Joe D’Aleo suggested earlier today that I take a look at some of the data from NCDC’s web page called “US climate at a glance“. This page allows comparisons of the actual data not anomalies used in the NCDC USHCN Surface temperature network. The NCDC web page allows you to compare and not only the nation but states and cities as well using the actual USHCN data. Joe’s interest was the urban heat island effect (UHI) in cities in Texas. First let’s take a look at the state of Texas itself for the last 100 years:
Source: http://www.ncdc.noaa.gov/oa/climate/research/cag3/tx.html
As you can see the trend is essentially flat, with the trend equaling 0.01F Per decade over the last 100 years. That trend by itself is interesting, but there’s a lot more of interest when you look at the cities individually.
Here is a list of cities in Texas based on population size, this table is from Wikipedia:
| Rank | Population | Place name |
|---|---|---|
| 1 | 2,099,451 | Houston |
| 2 | 1,327,407 | San Antonio |
| 3 | 1,197,816 | Dallas |
| 4 | 790,390 | Austin |
| 5 | 741,206 | Fort Worth |
| 6 | 649,121 | El Paso |
| 7 | 365,438 | Arlington |
| 8 | 305,215 | Corpus Christi |
| 9 | 259,841 | Plano |
| 10 | 236,091 | Laredo |
| 11 | 229,573 | Lubbock |
| 12 | 226,876 | Garland |
| 13 | 216,290 | Irving |
| 14 | 190,695 | Amarillo |
The third largest city in Texas by population is of course Dallas. Unfortunately, Dallas only has data going back to 1948 according to the NCDC pages that allow selection. So will use 1948 as a starting point for comparison, here then is the statewide trend since 1948:
The Decadal scale trend from 1948 to 2011 is 10 times larger than that of the last 100 years at 0.10 Fahrenheit per decade.
Now let’s look at major cities in Texas available from the NCDC cities page, first Dallas:
Source: http://www.ncdc.noaa.gov/oa/climate/research/cag3/city.html
The decadal-scale trend in Dallas is almost three times larger than that of the state of Texas at 0.28 Fahrenheit per decade.
Now let’s have a look at the largest city in Texas, Houston:
Being the largest city, one might expect that Houston would have a larger trend than Dallas, however it should be noted that Houston has a strong ocean influence from the Gulf of Mexico. So, one would expect that it’s trend would be muted compared to an inland city.
Corpus Christi is another Texas city that has an ocean influence. It’s decadal-scale trend is also somewhat muted by comparison:
It is also a significantly smaller city with less growth:
San Antonio however being the second largest city is well inland away from the ocean – look at its trend:
At 0.41 Fahrenheit per decade, it is four times larger than the statewide trend from 1948 to 2011. The population of San Antonio looks like a hockey stick, especially after 1940:
According to the Wikipedia entry on San Antonio: “It was the fastest growing of the top 10 largest cities in the United States from 2000-2010, and the second from 1990-2000.”. So I suppose it is no surprise to find it having such a large temperature trend compared to other Texas cities and the state itself.
El Paso, TX:
Like Corpus Christi, El Paso didn’t grow quickly either.
Amarillo:
Amarillo didn’t see wild growth like San Antonio.
So what can we conclude from all of these comparisons? First, I’d like to point out that this is not a definitive comparison, as it is lacking many of the cities in Texas but these are the cities that were available from the NCDC page.
But, what we can conclude with certainty is that all of the (available) cities plotted from NCDC Data at “US climate at a glance” show a decadal-scale trend that is larger than the decadal-scale trend for entire state of Texas for the same period. Of course, Texas being composed of wide open range has many USHCN stations that are not in populated areas. Thus, it is not surprising to see that the state of Texas has very little trend while Texas cities have a significantly greater trend.
Dr. Roy Spencer has found more UHI examples in Roy Spencer’s ISH population adjusted discoveries. He writes:
The bottom line is that there is still clear evidence of an urban heat island effect on temperature trends in the U.S. surface station network. Now, I should point out that most of these are not co-op stations, but National Weather Service and FAA stations. How these results might compare to the GHCN network of stations used by NOAA for climate monitoring over the U.SA., I have no idea at this point.
@Joe D’Aleo
> Thus, it is not surprising to see that the state of Texas has very
> little trend while Texas cities have a significantly greater trend.
So, Joe, would it be fair to say that you agree, qualitatively, with the AGW crowd that ‘man-made activities’ (i.e. urban heat islands) have created measurable increases in Texas temperatures over the past century. But you disagree, quantitatively, on how those increases are distributed?
REPLY: Joe didn’t write that, I did. I disagree with the way the data is homogenized, combining the good stations with the bad ones for a smeared around data result that is claimed to be representative – Anthony
In the 1970’s oil shock the idea of “thermal mass” for storing energy/heat was talked about a great deal. Cities by their very existance have thermal mass. Black top roads and concrete buildings who would have thought they can get hotter than grass and trees. Ever listen to an announcer tell you the temperature on a baseball field at stadiums with artificial turf?
The other side of the coin is the data from sites NOT in/near UHIs. In Texas this would mean sites not near the cities listed above, those with about 200,000 or more population. What do the temperature data show for these sites?
More data to back up E M Smith’s great work, and suggest to Steve Mosher that although his sums are fine, his parameters need re-examination perhaps.
And of course, a whole pageful of UHI studies here. I shall now add Anthony’s excellent study here to that page as soon as I get a chance – and as soon as I can cope better with my own arm RSI. Thank you again Anthony for keeping this important issue up front. Hope your own hand healing process is being protected from further strain.
This post goes to the heart of my argument: the inconsistency of CO2-caused warming. If little warming is shown state-wide, yet the big cities are rapidly warming, then many places must be cooling.
Why does CO2 allow those non-urban areas to cool?
See http://sowellslawblog.blogspot.com/2012/05/warmists-are-wrong-cooling-is-coming.html
And the portion following:
“This is from Abilene, Texas which is right out in the middle of the state, a little bit west of Dallas. It shows absolutely no warming whatsoever for the past 110 years or so. The slope here, and you probably cannot read that, is actually negative. It is -0.19° per century, round it off -0.2. From an earlier slide [Figure 1], remember we were looking at a warming trend of about 0.6° per century, which is what the warmists are saying. I want to know why it ignored Abilene?”
Kristen Byrnes (Ponder the Maunder) — 1
Al Gore (Post Turtle) — 0
It’s official, CO2 causes *extreme* population growth.
