I’ve reposted this here in entirety with permission from Pierre Gosselin of “No Tricks Zone“, and it is well worth the read. Much of this work was inspired by posts that have appeared on WUWT. Ed Caryl has done a great job pulling various threads of info together. One generally doesn’t think of any Arctic circle outposts as being “urban” but the fact is that islands of humanity, essentially small towns, surround many of these stations. And in the Arctic, you produce a lot of energy (which has to go somewhere) or you die. What I find most interesting is the plot of “isolated” stations versus the Atlantic Meridonial Oscillation (AMO); a clear correlation of the driver for those temperatures.. – Anthony
By guest writer Ed Caryl
Arctic stations near heat sources show warming over the last century. Arctic stations that are isolated from manmade heat sources show no warming. The plots of “isolated stations” and “urban stations” below clearly illustrate the differences.
Stevenson Screen, Verhojansk, Russia
All the GISS temperature anomaly maps show the Arctic warming faster than the rest of the globe, especially northern Alaska and Siberia, but the satellite data shows a different pattern. See the 2 charts for 2009 that follow. The GISS surface map:
Satellite chart:
The baseline period selected for the GISS surface temperature chart is the 1933 to 1963 Atlantic Multi-decadal Oscillation (AMO) warm period. This period more closely matches today’s temperatures than the default 1951 to 1980 cool period that GISS uses. The satellite data uses the average over the satellite period since 1979, the modern warm period.
The satellite data show cooling in central Siberia, similar to the surface anomaly map, and very little warming for most of Alaska. It also shows cooling for the Antarctic Peninsula, where the surface map shows warming. But there is a scattering of hot grid squares across the HISS surface station map for the Arctic. So what is going on?
I selected the stations that correspond to those warm grid squares, as well as other stations in the same latitudes. In this age of everyone carrying a camera posting all photos on the Internet, there is a lot of information available on these stations. For some I could locate the Stevenson screens, for most I’ve found pictures of the surroundings, while others have investigated many of these sites already, and so links to that research are included. I downloaded the raw temperature data from GISS for 24 stations closest to the North Pole, which are all classified as “rural”.
“Urban” Arctic Stations
Contrary to GISS claims, many of these stations are actually not “rural” with respect to their siting quality. Many are at airports associated with sizable towns or research stations with sizable staff and infrastructure. In the Arctic, any town of more than a few families can be a large heat source. In the case of many towns in Russian Siberia, “central heating” takes on a whole new meaning. These towns have a central power plant that provides electricity and steam heat to the whole town. Large pipes, both insulated and un-insulated, carry steam, water, and sewage, up and down the streets to and from each dwelling. These pipes cannot be buried because of the permafrost, so they are elevated, and at street crossings are elevated 4 or 5 meters. The temperature differential between these pipes and the surrounding air can be 140° C in winter, and even more for a pressurized system.
But GISS applies the same Urban Heat Island (UHI) criteria to all stations globally, regardless of the latitude or average temperature. They look at the satellite night brightness and population to judge whether urban or rural. By GISS criteria, all the stations in the high Arctic are rural; there are no corrections for UHI.
But let’s look at each of these “urban” locations. Each name is also a link to the GISS surface temperature raw data.
List of Urban Arctic Stations (see the annex at the end of this post for details on each station)
1. Kotzebue, Ral (66.9 N,162.6 W), Alaska
2. Barrow/W. Pos (71.3 N,156.8 W) Alaska
3. Inuvik (68.3N, 133.5W) Inuvik, Canada
4. Cambridge Bay (69.1 N,105.1 W) Nunavut, Canada
5. Eureka, N.W.T. (80.0 N,85.9 W), Canada
6. Nord Ads (81.6 N,16.7 W Northeast Greenland
7. Svalbard Luft (78.2 N,15.5 E), Norway
8. Isfjord Radio (78.1 N,13.6 E), Norway
9. Gmo Im.E.T.(80.6 N,58.0 E), Russia
10. Olenek (68.5 N,112.4 E), Russia
11. Verhojansk (67.5 N,133.4 E), Russia
12. Cokurdah (70.6 N,147.9 E), Russia
13. Zyrjanka (65.7 N, 150.9 E), Russia
14. Mys Smidta (68.9 N,179.4 W), Russia
15. Mys Uelen (66.2 N,169.8 W), Russia
The following graphic is a temperature chart for 10 of the above stations (5 of the shorter ones were left out to avoid over-crowding). All are warming, some faster than others. Barrow, for which we have the UHI study, is not the fastest warming.
Temperature trends of the “urban” stations.
Isolated Stations
Now let us look at the isolated stations, which are located at similar latitudes like the above “urban” stations. One important thing to note about these isolated stations – there is limited electrical power, and so incandescent light bulbs in the Stevenson screens is unlikely. Detailed descriptions of these stations are listed in the annex at the end of this report.
16. Alert,N.W.T.(82.5 N,62.3 W), Canada
17. Resolute,N.W. (74.7 N,95.0 W), Canada
18. Jan Mayen (70.9 N,8.7 W), Canada
19. Gmo Im.E. K. F (77.7 N, 104.3 E), Tamyr Peninsula, Russia
20. Ostrov Dikson (73.5 N,80.4 E, Russia
21. Ostrov Kotel’ (76.0 N,137.9 E), Russia
22. Mys Salaurova (73.2 N,143.2 E), Russia
23. Ostrov Chetyr (70.6 N,162.5 E), Russia
24. Ostrov Vrange (71.0 N,178.5 W) , Russia
Now here is the chart of the temperatures of these isolated stations, not subjected to manmade structures or heat sources.
