis, the warming trends might start to diverge.”
Re: John Hooper,
Spencer’s analysis is from 1989-present.
The divergence between rural and urban in the graph here starts around 1965 (well, the 11-year average does), and it already quite substantial by 1989. Eye-balling the chart above, it looks like rural and urban change by about the same amount from 1989-present, too.
So Spencer’s analysis doesn’t “nullify” much of anything. It may “nullify” 1989-present, but so does that above chart.
Spencer’s analysis could be used to claim that the drop-off in station numbers around 1990 has no substantial difference, but this analysis suggests a strong warming bias was introduced to the surface record in the 60s in the urban stations and that adjusting rural stations by this benchmark further skews the issue.
All urban weather stations (i.e. towns with pop > 15,000) should be removed from the raw average temperature data sets. Remember, these are local weather stations, that were never intended to be used for estimating world climate. By employing stations located in “hot spots”, we are not measuring climate change at all. Future climate monitoring should be based on satelite measurements of atmospheric heat levels directly – after all, we actually want to know: “is it getting hotter!
Steveta_uk (00:38:35) :
The primary fact to remember is that “global warming” is a social phenomenon…
Interesting point. The real point of recognizing UHI is the fact that even though humankind is capable of changing the climate, CO2 is not the primary driver of climate change.
As noted by Dr Pielke many times, land use has a tremendous effect on the warming of the globe, and we have to isolate the urban heat islands to analyze what is really going on. If the NCDC has been diddling the data and hiding the real effects of mankind’s huddling masses in urban areas, it is scientific (and social) fraud.
Your social consequences probably revolve around the huge collectives of humans living in restricted spaces.
Geo, I also was interested in the way the urban-rural split started after the 1960’s. To me it suggests that the warmer urban temperatures may be due mostly to air conditioning, which started to become widespread about then. As we all know, air conditioners work by taking heat from inside buildings and transferring it outside — plus all that waste heat from the extra electricity being used. If you look at an old and classic film like rear-window, set I believe in the 1950’s, notice how everyone keeps their windows wide open because no one has air-conditioning. People who grew up in the 1950’s remember going to department stores or movie theaters just to enjoy their air conditioning during hot days. By the 1960’s most people had home air conditioning and air-conditioned cars, so it was no longer a draw.
rc (04:14:19) :
If the first graph correctly shows the UHI effects in urban vs rural stations, why does it begin in around 1965?
Just puzzled why it wasn’t showing up earlier or why it happens all at once.
How old are you? I’m old enough that 1965 is about the time I graduated from high school (1964 to be exact). I grew up on the west coast, but every other year my folks would take the family back “home” to Arkansas, usually during the summer time, for a couple of weeks. We’d visit grandparents, aunts and uncles, and other relatives. Even as late as the mid 1960’s, I do not recall any of them even having window air conditioners, let alone whole house central air and heat. I remember some “swamp coolers,” and sleeping with windows open at night. All of that began to change in the 1970’s. New homes were being built with central air and heat. Older homes began to have window air conditioners, and so forth.
I doubt that the experience in Arkansas was much different than in many other places. In growing up on the west coast (California until 1964, when I graduated from high school, and then 10 more years in Oregon, before migrating back to Arkansas), I never lived in a home that had air conditioning. While I’ve not been back to the west coast, except to visit a few times, I cannot imagine any new homes not being “climate controlled” these days.
And then there is the rise of office towers in the cities. In the 1960’s, few metro areas had all the tall office towers we see today. When I went to school at Oregon’s Portland State College in the mid-1960’s, I don’t recall any really tall towers, maybe no buildings in town with more than 12 stories. As in:
http://en.wikipedia.org/wiki/Wells_Fargo_Building
Most of the skyline you see today:
http://upload.wikimedia.org/wikipedia/commons/thumb/0/08/Portland_Night_panorama.jpg/1000px-Portland_Night_panorama.jpg
was built after 1970.
And that was probably the case in many metro areas throughout the country. When I came to Little Rock in the mid 1970’s, the only “tall building” was the Worthen Bank building, built in 1968. All the taller buildings that now mark the city’s skyline were built after 1970.
This has been repeated over and over throughout all of the mid-sized metropolises of the US. The modern skylines of those cities date from the 1960’s on. Couple that with the change in home (and apartment) construction to central air (and heat), and it is not surprising at all that we’d see this kind of divergence beginning in the mid 1960’s.
DavidM (05:36:12) :
As David points out, I’ve never quite understood why you’d want to sample thousands of sites to show a warming a trend. A notable change in temperature will have to show in single sites when applying appropriate smoothing when analysing a 100 year record. To get a global trend it definitely has to exist in the individual sites contributing to it. If you take a handful in a certain region to rule out local effects I would hope the long term trends would match quite well between nearby sites. One of the clearest indicators for ‘unprecedented’ warming to me would be a site unchanged over a long period of time that showed a notable trend over 100-150 years. From my cursory looks I don’t really anything of significance over the notable 1930’s/40’s peak. More smaller studies such as this, you need to define your sample set well, and others like the surface stations project provide a good summary of historical temperature trends.
This, if confirmed, is going to have major implications, not only for AGW crowd, but for some people on “our side” as well, for example Spencer and Christy. Their satellite record show the warming of 0.22 degrees C per decade since 1979 for the USA 48. If this paper is correct, the rural stations in the USA 48 would have at least 3 times lower warming rate than that of UAH! What confidence we can have in the UAH data set after that? I suppose that rural trend is as close as possible to the real climatic trend. It is somewhat ironic and very worrisome in the same time, that UAH satellite data, allegedly free of any non-climatic bias, are much, much closer to the USA urban and rural-adjusted data, than to the real, unadjusted rural record!
So, as a country’s urban centers increase so does UHIE. I wounder what the first graph would like like for different countries around the world, because not every country has grown at the same rate.
One more issue to think about. Apart from ground stations and the like…what about the scientists in charge?, it seems that nothing changes. Are there not honest scientists any more? …All this is just crazy: Biased ground stations, adjusted records, satellites adjusted to adjusted and biased ground stations…a feedback of lies everywhere. It seems that the best you can do now it’s just go outside suck your finger in your mouth and raise it above your head to feel how the weather is…LOL
Several people here have called attention to the recent satellite-based temperature data. Going from the data produced by the satellite radiation sensors to an estimate of the earth’s atmosphere and surface temperatures is an “ill-posed” mathematical problem. This means that small random errors in the satellite sensor measurements — and these sorts of errors are always present, they can’t be avoided — lead to big, odd-looking, and obviously wrong temperature estimates unless the computer program estimating these temperatures makes some assumptions about what the satellite sensors are really looking at. These assumptions could be that the actual temperatures are not too far from the climate average expected for the place on the earth and the time of year where the satellite is taking data, or that temperatures close together in the atmosphere or at the surface cannot be different by more than a certain amount, and so on. Then, always insisting that these assumptions are satisfied, the computer programs attempt to find the temperatures that do the best job of matching the radiation measurements. Change those assumptions and the programs will produce different temperatures for the same radiation data coming down from the satellite. People who run these large and complicated programs do not like doing this, because it’s all too easy to introduce bugs that result in no temperature estimates at all being produced, but I would not be surprised to find that under the right sort of outside “encouragement” the programmer would be told to make the effort. All the data coming from the satellite systems is highly digitized, making it easy to produce cool graphics and so on, but given the ill-posed nature of the mathematical problem they are solving I would be wary of treating that temperature data as gospel. What skeptics should really be looking at is the raw radiation sensor data coming from the satellites.
This has been done before. Well, in a smaller scale;
The conclusion makes sense to me, however, I’d like to see this get into a peer reviewed journal, so it is taken more seriously.
NASA GISS, 1934 warmest year!
A new leaderboard at the US Open
http://climateaudit.org/2007/08/08/a-new-leaderboard-at-the-us-open/
As others have noted, the underlying truth of the Dr. Long’s article are not news to readers here. That doesn’t detract from its value though as the timing of the article is as or more important than its content.
The weaknesses of the paper are the lack of random sampling and that it has been published outside of the peer review literature. While these are not fatal flaws, they will be used by the AGW movement to try and dismiss the paper.
We still have not seen “Dr.” Anthony’s paper, which I assume is still being held up by the establishment “peer” reviewers at the journal where it was submitted. I was hoping to see that paper before either the EPA “finding” or Nopenhagen, but that is the nature of system as it exists. It does seem a little long though.
“why does it begin in around 1965?”
In 1965, cities such as San Jose, Sunnyvale, Santa Clara, Cupertino, Campbell, and Los Gatos in California were mostly orchards. There were orchards on both sides of Stevens Creek Blvd. where there are now car dealerships. Much of Anaheim was berry fields. Most of Riverside was orange groves, even in the city limits. In the late 1970’s you could drive between Santa Clara and Sunnyvale and tell when you left one town and entered the other. There was fields in between and Great America amusement park was in the middle of nothing. It is now in the middle of an urban area. I don’t think people appreciate the amount of growth that happened after 1965.
1965 was when the boomers started entering the housing market. There was literally a housing explosion starting at about that time.
Basil, I graduated from high school in Florida in the early 1970’s and remember that we got our first window air conditioner in the mid 1960’s — but then it gets awfully hot in Florida without an air conditioner.