😉
Like Tadchem, I reckon that if all major cities show a greater temperature rise than the State as a whole, then rural areas must show a decline. The only way to display global temperatures is to eliminate all urban sites. That blows AGW out of the water.
with TX cities, you also have to consider the huge amount of growth in the suburbs outside the city limits. the last 15 years has seen a large influx of people to the states major metro areas. in Houston, you can see where large areas, 20-30 miles out from the city, that used to be woods in the 90’s are now parking lots, subdivisions and strip malls…
Without looking at the data – is it that in rural areas that temperature has shown little or no change and that ‘adjustments’ for UHI are far, far less than the recorded amount of change when compared to rural temperatures thus leading to the deceptive appearance that Texas has seen a rise in temperature ?
Be interesting to see unadjusted average temperatures of the rural areas plotted against the same in urban areas to see how far off the ‘adjustments’ for UHI are in Tx.
The trend may look flat. But just wait until the past gets cooler.
Take the data from the top cities out and see what happens for the rest of the state.
Perhaps there are better ways to handle UHI that are better than a simple across the board CO2 type tax
John Day: ” ‘man-made activities’ (i.e. urban heat islands) have created measurable increases in Texas temperatures over the past century”
Don’t confuse temperatures of Texas cities with temperatures of the state of Texas. Just because the roof of your house is very hot does not mean that your backyard is the same temperature.
KTWO says:
June 28, 2012 at 11:12 am
“The trend may look flat. But just wait until the past gets cooler.”
As I noted in another post, even the Weather Channel had a brief item last night re the UHI phenomina though, at least in the part I saw, did not relate it back to the mismeasurement of overall temperatures. The past may not get cooler in the UHI areas as concrete and roof areas increase over time.
Somewhat OT, but the SCOTUS ruling on the AHCA today dealt a blow to using the Commerce Clause indiscriminately. This will have widespread ramifications on various regulatory agencies who rely on it as their legal right to regulate many things. Including issues related to food, farming, water, etc. We’ll have to wait and see, but I think it will be of benefit in reining in the EPA, USDA, and others.
Of course, you know that the UHI effect can be seen as evidenced in the higher-res IR satellite imagery for some of these cities (like Dallas) as evening turns into night and radiative cooling takes place in the countryside …
.
This is pretty good data as it puts a few myths to rest.
1. Most studies of UHI ( like Oke ) focus on UHI MAX. that is the maximum UHI that
a city can see. To do this researchers cherry pick the days to study. They study
days that have the optimal synoptic conditions for UHI: no wind, no clouds, no precipitation
in the previous days leading up to the observation. This is all well and good for capturing
the maximum, and you will see figures like 2C, 4C, and higher. But this is not average
UHI. Average UHI is what biases the record so we need a good estimate of the average
which means we need to look over time.
2. Its unfortunate that the data was presented in F. But we can fix that. First thing we have to note is what the literature already shows for a range of UHI Bias. Now most of this
is for large cities, but generally the bias is anywhere between .05C per decade to .125C
per decade for cities and regions such as : large US cities, tiawan, korea, china, japan,
and London.
What do we find in texas for 1948 through present, a baseline trend of .1F decade
for a quick and dirty estimate of the UHI bias added above this trend we have
Dallas: UHi ads approx .1C per decade
Houston: around .05C
Corpus Cristi : < .03C decade
San antonio: .15C per decade
El Paso and amerillo.. lost in the noise.
With the exception of San Antonio all are within previous estimates. It would be interesting
for example, to see what happens to the average in texas ( and the world) if you remove
all cities larger than 10,000. Another way to look at it is this. If we make one pile
of all the stations that have tiny populations ( less than 10 people/sq km ) and
another pile of all the other stations ( on average 500 people per sq km).. the UHI
Bias is on the order of .04C per decade. ( Hausfather & Mosher)
As a side note population density in places like dallas and san antonio is on the
order of several thousands per sq mile ( and 1-3 thousand per sq km ) far above the
average of all stations.
The other things we see of course is that other factors ( such as distance from coast )
can really drive UHI. For the global database, therefore its good to remember that a good majority of human population lives on the coast in coastal cities. consequently in the global database its important to realize that the total effect of UHI can be muted by city location.
the more cities in your database that are on the coast the lower your UHI bias.
The other really important factor here is that UHI is also known to be much higher in northern latitudes than in southern latitudes. Texas is a northern latitude location.
An one last thing to note is that while a "log" curve is a good approximation for
UHI MAX for large cities, the data here ( UHI average ) indicates, as does other research,
that average UHI is not easily modelled as a function of population. Oke himself realized this and modified his formula to take regional windspeed into account as well as the regional building practice. Large population in high rises exhibit the highest UHI whereas large populations spread out in sprawling cities have lower UHI. Basically building height matters ( statistically it matters more than other factors ) Specicially aspect ratio matters.
( compare the aspect ratios of dallas and san antonio for example) and its also clear why san antonio would tend to have the higher UHI
Finally, all of these cities are large population. you dont see any "village UHI" here and what the data seems to indicate ( if you plot UHI versus change in population ) is that the bias
vanishes as you go to smaller and smaller populations.
As an example: in the Berkeley Earth dataset, around 10000 stations have zero population.
You can in fact build a global database where there are no large cities, no medium sized cities, no small cities,..
“So, Joe, would it be fair to say that you agree, qualitatively, with the AGW crowd that ‘man-made activities’ (i.e. urban heat islands) have created measurable increases in Texas temperatures over the past century. But you disagree, quantitatively, on how those increases are distributed?”
Man caused, yes.
CO2 caused, no.
So controlling CO2 is the wrong solution for this problem.
Good vs. Bad stations? There are a bunch of people in these rapidly growing cities that care about how hot it is in those cities. Temperature measurements in those cities are valid for those cities for many purposes – not just dithering about global warming. To exclude temperatures from where millions of people live because millions of people live there seems a little absurd.
In arguing for a UHI, this article compares absolute temperature records when temperature anomoly records are used to determine GW.
Why are you using absolute temperature instead of temperature anomoly? Here is NOAA’s explanation of why anomoly is superior: http://www.ncdc.noaa.gov/cmb-faq/anomalies.php go to question 7.
It would be very interesting to discuss why NOAA’s methodology does not account for UHI. Here is how they address it: http://www.ncdc.noaa.gov/oa/climate/research/ushcn/#urbanization
Intersting, I just moved to Corpus Christi – With so much air moving in the city from the ocean, you can see while driving the change in temperature as you drive through the town, but it isn’t much.
