Jet exhaust as climate forcing
Guest Post by Willis Eschenbach
The good folks over at the Berkeley Earth Surface Temperature project have published their paper about urban heat islands. It’s called “Influence of Urban Heating on the Global Temperature Land Average using Rural Sites Identified from MODIS Classifications”, by Wickham et al, hereinafter W2013.
They find no urban heat island effect, saying at the close of the Abstract:
Time series of the Earth’s average land temperature are estimated using the Berkeley Earth methodology applied to the full dataset and the rural subset; the difference of these is consistent with no urban heating effect over the period 1950 to 2010, with a slope of -0.10 ± 0.24/100yr (95% confidence).
Having read the paper, I can’t say I’m surprised that they find no difference.
The W2013 authors have used the MODIS 500 metre dataset to identify urban areas. It’s a dataset that uses the MODIS satellite data to classify the planet into land-cover classes, including urban. The W2013 study uses the MODIS data to divide all the world’s temperature records into “very rural” and “not very rural”. Then they show there is little difference in the trends between the two groups.
Figure 1. Actual MODIS grid overlaid on Henderson Field, Guadalcanal, Solomon Islands. Picture is from 2003, prior to recent development. All gridcells would be classified by MODIS as not built-up, since less than 50% of the area of any given gridcell is built-up area. The ocean is at the upper right. Click to embiggen.
Let me talk a bit about the W2013 study and the MODIS map, and demonstrate by example the reason why I didn’t expect their “very rural” split to have much discriminatory power regarding temperature trends. As an example, let me use one of my favorite airports, Henderson Field on Guadalcanal.
Here is the description from the W2013 study of how they identified the “very rural” stations.
The MOD500 map is available as a raster image, providing a binary classification (urban or not urban) for a global grid with pixels of size 15 arc-seconds.
…
Rather than compare urban sites to non-urban, thereby explicitly estimating UHI effects, we split sites into very-rural and not very-rural. We defined a site as “very-rural” if the MOD500 map showed no urban regions within one tenth of a degree in latitude or longitude of the site. This choice should minimize errors that occur from MODIS classifications in fringe areas. We expect these very-rural sites to be reasonably free from urban heating effects.
This led me to investigate the MODIS “MOD500” map. The MODIS dataset is described in A new map of global urban extent from MODIS satellite data. Basically, it uses multi-spectrum radiation to discriminate between types of land cover, and to identify the signatures of various built-up areas..
Of immediate interest to this discussion is their definition of “urban areas”:
a. Urban areas
In both datasets, urban areas (coded class 13) are defined based on physical attributes: urban areas are places that are dominated by the built environment. The ‘built environment’ includes all non-vegetative, human-constructed elements, such as buildings, roads, runways, etc. (i.e. a mix of human-made surfaces and materials), and ‘dominated’ implies coverage greater than or equal to 50 percent of a given landscape unit (here, the pixel). Pixels that are predominantly vegetated (e.g. a park) are not considered urban, even though in terms of land use, they may function as urban space. Although ‘impervious surface’ is often used to characterize urban areas within the remote sensing literature, we prefer the more direct term ‘built environment’ because of uncertainty and scaling issues surrounding the impervious surface concept. Finally, we also define a minimum mapping unit: urban areas are contiguous patches of built-up land greater than 1 km^2. SOURCE
Now, each “pixel” that they mention above is one of the gridcells shown in Figure 1 above. Those are the actual gridcells used in the MODIS map. If more than half of a gridcell is “built environment” (houses, roads, runways, etc.) then the gridcell is counted as “built-up land”. However, there’s a final hurdle. You need to have five adjacent gridcells of built-up land to have those gridcells classed as part of an urban area in the MOD500 map.
This is kind of an odd definition. It means that any small hamlet is rural, since it won’t cover a square kilometre (about 250 acres). You have to have five contiguous built-up gridcells, which totals just over 1 km^2, for those gridcells to be classified as urban in the MOD500 map.
Figure 2 below shows how much of the land shown in Figure 1 could be built up, covered with houses and roads and parking lots, without anything being called “urban”.
Figure 2. As in Figure 1, overlaid with theoretical possible buildup without any areas being classified as “urban” in the MODIS dataset. Gray areas are 100% built-up, white triangles show 40% built-up. A total of about 70% of the land is built-up. None of it is classified urban because nowhere are there are five contiguous built-up gridcells.
In any case, that’s the history. Figure 3 shows the situation today:
Figure 3. Actual MODIS grid overlaid on current view of Henderson Field. Picture is from January 2013. All gridcells would still be classified by MODIS as not built-up, since less than 50% of the area of any gridcell is built-up area. The gridcells shown in red are the nearest to being classified as built up, as they all have about 40% of their area covered with roads, houses, and runways.