Adding to what Basil (08:25:55) said, don’t forget that as well as all the heat generated by power sinks such as ACUs and heaters, the additional power has to be generated. Since power generation is not very efficient, then for every watt consumed there is likely to be a watt or two of waste heat produced at the generating station, and by the distribution grid.
>>rc (04:14:19) :
>>If the first graph correctly shows the UHI effects in urban
>>vs rural stations, why does it begin in around 1965?
Central heating, air conditioning, office blocks, bigger cities, more densely populated, cars, electronics, computers. Our use of all types of energy in cities has rocketed since 1965.
We had coal fires in our London house until the mid ’60s. These were only lit in the evening and went out at night, and we only ever had one lit in the living room. We always had ice on the inside of windows on winter mornings. Compare that with todays energy usage.
.
Obviously the important point is the upward adjustment of rural stations, which should be independant of any cherry picking.
Steveta’s bit was the wittiest thing I have ever seen on this blog. Some of you guys are thicker than two short planks.
Sean Peake – ROFLMAO.
The population of the rural environment in the US is aging rapidly, as the kids move to the cities. Therefore, I suspect that rural areas are warming and have been since the advent of Viagra.
JonesII (05:06:33) :
What happened in 1965, when curves began diverging?
Ah-ha! The trees have been vindicated! Well, not completely yet, but follow the reasoning anyway.
The tree ring data (Briffa etc) started diverging in the 1960’s, resulting in using “Mike’s Nature trick” to “hide the decline” as mentioned in the emails. The trees, which are rural, showed no warming and perhaps cooling from the 1960’s onward, which did not agree with the temperature record.
But as shown here, the rural data was adjusted upwards to match the urban data.
So the trees were not matching the temperature data, because the trees were honestly reporting the rural temperature, thus they could not match the artificial warming trend shown in the mis-adjusted temperature data.
The divergence problem with the tree ring data is actually non-existent, because the premise is based on comparing it to the “bad” temperature data.
Someone with better skills and more access to the data than I should do a better comparison of tree ring divergence to temperature record adjustments to see how well things match up, but offhand it certainly looks like that is what has occurred, and further investigation is warranted.
I’m surprised at some the criticisms of this paper. A look at the hihgly correlated squiggles large and small in the two curves is as good a measue of the legitimacy of the station seletions as any. Indeed, it is a visual proof that the official manipulation of the data I illigitimate and unnecessary..
Anthony,
How would the graph you posted as an “update” explain the first graph, which is the one I think we’re discussing which shows the divergence that begins in the 1960’s. The first graph, if labeled correction, is a comparison of rural and urban raw data, without any adjustments. The “updated” graph is raw v. final, with no breakout between rural and urban. In effect, rather than explaining anything, I see the two as just different versions of the same thing. I.e., the reason the “update” takes off in the 1960’s is because of what is shown in the first graph: urban temps take off in the 1960’s, and the adjustments between raw and final in the second graph reflects the perverse nature of the adjustments (instead of “cooling” the urban centers, the rural stations are being “warmed”).
Both graphs beg the question: why? And I think the answer lies in demographic and life style changes that have taken place since the 1960’s. At least that’s a plausible hypothesis that deserves more serious consideration than it has been given in the peer/pal reviewed literature.
“Richard Wakefield (05:52:21) :
Thus the Arctic trend and the lower lattitude trends are converging to a single temp. It’s 27C by 2016 when the two meet.
This begs the question, then what?”
doesn’t matter – the world ends in 2012!
The use of one station per contiguous state seems kind of odd; it doesn’t seem to randomize the selection. Instead it means more stations from the eastern US, especially New England and the upper mid-Atlantic states. Delaware, New Jersey, Connecticut, Rhode Island, etc. One gets 13 states (the 13 original colonies, minus New Hampshire, plus Maine) on the Atlantic coast, versus only three states on the Pacific coast. Too bad the paper isn’t online, I wonder how Long addresses the issue.
I’ve been visually comparing Long’s graph of ll-year-average urban-vs.-rural raw data above with Jeff Id’s urban-versus-rural graphs of Global Historical Climatology Network data back on Jan. 5, 2010. He says that the urban data “temp rise since 1978 is about 1.2C.” Meanwhile “the Rural stations show about 0.7C of warming since 1978.” The difference between urban and rural gridded data from stations with at least 100 years of records shows a notable spike around 1965 or 1966. An upward trend in the urban-rurual difference looks to me like it becomes established during the following decades, especially after a 1981 dip. (Compare with the 1965 fork in Long’s graph of ll-year-average urban-vs.-rural raw data. If it weren’t averaged over 11 years, would it look still more like Jeff Id’s result? And the converse?)
This is a very interesting report and makes a lot of sense but I still believe in global warming. /sarc
Actually, this is great. Anyone know how we can get our hands on the data?
Hansen openly states that he believes UHI is a net negative effect. This may be due to him participating in too many icy cold global warming protests in major cities.
Am I reading that right? Was the UHI routine was used to warm the rural record?
How is that possible? I’m guessing there wasn’t a ton of de-urbanization going on….
Carrick (00:20:36) :
What matters from the perspective of AGW is the temperature trend since 1980. The fact that the adjusted rural data gives almost the same value as the urban is surprising. I think this may be another way of stating, as I have sometimes seen, that the UHI correction overcorrects for urbanization.
You are so silly. You know what homoginization does. It increases rural sites to match nearby urban sites to smooth things out. So presto, they are close.
My guess is that the divergence starting in 1965 was related to emissions controls beginning to be put in place in the USA. The amount of particulates in US urban areas in the 1950’s and 1960’s was unbelievable. I remember driving with my family down the Jersey Turnpike in the mid-1960’s and it was like visiting Mordor, the sun was actually blotted out by the smoke. Even nearby suburban areas were quite different: driving from 25 miles north of Boston into the city those days and you could taste the sulfur in the air once you reached the city. All of that has since been substantially cleaned up. The visible problem probably peaked in the USA about 1965 leading to adoption of countermeasures (the EPA was created in 1970, for example). Local urban particulates might have been suppressing insolation sufficient to mask UHI. I believe some of the climate models assuem this masking on a global level, but from personal experience, for what it’s worth, there was a *lot* of urban pollution in the 1960’s in the USA.
Along with all the other anecdotal evidence about how things began to change in the 1960, here’s another dimension to the story.
Up until the late 1960’s and early 1970’s electric utility engineers could project energy usage by plotting historical usage on semi-log paper. As electric utility rates began to rise in the 1970’s and 1980’s, the process became much more difficult. I remember doing electric utility load forecasting using economic and end-use demand models (I’m an economist) in that time frame, and arguing with utility engineers still trying to plot linear curves drawing lines through the data on semi-log paper with a straight edge ruler. It was comical, really, but the world was changing fast, and some of the old guard were slow to catch on.
Someone else above made the connection to the baby boom. The mid-1960’s were when the baby boomers began to come of age. From that point on, we’ve had 40 years of that generation adding to all the different life style changes that make the years prior to the mid-1960’s seem so bucolic.
I’m sure similar kinds of changes can be charted in countries all around the world. I lived in Taiwan in the early 1960’s. If I went back today, I wouldn’t recognize it. Japan is becoming, quite likely, one huge UHI, even in the literal sense of the word. And so on and so forth.
Bob (Sceptical Redcoat) (08:16:38) :
All urban weather stations (i.e. towns with pop > 15,000) should be removed from the raw average temperature data sets. Remember, these are local weather stations, that were never intended to be used for estimating world climate. By employing stations located in “hot spots”, we are not measuring climate change at all. Future climate monitoring should be based on satelite measurements of atmospheric heat levels directly – after all, we actually want to know: “is it getting hotter!
—————————
I agree with you, Bob: but will not satellites also ‘homogenize’ the UHI with the natural signal? How high up does the UHI extend? So if the satellites also detect warming, how will the sources of this warming be distinguished?
Peter Plail (09:06:54) :
Excellent point. I followed on with a description of my experience forecasting electric utility demand in the late 1970’s and early 1980’s. I overlooked what you are pointing out, that electric utility production in an extremely inefficient process, with two thirds of the heat content of the energy produced being wasted. However, most utility plants are located in rural areas, so that waste heat probably wouldn’t add directly to the UHI effect. But it might understate it, in the sense that it might raise rural temps that went up because of increasing demand to service urban areas. If there were a way to quantify that, it would make the net effect of all the changes we’re discussing even greater.
In my opinion, that first graph blows the CO2 induced CAGW theory completely out of the water. The only questions that remain are;
-Were the staions cherry picked?
-Are there legitimate corrections that should be made, for time of observation and type of equipment?
-Where can we find enough prison space for all the crooks who were perpetrating this CO2 fraud on the people?
PS If you further correct the rural station data by using only CRN 1 and 2 stations what happens to the .13C per century warming trend?
Is it not obvious?
The final graph of the difference and final USHCN data sets forms A PERFECT HOCKEY STICK.
Say no more!!!!
My question is why bother adjusting rural data? Surely there is no need to adjust temperatures that are not influenced by man?
Can’t we have a world, raw, rural dataset only? Mapped over 100 years or so it should show the trend better than the homogonised, urban sprawl contaminated data.
“The divergence problem with the tree ring data is actually non-existent, because the premise is based on comparing it to the “bad” temperature data.”