Driving into San Antonio, your A/C sound will change, it is almost a line you cross. The town is significantly hotter from outside the city limits compared to inside. You can feel the difference.
0 population doesn’t mean no UHI. Airports don’t have any population.
What seems to be missing in the discussion of UHI is that it is not just a factor of population. The radical increase in air conditioning and use of asphalt in the 1965-1985 time slot (for the US at least) would give a much larger anomaly jump during those years. Any study that looks at a different time period to calculate an average UHI would miss this.
SocialBlunder says:
“To exclude temperatures from where millions of people live because millions of people live there seems a little absurd.”
What’s absurd is taking a temperature (absolute or anomaly) increase that has been artificially increased due to population increase and attributing that increase to “enhanced greenhouse effect”; excluding those temperatures is the exact opposite of absurd.
There are other local factors at play in addition to population. As this map that Muller produced shows, there are many stations with warming trends next door to ones with cooling.
Simply averaging them all together is nonsense.
http://notalotofpeopleknowthat.wordpress.com/2011/10/22/kansas-temperature-trend-updatemuller-confirms-there-is-a-problem/
This is Oklahoma 1895-2012 and right now, just about to tick a very normal 100F, I can’t wait for a little of that long-term cooling in the fall !! Global warming, right, and pigs fly… I’ll deny both.
http://i46.tinypic.com/2dvu88l.png
@AnonyMoose
You’re missing the point I was making about the ‘qualitative’ impact of UHI.
For example, do you agree, qualitatively, that the “hot roof” of my house increases mean temperature of my property (where PROPERTY=HOUSE+YARD)? Yes or no?
(Does one child, with a fever, increase the average temperature of a classroom of children?)
If ‘yes’ then we can argue, quantitatively, how to obtain an unbiased estimate of that increase.
So it’s all about the ‘weighting factors’, right?
But having said that, I also happen to believe that surface temperature is only one factor in computing the Earth’s radiative balance. Others include clouds, oceans, convection and heat/cooling induced by evaporation/condensation etc.
😐
KTWO says:
June 28, 2012 at 11:12 am
“The trend may look flat. But just wait until the past gets cooler.”
________________
Jim G says:
June 28, 2012 at 11:44 am
….. The past may not get cooler in the UHI areas as concrete and roof areas increase over time.
___________________
AHA, but the past DOES get cooler at least if Hansen controls the data Hansen’s 3 GRAPH Set
JW: Attributing UHI warming to GHG is absurd. Excluding temperature readings would be cherry-picking (absurd if you want to be taken seriously – especially by someone who lives in San Antonio). Adjusting for the effect of UHI in the temperature record seems like the best way to go – which is why it would be so interesting to understand whether and why you believe the adjustments were done incorrectly. Can you explain why NOAA’s approac is inadequate?
Gail. I was indeed referring to how the past seems negotiable and plastic. Then I was astonished when Jim G. seemed to take my cooling comment seriously. That seemed so unlikely I thought he was responding in a clever way I did not grasp..
The Amarillo airport is on the far east side of the city while most of the growth for the last several years has been to the southwest. No surprise the thermometer has not sensed any UHI.
Anthony
If you run a linear regression on the decadal temperature increases vs the current population, excluding Houston and Corpus Christi due to the oceanic moderation effects, you get a correlation coefficient (R2) of 0.862 which seems to indicate that population and population growth (Duh!) are affecting temperatures significantly. Although there are only 4 points for comparison due to lack of data, I’m sure if you did a comprehensive analysis using population growth change since 1948 for all of the cities in your list you would derive an even stronger, more robust relationship. This effect cannot be anything other than UHI and including this type of data when looking at climate change can only be considered an “harmless” way of proving that global warming is out there ready to destroy us all without letting truth or facts or common sense get in the way.
Another ‘problematic’ temperature data set?
‘Voice’ of the supersonic solar wind from a coronal hole:
Ev’ry June night I’ve been huggin’
The Earth’s magnetosphere like pillow
Dreamin’ dreams of Amarillo
I’ve been breezin’ like a willow
To warm sweet Marie in Amarillo.
http://www.vukcevic.talktalk.net/A-E.htm
Yeah, I wonder if these hot temperatures today should even count. It hasn’t rained in a long time. I was just out and the ground is parched… I bet the surface temperature is like 120 or higher, even over the grass which is all dried out and no longer transpiring any moisture. It’s basically like the weather stations are reading over cement or asphalt given how hot the ground is… so these records are questionable. The sensors need to be at least 30′ above the surface to avoid the effects of thermal radiation off the ground.
Bingo!
Has everyone here forgoten Anthony’s surface stations project and study. He found that recorded urban temperatures are a little COOLER during the hottest part of the day and a little warmer at night than well sited rural stations! But they average very close to the same. How can this Texas info be rectified with Anthony’s study? Is it just cherry picking?
Anthony, are you going to do any more analysis to explain the perplexing results of your UHI study? Did the climate scientists dump cool rural stations? Did they move the urban stations to irrigated lawns? Do urban stations use cooler instrument designs, or what?
Looking at your State of Texas for last 100 with it’s black average and green trend, prompts the following question :-
What would be the value for the very next future point on this graph, that would convert the green trend line exactly into the black flat line ?
Enquiring minds want to know !!
weighting factors, anomalies and statistical tricks.
There used to be a saying that a soldier wearing a steel helmet was always marching south. If anything artificial is affecting the instrument then either it, or the instrument should be removed.
If you leave the helmet on, take the reading and then try to compensate, you will get lost
Anthony – I suggest it would be nice to see on the same page some graphs for rural stations.
All the best.
Mindbuilder, here is an explanation:
“A new index of calculating the intensity of urban heat island effects (UHI) for a city using satellite skin temperature and land cover observations is recommended.
UHI, the temperature difference between urban and rural regions, is traditionally identified from the 2-m surface air temperatures (i.e., the screen-level temperature, T2m) measured at a pair of weather stations sited in urban and rural locations, respectively.
However, such screen-level UHI is affected by location, distance, and geographic conditions of the pair of weather stations. For example, choosing a different pair of rural and city sites leads to a different UHI intensity for the same city, due to the high heterogeneity of the urban surface temperature.
To avoid such uncertainty, satellite-observed surface skin temperature measurements (i.e., skin level, Tskin) is recommended to record UHI, known as skin-level UHI or UHIskin. ”
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-11-00509.1
@more soylent green, EXACTLY!
