By Steven Mosher.
In his august draft of Hansen2010, Dr. Hansen makes the following claim:
“We present evidence here that the urban warming has little effect on our standard global temperature analysis. However, in the Appendix we carry out an even more rigorous test.
We show there that there are a sufficient number of stations located in “pitch black” regions, i.e., regions with brightness below the satellite’s detectability limit (~1 µW/m2/sr/µm), o allow global analysis with only the stations in pitch black regions defining long-term trends. The effect of this more stringent definition of rural areas on analyzed global temperature change is immeasurably small (<0.01°C per century). The finding of a negligible effect in this test (using only stations in pitch black areas) also addresses, to a substantial degree, the question of whether movement of weather stations to airports has an important effect on analyzed global temperature change. The pitch black requirement eliminates not only urban and peri-urban stations but also three-quarters of the stations in the more than
500 GHCN records that are identified as airports in the station name. (The fact that one-quarter of the airports are pitch black suggests that they are in extreme rural areas and are shut down during the night.) Station location in the meteorological data records is provided with a resolution of 0.01 degrees of latitude and longitude, corresponding to a distance of about 1 km. This resolution is useful for investigating urban effects on regional atmospheric temperature.”
The are several claims here but I will only narrowly examine a few of them. I do not assess the claim about the role of UHI in the global record. That claim, in my mind cannot be assessed until the categorization of rural/urban is settled. So, my observations here have nothing to do with the effect of the issues that the case of Middlesboro will raise. In short, I still believe the world is warming and that man is the principal cause. Instead I will focus on Dr. Hansen’s methodology. In particular, the assumption that the station locations are accurate to .01 degrees or 1 km ( at the equator) and his assumption that selecting “pitchblack stations” gives you a rural sample. Very simply, the station locations are not accurate to .01 degrees as we have seen repeatedly in this series.
To understand this problem in detail requires focusing on individual stations. That focus should neither convince people that the problem is widespread nor should it convince them that it is rare. What it should do is motivate those concerned to be more comprehensive and diligent in their work and their criticism. The conclusions I draw then are most narrow. First, station location data is too inaccurate to use with a simple look up into nightlights, second, a pitch black requirement does not eliminate the issue, and third nightlights is not a reliable indicator of the actual physical processes that cause UHI.
We will start with the GISS inventory data for this station: found here
42572326006 MIDDLESBORO 36.60 -83.73 358 469S 11HIxxno-9x-9COOL FOR./FIELD C2 0
decoding: the latitude is 36.60, longitude is -83.73. The “S” indicates it is a small town, 11 indicates a population of 11,000 and finally the last value 0, indicates that the station is pitch black by nightlights. In H2010 this last value is apparently the one used to determine if a station is dark. Lets look what our replicated inventory shows. it shows that Nightlights is 0, but it also indicates that there is a light with value 54 within 55km of the site. More importantly, the expanded inventory shows that within 3km of the station location there is a light with a value more than 35 DN. Simply, there are urban lights very close to the proported station location. Because I process all the pixels within a radius of every station I can locate these cases automatically. I merely sort for all the pitch dark stations and then sort for those with urban pixels within 3, 5, 10 20 km all the way out to the 1degree cell boundary. Having identified this station as a possible issue the program then outputs the relevant google map with an overlay of nightlights contours. Like so: look at the pale blue cross. So, my algorithm works.
The program also outputs a kml file which then I can bring
up in Google earth and tour all the stations.
Not seeing anything that looks like a weather station at the location, perhaps at the airport? Well, if we check source data at NCDC we find the actual location(s)
And we can map all four which are all north of 36.60. In the bright zone
Checking close to the airport 36.61 -83.74 E
cellFromXY(hiResLights,c(-83.74,36.61))
[1] 276750752
The Nightlights value value at that location? not zero. its 33.
cellValues(hiResLights,cell=276750752) 33
To repeat. GISS have the station at 36.60,-83.73. The “lights at that location are Zero. But the actual station location is north of that in the bright zone .The lights at the airport are 33, which qualifies as Periurban, periurban type2. There are lights as high as 56 within the region. That qualifies as urban, urban type2 by Imhoff’s criteria.