Isolated Stations
Note that most of the trends are flat or decreasing. Only Resolute and Ostrov Vrange are increasing slightly. Both of those might be slightly influenced by UHI. The longest records clearly show warming in the late 1930’s and 40’s, and cooling in the 1960’s, and none show a hockey stick. The GISS data for Alert ends in 1991, though the weather station is still there, and still reporting. Data for Mys Salaurova and Ostrov Chetyr also ends at about that time, probably due to the fall of the Soviet Union.
Here is an average of all the isolated stations:
Isolated Stations – Average
Note that the peak-to-peak trend is nearly zero. The linear trend is about 0.4°C/century, but the R2 value (the statistical significance for the trend) is very low, 0.023.
Here is a plot of the AMO versus the average temperature of the isolated stations.
The temperature as measured at stations isolated from any UHI is simply tracking the AMO.
Looks like an awfully good fit. There is very little, if any, global warming. We need to wait until the bottom of the next AMO cycle to get a decent reading of global temperature change. That will be in about 2050 if the AMO cycles as it has since 1850.
———————————————————————————————-
Annex – station descriptions
The “urban” stations, nos. 1-15
1. Kotzebue, Ral (66.9 N,162.6 W),
2. Barrow/W. Pos (71.3 N,156.8 W)
These towns are of similar size, and are growing at the same rate. In 1940, both towns had a population of 400. In 1980 both had just over 2000 population, and now they both have over 3000 people. Both have airports of sufficient size to handle multi-engine turboprop and small jet aircraft, and both are served daily by regional airlines. Kotzebue is on a peninsula and the airport is across the middle of the peninsula, somewhat restricting the growth of the town. Barrow has somewhat the same problem due to a series of small ponds around the town and the airport. Barrow was studied for UHI effects in 2003. That paper was in the International Journal of Climatology here. That paper describes the UHI average temperature increase in winter as 2.2°C compared to the surrounding hinterland. GISS data indicates that Barrow average temperature has increased over the years as population has increased. (See below, or click on link above.)
Barrow, AK
Source: http://en.wikipedia.org/wiki/File:BRW-g.jpg
Source: http://en.wikipedia.org/wiki/File:OTZ-g.jpg
The Barrow NWS station (Stevenson Screen) is here. On the airport picture, it is at the base of the rotating beacon tower. Kotzebue NWS station is not visible in published pictures.
Inuvik is a relatively new town, begun in 1954. The population as of 2006 has grown to about 3500 people. Because it is a “planned” community in the arctic, built on permafrost, the water and sewage infrastructure is above ground in heated and insulated “utilidors”, like the heating systems in Siberia. The weather station, from weather reports, Google Earth and Google Street View, appears to be at the airport, in a compound just north of the entrance.
4. Cambridge Bay (69.1 N,105.1 W), Cambridge Bay, Nunavut, Canada
There is a Wikipedia picture of Cambridge Bay here. The population has grown from just a few people in the 1940’s to about 1500 today. It also has an airport with daily regional airline service.
5. Eureka, N.W.T. (80.0 N,85.9 W), Eureka, N. W. T., Canada
There are the only four stations at or north of 80° latitude, Eureka, Alert, Nord and Krenkle (Gmo. I.M.ET). Only Eureka has an unbroken temperature record to the present date, and it begins in 1947. The population at Eureka has
Eureka station
never been high. In winter it has always been 4 or 5 men. In summer, the population increases to as high as 20. The station infrastructure though, has expanded through the years. Each year, some of those 20 workers add or expand buildings. In the beginning, it was one or two buildings, with water and sewage handled in tanks and barrels internal to the buildings. The Stevenson screen was originally placed where the blue New Main Complex building is now. When that was built, the Meteorological instruments were moved to the current location. Over time, the water supply, plumbing, and sewage treatment was upgraded and the outfall pipe installed. It, of course, must be heated to facilitate flow to the sewage lagoon. All the water pipes exposed to the outdoors must be heated to prevent freezing.
Image from a recent article by Anthony Watts on WUWT here.
6. Nord Ads (81.6 N,16.7 W, Northeast Greenland
Nord Station
Nord is the furthest north inhabited place on earth, on the Northeast coast of Greenland. It was built in the period from 1952 to 1956 as an emergency airfield for aircraft operating out of Thule. Access is impossible by sea because the sea ice never moves away from the coast there. Legend has it that “Blowtorch” Murphy, a mythic arctic construction worker, scraped the first runway, using a parachute dropped caterpillar tractor after he himself parachuted onto the site. His nickname came from his habit of wearing a lit blowtorch hanging from his waistband on a wire; a lit blowtorch being somewhat useful when working outside when it’s 40° below zero.
There are about 40 buildings at Nord. Not all of them are continuously heated, but those near the Stevenson Screen are. The winter population is 5 or 6 men. More pictures here.
7. Svalbard Luft (78.2 N,15.5 E)
8. Isfjord Radio (78.1 N,13.6 E)
These two stations are only 47 kilometers apart. But data for both is fragmentary for 1976 and 1977, and there is no overlap. Svalbard Luft (airport) has been discussed on WUWT here and here, so I won’t cover it in detail here. Warwick Hughes has an article on Isfjord Radio here that makes the case for warming of Isfjord Radio due to moving of sea ice away from the islands in summer since 1912. Neither station in Svalbard shows on the anomaly map because there was no common station in both the base period and the anomaly period. Here’s a map with 1998 to 2008 as the base period where Svalbard appears.