Again, in the MOD500 map, none of these gridcells would be classified as urban. Even if those four gridcells were more than 50% built-up, still none of them would be classified as urban because there aren’t five of them and they aren’t contiguous.
However, the fact that the MOD500 map classifies all of these gridcells as being rural makes no difference—the Stevenson Screen housing the thermometers is still in a horrible location. Here’s why, borrowed from Anthony’s post on the subject. This shows a ground level view of the station taken from the terminal. Note the white box of the Stevenson Screen housing the thermometer and other instruments in the green area just left of center, below the smoke visible in the distance.
Here comes a plane! Weather station visible to the left of the plane’s tail, right of the white mast.
Coming into the terminal…
Hey, park it over here!
Uh, oh, look where the jet exhaust is pointed:
Hmmm, a new high temperature today?
Back to normal.
Now, that’s the problem with the location of the Henderson Field weather station. There are lots of good places to locate the Stevenson Screen in the local area … and it’s in a bad place. This situation is mirrored in many airports and weather stations in general around the planet.
The difficulty I have with the approach of using the MOD500 map to distinguish urban from rural is simply stated:
Many of the siting problems have nothing to do with proximity to an urban area.
Instead, many of them have everything to do with proximity to jet planes, or to air conditioner exhaust, or to the back of a single house in a big field, or to being located over a patch of gravel.
And sadly, even with a map averaged on a 500 metre grid, there’s no way to determine those things.
And that’s why I didn’t expect they would find any difference … because their division into categories has little to do with the actual freedom of the station from human influences on the temperature. Urban vs Rural is not the issue. The real dichotomy is Well Sited vs Poorly Sited.
It is for this reason that I think that the “Urban Heat Island” or UHI is very poorly named. I’ve been agitating for a while to call it the LHI, for the “Local Heat Island”. It’s not essentially urban in nature. It doesn’t matter what’s causing the local heat island, whether it’s shelter from the wind as the trees grow up or proximity to a barbecue pit.
Nor does the local heat island have to be large. A thermometer sitting above a small patch of gravel will show a very different temperature response from one just a short distance away in a grassy field. The local heat island only needs to be big enough to contain the thermometer, one air conditioner exhaust is plenty, as is a jet exhaust …
The only approach that I see that has any hope of success is to painstakingly divide the stations, one by one, based on what is in their viewshed, and exactly how far are they from a variety of ground covers. The work done by Michel Leroy of METEOFrance in 2010 lays out one way to do this, as discussed here.
Because even with the outstanding resolution of the MODIS dataset, it still can’t tell us whether the siting of the weather station is up to snuff, or whether we’re just measuring the temperature of a jet engine at 50 metres … and that’s why I don’t find the results in the W2013 paper at all persuasive.
Best regards,
w.
PS—One curiosity. The published paper is a slightly polished version of their earlier pre-publication paper with the exact same title, available here. The curiosity is the re-ordering of the authors on the two title pages, viz:
Internal politics?
I also note that my friend Steven Mosher is now listed as an author on the paper, my congratulations to him.
[UPDATE] Steven Mosher has pointed out that in the analysis, this particular station (Henderson Field) is classified as urban. I have no problem with that, as it is not a long ways from the capital and is likely classified urban by BEST (although likely not by MODIS) on that basis for their study.
Nor was the classification of that particular station my point, which I quote here from above:
And that’s why I didn’t expect they would find any difference … because their division into categories has little to do with the actual freedom of the station from human influences on the temperature. Urban vs Rural is not the issue. The real dichotomy is Well Sited vs Poorly Sited.
It is for this reason that I think that the “Urban Heat Island” or UHI is very poorly named. I’ve been agitating for a while to call it the LHI, for the “Local Heat Island”. It’s not essentially urban in nature. It doesn’t matter what’s causing the local heat island, whether it’s shelter from the wind as the trees grow up or proximity to a barbecue pit.
Steven also adds the following comment:
My main concern is that people will think the article is about urban/rural (see the title … very rural, not) when the text is about “siting”.
Also, folks may get the idea that airports can never be CRN1 [a measure of station quality] … something which Fall 2011 doesn’t support, as many of CRN1 and CRN2 are at airports.
A clarification might help prevent future misunderstandings and gotchas.
My thanks to Steven for calling that classification to my attention, and also for his clarification.
Australia has climate records for over 1,000 sites. A few years ago I selected about 50 of those least subject to the hand of man, which I called pristine.