The lights in the area near to the station suggest something btween periurban type2 or urban type 2. Urban type 1 is roughly 680 people per square km. The town in fact has 20 square km which translates into roughly 13K people. Checking back with the GISS inventory:
469S 11
11K people . You can check wikipedia. So Imhoffs nightlights did a good job of guessing the population, but if the station location is wrong you look up a dark pixel as opposed to the bright picels right next to them.
Hansen’s screen of pitch black stations is not adequate. A tighter screen, such as no dark pixels within the area of station location uncertainty would be better. We will work our way through that as we improve the tools here.
And in case you wondered about the temps?
Now there is one last thing I had to check. Hansen speaks of stations in pitch black “areas” Looking at his charts however it appears he picked stations at pitch black pixels. To check this the only think I can do is compare his view of USA stations with my view. They match fairly well ( he shows fewer which may mean the stations drop for other reasons like short records), so I’ll assume that he picked stations at pitch black “pixels”. As we have seen the value at the “pixel” of a station can be misleading because of very very minor location errors.
hansens graphic and then mine
For one final check, I produce a graphic of stations with periurban pixels within 3km ( marked by a cross) and those with periurban pixels within 5km of the site. Confirming the supposition that hansen has picked stations at pitch black pixels. he does not consider potential station location errors
An interesting start. Can you identify a list of stations that are furthest from any medium and/or strong light source and compare the trend at “dark stations most likely to really be dark” to “dark stations most likely to be light”?
Stations in a “black” area can still be sited over asphalt, on a roof, a parking lot, or next to an air conditioner. Gotta love Hansen’s thoroughness and thoughtfulness.
The site surveyed by surfacestations.org was 36.60861, 83.71444, which matches #2 on your list — the current station just began operating in 2010, as indicated on your chart.
Wow ! Great work – really interesting. Fantastic effort ….
Seems that Hansen is trying to provide more detail in his ‘high-level’ approach but doesn’t quite appreciate the value of going ‘brick-by-brick’. But as you and Anthony have demonstrated, the answer is in the detail. Well done.
Btw – wouldn’t those rural (black) airports have pavement too? Even if well-located to within 0.01 of a degree?
We will soon be hearing that it is “Rotten Black” and the light
is coming back in the morning, followed by widely scatterd darkness
in the evening…….
VY 73
I’m not as afraid of the numbers, as I am of what they do to the numbers after they get their hands on it……
One expert claims there’s been no warming, at the same time another expert claims it’s record breaking…..
Sorta makes the whole thing out to be a joke
latitude says:
October 19, 2010 at 5:33 pm
One expert claims there’s been no warming, at the same time another expert claims it’s record breaking…..
=========================================================
Theirs are a record breaking number of claims!
Nightlights are perhaps a sufficient condition for UHI at a properly identifed site, but as Jim points out above, not a necessary condition. The fact that Hansen ignores the effect of asphalt at dark sites proves he is either incompetent, has an agenda, or both.
I did note the time of the query by ‘guest’ at “3:38 am on 2010 10 19”.
I trust that the server clock is in GMT ? Ha ha ha!
Seems par for the course.
Agenda determines result and then select values to achieve desired effect.
Thanks for not trusting the untrustworthy.
Confirmation beats affirmation, any day.
Hansen is playing word games to cover his scam….. A temperature station in a Rural area surrounded by tarmac and concrete and next to an airconditioning heat exchanger is going to show nothing but flawed raw data….. and to deliberately use these elevated temperatures to support a climate hypothesis is a travesty of the scientific method.
Ground truthing was still being taught in GIS/RS course in late 1990’s when I last took a course, but perhaps the GISS folks took different courses.
This is really elemental stuff. Remember the bombing of the Chinese embassy in Serbia? Same thing, the idiots who programmed the mission had really good imagery, but did not do the simplest form of ground truthing.
Crude typo: “I do not asses …”
“In short, I still believe the world is warming and that man is the principle cause.”
From what I’ve been able to ascertain, the earth stopped warming nearly a decade ago (even CRU’s Phil Jones seems to agree) and may be entering a period of long-term cooling, perhaps even another Dalton Minimum or, worse, a Maunder Minimum, given the confluence of a negative PDO and the weakest solar activity we’ve witnessed in more than a century. There is some research indicating that we may be on the cusp of another Little Ice Age or even a Bond Event.