This is the Krenkel meteorological station on Hayes Island, or Ostrov Kheysa in Russian, in the Franz Josef Land Archipelago, Russia. Link The station has been moved or re-built twice since it was established. It was moved from Hooker Island (article in German) in 1957/58. A fire destroyed the power station in 2000, and it was rebuilt in 2004 closer to the shoreline. The GISS record is from 1958 with a gap from 2001 to 2009. The population was as high as 200 during Soviet times, but is down to 4 or 5 now. The population and the temperature seem to track roughly during Soviet days, and the move in 2004 was to a warmer location. In the picture you can see the old buildings on the ridge in the distance. The red grid-square on the anomaly map above corresponds to this station.
Source: http://www.sevmeteo.ru/foto/15/88.shtml
This is the town of Ust’-Olenek, Russia.
The town doesn’t look like much, but notice the Tundra Buggies parked next to the Stevenson Screens. It is on the Laptev Sea, on the northern Siberia Coast, but on a peninsula on a south-facing beach. The buildings are right on the shore. The wide view above was taken from out on the ice. This is one of the few places in Russia that the Google Earth satellite view actually has enough resolution to see the Stevenson Screens. They are much too close to the heated building.
11. Verhojansk (67.5 N,133.4 E)
This is one of the “centrally heated” towns in Russian Siberia. The picture at the top of this article is of the Stevenson Screen. Verhojansk is called the “cold pole” of the earth, but the measurements are too warm by far. Look closely at the picture. Any photographer will note that the warm glow inside the Stevenson Screen is just the color temperature of an incandescent light bulb. If the steam heat in the town isn’t enough, or the cattle in the pole-barns in the distance, the heat from the light bulb will warm up the measurements. This site was covered on WUWT here and here. Anthony Watts notes that warm anomalies would appear and disappear in this part of Russia “as if a switch were thrown”. Could it be as simple as the switch on that light bulb?
Also spelled Chokurdakh. The population has been dropping in recent years, but was still over 2500 people in 2002. The town is sandwiched between the Indigirka River and the airport. There is no way to tell where the Stevenson Screen is located, but the infrastructure at the airport blends right into the town. See an aerial photo here.
13. Zyrjanka (65.7 N, 150.9 E) Also spelled Zyryanka, another steam-heated town in eastern Siberia, well inland. The airport is in this picture on the north edge of town, along the Kolyma riverbank. This airfield was built during WWII as a stop for aircraft being ferried to the Soviet Union from Alaska. A second airport 7 miles west of town was probably built during the cold war for the military. The town was established in 1931. The population is currently about 3500. During the Soviet Union it was up to 15,000.
14. Mys Smidta (68.9 N,179.4 W)
Or Cape Schmidt. John Daly wrote a bit about this location in 2000 (scroll way down in the article). The population was nearly 5000 in 1989, but has dropped since the fall of the Soviet Union. The population now is probably less than 1000. It is on the north coast of eastern Siberia, nearly at 180° longitude. The airbase there was built in 1954 as a staging base for any bombers headed for the U. S. It is still used by a regional airline.
15. Mys Uelen (66.2 N,169.8 W)
Or Cape Uelen. This is on the easternmost tip of Siberia, across Bering Strait from Kotzebue, Alaska. The current population is about 700 people. It is also centrally steam heated. The town is restricted by the geography, on a narrow spit sticking out into the sea, backed by a cliff on the landward side. The airport is a helipad. Cargo and fuel arrives by barge in the summer.
Below is a temperature chart for many of the above stations. All are warming, some faster than others. Barrow, for which we have the UHI study, is not the fastest warming.
16. Alert,N.W.T.(82.5 N,62.3 W), Alert, Canada
Alert, Canada has had a weather station since 1951. The population has never been more than 4 or 5 in the winter, with a higher population in the summer. I could not definitively locate the Stevenson screen, but there are two possibilities in this photo, both well away from the buildings.
THE ISOLATED STATIONS, NOS. 16-24
17. Resolute,N.W. (74.7 N,95.0 W)
The population of this Canadian station rose from zero prior to 1947, to 229 in 2006. There is an airport here, and the Stevenson Screen can be seen across the aircraft parking area from the airport terminal at the left edge of the photo.
Pictures of the station are here, and a web site is here. The 18 people on the island live at Olonkinbyen, or Olonkin “City”. The meteorological station is 2.6 km away. The 4 people that work there live in Olonkin City. The Stevenson Screen appears to be well away from the station building, and the surroundings have probably not changed since the station was built.
19. Gmo Im.E. K. F (77.7 N, 104.3 E)
This is a Russian station on the Tamyr Peninsula at Cape Chelyuskin (Mys Chelyuskin). Nothing is visible at that location on the Google satellite view, but the resolution is very low. I found an article by Warwick Hughes dated September 2000 that speaks of cooling of the Tamyr Peninsula here. He also talks about “non-climate” warming of Verhojansk and Olenek.
20. Ostrov Dikson (73.5 N,80.4 E
Dikson, Russia airfield
This is Dickson Island in English. There is a town of Dikson 10 kilometers away on the mainland. The airport is on Dikson Island at the point called Ostrov Dikson on the map below. Pictures of the airport can be seen here. The town is pictured on this 1965 stamp.
Wikipedia link
21. Ostrov Kotel’ (76.0 N,137.9 E)
The full name is Ostrov Kotel’nyy. In English this is Kettle Island. The first documented explorer found a copper kettle, so obviously he was not the first person to find the island. A single building is barely visible on Google 3D mapsat the “settlement” known as Kalinina. This may be the meteorological station. No other signs of civilization can be seen on the whole island.