In fact, the NCDC data base for 48 Contiguous states shows 8 states with cooling trends and three with zero trend. Yet we know these states contain cities with rapid warming trends.
Therefore, CO2 is not getting the job done in the cooling sites. Can physics act arbitrarily? Capriciously?
I think not.
See the Figure 1 at:
http://sowellslawblog.blogspot.com/2011/09/us-long-term-temperature-trend-from.html
SocialBlunder said (June 28, 2012 at 11:58 am)
“…In arguing for a UHI, this article compares absolute temperature records when temperature anomoly records are used to determine GW.
Why are you using absolute temperature instead of temperature anomoly?…”
Anomalies are bad because they use a time in the past as their reference (GISS, for example uses the oldest reference period – 1951-1980). If the effect from UHI was less around 60 years ago, then naturally any current “warming” (about 1 degree or so) would show up.
Using raw data shows how much of that anomaly rise can be attributed to UHI, and how much to data processing.
Another question for population enhanced UHI. Just how much is contributed to the UHI increase of a hot populated place such as Houston for example, by the effect of having everybody in such a town, being inside of an air conditioned enclosure, which is internally cooled down to the common chilly AC optimum temperature like 60 deg F thereby putting all that extra heat outside the buildings to add some positive AC feedback to the solar heating of the outdoors ?
Just asking !
For me, what all of these graphs reinforce is the cherry picking of the recent data sets used to promote the sustainably schemes to solve global warming. Notice how the late 1970s lows can be used to create a strong statistical upward trend going into the 2000s. All of the hog swallow I’ve seen lately justifying the Climate Action Plans start their data in the 1970s with a complete disregard for the previous 70 years of data that flatten the historical curve.
S Mosher, when evaluating data from 10,000 stations with 0 population, how do you deal with features that influence temperature, including location, elevation, topography,average precipitation,and influences from maritime, riparian and lake effects, etc?
It is about 100 degrees in Chicago right now, and it feels like it.
What happened to the time, when you went thru days like today, with the feeling that you have survived the worst She can throw at you, and have lived to spread stories of the hellishness of it all.
I wonder.
Anthony,
Reviewing the excellent post of Joe D’Aleo on the Urban Heat Island effect in Texas makes me wonder again how the raw data is “adjusted” when entered into global averages. I’ve made up some hypothetical city data and their average temperatures by year, as follows:
SAC DAVIS YOLO
1960 80 80 80
1970 81 80 80
1980 82 81 80
1990 83 81 80
2000 84 81 80
2010 85 81 80
SAC is a fast growing metropolis, DAVIS is a bedroom village 20 miles away, and YOLO is a slowly growing ag town 50 miles away. SAC qualifies as a Heat Island. Assume all three locations are included in the global averages. Without getting into the mathematics used in the adjustments, can you, in a general way, show what the adjusted temperatures might be for each of these cities when entered into the global mix?
Many Thanks,
Bill Kurdziel
Curiousgeorge says:
June 28, 2012 at 11:47 am
The ruling did declare that you can’t use the Commerce Clause to justify anything, but at the same time it also declared that you can force people to do anything congress wants by using congress’s power of taxation.
In other words, there is no limit to congress’s power to run our lives, they just used a different part of the constitution to justify the new powers.
The trend reversal in 1976 is very clear in those urban temperatures.
What happened?
Answer: the catalytic converter was mandated on all new petrol vehicles in 1975. One thing all urban areas have in common is a lot of cars.
Interesting to note that in the first graph for the entire state there appears to be an 80 year heating & cooling cycle and, further, that many of the individual city polts also indicate a similar cycle with both warmer and cooler phases.
I’d add. What we are seeing is the Weekend Effect on a multi-decadal timescale.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC208739/
There used to be a good wikipedia page on the Weekend Effect, but its been dissapeared.
Mindbuilder says:
June 28, 2012 at 1:00 pm
Has everyone here forgoten Anthony’s surface stations project and study. He found that recorded urban temperatures are a little COOLER during the hottest part of the day and a little warmer at night than well sited rural stations! But they average very close to the same. How can this Texas info be rectified with Anthony’s study? Is it just cherry picking?
Anthony, are you going to do any more analysis to explain the perplexing results of your UHI study? Did the climate scientists dump cool rural stations? Did they move the urban stations to irrigated lawns? Do urban stations use cooler instrument designs, or what?
===============================
The answers (including some you have yet to ask) are in the pipeline, awaiting release.
I suspect UHI has a greater effect than just temperature. As a very long time windsurfer, I’ve noticed changes in wind patterns around Sydney, Australia. An afternoon summer NNE sea breeze blows at typically 20 knots, 30 Km N of Sydney. However it now blows just 5-10 knots up to 10 Km N. Conversely, up to 5 Km S it blows 30 knots.
SocialBlunder says:
”Adjusting for the effect of UHI in the temperature record seems like the best way to go – which is why it would be so interesting to understand whether and why you believe the adjustments were done incorrectly. Can you explain why NOAA’s approac is inadequate?”
Why would adjusting for UHI by excluding temperature readings affected most by UHI be cherry picking? IMO, not excluding them is cherry-picking. I’m not saying NOAA’s approach is necessarily inadequate, but that it is an overly complicated solution to a simple problem.
The problem: UHI effect – Solution: exclude UHI affected readings. OR Problem: UHI effect – Solution: Run raw data through a complicated mathematical procedure to eliminate UHI effect.
Analogy:
Problem: In Los Angeles need to be in Las Vegas Solution: Drive to Las Vegas OR Problem: In Los Angeles need to be in Las Vegas Solution: Fly to NY, drive to Chicago, fly to Miami, drive to Atlanta, and fly to Phoenix, bike to Las Vegas.
Both solutions get you to Las Vegas, but one is better. (Hint: KISS)
On the other point, I don’t see how whether where one lives is or is not included in the calculation of global average temperature matters one iota.
For most of the states in the Union there is a correlation between the population around the stations and the temperature they record, in a log relationship, when TOBS temps are used. (Populations can now be found on the web). But, for Texas, this relationship does not have as high an R^2 value as do many of the other states. The plot (among others) is found on Bit Tooth Energy
I’ve been watching the BBC’s weather page over the last few months which has a list of ‘Hotspots’. Heathrow has been top of the list (by quite a few degrees) for days on end while the rest of us are damp and well below average for the time of year. I suspect that is purely due to it being a very busy airport and nothing more, I wonder where the temperature stations are at Heathrow because something isnt right with the recorded temperatures.
