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.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
“”” Bill Illis (17:14:59) :
George E. Smith (16:31:09) :
Almost everything in the climate exhibits a logarithmic nature.
Temperature itself is logarithmic with respect to the energy which drives it so we should expect to see it here as well. “””
That seems a little odd; evidently climate and Physics behave somewhat differently.
My Physics Handbook gives the Total Kinetic Energy for an (ideal) gas as being (3/2)N.k.T where N is the number of particles, or the mean Kinetic energy per particle as (3/2)kT, which would then seem to apply also to a non-ideal gas since it is a per particle (molecule) energy. k is of course Boltzmann’s constant.
So that must not be the energy that drives the Temperature, since it is quite linear with Temperature, rather than logarithmic.
I guess I need some Climate text books, to see how it is different.
Could get at land use effects by comparing rural temperatures in Dominican Republic vs Haiti. The differences in land use are striking, unrealted to climate.
Dr Spencer – fantastic, creative work. Agree – needs to be published as a paper, but I would give it as a talk at any local meteorologic or geologic society to ensure retention of IP.
My guess is – Mr Watts would concur given the rough treatment HE received.
You should be proud. Awesome breakthrough.
George E. Smith (18:18:04) :
http://img524.imageshack.us/img524/6840/sbearthsurfacetemp.png
You can extent this chart out (ending at 456 W/m2) to 63,250,000 W/m2 for the surface of the Sun and the temperature derivation of 5,779K will be correct.
The Sun needs to add 43,800 W/m2 to increase its surface temperature by 1.0C while the Earth only needs to add 5.5 W/m2 to increase its surface temperature by 1.0C.
@crucilandia (15:03:31) :
“what is the proportion of global UHI (joules) to the total amount of energy stored on Earth. If it is statiscially significant, this supports the view that man is warming the planet.”
– – – – –
If you want to estimate anthropogenic joule heating of the globe, you need to take the ratio of total anthropogenic joules to incoming sun joules (insolation) for the same time period. First subtract all anthropogenic joules generated from renewable energy sources (wind, solar, hydro) since those are just the sun’s energy redirected. This is a very rough estimate.
Total anthropogenic joules /yr = 8 sec solar insolation (joules)
The ratio is approximately 1 to 3.9447 million
[anthropogenic joules + incoming sun joules] /incoming sun joules x 100% =
100.0000254%.
This is a 0.0000254% (254 ppb) increase in heat due to humans.
Dr Spencer, why did you decide to use GMT times globally rather than local sidereal time?
I bet Joe the plumber, (Joe six packs brother) could tell you the average time it takes to freeze plumbing in an empty house when the power goes out, Just from looking back at his emergency work call logs. I would bet it runs less than 72 hours with highs @ur momisugly 40 F and lows @ur momisugly-10F.
> Bill Illis (17:14:59) :
>
>Temperature itself is logarithmic with respect to the energy which drives it so we >should expect to see it here as well.
Temperature is a measure of average kinetic energy of the modes of molecular motion. So, it’s a direct measure of molecular energy, so long as the modes of motion don’t decouple. An example of decoupling is the fact that electrons in a fluorescent lightbulb have a temperature of thousands of degrees F, while the heavy ions are basically at room temperature. This knowledge was a huge breakthrough in physics and, surprisingly, it isn’t really clearly stated at the undergrad level.
Dr Spencer; After examining your graph I would offer this for U.S. land use. 1 to 5 per km2 is real farm and rural densities, open land, very few homes with little AC and some heating. 5 to 50 is funny farm to suburban, lots of trees and grass and a few high quality homes with HVAC. Over 50, high density, lots of roofs, pavements and building HVAC. The change in land use from real farm or rural to gentel farm and estates would cause quite a drop in local temperatures due to shading and ground covers.
Bill Illis (17:14:59) :
Temperature itself is logarithmic with respect to the energy which drives it …
A few links on temperature relating to various energies:
(don’t think simple, it usually isn’t)
http://hyperphysics.phy-astr.gsu.edu/hbase/kinetic/kintem.html#c1
http://hyperphysics.phy-astr.gsu.edu/hbase/kinetic/shegas.html#c1
http://hyperphysics.phy-astr.gsu.edu/hbase/thermo/stefan.html#c2
“David Schnare (16:39:52) :
Roy:
Until you can convince me that the stations themselves are not corrupt for micro-climate influences, your entire approach is as suspect as Jim Hansen’s luminosity approach. I simply don’t see the physics of a massive jump in UHI for population densities below 100 persons per sq. km. Unless you address how much energy has to be generated by the 100 persons to generate a heat capacity that releases in a manner that raises the mean temperature, you are just playing with the numbers. That, itself, is not a bad thing, I suppose. But you need to get confidence in station placement and construction and do the math on the physics before you have even the begining of a credible new UHI analytical approach.