That, my friend, is an excellent observation. Kudos!
I would guess the divergence starting around 1960 is somewhat related to increased use of air conditioning and reduction in the rooftop gardens in urban environments that started around the same timeframe. It’s not surprising that the concrete jungles have become increasingly warm heat bubbles; night time light pollution has also exploded (just look at the photos from the space shuttle and ISS).
The question is how much effect that has on the enormous energy pool we call climate. The two graphs — if accurate — certainly seem to be prima facie evidence that GISS is cooking the books. I’d love to get Dr. Curry’s reaction to this.
If urban area of the planet is, and I don’t have anything other than a one half second guess, but .01% of the earth’s surface, then to calculate the planet’s temperature, should not the number of urban stations being read be no more than one-ten-thousandth of the number of rural & oceanic sites?
you guys are missing the obvious…
those rural stations are not reflecting the recent warming, therefore they must be adjusted.
Even the text I use to teach high school Earth Science gets the UHI effect correct.
Steveta_uk (00:38:35), very funny; just the kind of understated humor I like.
Mike Bryant (04:56:27) : “Perhaps Judith would care to comment on these developments and similar problems being laid bare all over the world.”
It occurred to me that Dr. Curry could “peer review” this paper. If it’s worthy (perhaps with changes) of publication in a “legit” journal, perhaps she could even help with the process. Obviously she may not have the time/expertise/interest, and this may not be the best topic for outreach to the climate realists, but maybe…
ANTHONY ALERT – ANTHONY ALERT
http://www.foxnews.com/scitech/2010/02/26/climate-data-compromised-by-heat-sources/
Your surfacestation.org is on front page Fox News
but the Redding, Calif and Hopkinsville, Ky station links are broken
Hanksville, Tahoe City and Marysville links do work.
REPLY: They didn’t tell me they were planning to post a story and link to my web page, had I known I could have told them where to link to. So much traffic it should down my office network. I had to turn off the webserver to protect my business. -A
There was a change at NOAA in those tipping poit years:
http://www.lib.noaa.gov/noaainfo/heritage/ReorganizationPlan2.html
Anthony: The slideshow part of the Fox News item is working, however.
You are going to need mirror sites if this keeps up.
REPLY: Working on it now. My main gallery library is on high bandwidth, but my portal page is still on my office network. Setting up structure to move it now.
A
Kasmir (09:51:11) :
My guess is that the divergence starting in 1965 was related to emissions controls beginning to be put in place in the USA.
If you’ll look at the following link you will see that the divergence is related to many factors. However the one most closely approximating the trend above is the TOBS (Time of Observation) adjustment. Second, and occuring earlier, is the switch from the old max/min thermometers. Since both were mostly completed by 1995, can anyone explain to me why the adjusted anomaly keeps going up. Once you’ve adjusted for these “alledged” errors, the anomaly should remain static. If whatever difference TOBS represents, it seems to me that as stations change there will be an uptrend until that change is met. When all stations have been adjusted, then the anomaly should remain static at that temperature addition.
http://wattsupwiththat.com/2009/06/28/an-australian-look-at-ushcn-20th-century-trend-is-largely-if-not-entirely-an-artefact-arising-from-the-%e2%80%9ccorrections%e2%80%9d/
This study caught me in the middle of making station studies:
http://www.robertb.darkhorizons.org/WhatGlobalWarming.htm
Grants Pass, Ore – complete to 1982 with 2008 on the end.
Monster gaps in NCDC B91’s from 1950 to 1979 missing, data cannot be confirmed but is available. Whole months filled in from nearby Ashland, Ore
Sacramento, Ca – from AMS Journals and Un. of Utah data.
Weaverville, Ca – from Un. of Utah, dri.edu purchased set, NCDC B91’s, Trinity Journal Newspaper.
Orleans, Ca – shows spurrious data on back end of set, but it’s still not showing global warming.
What I do see in the rural sets is a step up in the early 20’s, then a slowly shrinking yearly diurnal indicating increasing moisture (from the pre-Dust Bowl dry years to present).
The 3 rural stations completed show flat line from 1920’s to present.
Only Sacramento shows the UHI beginning in 1965, exactly where it should be.
What global warming??
I pick my stations with length in mind, not because I want them to show global cooling, but because I want to see what’s been going on as far back as possible. The West Coast of the US is the gateway to the rest of the nation.
What happens or doesn’t happen out here runs downhill to the rest of you.
Global Warming/Cooling is NOT the burning issue. It’s what changes have occured in the past and may happen again.
The travesty is that the climate institutions of the world can’t seem to deliver a product that is either useful, forecastable, or reasonable.
There is a world of information out there waiting to see the light of day.
The problem is the warming agenda semi jacknifed on the freeway.
Somebody call the bulldozer dept. and order a fleet to clear the rubble.
Hans Erren (03:50:03) :
Warning: People using default excel colours usually have little skill in data processing.
LOL! And all vivid red-hot reds are reserved for the exclusive use by the scientists perched on high horses!
So instead of adjusting the urban data down, they adjust the rural data down?
Doesn’t make any sense.
….unless you are desperate to keep as much warming as possible..
It struck me that the variability of the difference between raw and final temperatures varies randomly quite a lot before ~1960, compared to the smooth progression seen later on. This kind of behavior is usually a sign that something fishy is going on. On this graph http://www.solen.info/solar/cycl4.html of solar cycle 4 you can see times where the dark blue curve looks very smooth vs. other times where it wiggles a lot more. The smooth portions are when there was no data, and Rudolf wolf simply interpolated to fill in the data gaps.
It does strike me that most of the UHI is caused by gas or electric-powered heat, light, aircon or transport activities, plus some heavy breathing by the 5 billion city-dwellers. All of these emit CO2, so it is hardly surprising that the growth if UHI shows a strong correlation with the growth in CO2.
Perhaps we could use CO2 as a proxy for the UHI and adjust the record to remove it, killing two birds with one stone – we get an accurate temperature record and eliminate AGW from the records, all in one go. Can’t be worse than bristlecone pines!
Sorry “growth in UHI effect”
Lubos Motl
I carry historic instrumental records on my site (including Prague)
http://climatereason.com/LittleIceAgeThermometers/
Comparing Prague with even older (but not necessarily continous) records is interesting as this demonstrates the early 18th Century warming that comes prior to Prague being operational-see Berlin Uppsala Stockholm and UK.
The trend for Prague can therefore be seen in even better context if we look back those additional 50 years or so.
It appears likely that the period around 1730 was at least as warm as today.
Tonyb
The last chart posted came from here.
http://www.ncdc.noaa.gov/oa/climate/research/ushcn/ushcn.html
where they have their own version of what they do to the data and ttheir own chart comparing Raw data with Urban data.
http://www.ncdc.noaa.gov/img/climate/research/ushcn/rawurban3.5_pg.gif
Does anyone miss Robert?
janama (12:00:59) :
That second link, graph yer posted.. what exactly is it showing? raw urban+rural vrs Urban ajusted? Thats how the labeling implies to me? Do they have a raw rural vrs raw urban? Yah know apples n apples.
Intriguing thread, It would be interesting to see a straight comparison with all raw rural vrs all raw urban…. globally:-)
What I’d like to see would be 50 year rural ground temperatures from around the world in areas with little or no measurable geothermal activity.
Leif Svalgaard (11:53:09) :
Yes, filled-in never looks right when it’s strictly interpolated as the shortest distance between two points.
Station data gaps are a huge headache. You want the real deal, but that’s not always the case. A day is a drop in the proverbial bucket. A month is a wound best filled in by a nearby station’s yearly output adjusted to mate with the patterns. A year missing is a 365 car crackup, because you can only adjust the nearby station pattern to sit in between the previous and suceeding years.
There in no guarantee that the missing data filled in by a nearby station is going to behave as the real deal, so the greater the wound, the more serious the scar.
Staking big claims on such premises is a slippery fish on the deck of a boat in rough seas.
“PaulS (05:34:55) :
[…]
The BBC story did talk about the conveyor belt and may cause winters earlier today, however, they have now changed the story, which no longer mentions cold winters, but does talk about the iceberg causing food shortages for pengiuns, which will have to travel much further for food.”
Oh no, they seem to be pretty sure about the danger to the oceanic conveyor belt system, i can read it right now:
“”That means that the bottom water production rate… will decrease.
“The bottom water spills over the continental shelf, flows down the continental slope into the deep ocean.”
This process helps drive the “conveyor belt” of currents in the Southern, Pacific and Atlantic Oceans.
Any disruption to the net flow of bottom water could result in a weakening in the deep ocean circulation system, which plays a key role in the global climate system. ”
Good Old BBC. Never let a good scare story go to waste.
At his blog in the Echo comments to “NCDC UrbanGate: how the urban warming was exported to U.S. countryside,” Motl makes a good point, that it seems hard to cherry-pick 48 sites so that the urban and rural data squiggle so nicely together for decades, then diverge so much, urban rising further and further above rural (while still squiggling alike).
That’s not to say that the study doesn’t need followup and verification. It very much deserves followup for verification.
Dr. Long’s paper is intriguing, but meaningless. First, it would be trivial to obtain his result by cherry-picking a rural station in each state with the largest adjustment in temperature (downward in the past) and possibly an urban station with a relatively small adjustment. Unless he finds a way to systematically select rural and urban stations, Dr. Long hasn’t proven anything.