22. Mys Salaurova (73.2 N,143.2 E)
This also spelled Mys Shalaurova. The station is on the south-facing shore of an island and is visible on Google Earth here. There is a tide gauge, and the tide data is on that same page.
23. Ostrov Chetyr (70.6 N,162.5 E)
The full name is Ostrov Chetyrekhstolbovoy. This is a small island in the East Siberian Sea in the Medvezhy Island (Bear Island) group.
Map source here.
A description of the place is found: here. “A polar meteorological station and a radio station are situated on the shore of a small bay which indents the S side of the island.”
24. Ostrov Vrange (71.0 N,178.5 W)
This is otherwise known as Wrangle Island. It is about 125 kilometers off the Siberian coast on the 180th meridian. The weather station is at Ushakovskiy on a spit at Rogers Bay, at the right in this picture, well separated from the village. One building in the village is visible at the left. Link
The population in the village grew to as many as 180 people in the 1980’s, but when the Soviet Union dissolved, subsidies declined and the population moved to the mainland. The last villager was killed by a polar bear in 2003. The population at the weather station, when occupied, has always been 4 or 5.
I will not say that the anomaly approach is incorrect, but there are issues with it as well. As far as I can tell, its the best method known right now, but it is not perfect. To argue that its the end-all is kind of ignoring the issues that it also brings up.
To clarify, anomalies are based on the area-weighted global average, which if this is incorrect for an area, it kind of defeats the purpose of using this in the first place. To put it simply, you can use this approach in the data above and it will probably change what you see simply because of the transformation of the data so to speak. But that begs the question that this study/hypothesis/article brings up…. namely we see issues in the NON ADJUSTED data based on hypothesized UHI effects. I think there are a number of issues brought up here, and this paper could go in about 4 different directions, but I think saying that anomalies must be used is wrong in itself.
Does this approach agree with reality? (lets do a reality check) . . . . . We are not talking about a text-book case in statistics, this is a complex system we are discussing and there are other methods that I think could possibly out-perform the anomaly system, but without seeing any that do, I must agree its the best system we know of for normalizing temperature data.
But I must also interject here and say one thing: If everyone uses the same method and that is ALL they use, how would we know this method is actually “correct”. I might be playing devil’s advocate there, but at some point I will take a shot at adjusting the data myself and the first thing I would do is NOT use the anomaly system.
Ed Caryl,
Nice post.
It clearly shows, as you note:
“The temperature as measured at stations isolated from any UHI is simply tracking the AMO.
Looks like an awfully good fit. There is very little, if any, global warming. We need to wait until the bottom of the next AMO cycle to get a decent reading of global temperature change. That will be in about 2050 if the AMO cycles as it has since 1850.”
========
Now, let’s figure out the larger and longer term cycles, this cycle is embedded in.
Or, let’s figure out the shorter term cycles, affecting this cycle.
Just some suggestions, to add to your fun 🙂
I’ll say it again, nice post.
AndyW, only young wet-behind-the-ears whipper snappers would say that something has never been done before.
Navy Bob says:
September 22, 2010 at 1:05 pm
“Fortunately, incandescent light bulbs will be a federal crime in the U.S. starting in 2012, thanks to the 2007 energy bill. So cozy warm Stevenson screen interiors – at least in Alaska – will soon be a thing of the past. Let’s hope less progressive Arctic nations will follow in our reduced-carbon footprints. Who says there’s nothing we can do about global warming?”
Nah, incandescents for Stevenson screens are exempt. Scientific use and all, you understand.
Mr. Mosher, you are highly critical of Mr. Caryl’s work in this post, and I take exception to that. What you fail to realize is that a plot of temperatures over time tells the story. Mr. Caryl’s graph labeled “Urban Stations” shows a definite upward trend in temperatures over the time period. In stark contrast, the graph labeled “Isolated Stations” shows zero or very little upward trend.
Mr. Caryl’s point is valid. UHI in the Arctic stations caused the upward temperature trends. No amount of fiddling with anomalies or gridding or other statistical methodology will invalidate that basic fact.
For those of us who work with vast amounts of data from manufacturing, often from different facilities around the world, this is nothing new. I would never perform the statistics you claim must be performed, simply to achieve an anomaly. If one temperature trend has a different average value than another, one can simply overlay the trend lines. My previous work was with data from oil refineries, usually several hundred refineries world-wide, each with thousands of data points for one year. The multi-refinery studies were conducted annually for several years, then every other year thereafter.
Kudos to you, Mr. Caryl. It will be quite interesting to watch the so-called experts try to manipulate the obvious in a manner that defends their status quo. This is devastating evidence that CO2 is innocent.
“Looks like an awfully good fit. There is very little, if any, global warming. ”
Thanks for the chuckle. “Awfully good fit” isn’t very precise, perhaps you could supply us with something more meaningful (you seem to preferentially report R^2 values). And just because the mean annual temperature of your selected Arctic stations “fits” the – wait for it – the AMO means no global warming? Wow. I bet the “urban” arctic stations (if there truly is such a thing) also fit the AMO. But you didn’t show that.
The sad part is this – amplified Arctic warming is a completely predictable phenomena (check the models!) associated with increased greenhouse gas concentrations, and its a function of decreasing sea-ice extents (less sea ice means warmer air temperatures). Yet nobody around here apparently trusts either the observations OR the models, which leads me to believe that it is close to hopeless trying to convince anyone otherwise. There is no UHI in the Arctic, and its warming, and its because of us.
jose says:
“There is no UHI in the Arctic, and its warming, and its because of us.”