The object was to set a baseline. Ideally, all pristine sites should have a similar trend over time, being natural climate change. This would make a baseline above which UHI would show.
It did not. The complete demolition of methods used for quantification of UHI using regional remote methods follows in these figures.
Sorry BEST, you have no story until you can explain what is going on here.
http://www.geoffstuff.com/Pristine_Summary_1972_to_2006.xls
(Data provided, so please be patient with download time).
I think one of the things Willis’s analysis shows is just how dangerous it is to rely too much on statistical wizardry and algorithms and not enough on proper local and practical knowlege.
GHCN’s Icelandic adjustments are a classical example of this. Who knows better the temperature history of Iceland? The experienced, knowledgable Iceland Met Office, or some computer programmer in GHCN?
‘Actually not. The cells (at the equator) are 463 m x 463 meters. Four of them make about 0.85 square km, and the MOD500 data (quoted above) says there must be 1 square km of contiguous built-up gridcells to be called an urban area. So your claim is 100% wrong.
This is why I went through the MOD500 information in detail, because I was pretty sure you guys didn’t understand it … and as it turns out, you didn’t.
Actually, it gets worse from there. At 60°N, it takes ten gridcells to make up one square kilometre. So your claim is not just wrong, it’s risible.”
The easy way to do it is this.
1. you take all the stations and classify them using the urban dataset ( 1km rule)
a when you do this make sure you fix the projection )
2. you then take a 500 meter dataset ( the source of 1 ) and do the classification using that.
3. you then take the 300 meter dataset and do the classifiaction using that
4. you then take a 30 meter dataset ( US and alaska) and triple check.
You’ll be surprised, but no nobel prize
Steven Mosher says:
April 4, 2013 at 11:18 am
For me the challenge is to convince people get off of the false “rural/urban” dichotomy entirely. There are terrible stations everywhere, being out in the country is no guarantee of good siting.
As I said above, the problem is in the name. If you called the phenomenon by a more accurate name, the “Local Heat Island”, you would see that (as you point out implicitly in your challenge) likely there is no way to divide stations into good and bad local sites using ex-ante rural/urban criteria. I think it can only be done by examining each site one by one, and using the actual siting criteria. There’s no magical shortcut, rural/urban, MOD500, or otherwise.
The result of your study, Steven, is only that you’ve shown that using MOD500 can’t separate good stations and bad stations from a satellite … you have to do it from the ground.
Finally, I was curious why you didn’t use your technique to investigate things like the Oke paper or the McKitrick paper which found evidence of UHI. I’d think you could use your method and the Oke or McKitrick datasets to determine whether they were wrong or not and if so why … seems like if you’re going to implicitly claim the previous studies are wrong, you should show it directly using their data.
w.
Great article, Willis! The AGW crowd are engaged in what Irving Langmuir called “Pathological science” and they know how to tweak the little things to twist facts to suit their theory.
Steven Mosher says:
April 4, 2013 at 11:23 am
Well said, Steven.
w.
Syncronicity as I pondered this only a day ago. Stood on a train platform freezing my unmentionables in a bitter Easterly wind. Train leaves platform giving gust of diesel and sudden onset of mediterranean exhaust warmth. Appreciated despite vile smell but gone as sudden as onset. Pondered weather stations in back fire range going from sub 30s F to high 50s (heatwave by current Brit standards). However despite Willis pictures BEST have said ‘nothing to see here move along’. Poor cold GingerZilla gazing at snow in South England in April now confused as told heat all in mind. Many Brits also in state of Mass Hysteria seeing imaginary snow in town that melts on contact but by a miracle settles down the country road-all deniers do not believe country folk. Rural people total liars about cold – all in their denier heads. No heat in town.*
/sarc
*this is factually correct as even in the pub someone keeps opening the door denying me heat.
Steven Mosher says:
April 4, 2013 at 12:28 pm
Thanks, Steven. So I take it that you did NOT do a sensitivity test on the MOD500 results reported in this paper, showing the “very rural” stations with and without airports? I’m not claiming it would show anything, just asking if it was done or not.
In any case, the issue is not airports. It is bad siting of the Stevenson Screen, which has nothing to do with airports.
w.
To understand superposition of anthropogenic energy loss / flux upon background temperature in a given zone, one must perform the integral of all anthropogenic energy sources and anthropogenically created energy imbalances due to albedo modifications within that zone. The whole concept of an “urban” heat island is flawed and antiquated. The above approach is what is needed. This approach can apply to any zone be it an urban area or at the opposite extreme, supposed “wilderness.”
