by Roy W. Spencer, Ph. D.
This is an update to my previous posts [here and here on WUWT] describing a new technique for estimating the average amount of urban heat island (UHI) warming accompanying an increase in population density. The analysis is based upon 4x per day temperature observations in the NOAA International Surface Hourly (ISH) dataset, and on 1 km population density data for the year 2000.
I’m providing a couple of charts with new results, below. The first chart shows the global yearly average warming-vs-population density increase from each year from 2000 to 2009. They all show clear evidence of UHI warming, even for small population density increases at very low population density. A population density of only 100 persons per sq. km exhibits average warming of about 0.8 deg. C compared to a nearby unpopulated temperature monitoring location.
In this analysis, the number of independent temperature monitoring stations having at least 1 neighboring station with a lower population density within 150 km of it, increased from 2,183 in 2000, to 4,290 in 2009…an increase by a factor of 2 in ten years. The number of all resulting station pairs increased from 9,832 in 2000 to 30,761 in 2009, an increase of 3X.
The next chart shows how the results for the U.S. differ from non-US stations. In order to beat down the noise for the US-only results, I included all ten years (2000 thru 2009) in the analysis. The US results are obviously different from the non-US stations, with much less warming with an increase in population density, and even evidence of an actual slight cooling for the lowest population categories.
The cooling signal appeared in 5 of the 10 years, not all of them, a fact I am mentioning just in case someone asks whether it existed in all 10 years. I don’t know the reason for this, but I suspect that a little thought from Anthony Watts, Joe D’Aleo & others will help figure it out.
John Christy has agreed to co-author a paper on this new technique, since he has some experience publishing in this area of research (UHI & land use change effects on thermometer data) than me. We have not yet decided what journal to submit to.
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“The US results are obviously different from the non-US stations, with much less warming with an increase in population density, and even evidence of an actual slight cooling for the lowest population categories.”
Am I reading this right? Did I misinterpret your original analysis? Doesn’t the above statement run counter to the original work? I thought we saw greater warming in rural areas with an increase in population density?
I like the log scale on the x axis.
This is EXTREMELY useful, thankyou Spencer and Watts. Poor warmists..
If anyone wants an easy overview of UHI around the workd, read:
“Urban Heat Island – World tour” / http://hidethedecline.eu/pages/u-v-w.php
James…my original results were based upon the year 2000 only, and (as I recall) global data…not US-only.
Also, I have changed to log-plots, since (as you mentioned) warming in the global average IS much stronger at low population densities.
How does the UHI correction vary with latitude?
Golly, they are quite consistent !
– I have to ask though; Could the results somehow be wierd artifacts of the altitude corrections?
( I cant quite think how exactly, but I suppose the question is; is there any trend in the altitude correction when plotted against the population?)
I appreciate that this is a miserable response to an awesome piece of work!
I think the US / Non-US labels are swapped in the 2nd graph?
Cool analysis!
(Well, er, uhm, “not a cool” analysis…. A hot analysis, maybe?)
(That will get ignored by the mainstream ABCNNBCBS “news” centers.
“We have not yet decided what journal to submit to.”
I would advise avoiding announcing which once you do decide. You could run into trouble with the gatekeepers.
This is really important – we all know that there is a logarithmic decay in the IR trapping capacity of CO2 as concentration increases. That is true as long as the rate of IR remains constant; one can add more CO2 without much additional heat retention for the simple reason that there just isn’t any additional IR in the correct wavelengths for additional CO2 to absorb.
BUT, if we are adding more heat AND more CO2, ther is scope for additional heat trapping.
In this scenario, it is land use which is the most important factor and the one whihc is most easily changed. Simply changing from asphalt (low albedo) to concrete (high albedo) would result in a HUGE reduction in the amount of insolent radiation converted from short to long wavelengths. So-called green rooves would also make a difference in urban settings. These are things which are easily implemented and don’t disrupt civilization.
I would hazard a guess that applying this a UHI correction based on the above would reduce the GMST trend significantly.
It would be interesting to see each observation time broken out. I suspect night-time will show as the largest deviation, and its signal may be being watered down by the others.
Error bars?
Would be very nice to see the pattern by geographic region or in latitudinal bands – it might help to explain what is going on.