So why is the Antarctic rapidly gaining ice?
Smokey: Way to change the topic. But since you asked, the simple answer is “its complicated”. The longer answer is: (1) stronger circumpolar circulation opens up more polynas, leading to more ice growth (paper here) , (2) warmer air temperatures produce warmer waters, increased precipitation, and a freshening (i.e. decreased salinity) of the surface waters. This freshening causes increased stratification in the southern oceans, and a corresponding decrease in the amount of heat transport as convection is suppressed. Less heat transport results in increased ice. (paper here) .
jose says:
“There is no UHI in the Arctic, and its warming, and its because of us.”
Well that settles it, no UHI in the Artic, a consensous of one, the science is settled.
Roger Sowell says:
September 22, 2010 at 9:11 pm
Mr. Mosher, you are highly critical of Mr. Caryl’s work in this post, and I take exception to that.
##################
did you take exception to the fact when I was highly critical of Mann or Jones?
did you take exception when a bunch of us spent a couple weeks on CA taking apart Parkers paper? or how about spending nearly 6 months now working through all the warts in GHCN? do you take exception to the last 2 weeks I’ve spent trying to put together a package so that people can look at ICOADS dat in its raw form so they can rip that apart? How about the last 8 hours tying in 185 data descriptions so that other people can work on data to find errors.
“What you fail to realize is that a plot of temperatures over time tells the story. Mr. Caryl’s graph labeled “Urban Stations” shows a definite upward trend in temperatures over the time period. In stark contrast, the graph labeled “Isolated Stations” shows zero or very little upward trend.”
What you fail to realize is that there is no objective criteria for separating or categorizing those two “classes” frankly when I looked at the pictures I thought he got the categaories backwards in some cases. In some cases there was NO EVIDENCE that the site fit he catagory. So, I question the very premise namely
“here are a set of isolated stations” and here are a set of “urban stations”
Look The biggest problem in UHI studies, the biggest FLAW in studies that say there is NO UHI, is lousy metadata. I’ve been saying that for 2-3 years. So, when I see sloppy non repeatable categorization I am going to say it. So, when I found the CRN guide on NOAA’s site and pointed ANthony at it, the idea was this:
here is an objective standard. something you can say ” 10 feet away” or no trees within X feet. Ed’s criteria is….. well nobody knows. If I gave you the pile of pictures and asked you to sort them, chances are you cant. To be accurate, the criteria mist be stated in advance. they must be based in the physics of UHI, and they must be objective. Not ” look at how the town blends into the airport” Not, “look at the trucks close to stevenson screen”. THAT is not the kind of evidence that impresses me, or is applicable to other sites. further, the mathematical methods were not robust or even correct. Sorry, they are not.
“Mr. Caryl’s point is valid. UHI in the Arctic stations caused the upward temperature trends. No amount of fiddling with anomalies or gridding or other statistical methodology will invalidate that basic fact.”
point number 1. Ed said that he subtracted the entire average from each series. that is a form of doing an anomaly. 2. he averaged stations together. that is a form of gridding. Its called unweighted gridding.
So, I guess you reject his work now. please. You are out of your depth. Its ok that you dont understand. keep quiet and we will not be the wiser.
“For those of us who work with vast amounts of data from manufacturing, often from different facilities around the world, this is nothing new. I would never perform the statistics you claim must be performed, simply to achieve an anomaly. ”
Sorry bud. My experience with manufacturing data is way vaster than yours and more important. See how silly that sounds. but I suggest you not try the game of who has worked with more data from more places for a longer period of time. The facts that you dont realize that that an aggregate average is a form of gridding and that Ed actually defended his work by saying that he did standardize by subtracting the global mean, shows me that I should not trust what you say about your skills.
“If one temperature trend has a different average value than another, one can simply overlay the trend lines. My previous work was with data from oil refineries, usually several hundred refineries world-wide, each with thousands of data points for one year. The multi-refinery studies were conducted annually for several years, then every other year thereafter.”
That probably WHY you missed the point I made about the noisy end points he discussed in his methods. and probably WHY you missed the point about autocorrelation and the point about changing variance. I’ll do a little toy problem to show you the problem.
Pipe A 10 10 10 10 10 10 10 10 10 10 10
Pipe B 5 5 5 5 5
Pipe C 1 1 1 1 1
Now take the average and draw the regression of all averaged. See the problem?
now its not this obvious in Eds case, but if you have sparse data, missing data,
you have to take care. its not at ALL like the the problems of hundreds of pipes with thousands of data points. AS ED NOTED the series are noisy at the ends. that is what you get with sparse data. And guess what happens to a regression line when end points are noisy.
now go ahead and apply anomaly methods to the problem above. See how you get the right answer. of course you do. Do you know why you use anomaly methods? well if you have 100s of pipes and thousands of data points you dont have to. temperature series aint like oil in pipes. But nice try.
Kudos to you, Mr. Caryl. It will be quite interesting to watch the so-called experts try to manipulate the obvious in a manner that defends their status quo. This is devastating evidence that CO2 is innocent.
“Its complicated”. I see that and I always think that means you have no idea what you are talking about and do not understand it whatsoever. If you understood it, you could explain without having to use a research link as a crutch since you do not understand it enough to teach us “simpletons” without resorting to said link.
All of those theories you post are the same worth as any other computer model. If you assert a wrong assumption, the model turns to garbage. Or like most people who are knowledgeable about it: Garbage in….garbage back at ya.