The notion that the warming of the latter half of the 20th century was human-induced is pure speculation based almost entirely on manipulated computer models, driven by a strong desire by government-funded scientists to milk the global warming scare for tens of millions in research grants. Even a doubling of atmospheric CO2 would probably have little or no impact on the earth’s temperature, as Dr. Ferenc Miskolczi seems to have demonstrated quite convincingly through his research.
“one-quarter of the airports are pitch black”
Sets alarm bells ringing!
(Talking of ringing, perhaps someone could phone then and see if they do shut down completely every night)
So what I see is that he is throwing out more data. That’s troublesome because he’s already thrown out so much. Now he finds a way to further work with the few stations that are left to apparently substantiate that his earlier data manipulations were OK.
But of course there are problems in the details of defining and describing this subset. And again, he can rely upon his known lack of precision of his own system to allow him to ignore it and at the same time to take advantage of it.
Does this guy and his minions sleep?
This is WUWT and we should fairly and painstakingly examine the premise and supporting data. Nice start. And by the way, I think most at this site don’t care about personal beliefs. “In short, I still believe the world is warming and that man is the principle cause.” Very well and good, if it helps you preserve your position off site. Personally I think we care about identification and use of data. Good job, great post.
Thank you
Not to be nettelson, but what might this method show if it happened to be “accurately” applied to all of the rural sites he has already thrown out during his long career as keeper of the data.
Just a thought.
This Hansen guy has never grown a garden during a cold summer in Wallowa County. The garden I tended with my grandma was in pitch black at night back country. So how did we keep our veggies growing on cold nights? We filled that garden with every heat absorbing substance we could find to keep our veggies tucked in and warm for the night.
The ONLY way this guy can back up his research is to compare his findings regarding pitch black areas via satellite with on the ground measurement of those same stations. Hansen, go back to graduate school. You must have skipped a lot of classes in research design.
Night lights are woefully inadequate. The most comprehensive classification of urban impervious surface area was conducted in 2004 using Landsat data, satellite observed nighttime lights, U.S. Census Bureau road vectors, and high resolution aerial photographs. I am not sure why this NOAA study has gone unnoticed by GISS.
http://pielkeclimatesci.files.wordpress.com/2010/09/isa-map-us.jpg?w=500&h=399
See “Large Scale Climate Modification – Agriculture & Urban Heat Islands Are Changing Regional And Continental Climates” http://pielkeclimatesci.wordpress.com/2010/09/10/guest-post-large-scale-climate-modification-agriculture-urban-heat-islands-are-changing-regional-and-continental-climates-by-bill-dipuccio/
I do not asses the claim about the role of UHI in the global record.
Need one more s in the bold word. Second sentence under italic paragraphs.
I was going to make the point about lights not causing UHI, but concrete, asphalt, etc causing UHI. Grr. Ok, there are often lights there, but methinks Hansen is overly enamoured of dark pixels. It’ll sound good at the next rally he speaks at.
The other thing is there are night lights and there are night lights. The former, in my mind, are the street lights with a bowl shaped diffuser and emit a lot of light upward. The other are”full cutoff” lights that send no light above horizontal. From the ground, you have a chance of seeing the Milky Way if full cutoff lights are in use and are not too close.
From an airplane, the difference is easy to spot. The full cutoff lamps have a diffuse reflection off the ground. (A lot of photographic subjects reflect about 18% of the incident light so that ground has likely swallowed up a lot of photons.) The bowl diffused lights have a similar ground patch, but right in the middle is a star-like point which is the @#$% direct light being spilled upward.
So, areas that use a lot of full cutoff lights will show up as darker and hence will have an inappropriately small UHI adjustment. Worse, as “enlightened” communities shift to full cutoff lights, they’ll be rewarded with higher adjusted temperatures!
Some other communities have been turning off every other streetlight to save money, they’ll also get hit with higher temperatures.
The town I live in has done some pretty horrible things with night time lighting. I should have gotten them a gift membership to the International Dark Sky Assn. See http://www.darksky.org
And another thing. It’s not pitch black on the surface of the planet. I’ve hiked part of the inner canyon of the Grand Canyon with just moonlight overhead because, well, let’s just say we didn’t have time to reserve a spot at the campground. Not so easy in tree cover in New Hampshire’s White Mountains when I lost track of time. Yay for little LED flashlight.