Not sure the urban temperature here is ‘cooler’ than that just outside the city here during our (right now in Texas! showing 105 on 3 different thermos) hottest part of the day … not born out on IR satellite image ATTM either, although the granularity of the scale (5C per step) may be obscuring differences … at night significant differences on satellite DO show up however. Practical experience (driving w/o air conditioning) does indicate that is is COOLER outside the city/urban areas; at 3 PM local try putting your hand down on concrete or an asphalt roof shingle vs a green pasture or grass …
One may look for oneself; this page will allow you to go back to the nighttime hours and and back as far as a week as well:
http://weather.rap.ucar.edu/satellite/
.
Philip Bradley says:
June 28, 2012 at 2:09 pm
The trend reversal in 1976 is very clear in those urban temperatures.
What happened?
Answer: the catalytic converter was mandated on all new petrol vehicles in 1975. One thing all urban areas have in common is a lot of cars.
Not to mention the heat from modern onboard electronics.
@ MarkW says:
June 28, 2012 at 2:01 pm
Curiousgeorge says:
June 28, 2012 at 11:47 am
The ruling did declare that you can’t use the Commerce Clause to justify anything, but at the same time it also declared that you can force people to do anything congress wants by using congress’s power of taxation.
In other words, there is no limit to congress’s power to run our lives, they just used a different part of the constitution to justify the new powers.
***********************************************************************
That may be true, however the ruling should make it more difficult. People have a natural aversion to taxation. If it applies retroactively to existing regulatory justifications, then that opens the door for rewrites and potential retraction of many regulations.
Philip Bradley says:
June 28, 2012 at 2:09 pm
Cats don’t work well until they’re up to the right temperature. In the UK at least, that excludes most journeys because they are under 60 miles. Last I looked, that’s how long it takes for a cat to start working. That’s why the Rover group favoured the “lean burn” engine.
DaveE.
John Day says:
“…would it be fair to say that you agree, qualitatively, with the AGW crowd that ‘man-made activities’ (i.e. urban heat islands) have created measurable increases in Texas temperatures over the past century?”
Certainly. If you agree that urban heat islands and their resulting measurable increases in Texas temperatures have absolutely nothing to do with increases in CO2.
In the USA, vehicle pollutants peaked mid-1970s and have steadily declined since. Although the decline in NOx has been small.
See figure ES-1
http://www.epa.gov/ttn/chief/trends/trends98/trends98.pdf
It’d be interesting to see how the temperature has changed in towns with little or no population growth that are located near these cities listed above.
Neo says:
Perhaps there are better ways to handle UHI that are better than a simple across the board CO2 type tax
Hmmm… so a city population tax? Live in a big city, pay through the nose for the privilege.
Sounds like a good idea to me.
The key is not state by state, but ENSO geographic area by ENSO geographic area. State lines are arbitrary and the jet stream/atmospheric pressure systems care not one wit for state lines.
I beg to differ; ever notice that sweet smell that emanates from a just-started engine? I don’t think those are raw hydrocarbons (at least none like I’ve ever smelled, and my non-cat 1500W generator still emits plenty of CO and unburned fuel on start-up which smells pretty much like it always did so it isn’t the change in fuel over the years …)
They may work better warmed-up; but that is not in contention …
.
Putting my stupid warmist hat on for a moment,.. I would blame UHI on the fact that more people using more SUV’s = more CO2 = higher temperatures. Easy. Next?
/sarc…
Pamela Gray says:
June 28, 2012 at 5:15 pm
The key is not state by state, but ENSO geographic area by ENSO geographic area. State lines are arbitrary and the jet stream/atmospheric pressure systems care not one wit for state lines.
———————–
Yep. I feel the same way when data is expressed by decades.
Nature, if it has a clock, runs on a different scale.
Anthony, clever turn of phrase on the title! (for those not acquainted, the State Song is ‘The Eyes of Texas Are Upon You’. I love tweaking UT folk by calling it the ‘I’ve been working on the railroad’ song, as it’s the same tune and it’s UT’s school song.
“How these results might compare to the GHCN network of stations used by NOAA for climate monitoring over the U.SA., I have no idea at this point.”
There is an interactive map here which shows unadjusted GHCN trends for 1951-2010, 1966-2010 and 1981-2010. It’s a map colored by trend; you can focus on Texas and display and click on stations to get numerical data. For 1951-2010 there is a general warming trend along the coast and a band of cooling in the interior.
@Louis Hooffstetter
Agreed, of course. I don’t think anybody, including the AGW crowd, claims that UHI is caused by CO2.
In fact, it’s the AGW crowd who tend to deny that UHI has any significant effect on global surface temps. So I guess I could call them “deniers”. But I won’t.
😐
Nick Stokes says: “unadjusted GHCN trends for 1951-2010, 1966-2010 and 1981-2010.”
Why not for longer periods? Would it not be most interesting to compare with the official NCDC record for the full period?
The first graph shows steps. You shouldn’t use OSLanalysis.
For those mentioning the inflection point ~1976, keep in mind we have several potential cycles and forcing agents at play in looking at temperature trends, including AGW (which I think is quite small), UHI, and various natural cycles such as the PDO. In 1977 the PDO switched from negative/cool to positive/warm. The temperature trends in southwestern states (away from heavy urban influences) generally reflect a PDO cycle over the period of the trend analysis in this post. When one does a trend analysis over a period of say 1948 to 2011, this happens to overlay one complete PDO cycle from the start of the negative phase in the late 1940s, to the approximate the end of the positive phase (NASA said PDO went back to negative in ~2007, if I recall correctly).
The temperature contours for the lows http://www.aerology.com/?location=Usa&mapType=Tmin&date=6%2F28%2F2012
and the highs show the UHI as well as natural differences in temperatures across short distances
http://www.aerology.com/?location=Usa&mapType=Tmax&date=6%2F28%2F2012
there are some cities that don’t seem to have heat signatures, like St Louis Mo.
And if it is not the fact that most of the wheat has been cut and the pastures grazed down by now, and mostly forests north of the line, what is with the shift across the USA Canada border?
http://www.aerology.com/?location=NorthAmerica&mapType=Tmax&date=6%2F28%2F2012
The raw data to make the maps above was gridded in 3 mile squares, with minimum smoothing of only 8 nearest neighbor with in an 8 degree radius, most stations, (75%tile) are with in 0.63 degrees of their nearest neighbors.