Or we can do this:
Assert: Increased warming seen in arctic temperatures must be caused by man.
Computer output: True.
Scientists: It is because of these physical properties that I came up with while smoking a joint that MUST be causing the data, because we have already proven the case in our computer models.
Environmentalist: Polar bears are going to die!
And all along you never prove the important issue. You state that the assertion must be true in the first line, and that because the computer recycles what it is told to say, then the assertion must be true. Here we have one possible interpretation that states why the arctic is warming quicker then elsewhere and it has nothing to do with warming temperatures, but namely warming thermometers.
Your entire posts on this subject are off-topic Jose. Here is a quick synopsis of your belief system that will one day fall when someone like me proves that you are wrong:
Like so:
Assert: Man is causing current warming.
Computer outputs: Thou programmed me to say it is, so it is.
Scientists: Man is causing warming because the computers says so.
Environmentalists: I will troll the internet and release more carbon into the atmosphere by using more bandwidth and more computer time because I am holier then thou! Even my poop does not stink! We shall apply carbon reduction only to non-believers because they belong in the lake of fire! Repent sinners!! The end of the internet is coming! (For you)
jose says:
“Smokey: Way to change the topic.”
Didn’t jose notice the three maps in the article showing the Antarctic? Or does his cognitive dissonance create a blind spot covering half the planet?
Jose’s provably wrong statements like “amplified Arctic warming is a completely predictable phenomena (check the models!) associated with increased greenhouse gas…” is a noob mistake here. Climate models are always inaccurate; if they could accurately predict the climate, there would be no debate. But as we know, they’re always wrong. The sensitivity numbers they’re programmed to come up with are preposterously high.
The Arctic is not ice free — but it has been ice free many times in the pre-industrial past. Arctic ice routinely melts, and it has nothing to do with human activity. If CO2 was the cause, Antarctic ice cover wouldn’t be at a record high.
Climate alarmists have bet on the wrong horse. They don’t understand that the real concern is extreme cold, which is the normal state of affairs on our usually frozen planet. A temperature decline of 6 – 10°C will be a true climate catastrophe. It’s hard to grow crops under several hundred feet of glacier ice.
1. UAH arctic trend is 0.47 deg per decade or ~1.5 deg warming since 1979.
2. A significant decline in Arctic ice extent has been observed over the past 30 odd years which has been particularly prevalent in the last decade.
Bearing these 2 facts in mind, it’s now worth noting that of the 9 ‘isolated’ stations listed only 4 have up to date records. Most of the others have none or very little data after 1990. So, we seem to be comparing ‘isolated’ trends up until 1990 with ‘urban’ trends up until 2009/10 and deciding that the ‘urban’ trends are greater. What a surprise!!
I haven’t looked at the 4 up to date ‘isolated’ records in any detail, but a quick comparison does suggest that Jan Mayen (isolated) and Eureka(urban) trends are quite similar over a common period (i.e. 1948-2009).
This highlights another problem with the analysis. You can’t simply take the whole of one record and compare the trend to another record of different length. It’d be like taking the whole of the CET record (since 1659), comparing it with the shorter UK record and deciding that Central England was warming at a much lower rate than the rest of the UK.
I think closer analysis might show the ‘isolated’ and ‘urban’ trends are much closer than one might think from this post.
RE:
Smokey says:
September 23, 2010 at 4:31 am
Climate alarmists have bet on the wrong horse. They don’t understand that the real concern is extreme cold, which is the normal state of affairs on our usually frozen planet. A temperature decline of 6 – 10°C will be a true climate catastrophe. It’s hard to grow crops under several hundred feet of glacier ice.
I would say the good news is that we are likely 1,500 years or so from such conditions. The bad news is that while such a decline is thought, by some, to be a gradual process it actually could happen, or at least part of it, quite rapidly. Several hundred feet of glacial ice would take thousands of years, however, the present green belt could migrate far south in short order.
The topic of this thread, Arctic isolated versus “urban” stations show differing trends, tends to again illustrate at present it could be said we really don’t have a clue as to what the actual global climatic temperature is let alone what it will be in 100 years. Anthony’s surfacestations.org project substantiates the above statement.
Thank you for a rational explanation of the apparently anomalous heating in Northern latitudes. It is outrageous that the so-called professional climatologists didn’t “engage brain” before ringing the alarm bells.
Thoughts on Anomaly Temperatures
Temperature is a PROXY for Energy.
The Energy content and the Energy transfer is what you really need to track. Calculating an Anomaly of High Energy air averaged with Low Energy air is only a rough approximation, even if the statistics are pristine. It takes more energy to change the temperature of Humid air.
Three examples where temperature anomaly is not telling the full story
* humidity
* surface
* radiant energy transfer
Humidity
You have probably seen the example (my excerpt from Max Hugoson post at WUWT)
http://wattsupwiththat.com/2010/06/07/some-people-claim-that-theres-a-human-to-blame/#more-20260
Go to any online psychometric calculator.
*Put in 105 F and 15% R.H. That’s Phoenix on a typical June day.
*Then put in 85 F and 70% RH. That’s MN on many spring/summer days.
What’s the ENERGY CONTENT per cubic foot of air? 33 BTU for the PHX sample and 38 BTU for the MN sample. So the LOWER TEMPERATURE has the higher amount of energy. …..Thus, without knowledge of HUMIDITY we have NO CLUE as to atmospheric energy balances.