If you want pitch dark, you pretty much have to go in a cave or mine. No visible light photons.
Just because the satellite can’t see any reflected photons does not mean the night sky wasn’t gorgeous.
“principal cause.”
Hansen has really gone over to the Dark Side with this one. Is Dr. short for Darth? I think we should be told.
When Giss adjusts station data based on nightlights locations aren’t the only way they can induce an error. Below are a few stations previously classified as rural that now get adjusted due to use of nightlights. The 2-digit value at the end is the nightlight value. All stations with a value of greater than 10 get their record adjusted all the way back to the station start date.
Pictou,Ns 45.7N 62.7W 403713980020 1881-1906 17
Dalhousie,Nb 48.1N 66.4W 403717110080 1880-1916 36
Stony Mountain,Ma 50.1N 97.2W 403718520040 1880-1937 17
Gravenhurst Canada 44.9N 79.4W 403716300010 1880-1921 24
Peace River Crossing,Al 56.2N 117.2W 403710680050 1908-1935 14
Alta Lufthavn 70.0N 23.4E 634010490000 1880-1939 47
Norway House,Ma 54.0N 97.8W 403711410010 1885-1946 12
Lake Megantic,Qu 45.6N 70.9W 403716100030 1914-1947 30
Windsor Kings College,Ns 45.0N 64.1W 403713960030 1880-1948 18
I fail to see why stations that were rural by population 25 years ago and haven’t reported any data for more than 60 years should be adjusted according to recent lighting data. All of these have been adjusted one way or the other. The Giss algorithm makes no physical sense.
Their new nightlight classification has resulted in so many changes it seems the only purpose it serves is to allow them to claim they adjusted for UHI.
Of the stations actually in use.
886 formerly rural stations are now moved into the adjusted category.
450 suburban stations are no longer adjusted.
267 urban stations are no longer adjusted.
There are numerous stations with more than a million population that are no longer adjusted. Santo Domingo is one of them.
They are correct, co2 concentration has zero effect on this earth’s temperature, scientifically that is.
“An interesting start. Can you identify a list of stations that are furthest from any medium and/or strong light source and compare the trend at “dark stations most likely to really be dark” to “dark stations most likely to be light”?”
I suppose so. It all depends on the final counts. Right now I’m just plowing through the data looking for patterns of errors that may be correctable or cleanly eliminated
Bob Koss says:
October 19, 2010 at 8:16 pm (Edit)
When Giss adjusts station data based on nightlights locations aren’t the only way they can induce an error.
This misses the point. The Giss algorithm merely coerces bright stations to dark station values.
The key is which stations are truely rural.
Bill DiPuccio says:
October 19, 2010 at 7:01 pm (Edit)
Night lights are woefully inadequate. The most comprehensive classification of urban impervious surface area was conducted in 2004 using Landsat data, satellite observed nighttime lights, U.S. Census Bureau road vectors, and high resolution aerial photographs. I am not sure why this NOAA study has gone unnoticed by GISS.
ISA is derived from nightlights. In any case their are other proxies one would want to consider, vegatative indicies, population, ISA, irrigation. In the end, the analysis is all dependent upon station location accuracy.
Further you need a world wide dataset, US alone wont cut it
Ric Werme says:
October 19, 2010 at 7:09 pm (Edit)
I was going to make the point about lights not causing UHI, but concrete, asphalt, etc causing UHI. Grr. Ok, there are often lights there, but methinks Hansen is overly enamoured of dark pixels.
Brightness is a proxy for population. More dense population means higher buildings, more concrete, more waste heat. So, there is a good rationale to use it
Jim says:
October 19, 2010 at 5:06 pm (Edit)
Stations in a “black” area can still be sited over asphalt, on a roof, a parking lot, or next to an air conditioner. Gotta love Hansen’s thoroughness and thoughtfulness.
……
easy to say, tough to prove.
LearDog says:
October 19, 2010 at 5:43 pm (Edit)
I did note the time of the query by ‘guest’ at “3:38 am on 2010 10 19″.
I trust that the server clock is in GMT ? Ha ha ha!