David Schnare, Ph.D.
Center for Environmental Stewardship
Thomas Jefferson Institute for Public Policy”
NICE!
Dr. Spencer’s first refereed comment! Dr. Judy, are you out there?
Like someone else mentioned, this needs to be repeated for each of the 4 temperature readings per day to see when the effect is greatest. Another thought would be to check this in different seasons, all I ever hear is winter is affected more than summer, but will it prove out that way?
“Richard Holle – I bet Joe the plumber, (Joe six packs brother) could tell you the average time it takes to freeze plumbing in an empty house when the power goes out, Just from looking back at his emergency work call logs. I would bet it runs less than 72 hours with highs @ur momisugly 40 F and lows @ur momisugly-10F.”
DeNihilist DePlumber finds that most frozen pipe calls, from occupied houses, occur when there is a strong wind and cold temps. Have gone through 3-4 weeks of calm cold (-3/-8C) with no calls. Yet in a week of 1/-4C with biting winds, the phone never stops!
Harry Lu (17:40:49) :
Armargh pllot as promised.
http://img52.imageshack.us/img52/1456/armargh.png
according to wiki irish pop decrease by 50% from 1840 to 1890. Assuming pop was 185/sq then by 1890 it was 90/sq
This would give a drop of about 0.2degC
This would flatten the initial hump by a bit (1/8th)
So Armargh still shows a warming of about 1 deg C allowing for UHI.
When Willis Eschenbach plotted Armagh back at this post, without such adjustments he got 0.57 deg C/century.
During the late 60’s thru the 70’s, they cut down millions of Elm trees that once created a cathedral-like effect over most of the streets of my hometown 750,000 pop. It was quite cool at street level with the giant Elms in place, and became noticeably hotter when they were cut down. The spread of the disease is well documented, and should have some effect on the local temperature in the cities effected. The Maples, Ash, and other trees that replaced the Elms are now covering the roads for the most part once again.
Also, in the same area, starting downtown where yards are postage stamp sized, the yards grow in size with every ring of suburbs. Many newer subdivisions have 5 acre minimum lot sizes specifically to discourage urban sprawl and long commutes. Suburbs built in the 70’s on farm land now look like forests with houses scattered amongst the trees.
It would be very interesting to know what the temperatures looked like before, during, and after this huge deforestation that exposed all that man-made stuff beneath. At the time, everyone was aware that it got hotter, and they knew why.
Unless you address how much energy has to be generated by the 100 persons
I doubt the heat has been “generated” by the people.
As toyotawhizguy (18:50:14) shows, our efforts to heat pale into insignificance compared to the sun’s effects.
UHI is a largely matter of how much we trap the sun’s heat and then release it slowly overnight.
Wait for a warm, sunny day with clear night. Then compare the temperature in a field with the temperature in a asphalt parking lot (away from artificially generated heat). That’s UHI. Not a joule “generated” by anyone.
Another good test.
Take a snowy grass field and asphalt area. Clear an equal small area of snow from both. Come back two clear days later, and see what has happened.
Lots of snow will have melted on the asphalt, and barely any on the grass, yet not a joule generated by a human to be measured.
“David Schnare (16:39:52) :
Roy:
Until you can convince me that the stations themselves are not corrupt for micro-climate influences, your entire approach is as suspect as Jim Hansen’s luminosity approach. I simply don’t see the physics of a massive jump in UHI for population densities below 100 persons per sq. km. Unless you address how much energy has to be generated by the 100 persons to generate a heat capacity that releases in a manner that raises the mean temperature, you are just playing with the numbers. That, itself, is not a bad thing, I suppose. But you need to get confidence in station placement and construction and do the math on the physics before you have even the begining of a credible new UHI analytical approach.
David Schnare, Ph.D.
Center for Environmental Stewardship
Thomas Jefferson Institute for Public Policy”
The “energy” does not need to be generated by the 100 persons, it just has to be stored in the nice new concrete and tarmac and re-released during the hours of darkness. Although this also has to be quantified.
Ed
Dr Spencer,
I should apologise for the flippant post that I made when you first reveiled that you were trying to quantify the UHI effect. I suggested that such an enterprise was futile in view of the complexity of the task.