Second, some adjustments to the temperature record may show a rural bias AND STILL BE CORRECT. For example, there is a problem called “time of observation bias” that occurs with the min/max thermometers that provide the bulk of our temperature data. Stations that are read in the morning almost always record the high from a single daily temperature cycle (which usually occurs about 18 hours earlier), but the low they record may be the low for the current cycle (a few hours earlier) or a previous cycle (recorded about 24 hours earlier). Stations that are read in the afternoon almost always get the low from the current cycle (about 12 hours earlier), but may record a high for the current cycle (from a few hours earlier) or the previously cycle (recorded about 24 hours earlier). Morning records (with two opportunities to record a low) are on the average lower than evening records (with two chances to record a high.) Being a skeptic, I downloaded a month’s worth of real hourly data for one random site, and found that the problem is real: You really do get a significantly different average high, low and mean temperature for a month when you record minimum and maximum temperatures at the most common reading hours of 7:00 am or 5:00 pm. (0.78 degC cooler at 7:00 am vs 5:00 pm). Averaging the readings for every hour of the month (the “true” average temperature) gives a number that is between. Tom Karl’s accessible paper on this subject (http://ams.allenpress.com/archive/1520-0450/25/2/pdf/i1520-0450-25-2-145.pdf) shows that this time of observation bias depends greatly on location and month. He doesn’t give an average value for the 78 stations he studied, but I’d estimate from his information that the changing from 5:00 pm to 7:00 am readings introduces a cooling bias of 0.5-1.0 degC. Karl develops a method for correcting for time of observation bias and shows that it works reasonably well for 28 other sites. Unfortunately, US stations records show that 30% more sites are recording data in the morning instead of the evening near the end of the 20th century than near the beginning. When considering warming of around 0.5 degC, the adjustments for a 0.5-1.0 degC time of observation bias at 30% of stations is a significant factor.
I don’t know if Karl’s methodology for correcting time of observation bias (TOB) has been independently validated or “audited” by a climate skeptic. (It was published in 1990, before most of the frenzy about AGW.) I don’t know how or if Karl’s method has been implemented in GISS adjustments to the temperature record, but they reference the paper. (Do they use real station metadata, or make assumptions based on discontinuities in the temperature record? Obviously only one net TOB adjustment is possible for any station.) However, I’m forced to be more skeptical about Long – who doesn’t say a word about the possibility of that TOB bias could account for his results – than about GISStemp.
We obviously need a national and world climate database with raw data, multiple types of adjustments (with references, validation and published code), and perhaps more than one adjusted temperature (to address controversial problems like adjusting for UHIs). If two equally validated methods for TOB-adjustments give significantly different results, then we need both. That record can’t be in the scientific fiefdom of Drs. Hansen, Schmidt, Jones, or any other save-the-planet or save-the-economy advocate for or against climate change policy.
Automated weather stations show values of
-4 C , O C and -9 C .
The other nearest 20 manned stations show values
from minus 35 C to minus 40 C .
And those 20 will likely be discarded for various reasons.
http://www.ogimet.com/gsynop.phtml
under Zona geográfica
click on
“Canada este”
and then on
“Temp. mínima en 24 horas ”
and then click
“ver”
————-
upper left —
click on map numbers to see stations
names and details —
The automated stations are–
-4 “Rampart river automated reporting”
-9 “Haldane river automated reporting”
0 “Clut Lake automated reporting”
the automated stations are
likely buried in snow or underwater.
Yea where is Robert and the self styled stat guru Tom P ???
Even though rural stations are “at the outer boundary of a small community whose population does not exceed a small multiple of a thousand residents” many of these areas may have grown and suffer increasing heat island effect.
To: KevinM (07:21:26) :
I am shocked at how many have failed to realize that Steveta_uk’s comment was sarcasm.
Get a sense of humor, people
Apologies especially to Seveta_uk, for my lack of humour. I’ve heard so much stuff like this, meant for real, in this “post modern” “ethical relativistic” “true for you but not for me” society – or used for fogging – that
I’ve forgotten how to laugh! Not just a colonial afflicion btw. Maybe AGW kills our sence of humour? Its all the fault of CO2!! Sorry tho’
James Chamberlain (12:21:12) :
“Does anyone miss Robert?”
I don’t. But it was interesting having someone commenting 12 – 15 times a day who, IIRC, was never right about anything.
Suggestion: Repeat this study by
-dividing all thermometers in NCDC/USA into two groups: Urban/rural
using some well-defined proximity to population center criterion.
This classification does not need to be perfect.
-Do several runs, on each run picking 50 from each group randomly with a
good random number generator
-If the urban/rural dichotomy is real, it should clearly stand out in most of
the runs.
-Average a sufficient number of runs to get a conclusive result.
I think this emulates a double-blind study.
Frank (13:07:13) :
Dr. Edward Long has sucessfully highlighted inconsistency in the NDCD raw to adjusted data set.
My own search into that area does nothing but support his findings.
Dr. Tom Karl has left a lot of unfinished business documenting the impact craters in the observational records from his NCDC site, which is another story that needs telling.
Have you, or are you planning on, digging into data sets of your own selection?
I highly recommend it. Nothing quite like independent confirmation.
Why is anyone remotely surprised by the result of this paper? Hasn’t it been obvious for a long time now that AGW is fiction and that this is how the team created and maintain it? This is the way to continue the attack on the alarmists, through the temperature records, the UNADJUSTED temperature records.
I am a geologist living on a farm in truly rural Illinois about 50 miles from St. Louis. The UHI effect between where I live and St. Louis is readily apparent and discussed by meteorologists every evening (“temperatures will be lower in outlying area”). Since the 50’s the St. Louis metro area has both grown rapidly, and greatly expanded in area covered by buildings and pavement. With this has grown the area enveloped by the associated heat island. This should not be a surprise to anyone, let alone climate scientists. I would also expect that the temperature within the core of the UHI has commensurately increased through time due to increased building, paving, traffic, etc.
In a similar vein, along with the construction and development impacting the UHI, what has been the result of diminished particulate matter in major cities? As recently as the 50’s and early 60’s we would drive into a very dirty, smoky and smoggy St. Louis. The clean air act worked wonderfully to clean up this portion of particulate air pollution. Coal, once widely used not only in large manufacturing plants, but also for home heating is now mostly a thing of the past. Reducing airborne particulate matter must have allowed for a relative increase in local temperatures in the following decades, again positively effecting UHI. I also witnessed this effect in Cork and Dublin, Ireland with the introduction of smokeless peat and coal. The impact was quick and dramatic. Within one year the cool season air in these cities went from thick, acrid, smoky and smoggy to clean with amazing reductions in smoke and smog. Sunlight could now penetrate where it could not before. This must have had an impact on autumn, winter and springtime temperatures. How is this accounted for?
My question, with all of the discussion of what is the UHI effect, have there been no systematic studies of temperature changes around different size cities and truly rural (no significant towns for 5 miles, no asphalt, white barns, concrete, etc.). Even more significant would be to continue such a study over time, which could then be used to track comparative changes against ongoing development. I seriously question the use of any temperature data from any metropolitan area, corrected or not, unless your purpose is to observe changes in UHI. Do not contaminate good raw data with manipulated data. Why use it if you do not need to?
My observation, living in the country (over 5 miles from any town of over 500 people) in Illinois, North Dakota, and Texas, and having observed rapid development not only in major metropolitan cities, but also towns of even a few thousands of people, is that there is an increasing UHI effect even in modest size towns of a few thousand people, especially those such as Brenham, TX (recently discussed as a “rural” setting) which have seen rapid growth as compared to the surrounding countryside. Why not restrict point forward usage to strictly rural sites? I have observed one such rural weather station, located approximately 10 miles west of Bottineau ND. I would trust this stations record as it is in open countryside, in a grassy roadside about 30-40 feet off of a two lane highway. While the overall coverage of such stations would not be as great as otherwise, at least one could not argue over methods, site issues and proper corrections. A true base case could be established.
There seems to be some assumptions going on in the selection of 1 station from each State.
Some people seem to assume that the selected thermometer is measuring the temperature of that State. It isn’t. All it is measuring is the little sleeve of air at the bottom of the thermometer bulb. What you have in effect is tiny “pin-pricks” of measurement scattered throughout the CONUS. There is a greater concentration in the N-E (smaller States) but the entire country is covered.
Yes, it would be nice to have the pin-pricks evenly spaced – this is probably the subject of a grant application ( 😉 ) but this does not alter the fact that those thermometers will not correlate with each other due to local phenomenon. It has to be a truly nationwide event (like the recent snow) for them all to rise or fall.
I can never understand why glaciers calving is used as proof of global warming. (Well apart from *everything* is used as proof of global warming.)
Do you have fingernails?
Have they ever snapped off at the end?
Was this because they were too long, or because they were too short?
Re: Steveta_uk (Feb 26 00:38), If a believer moves from the city to the countryside, does he take his hot air with him?
We are only seeing AUW = Anthropogenic Urban Warming
not AGW
Dave McK (12:47:05) :
UHI effect seems to act as a simple thermal mass, stabilising local variability into a narrower range and a slightly higher mean.
It’s a lot more complicated than that.