Steven Mosher says: April 4, 2013 at 11:39 Temperature measuring in the middle of an airport has only ONE valid and very important use. It gives the pilots information they need to set safe, efficient take off and landing speeds.
_____________________________________
Not quite, Steven.
Temperature is irrelevant to landing speeds, which vary according to weight only (plus an allowance for high winds and gusts).
For take off, temperature is mainly used to determine thrust, and it is thrust and weight that determine the take off speed, not temperature. On our jet, temperature alone only adds one knot to V1 and V2 airspeeds, between 0 and 40 degrees c.
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ralfellis: maybe the values of V1 and V2 for your aircraft are based on the worst-case scenario at the worst airport where the machine is certified to land? The decision speeds seem to be set somewhat arbitrarily, and in different manner for different aircraft.
Surely your Vy depends on altitude, quite a bit. According to this chart, at 40C, you’re already at 7500 feet above the ground, compared to standard atmosphere:
http://upload.wikimedia.org/wikipedia/commons/thumb/6/6f/Density_Altitude.png/567px-Density_Altitude.png
I hear from small aircraft owners that they get stuck at high-altitude airports for days, waiting for a cold enough weather to take off? In what way are their machines different from yours, other than having a lower ceiling?
Steven Mosher says:
April 4, 2013 at 12:38 pm
Steven, you claimed four gridcells were enough to be counted as an urban area by MODIS in the MOD500 map. That was not true.
A simple “Gosh, I guess I was wrong about the four cells being sufficient in MOD500” would have sufficed.
Giving me an unwanted lecture about some other method of investigation you advise us to take is just handwaving to distract people from your error. Man up, admit your error, and move on. Then we can discuss your next proposed analysis.
w.
They have learned nothing since their original paper. In fact, it looks like a regurgitation of the exact same method. I’m particularly disappointed to see that (a) they do not cite Watts(2012) and (b) Judith Curry is still a co-author. There was a lot of discussion on Judith Curry’s blog of the first paper, and it is very disappointing that she in particular appears to have learned nothing from it. They surely must have been aware of Watts(2012). Since it shows that their method is totally flawed, it is breathtaking that they go ahead without a mention. Surely responsible scientists would at the very least cite the paper and say why it didn’t apply to them. [I’ll answer my own question: The obvious problem is that it does apply to them and it tells them that what they are doing is invalid. ie, they are not reponsible scientists. It pains me to say this about Judith Curry, as she has been prepared to take a lot of flack in the interest of good science.]
Michael R. Moon on April 4, 2013 at 12:14 pm
Appart from a lack of a hockey stick you did not mention ‘Climate Change’, ‘Weird Weather’ or ‘Unprecidented’. Sorry your grant has been declined.
We, the people of the gate, suggest you apply the FEAR Index for a statistically significant study/press release that the media will pay attention to.
/sarc
Oh, and as an aside. Pilots like temperature sensors that are in the ‘wrong’ locations. We don’t want to know the temperature out in the countryside, we want to know the temperature of the air that our engines are sucking in during take-off – which is the temperature out on the burning-hot black ashphalt runway.
Side-of-runway locations give a great temperature for aircraft, but a lousy temperature for weather/climate studies. It warms up more than rural locations in the day, especially if the runway is black, and it cools down more at night. Luckily, grooved concrete is becoming more common for runways, which one assumes does not have such temperature extremes.
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The basic trouble with using airport based measurements is that airports are not typical of their surrounding environments. That did use to to matter becasue these measurements where ‘only intended ‘ to be used for aircraft movements and and out of the airfield so knowing what the conditions on the airfield was fine .
Once they became used for 101 other things , largely because they were there already and so it meant you did not have to create new sites not becasue there were ‘good sites’ , that is when the trouble started.
And even that it did no really matter because people accept weather is chaotic and hard to predict so ‘approx ‘ was good enough . But with AGW and its ‘settled science’ we seen claims of super accuracy with the data taken political importance , whilst the old problems over airport based measurements still remain .
This Page is a Photo Riot of Thermometer siting.
http://www.bobbyshred.com/fools/falsetemps.html
ralfellis before jets , when most airport where set up , knowing the weather conditions was a lot more important . There are still issues , such has the need to de-ice, that need temperature data .
My wife has told me I mustn’t read blogs like this because it puts my blood pressure up!
Steven Mosher says: April 4, 2013 at 11:39 Temperature measuring in the middle of an airport has only ONE valid and very important use. It gives the pilots information they need to set safe, efficient take off and landing speeds.