———————– (end of excerpt)
So might a better anomaly track temperature in similar humidity areas? Tracking Phoenix with itself might be OK, but maybe we shouldn’t track Minneapolis even with itself, since summer vs winter humidity is significantly different. It has been suggested that Dew Point might be a better indicator than Tmin averaged with Tmax.
Surface
Surface temperatures on land are actually ‘near surface’ air temperatures 1 to 2 meters above ground. The energy flow has already started its trek toward space. Ocean temperatures, especially the ARGO floats, are more truly surface or sub surface measures (before the energy moves to the air). Heat Capacity (used to determine energy content) of liquid water does not change much with temperature, so ‘averaging’ warm and cold water is a smaller error than for dry vs humid air. Which is why OHC, Ocean Heat Content, has been suggested to be a better measure of the Earth’s warming or cooling. And finally, because liquid water has a much higher Heat Capacity than air, when energy moves from the ocean to the air (as in an El Nino) a temperature change in the liquid, gives rise to a larger temperature change in the air. So again, an Anomaly that averages land surface with ocean temps is another ‘apples to bananas’ comparison – both fruit, but different texture.
Radiant Energy Transfer
Energy transfer from Earth toward space begins at the true surface, the dirt, grass, pavement, etc. On a clear sunny day, the surface temperature of an asphalt parking lot can be much higher than the air above it (the measured air temperature is then another proxy of the surface). Radiant energy transfer from the surface toward space is proportional to the absolute temperature to the 4th power (T^4). As the average anomaly temperature changes linearly, the energy transfer changes to the 4th power. An anomaly that averages a 5 degC change in the Sahara with a winter time change in Siberia isn’t telling the full energy story.
I have toyed with the idea of an ‘anomaly correction’ for radiant affect, but have not actually worked it past the concept stage. The idea would be to take each location, adjust for Radiant Potential (temp to the 4th power), then compute a Radiant Anomaly on the transformed temperatures. The Radiant Anomaly might then let us compare the Sahara to Siberia in terms of the surface ability to shed heat. Sort of like the ACE energy metric for hurricanes, but applied to surface temperature.
Murray Duffin says:
September 22, 2010 at 8:42 am
Barrow was served by ski plane in winter and float plane in summer until the airstrip was built, which was less than 20 years ago if memory serves. As I recall the airport matches a jump in the Barrow temperature record.
I flew in and out of Barrow in 1982 in a Wien Air Alaska 737, which is more than 28 years ago.
I selected the stations that correspond to those warm grid squares, as well as other stations in the same latitudes.
I am curious as to how these stations were selected. I searched a bit (certainly no an exhaustive search) and found several other stations that were “in the same latitudes”. Was there some specific criteria used to select the other stations? Why not use all the “arctic” stations for comparison?
Ostrov Vize 79.5 N 77.0 E rural area 1951 – 2010
Danmarkshavn 76.8 N 18.7 W rural area 1951 – 2010
Clyde,N.W.T. 70.5 N 68.5 W rural area 2005 – 2010
Cambridge Bay 69.1 N 105.1 W rural area 1929 – 2010
Hall Beach,N. 68.8 N 81.2 W rural area 1957 – 2010
Cokurdah 70.6 N 147.9 E rural area 1939 – 2010
Hatanga 72.0 N 102.5 E rural area 1929 – 2010
Dudinka 69.4 N 86.2 E 20,000 1906 – 2010
Dzardzan 68.7 N 124.0 E rural area 1936 – 2010
Cokurdah 70.6 N 147.9 E rural area 1939 – 2010
Svalbard Luft 78.2 N 15.5 E rural area 1977 – 2010
Danmarkshavn 76.8 N 18.7 W rural area 1951 – 2010
Lee Kington says: at 4:50 am
“The bad news is that while such a decline is thought, by some, to be a gradual process it actually could happen, or at least part of it, quite rapidly.”
I agree and think this idea needs more exposure. The AGW hypothesis has to invoke “tipping points” to get a response from anyone because otherwise the changes would be so slow in coming as to be unnoticeable – even if the claims were true.
Cold periods, except when caused by volcanic eruptions,
http://www.suite101.com/content/the-year-without-a-summer-1816-a54675
have triggers not yet explained. However, this past April we had two early morning freezes. Cherries and apples lost all their fruit, walnuts lost all their leaves and re-leafed a month later and will survive. Three miles south of us and 500 feet lower there was very little damage. But in the wine grape region that begins 30 miles south of us the harvest is two weeks late. Now in late September one can look around and “see that all is normal” – well we still don’t have apples, cherries, or walnuts in our trees. So the point is not much has to change for local crop failures. Modern growing, shipping, and marketing practices in the USA compensates for such things so not too many folks notice.
I expect crop failures on the margins to increase if the World cools. History tells us this could proceed quite rapidly. It doesn’t tell us why.
“”” Dave in Delaware says:
September 23, 2010 at 5:43 am
Thoughts on Anomaly Temperatures
Temperature is a PROXY for Energy. “””
Dave, I have for some considerable time pointed out, that even if it was possible to measure the true average global (surface) Temperature; (which it isn’t) , that we still would know nothing about the energy transfers; and the roughly black body Stefan-Boltzmann like fourth power relationship, is one part of that problem.
It is a trivial problem in calculus and trigonometry to prove that if the Temperature goes through any arbitrary, single valued continuous function (of time) cycle, whose average value is Tzero, that the average value of the instantaneous fourth power of that temperature function, is ALWAYS Tzero + deltaT.
Now a lot of folks love to point out that the earth surface is NOT a “Black Body”, so they argue that the fourth power thing is not valid.