First of all, UHI affects local albedo. Not only via its colour (on a number of different wavelengths), but by the number of reflections a wave must travel before heading off out of the vicinity.
Urban areas are also drier than rural ones. A mature oak can dump a ton of water a day. That is a lot of energy to make that phase change with much less left to heat things up. A concrete building on the other hand just absorbs solar energy by getting hot.
Then there is the thermal mass on top of that.
It has reached the stage that no matter how much evidence is released showing that the AGW thesis is a hoax and a fraud, nothing will change, or at best there will be a very slow process of unraveling the truth, which may take decades, by which time it will be far too late to stop the introduction of new taxes and false green technologies that will cost far more yet deliver no appreciable benefit to the climate. There is only one way to avoid all this is to charge the leaders of the AGW hoax with fraud and force them to defend themselves in the courts. Hopefully, with all the evidence that’s available they could be found guilty, with appropriate punishments allocated to them.
Frank (13:07:13) :
Dr. Long’s paper is intriguing, but meaningless. First, it would be trivial to obtain his result by cherry-picking a rural station in each state with the largest adjustment in temperature (downward in the past) and possibly an urban station with a relatively small adjustment.
Dr. Long picked 2 of the best sites in Texas, Beeville and Corpus (according to surfacestation.org).
Speaking of observational records and raw data:
http://www.robertb.darkhorizons.org/WhatUpWithThis.JPG
Highlighting 5 missing months in a 12-month span no more than 7 years ago and a 30 year gap to stick in anybody’s statistical craw.
Does that bother anyone? It bothers me.
If I were the head of NCDC and my records had things like that going on in them, I’d be taking names and asking a lot of questions.
I surely would not be sitting still or putting up with it.
Steveta_uk, if that was pure satire, you sure sucked many in. It’s just that in very similar conversations, they are serious!
Not far from my home is a rural airport that has a temperature record going back to 1908 and is still functioning. The airport ceased it’s daily return flights to Sydney back in 2002 and the only change since then is they’ve added a new trailer park which is still well away from the measuring station as you can see in this picture.
http://users.tpg.com.au/johnsay1/Stuff/casino_airport_1.jpg
The airport is well away from the small town of Casino.
http://users.tpg.com.au/johnsay1/Stuff/casino_airport.jpg
I downloaded the max mean and the min mean from BoM and created a Mean temperature chart – it says it all really.
http://users.tpg.com.au/johnsay1/Stuff/Casino_temp.jpg
This is worse than we thought.
On the up side the US rural weather stations seam to correlate well with rural weather stations in the rest of the Northern Hemisphere, so if the “scientists”,
( it seems more like bean counters ), had any integrity they try a re-do with rural raw data only.
I know this is never going to happen with the current crop, but a man can dream, a man can dream.
Another thought struck me, looking at the obvious implications, this chicanery will mean large numbers of papers which relied on this data will have to be consigned to the file B1N.
Sadly it looks like in the UK an election will be announced this weekend so the CRU enquiry will be allowed to quietly disappear, the fix is in. 🙁
TKL (08:50:20) :
I’d like to see a retrieval of the satellite sensors and subsequent calibration. The reference is a platinum resistance thermometer. Looking at this is exactly like looking at the air? What are the effects of cosmic radiation and solar flares on the sensor and associated electronics.
As you point out, conversion of what the sensors detect and atmospheric temperatures involve quite an involved process. Remember it was only a few years ago that the satellites were showing no warming. Then a previously undiscovered “correction” was applied due to orbital decay. So just how good was this correction and how exactly was it arrived at?
I no longer heavily weight ANY of the instrumental record including the satellites. Historical, archeological and geological evidence seems a better way of arriving at climate changes. Looking at these there’s nothing at all unusual going on at present. It is time that climate “science” went back to being a minor field as an offshoot of meteorology, mainly of interest to those working in it and few fewer of those and far less taxpayer funding.
You want to talk about a rural station? Consider Pineville, West Virginia, USA. The town was settled in 1853 and incorporated in 1917. The 2000 USA Census registered 715 people, and the town suffered a huge population decline in the 1990s.
Here’s the USHCN plot of their mean monthly temps since 1900. No AGW signature that I can see. (If the image won’t display, just cut’n’paste the source link)
” Jeremy (07:52:01) :
Interesting that the upslope of the urban wrt the rural stations starts around 1965, rather than post-war.”
The United States federal government has enacted a series of clean air acts, beginning with the Air Pollution Control Act of 1955, and followed by the Clean Air Act of 1963.
Cooler winters and warmer summers, coal dust and soot melts ice/snow in winter and soot/dust blocks sunlight in summer.
My parents describe going to school in the UK in the 1940’s midlands and braving smog, visibility about 3 feet.
Looking at figure 1 the rural and urban match until about 1970 or so then the urban deviates upward. The adjusted figures (2) show the urban a bit higher than the rural for almost the entire time period. The alarmists can then claim that (1) we know that UHI exists, see the cities are warmer than the countryside, and (2) but we aren’t worried about the absolute temperature, it is the rate of change that is important and the rural and urban have the same rate of change, so rural and urban don’t effect our analysis.
Really rather ingenious to find an algorithm that lets you mollify the UHI believers (everybody) and at the same time say that it doesn’t matter.
What are the chances that adjustments made purely for sound scientific reasons results in the best possible evidence for AGW (Accept UHI, common knowledge, but deny effect.) It is both increasing the slope of rural after 1970 AND adding a differential prior to 1970 that could cause one to wonder about the legitimecy of the adjustments.
By the way, the way that the urban deviates upward only after 1970 or so would seem to imply that UHI is not simply an effect of increasing city size but more an effect of energy use (air conditioners, airplanes, etc…). That would mean that a study of UHI based on a time period prior to 1970 and in a place where there was not intense use of Air conditioners etc.., Say China, 🙂 would show little or no UHI and justify not including UHI corrections in the Temp analysis.
Also by the way, I don’t believe the adjustments were to correct for UHI. They are just part of the infill/averaging/weighting algorithms. Am I wrong on that?
Well, nothing displayed at all. Let’s try this:
Pineville, WV
Thank you for the third graph. I hope NCDC will take this paper seriously enough to produce a response for why it is “wrong” or otherwise misleading. Unless they can show the 48/48 sites have been cherry picked inappropriately (heckifino), I should certainly like to hear what other rationale they can come up with as to why this paper misrepresents reality. The paper claims “more than 5x”, but it seems by my math to actually be “more than 6x” difference for urban vs rural, at least in the US.
Anthony, you and Evan are the Lords of Siting –see anything about those 48/48 that gives you pause?
”””’James Chamberlain (12:21:12) : Does anyone miss Robert?””””
James,
Actually, I immensely enjoy the give and take between some of the WUWT regulars and any commenter like him.
So, yes. I miss him in that regard.
John
I can only look at this sad saga from a laymans point of view. So lets see.
Across 2 ends of the world, we have 2 wolves who predicted doom and gloom due to AGW. (Jones at one end, Hansen at the other)
We put these wolves in charge of the sheep (temp data) and now find our sheep have been disappearing at a great rate.
Any surprises?
Interesting study that I should read. Why select 1 or 2 sites per state?
I worry about being open to the characterization of a cherry-picked dataset.
What I would like to understand is how the GISS corrections are made. If the protocol is actually to AVERAGE the data in one of their 5×5 grids – one could imagine the urban sites swamping the rural.
It sure does look suspicious tho. The correction for urban Heat Island Effect doesn’t ratchet urban areas down – it rachets other areas UP!
Their thinking must be: differences minimized, mission accomplished !
Sloppy sloppy work
crosspatch (09:02:30) :
That answers a question I never got around to asking when I was there. The name of Knots Berry Farm amusement park.
DaveE.
There’s a kind of levelling off of urban raw temperatures in the 1970s, before the rise begins again in the 1980s. Since some of us here are trying to explain the rise in urban temperatures via demographics, increase in asphalt, concrete and other hard surfaces, population shifts and intensification of heat-emitting technologies, this temporary plateau might reflect to some extent the effects of the energy conservation initiative due to the Oil Crisis of 1974, the government conservation initiatives, and the stagnant economy. I wonder how widespread was the temporary shift to wood-burning stoves in the late 1970s as a part of the attempt of ordinary people to cut their heating bills? Would this be reflected in any of the data?
Why divergence started around 1965? Doesn’t anyone remember the “Great Society”? People started flocking to the cities effectively killing an agrarian society. Small farms were left vacant to become pastures. Small towns dwindled away to nothing. People migrating to the city left some conditions causing
flight to the suburbs, but still near the cities.Conditions were ideal for the increase of UHI. At first nature managed a heat bias by itself, until some
opportunists decided to help nature. The urban graph mirrors these results perfectly.
[I’ll try to keep this short…]
I think this sums up what most of us see as the real reality that should be being observed/measured.
The rural sites, in toto, should be as un-biased a dataset as we can find. If the urban heat islands are affecting the overall, then it should be reflected in the rural dataset to some degree. If the assumption is that rural temps, less the urban contribution to them, are completely stable (which is not really a correct basic assumption, but we do have to have some basis to start from), then any rise in the rural dataset can be said to be from the bleed-through from the urban heat islands.
I tend strongly to agree with wayne: If the claim is that the average is rising, then that should be best seen where spikes are not present, out away from them, where the blending has smoothed everything out.
