The Urban Heat Island effect on temperature records is real, despite what some people wish you to believe. Peter, a sixth grader, and his dad, thought so too, and take the data from NASA GISS and show in a simple video, what we’ve been saying for years here at WUWT. Urbanization, land use, and station siting matter.
Watch Peter’s excellent video below:
They used a simple pairing of rural and urban sites to show the differences. This shows why homogenization, which smears all the data from urban and rural sites together, is a bad idea, and gives trends that don’t exist in reality.
I like the ending where he says in the rolling credits “Peter’s dad is not employed or funded by any energy or oil companies”. It’s funny that they’d feel a need to say this. No National Science Foundation funding needed either.
This video appeared in comments on WUWT, if anybody knows how to contact Peter or his dad, please advise. We are in touch now.
One wonders what the response of the well funded Hadley Centre, Met Office scientist Dr. David Parker, might be to this video.
Parker’s 2006 paper published in the Journal of Climate titled: “A Demonstration that Large scale warming is not urban” claims:
The analysis of Tmin demonstrates that neither urbanization nor other local instrumental or thermal effects
have systematically exaggerated the observed global warming trends in Tmin. The robustness of the analysis to the criterion for “calm” implies that the estimated overall trends are insensitive to boundary layer structure and small-scale advection, and to siting, instrumentation, and observing practices that increasingly influence temperatures as winds become lighter. Furthermore, even at windy sites (e.g., St. Paul, Aleutian Islands, in Fig. C1), the calmest terce and especially the calmest decile will be strongly affected by occasions with very light winds in passing ridges or blocking anticyclones, and should reveal any urban warming influence.
…the results of the present study also suggest that they have not affected the estimates of temperature trends.
Steve McIntyre gave Parker’s paper a scathing review in 2007’s article:
Wow, that is really good.
It would have taken a lot of work and one doesn’t put this much data together and produce a video if one was using fake data.
In a way, they did something very close to what the NCDC does with the homogenization adjustment – except the NCDC is using more than a pair of stations.
Give the adjustment from the NCDC’s homogenization adjustment – the Maximum daytime temperature is adjusted UP 0.45C from the raw numbers, 0.225C for the average Mean temperature – they must be using the urban stations to spot potential errors in the rural stations so they can they adjust the rural stations up.
You couldn’t use the presentation above and somehow adjust the Mean UP by 0.225C. If they were looking for UHI bias, they would be adjusting it down rather than up.
This really needs to be sorted out and people should be removed from their positions if this is what they are doing.
I scan the comments to the articles on a daily basis at The Huffington Post et al, to measure what I call the “Mass Brainwash Index”, that publication being one of the best places to get accurate results from the populous. Six months ago my index was at a reading of 9.5, 10 being the most brainwashed and 0 being the least. Today my Index has fallen to a reading of 7.5. Something dramatic is happening to the psyche of the American population.
The experiment was simple and elegant. What a great learning experience for the young man!
Most impressive to me was the clear-cut conclusion, without extravagant claims.
Something’s very wrong with this little analysis. Where’s the characteristic shape of the 20th century warming in the USA? There should be a warm bump in the 1930s. Even if you argue the warm bump is artificial, it should be in the urban trend line.
It’s pretty obvious that this thing is not real.
Anthony — you know what the trend looks like from the best rural stations. Steve McIntyre did it a couple of years ago. The most cursory reality check makes it obvious that there’s something very wrong here.
I posted a link to this You Tube video on RealClimate at 7:53 Eastern Time. It is in moderation. I wonder how long Gavin Schmidt will allow this one on the websited before it is removed.
Guess I will check back in an hour or so.
If Hansen had more funding he could have eliminated all these rural sites by now.
Steve McIntyre watch your back. This kid is after your job!
Well done Peter and helper.
subtitle for this post:
disproving AGW
…. so easy , a caveman can do it :))
JohnV (16:55:11) :
JohnV is right that we should be looking for these things, but the warm 1930s was almost exclusively just 1934 for the US as a whole.
Here is the US monthly anomaly (which doesn’t look far off what they produced).
http://img44.imageshack.us/img44/3491/usmonthlyanom.png
Good read;
The Myth of Neutral Academic Peer Review Exploded
http://www.lewrockwell.com/north/north791.html
Re: JohnV (16:55:11) :
JohnV, good question. If you go to that web page and click on Oklahoma, you’ll see rises in temperature in the ’30’s on the rural sites (I checked about 7 random rural sites and they all showed a bump in the ’30’s).
Like I said on the thread this was introduced, this would make a great segment on Fox News. However, as I cautioned there, we need to make sure the rural stations are not cherry picked.
Fantastic seeing kids doing real science instead of being spoon fed AGW garbage like this latest piece of rubbish on ClimateGate from New Scientist:
http://www.newscientist.com/article/dn18238-why-theres-no-sign-of-a-climate-conspiracy-in-hacked-emails.html
– “… with its talk of manipulation and “tricks”. But raw data almost always has to be “fixed”. ”
– “Manipulating data is what scientists do.”