##################
No, that was local time. ha, had a couple more hours after that.
tom says:
October 19, 2010 at 5:40 pm (Edit)
Nightlights are perhaps a sufficient condition for UHI at a properly identifed site, but as Jim points out above, not a necessary condition. The fact that Hansen ignores the effect of asphalt at dark sites proves he is either incompetent, has an agenda, or both.
…………..
actually, he does recognize that the station location information is not accurate enough to assess that. This is not about bashing a man. This is about a cold factual assessment of station location accuracy and its impact on nightlights readings.
Phil’s Dad says:
October 19, 2010 at 6:23 pm (Edit)
“one-quarter of the airports are pitch black”
Sets alarm bells ringing!
(Talking of ringing, perhaps someone could phone then and see if they do shut down completely every night)
##########
actually if you take the time to google tour the airports you will see that a good portion of the airports in the ROW are remote and not lit. There is also a variable that indicates how far the airport is from the town.
Touring 7300 stations in google earth is time consuming. More people should do it. I’ve made the assets to do this freely available
Policyguy says:
October 19, 2010 at 6:23 pm (Edit)
So what I see is that he is throwing out more data. That’s troublesome because he’s already thrown out so much. Now he finds a way to further work with the few stations that are left to apparently substantiate that his earlier data manipulations were OK.
######
you dont need that many stations to define the average. refining the dataset to the best stations is a perfectly reasonable approach. GIGO.
What’s the point?
Find a few locations where a very, very thorough on the ground check indicates the records will be maybe just okay going back a few decades. Then use eyes, ears and commonsense. That might tell you the tiny bit that’s a tiny bit knowable about past climate. If you’re really curious.
Please don’t make a graphic that’s like Hansen’s, only better. There’s no AGW, and I don’t want a crap energy supply, carbon taxes or emissions trading, courtesy of the Hastily Reformed Church of AGW.
If you are measuring temp using a max/min thermometer, a jet exhaust is going to effect the results no matter how many lights are/are not turned on at night.
“that man is the principle cause”
Should be principal.
So the only thing that is being measured is how bad we are at measuring. How about using a temperature trend of zero, comparing all station raw data to that then go check all the stations that deviate from that trend to find out why. No assumptions, just curiosity. Science you can believe in.
In the last few days EM Smith’s research has shown that all the METAR temperatures are rounded up to the nearest degree. As the temperature record has been gradually taken over by this reporting method (particularly since the 90’s) this may have resulted in a large warming bias being built in to the data.
Just shows how difficult it is to get an accurate temperature let alone an accurate average temperature. Perhaps we should take note of those peer reviewed papers out there which prove that it is impossible to take a temperature unless a system is in equilibrium. The atmosphere never is!
The thing that most surprises me is that only assumptions seen to be given any validity. No-one appears to attempt to obtain real measurements/observations. I’m certain I could design an experiment to actually measure UHI (assuming it exists) in 10 minutes. ‘Struth, I’ve practically done it whilst writing this post.
The sooner “climate scientists” realise that hard data trumps assumptions the better off they will be, if only because they will then be using the scientific method.
Steven,
I’m perplexed by your belief that the world is warming and that man is the root cause. We’re on the rebound from the LIA (oceans have risen at a consistent pace for 150 years) and you’re obviously a bit skeptical of UHI (and cautious in believing in those who discount it). Unjust wonder what is convincing that man is the root of any observed warming?
Come on guys, you can all see the steep upward temperature trend due to global warming in the Graph Steven posted for MIDDLESBORO .
/Sarc off
Hansen and all the others use thermometers to create their temperature series. It’s ironic then that the one thing they don’t use is thermometers to measure the UHI bias for each station.
People who have done temperature scans simply by driving a car with an external thermometer show very consistent UHI effects that can amount to several degrees. So why are the scientists not doing this? One obvious reason is cost. Counting black pixels will always be much cheaper. But there’s another, less honourable, reason. Using indirect methods to assess UHI gives lots of opportunities to, shall we say, ‘adjust’ the data in order to confirm any initial beliefs.
In my view there’s no substitute for measurements that are simple and direct and do not require endless ‘adjustments’. To do repeated scans around a large number of temperature stations would cost millions, but it would be well worth the expense. The AGW belief threatens to cost the world countless trillions of dollars, so a relatively trivial cost of a few millions would be well worth it.