UHI remain something of a mystery to me. The general notion is obvious, and virtually self-evident (despite the “possibly negative” results that John shows!), but the manner in which fairly well established numbers for urban warming are used seems to my poor brain to be lacking in clarity. We see long postings or papers that describe in detail some numerical values that describe the effect, but I seem to have missed some vital information that would set in stone the way in which these numbers are to be used. Let’s say that it has been established to everyone’s satisfaction that the urban heating effect for a particular place (called Town) is 1.4 degrees C. To me this means that if a series of actual temperature measurements is made at Town, and then reported in the literature as 10.0, 11.0, 9.4 and 7.1C, I, the user, should put them into my computer as 8.6, 9.6, 8.0 and 5.7C . Is this wrong? If so, what should I believe about the real temperature at Town. Should I accept that Town has recorded 10.0, etc and that this is the value to be included in my archives and analyses, or that Town has already done its subtraction sums (and thus their thermometer actually read 11.4, 12.4 etc).
These may be stupid questions, but I would really like to have a clear answer. Can someone help me please?
Robin
And now – what do we know about the AHI? The Airfield Heat Island effect.
These graphs are much easier to read. Is that a Hockey Stick in the U.S. temps? :>0
Dr Spencer,
Ron over at the whiteboard was doing some data with gridded population density datasets.
Somehow Jeddah,Riyadh,Dharan,Basrah,Najaf,Sulimaniyah,Kirkuk, Mosul and Damascus all ended up in his rural dataset. Those were just the cities I was familiar with.
I would urge caution using some of the international datasets. A liberal dose of random checking via google earth can save a lot of embarrassment.
Night lights tells part of the story, but that can lead to false rurals in areas that are electricity deprived.
Dr. Spencer:
I believe the key to why the UHI doesn’t show on all years is where the UHI is showing up: In the nighttime temps and in the warm season (by a factor of 2-1 from what I have seen so far).
So that would mean digging down to specific site conditions( cloudiness, RH) to find a common denominator.
“Doesn’t the above statement run counter to the original work? I thought we saw greater warming in rural areas with an increase in population density?”
– its the log scale that’s throwing you off, I think. There is still a much higher temp gain per population gain at the low end.
Dr. Roy could you tell me what is the phase relationship of the red pyramids in this video http://www.youtube.com/watch?v=II9jLTzPv30 to the Synod conjunctions with the outer planets?
I would surmise that they lead the timing of the peak warming by about 3 to 5 days, about the same time as the Ice peaks before dropping off through the peak heating and most of the cooling phase.
My question is what is the relationship, if there is one at all, between the outer planet Synod conjunctions, and the phase of this composite signal you have found. I know you haven’t looked yet, but let me know when you do.
Way to go Spence! Finally there is the ~0.2C convergence near the global mid sea temperature that increases over last few decades. Here’s my take: back out the cities UHI influence and there is the solar grand maximum’s influence that also occured on the other planets. Good work!
“James Sexton (12:08:01) :
[…]
Am I reading this right? Did I misinterpret your original analysis? Doesn’t the above statement run counter to the original work? I thought we saw greater warming in rural areas with an increase in population density?”
As population density increases you move to the right in Dr. Spencer’s graph and it gets warmer. That’s how i would read it.
For the fact that the U.S. behaves differently than the rest of the world, i suspect it might be because the U.S. already had a high per capita energy consumption in 2000 which might not have risen as much during the last 10 years as per capita consumption in less developed countries. It should be reflected in the high GDP growth rates of, say, the BRIC countries. Just a guess.
This obviously confirms UHI and puts some scale to it. But could you please explain why the graph starts at 0.2 as I would have thought that as the temperatures are relative to population they would have started at zero.
And just a quick thought, from a glance at the annaul global average temperature anomalies the biggest anomalies on your graph appear roughly inverse to those of the temperature anomalies. Does that suggest that urban centres are less impacted by year to year changes or have a mechanism to regulate their temperatures (turning heating on and off for instance)
this uhi effect i may have missed the point, does this apply equally to satellite data, this is something that one feels should have been analysed years ago, ie are temperatures higher because of population and can they distinguish on the grids like they can with these weather stations, do they measure 1 km square portions of the atmosphere as well. ppresumabley data beneath a certain atmospheric level would be more useful. i presume these statistics are probbly somewhere as i remember the satellite data average various areas of land threoughout the globe…………….
This is is interesting, what we need to go with this is a map of global population density to get a feel for how much we are warming the landscape from our activities. I find the lower US figure puzzling, I wonder if this is related to pollution?