I’ve been flying for . . . too many, 36(?) years – That is news to me! What the other guy said.
My primary concern with temp at the airport is airfoil contamination by Ice/Snow/Frost/Freezing precipitation, or whether or not I’ll have to have a few hundred gallons of Glycol mix sprayed at very high cost. Temperature WILL affect air density and therefore Ground Speeds, and will affect landing and take-off distances, but it has >NO< significant impact on what AIRSPEEDS the Pilot or Automation systems reference to operate the Machine. To be thorough: As temperature increases, density decreases (pressure constant) – a given AIRSPEED (mass flow) will require a higher GROUNDSPEED. Hot days or High Elevation airports require longer runways or lower aircraft weights, all else being equal.
This is not addressing the main issue with regarding rural and urban.
An airport location if it is warmer will generally stay warmer all the time without changing trend. A badly located station will always remain on the warm side with the trend not changing. The trend is no good to use in these studies as it is totally irrelevant. When a rural location suddenly has a airport built, the station will only change for one years data suddenly and after that the trend’s influence on the months will be same over the long term. It only takes a change like this to offset the same data set over a recent period from one much longer in the past. The trend says nothing about how sudden changes to local stations have a long term effect.
I supply meteorological equipment to airports for a living. The exact siting usually depends on the availability of power and comms rather than the position that will give the most accurate representation of the temperature on the runway (which as mentioned above is what the pilots want, though not the meteorologists). There are also ICAO standards that define how far away instruments should be from the runway centreline, for safety reasons. This is typically around 100m minimum.
This makes me think of an applicable engineering example where one has to qualify his design by running it through a thermal test. Let’s say for this example the customer wants you to perform an eight hour test at -50 and since you usually use Fahrenheit at work you assume that is correct (it happens, information is lost in translation). Let’s also say you are a small company with no thermal chamber of your own so you have to hire a company to test it for you, while supplying someone to travel out there to monitor the design. You do all this, get the results back and after a week of aligning your results with the test house results you write your test report. You send it to the customer and they immediately come back telling you that it was -50 Celsius. Well you don’t want to spend the money to travel out again and you are under the gun to finish this all up so you make an addendum stating that the test run was only 4.44 degrees (Celsius) higher which isn’t much. Furthermore you look up all the components and see that they are all rated to -55 C (for this example) so they will work either way.
Should be acceptable right? Yet your unit hasn’t run at -50 C yet and from experience a few degrees can make a difference, especially if the design has flaws. A simple operating temperature range for each part doesn’t mean the whole design will work through that range and something as simple as a floating pin can cause problems at low temperatures. In the end the test has to be performed according to the customer’s demands or it hasn’t passed.
Seems to me the siting issue is very similar. It is expensive to go back and do so it’s easier to try and “fix” it with analysis, but in the end you have to bite the bullet or you will never know. The real work here is the gathering of data, not the analysis of that data (as important as that is). You also end up spending more money and time than if you had gone back in the first place.
This is reminding me of the North Korea at night from space Image . . . What I mean is, that it is a good relative representation but distorts the reality of the contrast area . . . IOW, there’s a Whole Lotta Nothin’ between the Connecticut coast and Plattsburgh NY, between Portland, and Presque Isle Maine, Between Gander Newfoundland and Boston, MA . . . . Between Vancouver, BC and Portsmouth, New Hampshire.
ralfellis says:
April 4, 2013 at 12:49 pm
Steven Mosher says: April 4, 2013 at 11:39 Temperature measuring in the middle of an airport has only ONE valid and very important use. It gives the pilots information they need to set safe, efficient take off and landing speeds.
_____________________________________
Not quite, Steven.
Temperature is irrelevant to landing speeds, which vary according to weight only (plus an allowance for high winds and gusts).
For take off, temperature is mainly used to determine thrust, and it is thrust and weight that determine the take off speed, not temperature. On our jet, temperature alone only adds one knot to V1 and V2 airspeeds, between 0 and 40 degrees c.
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I fear I’m in way over my head, but pilots need to know the temperature, because it affects the length of the take-off run, which limits the length of runway left to stop in case of an engine failure.
(do you take-off and limp the aircraft around for repairs, or slam on the brakes/ reverse thrust and run off the end of the runway).
Temperature matters for pilots, higher temperatures decrease engine power.
I’ll leave the nuances of where to place climatic weather stations, to others, for now 🙂
They looked for any bias due to UHI and didn’t find it in the Global Temperature Land Average.
Other things usefully you could look for in the Global Temperature Land Average is evidence of confirmation bias and perhaps what effect a massive human population increase has had.