However, having taken the trouble to look at what you have done on the subject, I would like to say that I am very impressed by the power of your approach and I believe it could well develop into the definitive work.
I expect that as Dr Spencer continues his research, his findings will become clearer. At the moment it is not clear to me what he is attempting, but maybe I just don’t understand what he is trying to say.
Just looking at the first chart, which plots the urban heat island warming in degrees celsius against population density, it appears that he is saying that even areas that are by no means urban nevertheless demonstrate an urban heat island warming, which is quite substantial. Even those places that have a very low population density (3 people per sq km) have a measurable UHI warming of between 0.17C and 0.3C, according to the chart. Or maybe I have misunderstood the labels on the axis.
Three people per sq km is each person on average occupying the equivalent of about 330 quarter-acre house blocks, if my calculations are correct, which is not normally considered urban.
Places with only ten people per sq km have a UHI warming of between 0.37C and 0.78C. This population density is the equivalent of each person on average occupying the equivalent of almost 100 quarter acre blocks. This doesn’t seem to be urban either.
I hope someone will be able to clarify this.
Dr Spencer
We call cities, towns and hamlets “Heat Islands”, from your perspective at UAH aren’t they more like factories with smokestacks, of various sizes of course? If so, aren’t these various sized smokestacks pumping heat into the atmosphere in a way similiar to all smokestacks? Doesn’t the “smoke/heat” move vertically and then, at a certain level in the atmosphere, start to move in a horizontal direction? Isn’t this average level near the same level your spacebased readings for monthly global temp anomolies are measured? To get a picture of actual surface temperatures, might not space readings at a lower level -closer to the surface- be equally significant; and for day-to-day ‘people environment temps’ perhaps more significant?
I’ve just posted a comment on the discussion of the original UHI paper of Dr Spencer’s, wattsupwiththat 03/03/2010, explaining how I think that Dr Spencer’s method can only result in an overestimate of the UHI. I outlined a test to confirm this there.
There are clearly other problems too. All the graphs presented here seem to rely on differences at population densities less 20 persons per square km. These are then integrated up. Once past 20 persons per square km all graphs seem about parallel. I suspect that the differences seen between years and areas are largely down to errors in the analysis or underlying assumptions at these low population densities. Perhaps this could be checked by dropping random stations from the analysis? Randomly ditch half the low population stations and see what happens. Or ignore all stations in a particular population bin – say bin no. 2 – and rely on comparisons spanning across that bin (bin no. 1 to bin no. 3). If the analysis is robust these sort of tests should not effect the outcome significantly. The fact that the results can be changed significantly by the addition of interstation comparisons within the lowest bin suggests it is not robust.
I think that this could form a useful basis for estimating the UHI but at the moment the problems and unknown errors in the methods render it all largely meaningless.
So I guess the next question is this: can you, from such data, make a ‘reasonable’ adjustment to temperature records of urban stations to determine what residual warming signal remains after UHI effects are eliminated??
The other question I pose is this one: what percentage of the earth is ‘unpopulated’? And hence what is the ‘true’ ‘global temperature change’ if you factor in the small % of the earth which has a UHI signal????
It’s always amazed me that some people actually think that things such as asphalt, airplanes, cars, and air conditioners among other things can’t contribute to a bias in temperatures. Some have even gone so far as to say that the bias in temperature is insignificant.
Looking forward to reading the paper.
Mooloo, Toyota,
My back of the envelope calculations on electrical consumption gave an average “urban” forcing of ~2.7 W/m2 (did not account for any other type of fuel consumption like natural gas, heating oil, or those heat engines we climb into every day to go to work).
Averaged out for the earth’s surface, our ~18 TW of electrical consumption is just noise, but when you consider that at least 50% of said consumption is concentrated on just ~1.5% of the earth’s land surface (not to mention the heat island effects around power plants probably in the neighborhood of 36 TW’s worth of forcing) then I think it’s safe to say that power consumption could constitute a significant local effect.
That said, I do agree that this is a relatively minor variable in comparison to the effects of albedo and thermal mass due to land use changes.
Pascvaks (05:20:42)
That is a very interesting point, on non-windy days heat island signatures should be able to be seen in the satellite records due to convection.
Of course, there is the question of resolution for the satellite records (which I don’t know the answer to, I’d think it could do 1 km2 maybe) and what you’d be looking for would be real temps I bet… or maybe I’m the only one who thinks the whole anomaly analysis just confuses/obfuscates.