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.
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