Will it happen? Not a chance. With UHI properly accounted for, the measured amount of global warming would probably be cut in half. That would be Hansen’s worst dream come true.
Chris
Chris Wright says:
October 20, 2010 at 3:21 am
The largest issue for me is that they do have the money, but they use it to create even more models based on what *MAY be faulty data, while other people who are unpaid are poking holes in their theories by these simple and cheap methods. Is the data faulty? Well without a good old fashioned testing we won’t know for sure how faulty or whether it makes a difference…
“The effect of this more stringent definition of rural areas on analyzed global temperature change is immeasurably small (<0.01°C per century).”
That’s exactly how much the CO2’s part in the atmospheric composition of gases has increased during the past century and funnily enough it is also how much less influence the decrease in the Sun’s activity has on the Tropospheric temperature. – According to some “Scientists” that is.
So in the case of CO2, 0.01% is too much and in all other cases too miniscule to be significant.
Hansen trained as an astrophysicist–he only collects data from space. Getting down on the ground and looking at sites is beneath his dignity.
Why bother with the demonstrably inadequate nightlights variable when Anthony has shown that microsite factors are abundant and consequential? Even population density is more refined that a dark/light pixel analysis. Unless, of course, the ulterior purpose is to develop algorithms for future work and demolishing Hansen’s lazy effort is a nice byproduct along the way.
Phil’s Dad says:
October 19, 2010 at 6:23 pm
(Talking of ringing, perhaps someone could phone then and see if they do shut down completely every night)
Given the relativiely small number of locations, you’d think some simple direct enquiries might be worthwhile.
Steve, have you contacted Hansen with this information?
MattE says:
October 20, 2010 at 2:55 am (Edit)
Steven,
I’m perplexed by your belief that the world is warming and that man is the root cause. We’re on the rebound from the LIA (oceans have risen at a consistent pace for 150 years) and you’re obviously a bit skeptical of UHI (and cautious in believing in those who discount it). Unjust wonder what is convincing that man is the root of any observed warming?
1.known physics. more ghg’s cause warming, not cooling.
2.’on a rebound from “LIA” is a meaningless restatement of observation .
its getting warmer. the cause is not “a rebound”. thats circular reasoning.
“Will it happen? Not a chance. With UHI properly accounted for, the measured amount of global warming would probably be cut in half. That would be Hansen’s worst dream come true.
Chris”
not physically possible. land is only 30% of the total. UHI might contribute .1-.15C
The number of data stations is not overly large, especially post 1990. Is it not reasonable to have half a dozen NASA smart guys look at individual stations on Google-Earth or NASA satellite imagery, plus the temp profiles, pre- and post-adjustments, and make a rural/urban call (and suspicious adjustment call)? Then follow up? Or are human brains not up to the task that computer programs do?
You know, all that is needed to refute Hansen’s ridiculous analysis is some back-of-the-envelope stuff Roy Spencer posted here not long ago. Have you published yet, Roy? Might be a good time, finishing your paper with a thorough evisceration of Hansen’s claims.
Spencer shows, for those who don’t recollect his analysis, that MOST of the UHI effect takes place below 100 persons/km^2, and the effect is strongest (about 3x the rate for larger densities) under 20 persons/km^2.
Wondering what the luminosity rating for populations under 100 persons/km^2 is? I imagine in most cases it is “pitch black”. In other words, simple analysis of UHI shows that the interesting distinction between UHI and non-UHI stations will occur BENEATH the pitch black threshold. Hansen’s analysis is akin to denying that water freezes when it gets cold because he tried cooling it all the way to 35 degrees F, and “that’s damn cold for swimmin’ ” but it didn’t freeze.
Dr Hansen really needs to get out of the office and out in the real world to check if his assumptions have merit. If he did this his papers would have a lot more value as science. “The result is what I wanted” is not science.
Steven Mosher says:
October 20, 2010 at 8:24 am
“2.’on a rebound from “LIA” is a meaningless restatement of observation .
its getting warmer. the cause is not “a rebound”. thats circular reasoning.”
I can’t believe you put that in print as an argument.
What CO2 or GHG increase accounts for the rise in temperatues since the last Ice Age let alone the the LIA?
Or does that not somehow count?