– “…highlighted temperature reconstructions like the “hockey stick” graph because they are easy for people to understand, but in scientific terms they are not of great significance.”
-“…he calls on other researchers to delete certain emails. While on the face of it this does not look good…”
– “But nothing in them justifies claims of a massive conspiracy, or undermines the certainty about climate change and its causes.”
I notice most people assume UHI is not significant in populations below 10,000. I’d hazard a guess that UHI is in effect anywhere close to any human habitation.
I regularly visit a small country town, population less than 2,000. The weather station is in the yard behind the Post Office. Now I have read that the effects of global warming will be seen mostly- at night; in winter; at the poles. On a cold winter’s morning there may be a light frost in the town but on the open flats outside town there will be a heavy frost. The minimum temperature recorded might be 3 degrees C (and frost!), but I bet it’s a lot colder out of town. Out in the bush, a heavy frost might come right up to the house, whereas a light frost won’t.
Now I do think we’ve got a bit warmer over the last 30 years, but not much. And I don’t think land based thermometers can be relied on to measure it.
tallbloke (12:35:59) : Give the lad a scholarship at UEA. NOW!
==========
Lord, I wouldn’t wish that on anyone, let alone a decently bright kid! Not to mention, there’s nothing good he’d learn from them and they’d be at him day and night with Orwelllian doublespeak trying to convince him of the joys and benefits of ‘post-normal science.’ It’d make more sense to give the CRU ‘Team’ scholarships, to be paid out of their own already awarded grant money (out of their own pockets far better, actually), to study under the direction of the University of Peter & Dad
– except I wouldn’t want to inflict the ‘team’ on Peter and Dad either!
I picture them like a dozen Gollum’s from Lord of the Rings, all pawing and scrabbling round Peter & Dad crooning about their ‘precious post normal science,’
trying to pull them both down to trample all over them.
Give the boy a scholarship under someone who’s a REAL scientist!! Or under someone like Macintyre if he prefers a different discipline. Transfer the UEA grant money too.
The vid really does put the entire ‘climate’ society to shame, doesn’t it? KUDOS!!
tallbloke (12:35:59) :
Give the lad a scholarship at UEA.
NOW!
Do you want to stigmatize the poor boy for the rest of his life?
I see you were a financial modeller?
Yes.
In what area?
Sub-prime mortgages.
Ok, thanks for your interest.
I see you have a Phd in climatology.
Yes.
From which university?
UEA…..
Regarding the 30’s, I suspect they did straight averages instead of moving averages and may have ended up flatlining the seasonality.
Peter’s dad here again. Just to answer a couple of questions. We used the data set “after combining sources at the same location.” It was just easier (I had to set up the excel spreadsheets by hand). If there was more than one rural site near the urban site we tried to use the one furthest away from the urban site but within the 100 km limit. A things being considered, you actually should use the ones with the lowest increase just because it should be the one least tainted by urban heat. But this gets into a circular argument about whether or not the data is “cherry picked.” If warming is a global effect then you can’t “cherry pick” the data. Anyway, we did the best we could.
Here are the site we used.
Hemlock 42.8 N 77.6 W 425725230070 rural area
Rochester Airport 43.1 N 77.7 W 425725290030 1,062,000
Roosevelt 1wnw 33.7 N 111.2 W 425722780080 rural area
Phoenix/Sky H 33.4 N 112.0 W 425722780003 2,395,000
Maryland 6sw 42.5 N 75.0 W 425744800010 rural area
Albany/Albany 42.8 N 73.8 W 425725180000 851,000
Smithfield 35.5 N 78.3 W 425723060010 rural area
Raleigh/Ralei 35.9 N 78.8 W 425723060001 856,000
Newnan 4ne 33.4 N 84.8 W 425722150010 rural area
Atlanta/Mun., 33.6 N 84.4 W 425722190001 2,960,000
Vevay 38.8 N 85.1 W 425744680030 rural area
Cincinnati/Gr 39.0 N 84.7 W 425724210000 1,818,000
Whitestown 40.0 N 86.3 W 425724380100 rural area
Indianapolis/ 39.7 N 86.3 W 425724380001 1,380,000
Kingfisher 2se 35.9 N 97.9 W 425723530020 rural area
Oklahoma City 35.4 N 97.6 W 425723530001 959,000
Tombstone 31.7 N 110.0 W 425722730040 rural area
Tucson U Of Az 32.2 N 111.0 W 425722740020 667,000
Colfax 39.1 N 121.0 W 425745000010 rural area
Sacramento City Usa 38.6 N 121.5 W 425724830031 1,481,000
Lemon Cove 36.4 N 119.0 W 425723890010 rural area