The obvious conclusion is that since there is a direct correlation between the number of people and temperature, ergo, people, not CO2, are the culprit in global warming. BTY this statement was peer reviewed by my dog.
TTCA
“Why not for longer periods?”
Partly availability – it’s mainly intended as a color-shaded world map, and with fewer stations it gets patchy.
But also just download time – each time period requires quite a lot of data to be downloaded. So I did the ones I thought would be of most interest.
blah blah blah anomalies blah blah blah superior blah blah blah…
Really? Anomalies are superior to temps? Allows you to compare changes to temps at very different ranges like cold areas and warm areas.
Wait, wait, wait… what was the goal again? To figure out if doubling of CO2 causes an energy imbalance of 3.7 w/m2? Wasn’t that the idea?
+1 anomaly at -40C = 2.9 w/m2
+1 anomaly at +40C = 7.0 w/m2
Someone wanna explain the value of anomalies to me again?
“Somewhat OT, but the SCOTUS ruling on the AHCA today dealt a blow to using the Commerce Clause indiscriminately.”
Not in any way relevant to EPA CO2 regulation. The only affect of the SCOTUS decision today on future commerce clause cases is to prevent Congress from punishing non-activity by means of penalties or criminalization. As emitting CO2 is an activity, the commerce clause ruling today does nothing to rein in runaway regulation, penalties or regulations. IMHO, the commerce clause ruling today is much ado about nothing–if congress decides to regulate non-activity, it will simply tax the non-activity. SCOTUS’ decision today gives them an almost unlimited right in that regard.
An interesting study. Which is why I’ve fled to Wisconsin for most of the summer this year! Although, today the temperature/heat index in Milwaukee was around 105 degrees Fahrenheit. Yuck! But it is supposed to be much less humid tomorrow.
Forgive me if i phrase this wrong. I know nothing about taking heat readings from space but it seems that if the heat reading patterns of vast areas of land could be converted to colored pictures then you should get a rather graphic display of the higher temperatures of cities. I mean if we have satellites that can measure ice extent and ocean depths it would seem surprizing that nobody has snapped some shots of heat patterns radiating up from the earth. I have seen pictures of city lights as seen from space. Could the same thing be done for heat? Has it been done? The size of the cities should make a difference in the amount of heat they toss up. With that information you could estimate the effects of population growth.
You know when you consider all the things going on in cities it is ridiculous to use readings from them to estimate global temperature rise. Rural temperatures should be the only temperatures used to demonstate any global heat rise due to CO2. If it is not happening in rural areas it is not happening at all.
Eugene WR Gallun
There is a major flaw in this paper, relating to populations versus UHI.
The population figures are that of local governments within a metro, not urban areas. For example, the population of urban Dallas is not 1,197,816. it is actually about 6,300,000 as of the 2010 census. San Antonio is about 1/3 of that, at 2,000,000. Houston is a little under Dallas, at about 5,900,000.
Dallas and Houston have grown from very small settlements to major metros in the last 150 years, and so the UHI relative to population should be glaringly obvious. Even since 1948, the population of Dallas was less than a million, so the UHI should show a sharp increase within the data available.
The Amarillo’s June temperature shows a degree of correlation with the solar magnetic cycle, the time relationship points at coronal holes as a possible cause
http://www.vukcevic.talktalk.net/A-E.htm
Eugene WR Gallun says:
June 28, 2012 at 10:28 pm
This has been done.
http://www.nasa.gov/topics/earth/features/heat-island-sprawl.html
Although this contains some misleading statements.
Dark city infrastructure, such as black roofs, also makes urban areas more apt to absorb and retain heat.
Cities generally are lighter (have a higher albedo) than surrounding rural areas. Therefore, Dark city infrastructure isn’t a general cause of UHI. Rather the reverse is true. Were lightness/darkness the sole effect at work, cities would be cooler than surrounding areas.
Development produces heat islands by replacing vegetation, particularly forests, with pavement and other urban infrastructure. This limits plant transpiration, an evaporative process that helps cool plant leaves and also cools air temperatures
Lack of evapotranspiration is the main cause of UHI. It cools air temperatures by increasing humidity. Heat content doesn’t change.
Urban Heat Island is a misnomer, because the reason cities are warmer isn’t because of increased heat. Its because of decreased humidity.
Note, waste heat, particularly from air conditioners, is a factor is some cities.
The urban heat effect from a metro with six million people should be larger than one with one million, but that may not be apparent in the summer. The Dallas metro is in a region that is currently experiencing temperatures in the hundreds, which may be masking the UHI effect.
The Houston weather may be falsifying the theory of water vapor as a positive temperature feedback. The local relative humidity levels in Houston seem to be reducing the Houston temperature ranges, relative to Dallas’, rather than amplifying them. Houston is not actually on the gulf, but is quite a few miles inland. Its principal airport and source of “official” temperatures, is farther inland still. It’s shipping is serviced by a deep water canal, rather than an actual ocean port. Relative humidity in Houston is substantially higher than Dallas’ relative humidity.
Texas is actually an interesting territory to analyze the UHI effect, due to its cities’ dependence on roadways instead of mass transit. The power consumed in Texas is actually produced in Texas, since the state has a separate power grid with very little connection to the rest of the United States.
Anthony, your paper has some interesting points, and the use of city government populations rather than metro populations may make little difference as to whether UHI exists at all, but it may be an error that at least appears to detract from the credibility of the paper. The sizes of local governments have no physical relationship to the UHI. Also, in your paper, you consider that Houston’s UHI effect should be greater than Dallas’, believing that Houston is much larger than Dallas, when in fact the Dallas Urban area is similar in size, and actually slightly larger. Thus, the UHI effects of the two metros will be similar.
Would be interesting to see a comparison between temperature and economic/industrial expansion of these cities.
Population alone might not correctly reflect the relations.
What I find wrong is that the first graph, Texas temperatures 1910-2010, shows a slight upward trend whilst the warmer years are 1910-1960 then comes cooler years and it is only the last 15-20 years that return to warmth but none as warm as those of the 20’s-30’s. To my mind the trend should be down.
And why do people talk trends in a cyclic situation.
Nearly half a century of making measurements (and an insightful boss) have taught me a simple fact: it’s quite easy to read a thermometer, and quite difficult to measure temperature. Similarly, the UHI effect results from both errors in the measurement, and changes in the temperature. Each change is corrected quite differently. Measurement errors can result from localized changes around the recording station, while actual changes in the temperature may be attributed to population. Neither change would be present over most of the land mass of the country. Unfortunately, a proper correction would require careful study of each reporting station and a large vareity of correction factors.