So why is it a “meaningless restatement”, I always thought that Science was based on Observations?
http://blogan.net/blog/wp-content/2006/10/korea2.jpg
North Korea must be the coldest country in the world is guess, and it must be true since Japan (the bright islands just east of it) that i have visited several times now is blistering hot (just don’t vist the westcoast and Hokkaido during the wintermonths and stay away from the mountainregions as well during those months).
I always wonder how someone like Mr. Mosher can be so astute about the scientific process and data analysis and not be able to recognize that CO2 emissions cannot warm the climate more than a probably undetectable amount. Water vapor is the dominant relevant gas and part of a massive global heat engine which convects heat upwards where it is lost to space. Only be specifically ignoring this huge elephant in the room can CO2 have any effect – and, even so. it s still small. Unless he has some other mechanism by which he thinks we are warming the climate, this is about the only supposed factor.
Has anyone thought to check Hansen’s stations against Surfacestations results? If Hansen’s list has both well and poorly sited stations it would be possible to compare the temp increase of the 2 lists and quantify the validity of his work.
I thought I would have a go att analyzing the 19 weather stations in Sweden on the GISS list.
Two of them have zero nightlights:
64502142000 JOKKMOKK 66.63 19.65 264 313R -9HIFOLA-9x-9WOODED TUNDRA A 0
64502456001 KREUZBURG SWEDEN 60.00 18.20 621 19R -9HIFOCO25x-9COOL MIXED A 0
The position for Jokkmokk is way off. The position given is in the middle of a large lake, so it is not strange that there are no nightlights. The actual weather station is at Jokkmokk airfield at 66.49 N, 20.17 E, 25 km to the SE, on the other side of Jokkmokk town. By the way the vegetation in the area is taiga (coniferous forest), not wooded tundra.
The case of Kreuzburg is even odder. There is no such place in Sweden. The altitude is absurd, the closest mountains that high are some 300 km to the northwest. The actual altitude at 60.00, 18.20 is about 40 meters. The position is in the middle of a large forest with no houses nearby, thus explaining the zero nightlights. There is a Kreuzburg (romanian name Teliu) near Brasov in Romania that is at approximately the right altitude. Perhaps that’s the place? The station number seems to indicate that the station might actually be Films Kyrkby, a small village at 60.23 N, 17.90 E, i. e. ca 30 km NW. Whether the actual weather record is for Films Kyrkby or Kreuzburg I don’t know. The difference in altitude would probably mean that the figures would not be obviously absurd.
So that is the two “dead black” sites in Sweden, both obvious errors. So let us take a look at how valid Hansens claim of 0.01 degree accuracy is at the other Swedish sites:
64502080000 KARESUANDO 68.45 22.50 327 371R -9FLFOno-9x-9WOODED TUNDRA B 12
I don’t know exactly where the weather station in Karesuando is, but it is definitely not in the position given, which is not even in Sweden, but rather about a kilometre inside Finland.
64502128001 STENSELE 65.10 17.20 327 380R -9HIFOLA-9x-9MAIN TAIGA B 12
The position given is in the middle of Rackojaure lake c. 4 km NE of Stensele village.
64502183001 LULEA FLYGPLATS SWEDEN 65.60 22.10 17 23S 42FLxxCO 1A 3MAIN TAIGA C 71
The indicated position is about 6 kilometres north of Lulea airport (flygplats=airport), inside Luleå town and in the middle of Luleaelv river
64502196000 HAPARANDA 65.83 24.15 6 5R -9FLxxCO 3x-9COASTAL EDGES C 41
The position given is also in the middle of a River (Torneaelv), but otherwise it seems likely to be within a kilometre of the correct position.
64502226000 OSTERSUND/FRO 63.18 14.50 370 317S 14HIxxLA-9A 8MAIN TAIGA B 22
The weather station is at Oestersund/Froesoen airport. The indicated position is on a golf course about a kilometre south of the airport.
64502361001 HARNOSAND SWEDEN 62.60 18.00 8 18S 19HIxxCO 5x-9WATER A 7
I don’t know exactly where the Haernoesand weather station is either, but is very unlikely to be in the indicated position on overgrown former farmland on Haernoe island, 4 km SE of Haernoesand.