The scientists want to homogenize the data? The atmosphere itself homogenizes the temps, and the resultant is the rural data.
Reading ONLY the rural data is the only way to get a true reading – as long as the rural data is still rural. If we are warming the WHOLE planet, shouldn’t that show in the moderate to remote corners of the planet?
If I have one caveat on this it is that the population of datapoints is so small. As a true study, I think this means only that a more in depth study should be taken. There is every probability that these do represent a trend in their methodology that is incorrect, but it needs to have a far wider study done. Replication, replication, replication…
I’ve been arguing that point for quite a while, that this is maybe a major source of UHI. When the indoor heat is displaced to the outside, the overall temperature is still the same, but added to it is the added heat generated by the air conditioner mechanisms’ inefficiency, which is given off as heat energy. The removed heat and added heat together both end up outside buildings, creating micro-climates that often overlap. Yes, there are other factors. This one, IMHO, does not get the attention I think it deserves.
I am glad someone else is considering this, for whatever that is worth.
Frank (13:07:13) :
“Dr. Long’s paper is intriguing, but meaningless.”
I’m sorry but I must disagree. If this is taken as a preliminary study it indicates that there may be a significant problem and that further study is warranted. Also, we do not know the detailed design of the study.
From experience, in an industrial setting for internal use only, the definition and design of a study takes longer and takes up more of the report, than doing the study and reporting the results. If the initial design and definition is inadequate then any study may be worse than useless, it may be so misleading as to result in actions that cause a bad situation to deteriorate into disaster. This is, of course, the major problem with much of the “peer reviewed” studies in the literature. They lack the essential detail and make it impossible to confirm or deny the results, or even that they are investigated the problem that the authors claim to be studying. They have the potential to turn a possible bad situation, CAGW, into a financial and humanitarian disaster far worse than any the world has seen. This is especially true when it is considered that the corrective action does not appear to have the potential to have any detectable effect.
A little elaboration on/restating of my point about UHI possibly affecting rural data:
If we completely assume that the work of CRU/NOAA/NCDC/GISS is all crap, then we need to begin assessing what is really happening, whether warming is small, large, catastrophic, or not happening at all.
If global warming happens in the real world of raw data, then rural areas should be the last to see it happening – but they MUST be seeing it happen IN THE RAW DATA. That is IF it is happening. Since they are farthest from the warming – whether the warming is from UHI, CO2, air conditioners, automobiles, or land use – the rural areas are the canary in the mine. Being remote, they should not NEED any adjustments, since everything else should warm (or cool) before they do. They should be the base line against which trends are measured.
The 0.11ºC/Century MAY be coming from bleed-across from urban areas. If that is the case, it is something to keep an eye on, and something that is easy to check. At the same time, 0.11º/century is an awfully small rate of increase, so other than a check every 25-50 years it shouldn’t be much to worry about.
Again, if the urban areas are affecting the entire globe, then we should be seeing it in the raw rural temps.
Something I am surprised no one has pointed out (and which WILL be pointed out by AGWers) is that this is “only” the U.S., and therefore is only essentially a local phenomenon, at most.
But it is a very important thing that the best measured place in the world is the one being checked out. That means there is no need for reaching across hundreds of miles for reference rural stations (this one intentionally does not use them, anyway), and no large areas unrepresented.
If you can’t look at the well-documented areas, what good can ANY study do?
It is a START. It by itself is not enough. These trends need to be verified with other studies (all easy enough to do), wider studies.
But the real point of this study is that THESE stations have been adjusted weirdly – and THAT is an important observation.
Why have THESE stations been adjusted in this way?
Is there any reason to think that no other stations have had this kind of weird adjustments? Of course not.
The next step is to ask those next questions and find out how widespred this is.
It can’t stop here.
feet2thefire (18:26:05) :
The scientists want to homogenize the data? The atmosphere itself homogenizes the temps, and the resultant is the rural data.
Excellent point.
That is why I am very encouraged to see many folks and scientists out there digging into the rural data.
To say that this “paper” is amateurish is being too kind. I produced far better work as an undergraduate when I had long hair, blood-shot eyes, and a 48-hour hangovers.
Picking two sites (one rural, one urban) from each state? Since when is it best practice to use less data? I don’t know if anyone has looked at a map of the U.S. lately, but states in the West are large and states in the Northeast are small. Before you even started loading data into Excel you’ve already biased your results geographically. Someone wasn’t paying attention during quantitative spatial analysis.
It has been pointed out over and over and over again that time of observation (TOBS) is a known bias in these data. One of your fellow skeptics even points it out above. It must always be accounted for. Why on Earth would someone ignore this? (Because they can…because this will never be peer-reviewed).
I see all these references to “fitted linear regressions”. Where are the model diagnostics? What scientist would discuss a linear regression model and not provide a p-value? Alarm bells should be ringing for anyone that is still conscious.
I would plead with anyone reading this that has anything approximating an open mind to please disregard this paper in its entirety. I won’t ask you to change your opinion; you’re certainly entitled to it.
But PLEASE, this type of “science” must be ignored, even if you agree with the conclusions. There are for more thorough analyses of surface temperature records out there.
One more point -and I really think this is important:
AGW says that increasing CO2 is causing an increasing greenhouse effect for the entire globe. If so, the rural and urban temps should reflect this, very nearly equally. Different large regions may vary from each other, but within smaller regions rural and urban should be very nearly equal in their increases.
1. The adjusted data seems to support this. If it is true.
2. The raw data should also reflect this. But it doesn’t. We can’t even say here, “If it is true.” How can raw data not be true?
But this study, as everyone here is noting – casts a very sinister eye on the NCDC adjustments – on the values used, on the trends in those values, and even on their directions.
IF THIS STUDY IS ALLOWED TO STAND, IT REFUTES THE CO2 GREENHOUSE EFFECT THEORY. If urban areas are warmer and climbing at different rates than rural areas, then something else is happening, not a greenhouse effect. it is a local effect, not a global one.
If so, the global in “global warming” is shot in the foot.
A point many here have noted.
If you read the paper, you’d see that the researcher specifically addressed this question.
As I see it, the point about THIS data is not necessarily where it fits into the larger picture, measured against other data. The point rally is: Why has THIS data been treated this way?
The time of observation is a constant differential for a single station, compared to itself and against the standard set by the NCDC. If the time is off by a constant 5 hours, for example, that variation does not lend itself to increasing over time. Why would the adjustment need to keep on increasing? Once determined, the adjustment must remain constant, barring time of observation or other changes.
In pointing at the way this data was treated, it begs the question if the rest of the data was treated in the same way.
If any group of data is adjusted in a weird way, it is legitimate to ask why. And if that data is not stand-alone, but part of a larger population of data, then it draws attention to the entire treatment and possible errors. In a perfect, non-political scientific world, the NCDC would look at this and review their data – especially for time of observation and urban heat island effect.
Small studies don’t solve anything; they can only point at what may have been done in error. They can only point to the need to look deeper.
feet2thefire (21:14:51) :
The raw data may need to be adjusted to properly reflect nature. Station moves, for instance, can have an effect on the data that hides a trend. Of course, you could just measure the trend to the move, and the trend from the move and I believe it would have the same effect with no need for adjustment. You would just have to move the baseline for the anomaly. You could make a whole new dataset for the new location, which seems to me like the option that reflects reality the best, but hey, who am I to say all these government scientists are making their own lives too hard?
Of course, what is the point of adjusting for a station move (10km) when you can use a station 100km away to homogenize the temperature?
Ummm…. I’ll go with the middle cup this time?!
Steveta, the proper perspective (in the U.S.) is this: People who live in urban areas during the summer experience much cooler temperatures inside of air-conditioned buildings, compared to when my grandfather worked as a farmer all day out under the sun (early 19-hundreds). As these people walk a few minutes from their offices to their air-conditioned cars, they experience on average a 0.6 degree higher temperature because of all the heat energy pumped out of buildings and cars, – and to think like this doesn’t take any advanced degree whatsoever.
“Re: Alexander (01:45:18) :
Another shoe drops…”
Hooray, Alex!
From an old woman in the still almost empty
and extremely beautiful beautiful Arkansas Ozarks!
feet2thefire (18:26:05) :
Thanks for the reply. Sure sounds like you are based in physics and have your head screwed on correct to boot.
I see you got my point. The logic being used today by the agencies seems totally screwed up.
Any logical person would say at most you should only apply the weight to each of rural and urban sites according to their respected measured land area that they occupy. Part of this reason is in increase variance spoken of below.
What caused the 0.11 slope of the rural is unanswerable, its possibilities are numerous, but a good collection of rural stations on a global scale would tell you the closest answer to what has happened to the global temperature over the last decades. For any excess heat created by an urban heat islands would instantly (in hours) move and disperse over the rural sites continuously. That is why you really only need the rural sites and that would be the most accurate possible.
I do see where the agencies are coming from. They have had papers written saying that it doesn’t matter; they had them peer-reviewed. Problem is they are still wrong. It does matter. That is also why you see the variance going up. In an urban site a good wind comes up, blows over the city, it gets cooler. Thirty minutes later it’s still again and the heat gradually goes back up. Now when did you say the temperature was taken? See, the exact time does matter and the variance can be large (ranges up to that of the UHI effect itself). Rural sites do not do this (or to a much reduced magnitude) for the wind blowing in is at or close to the local rural temperature to begin with.