Earle Williams says:
June 28, 2012 at 11:03 am
“It’s official, CO2 causes *extreme* population growth.”
Of course it does. When it is hot outside people stay inside. When men and women are kept inside together they get bored and have sex. Having sex causes reproduction of new humans which increases population growth. Increased population growth means more people inside. When more people are inside there are more people getting bored. When more people get bored there is more sex going on which leads to more reproduction which leads to increased population growth …….
That’s what is called positive feedback.
John Marshall says: June 29, 2012 at 3:09 am
And why do people talk trends in a cyclic situation.
Indeed
North and South hemispheres often move in the opposite directions
Possibility of the Earth and solar magnetic fields acting in concert ?
http://www.vukcevic.talktalk.net/A-E.htm
Interesting. Also don’t forget that Houston is extremely large with a relatively low density and large amounts of inner-city greenery. The urban heat island effect is muted due to that. San Antonio is in the hill country and has a much higher density.
Three comments:
@John Day – “So, Joe, would it be fair to say that you agree, qualitatively, with the AGW crowd that ‘man-made activities’ (i.e. urban heat islands) have created measurable increases in Texas temperatures over the past century.”
1.) Land use is not considered in CAGW global warming arguments, only CO2. ‘Man-made’, though, can mean either land use or CO2 emissions – as well as aerosols and ozone, for example.
2.) If land use is the culprit, then UHI spikes would naturally appear in fairly close proximity to high heat generating and high heat absorbing/retaining locations.
If CO2 is the culprit for the whole state, the atmosphere would show it distributed pretty much everywhere, and temps even at rural sites would be affected. Rural site temp data is what will tell on CO2.
The fact that the statewide – including rural areas – is flat tells us that CO2 emissions are not affecting rural areas. Land use sure isn’t either. This non-spike in the decadal increase points toward land use as the cuplrit.
3.) I’d also suggest that air conditioning came to Texas in a big way starting just about 1970. Air conditioners pump the heat out of buildings into the surrounding air. Temperature data doesn’t measure inside buildings where the heat has been removed, only outside, where the heat has been pumped to.
Steve Garcia
Breaker says:
June 28, 2012 at 10:07 pm
“Somewhat OT, but the SCOTUS ruling on the AHCA today dealt a blow to using the Commerce Clause indiscriminately.”
“Not in any way relevant to EPA CO2 regulation. The only affect of the SCOTUS decision today on future commerce clause cases is to prevent Congress from punishing non-activity by means of penalties or criminalization. As emitting CO2 is an activity, the commerce clause ruling today does nothing to rein in runaway regulation, penalties or regulations. IMHO, the commerce clause ruling today is much ado about nothing–if congress decides to regulate non-activity, it will simply tax the non-activity. SCOTUS’ decision today gives them an almost unlimited right in that regard.”
Right on. As Rep. Allen West of Florida said today, ‘what if the government said that everyone must buy a Glock 9mm or be taxed for not having one’. Very bad decision on the part CJ Roberts. Unlimited power in the hands of he federal government.
One question regarding the UHI is regarding the shape of the curve. Growth in the major metros of Dallas-Ft Worth and Houston is not linear, it is exponential, that is to say, the two metros do not add a constant population each year, but an increasing one. This would suggest that the temperature rise due to UHI should also be exponential, rather than a flat line with a fixed slope.
The sharp increase of air conditioning in vurtually every structure and vehicle that happened in the 1950s should show a corresponding step increase in UHI just due to additional outputs of energy needed to power them. Ideally, that should be visible in the data.
One poster mentioned the land use inside the metros that would mitigate insolation, since new subdivisions are always planted with trees, shrubbery and grass, and the income solar energy would be trapped by biological processes rather than heat the atmosphere and the ground. Since the massive population growth in Texas is exponential, the mitigation should also be exponential.
The temperature records for DFW and Houston are also problematic. Both metros built massive new airports in the 1970’s, initially in raw countryside that was later overwhelmed by suburban sprawl. Since the newer airports would tend to provide the “official” temperatures for Dallas and Houston, that would be a consideration. The previous airports, Hobby in Houston and Love in Dallas were well within the built-up area of the metros, but the successor airports and their temperature records would subsequently reflect temperatures outside the Urban boundary.
Finally, the terrain between the Gulf of Mexico and the Canadian prairies is relatively flat land. It is common for weather fronts to travel across this terrain, and reach Houston 24 to 36 hours after it passes through Dallas. This sort of weather front is quite common in the winter, but also during the summer. Thus, an urban heat bubble would tend to be dissipated by the weather front.
To illustrate the massive growth in the 4 major Texas metros since 1990, I built the following table. The percentage represents the growth since 1990.
1990 2000 2010 2011 Est.
Dallas 4,037,282 5,221,801 6,371,773 6,526,548 61.66%
Houston 3,731,131 4,669,571 5,946,800 6,086,538 63.13%
San Ant 1,324,749 1,592,383 2,142,508 2,194,927 65.69%
Austin 846,227 1,249,763 1,716,289 1,783,519 110.76%
Reference for the 2011 estimate is: http://en.wikipedia.org/wiki/Table_of_United_States_Metropolitan_Statistical_Areas
All other numbers are from: http://www.census.gov/population/www/cen2000/briefs/phc-t3/tables/tab01.txt
Careful now, lest they propose cap and trade tax for living near a city!
MN has a annual trend from 1895-2011 of 0.14F/decade. Minneapolis/St. Paul’s trend for the same period is 0.23F. I-Falls is the only other city listed, but its record starts from 1948. Comparing that time period gives a trend for I-Falls at 0.36F, Mpls/St. Paul at 0.39F, and MN at 0.33F. Interesting is the trend back from 1986(25yrs). MN is 0.07F, while Mpls/St. Paul is 0.34F, but I-Falls is at -0.34F. After 2012 is over, I’m sure these trends will be bumped up a bit (linear trends on this time scale move pretty easily), as it has been pretty warm for the year so far. We’re averaging roughly 6F above normal for the year so far across the state. It would take some pretty cool weather the next 6 months to get that down. 1931(45.8F) and 1987(45.7F) are the warmest years listed, and if my estimate holds true till the end of the year, 2012 will end up being the warmest by 2 degrees F in MN. The average temp for 1981-2010 is 41.8F.
Nick Stokes
http://wattsupwiththat.com/2012/06/28/the-uhis-of-texas-are-upon-you/#comment-1020642
“There is an interactive map here which shows unadjusted GHCN trends for 1951-2010, 1966-2010 and 1981-2010.”