64502418000 KARLSTAD FLYG 59.37 13.47 55 55U 51HIxxLA-9A 1WATER C 38
Also an airport. This position is pretty good. It is in a suburb about 500 meters NE of the airport
64502439001 OREBO SWEDEN 59.30 15.20 33 42U 171HIxxLA-9x-9MAIN TAIGA C 95
Also pretty good, probably within a kilometre of the correct position. Not in a taiga area though.
64502458000 UPPSALA 59.88 17.60 41 29U 157HIxxno-9A 2COOL MIXED C 80
Another airport. The position given is in a suburb of Uppsala town about 1.5 kilometers south of the airport.
64502464000 STOCKHOLM 59.33 18.05 52 13U 1357FLxxCO10x-9WATER C 120
This is the site at the old observatory in the middle of the city, which incidentally has a continuous temperature series since 1756. The position given is about 1.5 km SSW of the true one.
64502512000 GOTEBORG/SAVE 57.78 11.88 53 41U 691FLxxCO 7A 2WATER C 36
Also an airport. An excellent position, only about 300 m NW of the actual weather station.
64502512001 TORSLANDA 57.72 11.78 3 11U 691FLxxCO 1A 3WATER C 37
Classed as an aiport but isn’t. Torslanda airport closed in 1977. The position given is in a suburb about a kilometre north of the old airport.
64502550000 JONKOPING FLY 57.77 14.08 232 183U 131HIxxno-9A 5COOL MIXED C 24
Also an airport. A good position within a few hundred meters from the airport.
64502576001 VASTERVIK SWEDEN 57.80 16.60 9 7S 21FLxxCO 3x-9WATER C 36
I don’t know exactly where the weather station in Vaestervik is, but is not likely to be very close to the position given
64502590000 VISBY AIRPORT SWEDEN 57.67 18.35 47 18S 20FLxxCO 1x-9WATER B 17
This is NOT classed as an airport, despite “airport” being part of the name, and it most certainly is an airport. The position is excellent, being the only one except Goteborg/Säve to be within the actual airport area.
64502620001 HALMSTAD SWEDEN 56.70 12.90 64 37U 50HIxxCO 5x-9WARM CROPS C 37
This also is not classed as an airport, though it is one. The position is also badly off, being in mixed forest/farmland about 5 km east of the airport.
64502627001 LUND SWEDEN 55.70 13.20 73 40U 55HIxxCO 8x-9WARM CROPS C 41
Also an old station with a record going back to 1753, and now in the center of a major town. The position is within a kilometre of the correct one.
So that is it, folks. The two stations with zero nightlights have completely muddled positions, and would almost certainly not be “pitch black” if the positions were correct. At least half of the remaining stations are not within 0.01 degrees of their true positions. Airport/Non Airport data are unreliable. Population data are out of date (Lund has 110,000 inhabitants, not 40,000) and habitat data are shaky.
So what, this is climate science!
Wherever century-long small-town records are found intact, they manifest (as a statistical rule) far less, if any, warming during the 20th century than cities of modest size. Although Middlesboro is fragmented into four pieces, it shows that eastern Kentucky is no exception to that rule. Direct comparison with the records from Knoxville TN and Lexington KY (the two nearest urban stations) reveals that urban growth has added ~0.6K per century to current readings at the latter stations. This is very much in line with what is found by such comparisons throughout the globe.
The basic problem is that century-long small-town records are seldom found in GHCN for stations outside the US. China and Mongolia have none (as does all of equatorial Africa), Brazil has exactly one, and even Europe offers precious few (none in France, Ukraine, or European Russia. ) Thus records from cities of modest size (pop. of a few hundred thousand) serve in lieu of small towns as the de facto benchmark for “homogenization” of records from major cities. It requires a naiivete to which no one should aspire to accept the global station averages from GISS or CRU as having been corrected in any credible way for UHI. If anything, independent compilations show that these results differ little from an indiscriminate average of ALL unadjusted data records.
It’s only blind belief that sustains the premise that we know the century-long global temperature trend to within <0.1K. The ad hoc night-light criterion is totally misleading in undeveloped countries , where electricity is in short supply. It only serves as a distraction from patent corruptive effects of urban growth upon temperature records found routinely in GHCN.
tty says:
October 20, 2010 at 2:01 pm
Great analysis, thanks.