I keep saying, personal computers and easy statistics came in and proper logic and reason when out of the window!
Also, placement of the rural sites would need to be placed in all three dimensions as smoothly as possible to approach the closest measurement of the anomaly. The ultimate is measuring ALL variances of temperature everywhere there is land or sea, which of course is impossible.
If you were to take this and write a paper, then you would delve into the depths of the data and statistics necessary to back up your hypothesis but at least it would have solid logic and reason behind it.
Of course, that is only my viewpoint. This could be too simplistic or just not possible at all but approaching this idealism seem to be a better way.
Do you see the breach in basic logic and reason being made by the agencies as I do? You can see it in all graphs as the ones in this article.
feet2thefire (19:52:31) :
Something I am surprised no one has pointed out (and which WILL be pointed out by AGWers) is that this is “only” the U.S., and therefore is only essentially a local phenomenon, at most.
I forgot to mention that point you made. You infer they will say this is only local but this same type of problem is popping up all over the globe at other stations. This article was only on one station but look at the whole U.S. anomaly last month, the rural was 0.11 and urban 0.79, untouched. See, the same discrepancy applies when looking at all stations in the U.S. and most likely it is a system-wide error occurring globally in the computations because the logic itself is flawed. That is what needs the focus, to answer that question. If it can’t logically be correct, you shouldn’t care what the numbers say. Don’t let them concern you with their authority game.
I read years ago how a young boy, something like 13 years old, tore down a major scientific paper purely at the logic level. Wish I could remember what that was. You don’t need letters to be a scientist or have an impact, for that is truly what science is, proper thought, then followed with numbers to back it up.
(Some of the fluff I throw in is not necessarily for you but for young people following along, science needs all the help it can get these days, especially for future climatologists, don’t you think?)
feet2thefire (19:52:31) :
Do read the article on “Contribution of USHCN and GISS bias in long-term temperature records for a well-sited rural weather station”. Some of my comments were addressing it when speaking of a single station (kinda like a comment-ahead for I have already read it and was mixing to make my point clear to you).
DD More (07:22:27) :
I could never understand how UHI was minimized. If you look at New York City as an example.
Area, including water 468.9 sq mi ( 2,590,000 sq m)
Power used (2008) 54,869 GW-hr (http://www.nyc.gov/html/planyc2030/downloads/pdf/progress_2008_energy.pdf)
Watts/sq m = 2,416 total. The Mayor says 80 percent is used by buildings and therefore 100 percent ends up as heat loss.
So the forcing is 1,933 W/Sq M
The file also remarks that the city has seen a 23 percent increase in the last 10 years, which is close to the increase showing up in the charts.
Interesting to see the figures for NYC. I did some rough calculations for London a while back. Came to conclusion that UHI from anthropogenic heat alone (not including the component from concrete/asphalt and other land use changes) could increase the average temperature of the whole atmosphere in and and above the city by 1C after 4 days of windless weather (assuming no losses to space from the extra 1C heating). Here’s the calculations (pasted from a spreadsheet so forgive the poor layout):
London warming / UHI calculations:
if 6.67 billion on planet:
2398.8 W per person is average enery use
Europe is about 6000W pp
USA about 10-12Kw pp
(see http://www.carboncommentary.com/2008/07/18/86)
London pop c.: 8000000
total energy london: 48000000000 Watts
48000000 Kw
London area: 1600 km2
which is: 1600000000 m2
so London is: 3.03001187737992E-006 of Earth’s atmosphere
mass of atmosphere above London: 16059062950113.6 Kg
energy / area 0.03 kW m-2
0.12984590376905 so roughly equivalent to 8% of Sun’s average output
so it will take: 335735 seconds to heat up atmosphere by 1’C
or: 0.0106390846252544 years
which is: 3.88 days
My conclusions were that what I grandly/pretentiously termed Anthropogenic Atmospheric Heating (AAH) is insiginificant in global terms (averaged globally it is roughly only 1/8000th the heat we recieve from the sun) but that it is of a magnitude which can significantly increase ambient atmopspheric temperatures in large urban areas. , e.g. central London, Paris, Tokyo etc.
However, it is also possible that AAH is of sufficient magnitude to have a noticeable effect at a regional level, e.g. South-East England, Florida, or other highly developed areas. And all this is before we add in the well understood UHI component from land use changes.
Alexander Feht (00:58:08) : A very graphical example of fraud, obvious even to a child. Or should we call it politely “a convenient lie”?
It’s one of those pesky irregular verbs that we have in English:
I Adjust
You lie
He commits fraud
😉 (Stolen in concept from Yes Minister line in another posting)
BTW, it looks to me like a programatic adjustment has the urban and rural variables swapped in an equation somewhere. Something like:
variance = rural – urban
rural = rural-variance
Now if urban is hotter, the variance will be a negative number and if someone thought they were adjusting the things down with a minus, they would find they were actually moving it up with a minus minus.
If you made it instead:
variance = urban – rural
urban = urban-varance
you would have a positive offset for the variance and subtracting a positive from urban would be exactly what you wanted to do.
While this looks like a silly error with variable names like “urban” and “rural”, some programmers use names like annom_adj, annom_out and annom_in so written as:
annom_adj=annom_in-annom_out
annom_in=annom_in-annom_adj
it would be far less obvious that the programmer had gotten it the wrong way round… I’ve seen far worse done in programs. By good programmers.
Usually that kind of thing is caught with QA suites and sample data runs. But I’ve not seen a lot (or, frankly, any) evidence of QA suites in the “scientific programming” done by “climate scientists”. Nor any written acceptance test criteria either. So if they didn’t do much testing, I could easily see that kind of error going through unchallenged.
Just a thought…
I don’t know how to write this politely but obsessing over temperature variations less than the inherent limit of detection of the equipment used to collect that data, smacks of crass scientific incompetence.
Seems past use of chicken entrails, and other signs, hasn’t been divorced from the scientific method.
It looks like USHCN made a basic mathematical mistake they added a bias to the rural numbers without a physical explanation for doing so. If instead they had subtracted a bias from the urban stations, we have a physical justification: elimination of the bias due to recent urbanization such as increased pavement and additional buildings. You can’t claim one is equal to the other if you don’t have good rational explanation.
The only explanation they give for their choice is that it match tree ring growth. Mind you that most forests in the last 50 years have been managed to increase tree growth by eliminating fires planting faster growing trees and other farming techniques. Until we can properly eliminate the effects of forrest management on tree growth we have a problem with hat they did.
E.M.Smith (01:46:24) :
Good point E.M. Boolean and sign errors are sometimes the hardest to see and catch when not a blatant crash!
I was wondering what kind of machine these programs were originally written for. You are a programmer like myself, if this was written on very old hardware, you know the government, limited in all aspects, and never have been re-written from the ground up, this could feasibly be at the core of this type of programming error, if an error. You know what I mean. Keep adding and modifying ancient code written for legacy hardware until the maintenance is taxing and breaking their back, bugs can get buried very, very deep. You saw Harry’s code!
That was just a thought that pass by my mind a few days ago. However, I just can’t believe that if that were the case, someone at sometime would not have noticed the error. They would have to never really look at their end product from a scientific viewpoint. Could they possibly be in that bad shape? Papers were written by scientists years ago, the programmers code it until accepted, the scientists go away, the programmers are there to merely maintain the product with minor modifications, and no one even REALLY looks at the end product? Like, it’s just a paycheck. It would be a huge, huge stretch.
wayne (02:39:58) : I was wondering what kind of machine these programs were originally written for.
Well, it looks to me like it’s Sun Friendly code (though a couple of the f90 constructs look more like Cray Fortran of about that vintage). Some of that could just be how the programmer personal style was set, though. I’m not familar enough with SGI Fortran to know it’s fingerprints. FWIW, about the era in question, I hired some folks from NASA. Required experience was Cray and Sun and they had it…
if this was written on very old hardware, you know the government, limited in all aspects, and never have been re-written from the ground up, this could feasibly be at the core of this type of programming error, if an error. You know what I mean. Keep adding and modifying ancient code written for legacy hardware until the maintenance is taxing and breaking their back, bugs can get buried very, very deep. You saw Harry’s code!
I’ve also ported GIStemp to run on Linux. Yeah, you described it right. You can tell the “era” of the particular steps of the code and can even spot some of the (limited) maintenance done. The oldest bits require the f77 compiler and are written in THE ALL CAPS STYLE mandated by that era. The newer bits require the g95 / f90 compiler and are lower case. In between are some that work with both compilers and often have mixed case (especially in ‘maintained’ parts). All of it shows it’s age.
So I don’t think a bit will have been changed once it was assumed to work; unless the researcher wanted to try a new “trick”.
That was just a thought that pass by my mind a few days ago. However, I just can’t believe that if that were the case, someone at sometime would not have noticed the error.
And for how many years have folks pointed out that the averaging of an intensive variable is meaningless and it still is done? (i.e. counting the coins in your pocket without looking at the denominations. Averaging temperatures do not tell you how much heat is accumulating or leaving.)
And for how many years have folks said the thermometers are in poor locations and badly sited and don’t give good data?