Once again Nick you are attempting to mislead people by showing your fantasy colour coded world warming/cooling trend map.
Just exactly how do you manage to show all that ‘red’ all over the Canadian Arctic when there are but a handful of stations north of the Arctic Circle in Canada? Contrast you’re misleading anomalised and gridded map with its smearing of warming into the Canadian Arctic Circle with a proper indivual station trend colour coded map for Canadian and US stations here.
http://www.climateapplications.com/GHCNV3Maps/googlemap.asp?countryid=403&startyear=1880&endyear=2010&raworadj=raw&trendperiodid=2
http://www.climateapplications.com/GHCNV3Maps/googlemap.asp?countryid=425&startyear=1880&endyear=2010&raworadj=raw&trendperiodid=2
You may need to ‘pan’ a bit on the US link.
In both cases these are the warming/cooling trends for the 1880 to 2010 period for the GHCN-M-V3 dataset.
Mosh is now of course going to remind me that he thinks that these kind of individual station trend maps aren’t of much interest because I haven’t gone to the trouble of anomaling and gridding the raw data as you have done.
I wonder which looks more scary your map or mine. Which is more truthful?
For anyone who doesn’t want to be mislead by Nick’s interactive map can use the following link to choose any country you want and to also choose from different warming/cooling periods. For some reason Nick has found it hard to find data for the 1880 to 1910 coolling period followed by the 1910 to 1940 warming period followed by the 1940 to 1970 cooling period followed by the 1970 to 2010 warming period.
Here is the US map for the 1910 to 1940 warming period
http://www.climateapplications.com/GHCNV3Maps/googlemap.asp?countryid=425&startyear=1880&endyear=2010&raworadj=raw&trendperiodid=4
and here it is for the 1970 to 2010 warming period
http://www.climateapplications.com/GHCNV3Maps/googlemap.asp?countryid=425&startyear=1880&endyear=2010&raworadj=raw&trendperiodid=6
that is supposed to be so alarming different from the earlier natural warming period that we must ACT NOW and immediately reduce our CO2 emissions in order to save us all from catastrophic man-caused global warming.
Nick as a CFD expert I;m sure you already know how untrustworthy colour contour temperature plots produced from finite element anlysis codes can be. If so why ar eyou attempting to mislead readers here?
KevinUK
Sorry I missed of the link to the Google map from which you can choose any country and different time periods. Here it is
http://www.climateapplications.com/GHCNV3Maps/googlestationtrends.asp?countryid=651&startyear=1880&endyear=2010&raworadj=raw&trendperiodid=2
Just choose a country and time period of your choice and click the Update button. For some countries like the US you may need to ‘pan’ across the map and perhaps also zoom in.
KevinUK
The city graphs all seem to show the common v- shaped pattern centered on the 1970s.
This pattern appears in the global average record as well suggesting the composite analysis is fine.
Obviously if you trend a v with a linear fit you are going to get zero trend. So doing that is misleading.
The higher temps in the 1930s might reflect the dustbowl droughts, or might not. Similar dust bowl conditions in Australia in the same time period might reflect [SNIP: LT, I’m not picking on you, but it would be nice to see commenters in general rise above excretory adjectives. This is a family blog. Think of the children! -REP] agricultural practices.
KevinUK,
My map is certainly not misleading. Firstly, it’s not anomalized. It shows station trends on the unadjusted data. You can display the stations and click on them to get the numerical values.
It is billed as a station trend map, and the shading is my equivalent of your color coding. The methodology is transparent – you can display the triangular mesh used and see the color interpolation scheme, which is what is provided by HTML 5. So anyone curious about the Canada red can clearly see what stations are producing it.
And it uses a spherical projection, so the Arctic areas are not inflated.
I must say that my coloring scheme is not to commercial CFD standards. It is not meant to represent a continuum, and is not a finite element solution of anything. And, of course, it has to be done with what HTML 5 provides, so as to have interactivity.
The Google maps approach that you have used has merits too. However, you say that it represents trends from 1880 to 2010, but you seem to have a trend for almost every GHCN station. Some of those must be for quite short sub-periods. How can we tell? At least the labels should say what the period is. And the colors will be also misleading where they represent a trend over a shorter period.
That’s the reason my display of trend periods is limited. The trends I show are actually of the periods stated.
Larry in Texas says on June 28, 2012 at 10:10 pm:
An interesting study. Which is why I’ve fled to Wisconsin for most of the summer this year! Although, today the temperature/heat index in Milwaukee was around 105 degrees Fahrenheit. Yuck! But it is supposed to be much less humid tomorrow.
Vancouver’s best kept secret: No mosquitos in Summertime!!! All the young ladies wear tank tops, short shorts and flip-flops. They all are practically na-a-a-a-ked.!!!
Present temp and RH: 22 deg C and 75 %.
Come visit in August when the salmon start running up the mighty Fraser river.
After sleeping on it, I’ve reconsidered the idea that increasing population will increase the UHI. Since an increasing Population in a Sunbelt city will translate into increased sprawl, the density at the recording station should stay the same, and the heat content in, say, Joules, should be more or less stable.
Since 1990, the populations of the Texas metros has increased anywhere from 60% to 110%, but the settled area of the metro has just expanded.
One exception, would be the energy intensity of the downtowns, which should increase to an extent. but it would not increase linearly with population, since offices, as well as residential areas, have migrated to suburbs.
Houston’s downtown has grown upwards, however, massively, but on the other hand Dallas’s downtown has not appreciably increased upward, but has expanded to the north, due to height restrictions from a nearby airport. So the apparent UHI at a fixed point in Dallas’ old downtown should show a lower increase than Houston’s.
The basic problem with falsifying this hypothesis is the same as the basic problem in evaluating AGW in general… The quality and extent of the data is insufficient. Unless we can measure the physical world, we cannot know it. And the one location that would validate or invalidate AGW in Texas just doesn’t have a history of measured data behind it. In the 1950’s and onward, no one knew of a need to make accurate temperature measurements of Texas downtowns.
A couple of points;
–never forget that the “contribution” to global temperatures of cities is nugatory, trivial, except insofar as they corrupt the measurements and averages;
–the population of Houston in 1948 eyeballs to 600K. Dallas lagged by about 10 yrs., San Antonio by about 15, etc. The start point of measurement comparisons could be rejigged to match pop. levels instead of date, with interesting results, I think.