Fresno/Air Te 36.8 N 119.7 W 425723890000 756,000
Los Lunas 3ssw 34.8 N 106.8 W 425723650020 rural area
Albuquerque/I 35.0 N 106.6 W 425723650001 589,000
Saint Peter 2sw 44.3 N 94.0 W 425726490010 rural area
Minneapolis 44.9 N 93.2 W 425726580000 2,539,000
Philo 3sw 39.8 N 81.9 W 425725210010 rural area
Columbus United 40.0 N 82.9 W 425724280000 1,345,000
Hood River Experiment Stn 45.7 N 121.5 W 425726980080 rural area
Portland/Int. 45.6 N 122.6 W 425726980003 1,414,000
West Point 41.4 N 74.0 W 425725030050 rural area
New York Central Park 40.8 N 74.0 W 425725030010 8,000,000
Arcadia 27.2 N 81.8 W 425747960020 rural area
Fort Myers Faa Ap 26.6 N 81.9 W 425747960010 309,000
Boerne 29.8 N 98.7 W 425722530080 rural area
San Antonio/I 29.5 N 98.5 W 425722530000 1,324,000
Inverness 3se 28.7 N 82.3 W 425722110030 rural area
Tampa/Int.,Fl 28.0 N 82.5 W 425722110000 1,995,000
Santuck 34.6 N 81.5 W 425723120050 rural area
Charlotte/Dou 35.2 N 80.9 W 425723140001 1,162,000
Morgan Como Springs 41.0 N 111.7 W 425725720060 rural area
Salt Lake Cit 40.8 N 112.0 W 425725720000 1,072,000
Amite 30.7 N 90.5 W 425722330030 rural area
Baton Rouge Wso Ap 30.5 N 91.1 W 425722310090 470,000
Gardiner 44.2 N 69.8 W 425743920020 rural area
Portland/Intn 43.6 N 70.3 W 425726060000 184,000
Lowville 43.8 N 75.5 W 425743700010 rural area
Syracuse/Hanc 43.1 N 76.1 W 425725190000 642,000
Angelica 42.3 N 78.0 W 425725230030 rural area
Buffalo/Great 42.9 N 78.7 W 425725280000 1,189,000
Cuyamaca 33.0 N 116.6 W 425722930010 rural area
San Diego/Lin 32.7 N 117.2 W 425722900004 2,498,000
Brinkley 34.9 N 91.2 W 425723400040 rural area
North Little 34.8 N 92.2 W 425723400002 513,000
Albia 3nne 41.1 N 92.8 W 425725460010 rural area
Des Moines/Mu 41.5 N 93.7 W 425725460003 392,000
George:
I don’t understand. The annual average temps in the lower-48 were warmer in the 1930s than in the 1970s.
By the way, I am not arguing that UHI is not real. But this analysis doesn’t seem right.
“This video appeared in comments on WUWT, if anybody knows how to contact Peter or his dad, please advise.”
The credits at the end are a clue. http://www.atticanimations.com/
Peter Gundling
Send that link to he Senate floor. i wonder what Kerry would say?
hunter (14:57:31) “The annoying thing is that at this point, AGW believers and promoters asre in such denial of simple reality that they dismiss any and all counter evidence presented to them.”
Indeed, throwing red meat to partisan loyalists while preaching to the choir just camouflages a marathon as a sprint. Opposing a religion is tricky, sensitive business and the going is sure to be painfully slow – excruciatingly so. Science funding remains politically hijacked, so straightforward logic is not even furnished with a voice at this stage. It is patently delusional to think now is a time for resting on laurels. Folks with a short fuse can’t dominate the game as it is presently structured. The leaders who can win this war will be the ones with long-term vision, not the ones who noisily insist on choosing short-term battles unwisely.
CodeTech (12:44:40) :
Those were his peers.
My friends are always happy to tell me when I’m full of it. If they say nothing, it’s ok.
Excellent stuff by Peter (and Dad). Actually, I’m inspired. I thought I might try my hand by downloading some GISS data and subjecting it to some Monte Carlo Markov Chain (MCMC) analysis. Essentially, to start with, much the same as Peter’s analysis – except with a strongly Bayesian flavour. I’ve recently had to apply this technique to noisy power metering data to detect systematic bias of individual meters and establish bounds on the hidden ‘real’ signal. The UHI effect is essentially the same problem, it would seem, so I will simply adapt my existing programs.
Peter’s dad here again. Just another little clarification. Our data does show the warm “bump” in the 30’s, then cooling in the 60’s and 70’s. Our data set actually has 1921 as having the highest average annual temperature and this may obscure the “bump.” This data set is limited and is not meant to show anything other than a difference between two sets of data, the rural set and the urban set. We are now compiling new data sets and we hope to have a new video. It is difficult because there really are not that many sites that have good consistent readings. By the way, I am a molecular geneticist. I work in a laboratory daily and do a fair amount of data analysis. We are using a fairly simple excel analysis here because usually simple is better. I may use JMP next time. Peter and I again thank you for your interest.