And for how many years has the code had a compiler dependent failure that makes it warm 1/10 of the records by 1/10 C in the F to C conversion?
And for how many years did it have an “off by one” read error before it was found a year or two ago?
And for…
No, there is no decent QA suite or validation process run on this code and there is no ‘code review’ worth the name. This isn’t Engineering, after all, it’s only “climate science”…
They would have to never really look at their end product from a scientific viewpoint. Could they possibly be in that bad shape?
Never underestimate the power of self confirmation bias. Once you see what you expect, you assume you were right and nothing is wrong. End of QA process. Close can, ship it. Never look back.
I’ve seen far too many folks do exactly that.
Papers were written by scientists years ago, the programmers code it until accepted, the scientists go away, the programmers are there to merely maintain the product with minor modifications, and no one even REALLY looks at the end product?
I would only add that the programmers are likely not professional programmer staff, but fellow researchers, and they would not be going into the code unless something needed to be changed for some reason. As a result of some new research and even then they most likely do not look at any part other than what they are adding to support the new paper…
There is a reason the QA department is a different group in professional software shops. You really need a different mind set. And a benchmark / QA / Validation suite that is often larger than the code base itself. And have you noticed that NONE of the NOAA / NCDC / NASA / GISS web sites, or people, talk about their work in QA or have titles that look like it? There is no indicia of a QA department or process. Just “one guy” who is listed as the maintenance contact… with a ‘scientist’ title…
So yeah, I could easily see it being that bad.
“E.M.Smith (04:09:39) :
[…]
I would only add that the programmers are likely not professional programmer staff, but fellow researchers, and they would not be going into the code unless something needed to be changed for some reason. As a result of some new research and even then they most likely do not look at any part other than what they are adding to support the new paper… ”
Gotta second E.M. here. I once had to port a photogrammetrics package written by photogrammetrics researchers from Fortran to C++. The researchers were very good in their domain but hadn’t the slightest clue of modern software architectures nor interest in refactoring old working code just to make it easier to maintain it. It was the worst thing i ever did for money.
“JMR (02:15:20) :
It looks like USHCN made a basic mathematical mistake they added a bias to the rural numbers without a physical explanation for doing so.”
I object. This is not “a mathematical mistake”. Deciding whether to add an offset to rural stations or subtract an offset from urban stations is directly in the “core competence” region of the climatologist domain. We can’t let them out of this. Ok, they made a dumb mistake when converting from Fahrenheit to Celsius, we can blame that on pragramming incompetence. But this adding/subtracting an offset is a core methodology decision.
“Phil M (21:05:51) :
To say that this “paper” is amateurish is being too kind. I produced far better work as an undergraduate when I had long hair, blood-shot eyes, and a 48-hour hangovers.”
Care to give a link to a paper you produced when you had long hair, blood-shot eyes, and a 48-hour hangover? If it’s even better than the posted paper, i’m very eager to have a look at it, let alone the papers you produce with short hair, clear vision and no hangover.
Phil M.
“Picking two sites (one rural, one urban) from each state? Since when is it best practice to use less data? I don’t know if anyone has looked at a map of the U.S. lately, but states in the West are large and states in the Northeast are small. Before you even started loading data into Excel you’ve already biased your results geographically. Someone wasn’t paying attention during quantitative spatial analysis. ”
Spacial analysis doesn’t matter. The point here and in another recent analysis, is to pick flaws in the methodology and show that it is incorrect in some instances. Whether it is incorrect in ALL instances is rather irrelevant. It points out that the models being used to derive data sets are junk and that the mathematical models being used need to be revisited.
Refuting a point is much easier than making a point.
Simplistic Example:
Assertion – All green apples are sour.
Refutation – Find a single green apple that isn’t sour.
The point of a refutation is not to come up with an alternative theory, but to show that a theory isn’t valid and needs adjustment. Here’s the real scandal,.., why aren’t any of the “peer reviewers” poking holes in the data being used? What is the value in peer review if they don’t try to refute a point but instead just rubber-stamp an assertion that they agree with or spike an article that they disagree with?
Regarding Robert,
I would like to see him back as long as he learned his lesson about manners. I have no idea what he was saying about Anthony in that thread, but I think any of us that have been arond here for a while (I’ve lurked on and off for 2 years, maybe longer before I started following closely about 6 months ago) know that the real beauty of this site is the comments section, and that as the purveyor of this site Anthony is not one to get bent out of shape and overreact to valid criticism.
What is posted here, unlike RC and Tamino, is the starting point for a conversation, not the final word. The comments will challenge it and try and poke holes. Don’t get me wrong, there is plenty of cheerleading here too – sometimes more than warranted (Lacis’ thread comes to mind again – and I’m talking about in the comments not the original posts) – but I guess what I’m getting at is that there is open debate here, and I have always appreciated that.
We need to both challenge and be challenged but civility and respect, at some level, must be maintained.
If you were to start from an assumption that UHI is a minor issue you could end up convinced that the reliable stations are the urban ones.
Video of a boy called Peter who did the same study over a year ago with the same conclusion, but without a PhD or govt money :
looks like UHI started showing up in the Roaring 20’s
E.M.Smith (01:46:24) :
…..Something like:…..
“variance = rural – urban”
“rural = rural-variance”
E.M. , I think you are right.
I think this is what has happened;
Someone made a piece of code, with an error as you suggest above.
The result confirms what you expect; Global Warming.=>hurray!!!
So noone sees there is something wrong, and the years go by.
As you know;
-Detecting an error in software means you need a test setup.
-Finding and correcting it means stepwise debugging.
-Knowing where to look; You need to use Visual Soucesafe or
the like, in order to trace who did what and when….
When doing a change nomatter how minoscule it is, you run the test setup. All still well?
Maybe there are too many Managers (driving big SUV’s) in these institutions, and
too few who is actually doing Science (driving Volvo’s) ….
hehe!
George Turner said:
> I’m not so sure on this one. If the adjusted graph is correct,
> every year since 1990 should’ve been proclaimed hotter
> than 1934, which still stands as the record even in their
> own adjusted stats.
The plot is of the 11 year moving average, not the yearly average. So on its face, it looks about right.
Full report here:
http://scienceandpublicpolicy.org/originals/temperature_trends.html
If you look at the graphs in the plot which show both annual and 11 year averages, a few years in the 1930’s are much above the 11 year moving average, but funny that t1934 does not come out as one of the highest temp years. Is it because the temps are for te contiguous 48 and do not include Hawaii or Alaska? Someone help me out here…
Oh I see.. there are no graph show of the combined raw or adjusted annual contiguous US temperature data sets either above or in the paper. The graphs are shown only broken down s rural only or urban only. Presumably once you combine the two adjusted data sets from NCDC you get what the NCDC publishes here:
http://www.ncdc.noaa.gov/img/climate/research/2006/ann/Reg110Dv00Elem02_01122006_pg-v2.gif
EM & Anthony –
you guys really have a deep understanding of the sources of data and various ‘corrections’ made on these data.
As a newb to this – I would LOVE to be able (for family and friends) to access data from a rural station my family knows about (and whose quality isn’t in doubt) and be able to demonstrate the ‘corrections’ applied.
The Long paper highlights the problem (must be the luminosity = heat correction idk?), but now obviously needs to be done on a comprehensive and publishable basis (pdf on advocacy website doesn’t scratch my scientific itch I’m afraid, even if I agree with it).
Obviously looks like Anthony and Steve have a great start here – but the kind of Virginia analysis can be told on a site-by-site basis by interested others if given a little bit of a roadmap. I’m sure all the data have been subject of various posts and discussions before – but hard to find as a newb.
A post that describes:
1) describing the data (what is available (min? Max? Avg, tob?), how it is used, when it was released)
2) Accessing the data (where to go),
3) knowing what it is that one is accessing (is it raw (really),
4) where are the data from (the station code list tie to geography), and
5) surfacestation.org code, overview and
6) what differences were applied and when
would be a fantastic roadmap to this corp of citizen scientists. You might be able to harness the power of the internet in an analytic way.
Ummmm… Rural made warming…
What I don’t understand is what possible reason could they give for adjusting the rural data. To me it is the only non contaminated data, the only thing affecting it is the change in temperature
What they should do is completely disregard the urban readings and take any trends from the non effected urban data only. This way there is no need to adjust anything.
take any trends from the non effected urban data only
of course I meant non effected rural data,
He is not afraid of any opposition;
http://www.examiner.com/x-32936-Seminole-County-Environmental-News-Examiner~y2010m2d12-Former-NASA-scientist-defends-theory-refuting-global-warming-doctrine
Let’s say, the urban island/microsite effects are real! How would that change GLOBAL warming, e.g. Ts on a global scale. The US occupies 2% of the earth’s surface and the cities are small island within it. And even more so, considering that the reported data are T differences and not absolute Ts. As long as the site conditions do not change, the T differences should be real. And, on top of that, the T increase in the US over the last decades is much smaller than the T increase in the Arctic and Siberia. Considering all this, the surface station quibbles are a bunch of hot air.
Oh, and the so called paper is distributed by some obscure scence and policy institute (I guess more policy than science). It is not in a peer reviewed journal. that’s not a paper, that is a note. Hey, my letters to the editor are also scientific papers.
Wonder what happened if Mann and Jones published their stuff unreviewed from a science and policy institute website…