Well the black body assumption does set a maximum for the amount of radiant cooling that can occur; and many surfaces have a sufficiently constant spectral Radiant emissivity over the range of LWIR wavelengths that can be present in the thermal radiation from that surface at prevailing Temperatures; that simply applying some average emissivity to the BB calculated value from the S-B formula is a respectable value for the actual surface radiant emittance.
Actually the deep oceans behave like a fairly good black body absorber; well a grey body to be pedantic, since the surface Fresnel reflectance is about 2% (normal) over a fairly wide specral range; and certainly over the solar spectrum range; and perhaps 3% over the full range of incidence angles. So the deep oceans would be fairly well characterized as a Grey body with 0.97 total emissivity.
Actual LWIR reflectances at typical ocean surface temperatures; are not quite so easy to figure but I would expect the BB (with emissivity of 0.97 would be quite close to reality for the oceans; which after all are 70 % of the total surface.
Employing (with caution) BB radiation theory to the problem also gives us some other inputs to the Green House Gas absorptin of surface emitted LWIR thermal radiation.
If the surface emissions are in fact roughly black body like, then it is known that the spectral radiant emittance at the spectral peak of that emission varies as the FIFTH power of the Temperature, and NOT the FOURTH; and then the Wien Displacement law moves that peak to shorter wavelengths (~3000/T microns), so the higher the surface Temperature, the further down the thermal radiation tail the CO2 absorption band (15 micron) is. The total captured energy still goes up with Temperature; but the fraction of the emission spectrum energy that is capoured goes down; and more of it escapes the atmosphere. The spectral peak which is about 10.1 microns for the global average Temperature of 288K (they claim) will move further into the atmospheric window also.
On the other hand for colder regions the Wien Displacement moves the thermal radiation peak closer to the CO2 15 micron band; but the surface Total radiant emittance goes down severely for the colder regions.
All of which supports my contention that it is the hottest driest mid day tropical desert regions, that do most of the real radiant cooling (land) . The polar snow and ice regions are quite ineffective in cooling the planet; but if the arctic ocean should become ice free, then the north polar region would become a better cooler for that part of the planet.
And of course although this note is all about radiant cooling; we never lose sight of the fact that the ocean regions do a heck of a lot of cooling via the evaporation/convection mechanism, transporting latent heat into the upper atmosphere.
Mosh>
I get what you’re doing here, and you’re spot on in your principles. I would suggest, though, that you’d have spent less time phrasing your initial post more politely – wearing kid gloves, in your words – than you have done since defending it from people who picked up on your tone and got (wrongly) defensive.
It is my impression that one of the drivers of the antagonism in climate science debates is that a lot of people on both sides think that the best way to tell someone they might be able to improve their work is to get right in their face and shout ‘YOU’RE WRONG’. It’s human nature to be defensive of our work, and whilst it would be nice if everyone was completely detached and unemotional, we have to acknowledge that they’re not. Wearing kid gloves is an entirely worthwhile thing on which to spend a small amount of effort.
“”” Al Tekhasski says:
September 22, 2010 at 4:45 pm
evanmjones wrote: “So we would need over 120,000 stations? That’s a lot of stations.”
Sure it is. But I am afraid you might need more. “””
Well Al you must be new around here. If you had been visiting here more often, you would know that the general theory of sampled data systems is apparently quite unknown in “Climate Science” Institutions.
So your Nyquist Sampling Theorem is trumped by their Statistical Analysis, and probably the Central Limit Theorem as well. So long as they get the right r^2 value and proper trend line (with a slope error no more than +/-50%; or a 3:1 range) they don’t have to worry about undersampling.
But they are very good at what they call oversampling; which is creating a whole raft of phony values that nobody measured, on their computer. They can make as many grid points as they like; limited only by the size of the supercomputer that the tax payers bought for them. Well they don’t actually measure anything real at all those oversampled grid points. For some reason their computers are not able to go back and predict; excuse me that’s project, the actual values that would have been read at the handful of real actual global measuring stations. but they can interpolate somethign feirce.
So in climate science it is legitimate to core bore a single tree; and from those small sectors of that one dimansional sample ofr the three dimensional tree, in an even bigger forest; you can describe the complete climate history as to Temperature, wind, moisture, sunlight, humidity (maybe I alreadys aid that) and anything else you want to know; well but only for the age of the tree. And you can determine the age of the tree by doing a radio-carbon 14 C assay on some of those pieces of the extracted core. There might be other ways to tell the age of the tree and date the climate conditions; but they probably aren’t as reliable as 14 c assays.
And due to the coherence of anomalies, it is ok to measure the temperature in downtown San Jose California; and apply that Temperature value to the small town of Loreto about 1/2 way down the Baja, on the Sea of Cortez.
So they used to monitor the weather and climate of the entire arctic (north of +60 degrees) with just 12 total weather stations; now they have some totally huge number like 70-80 .
So I doubt that anybody is going to heed your request for 100,000 sampling locations.
And by the way; just in case you haven’t noticed these climate reporting stations get their daily Temperature from a min-max temperature reading; which gives you two samples during each 24 hour cycle; but since the diurnal temperature variation is not pure sinusoidal; there must be at least a second harmonic 12 hour periodic component presnt, so they fail they Nyquist criterion for the Time variable by at least a factor of two which means that the aliassing noise makes even the daily Temperature average value unrecoverable. So the spatial aliassing noise is just superfluous; which is why they don’t care about it.
But it is good to see somebody else with some understanding of sampled data systems.
A little OT but for anyone interested in the new release of the NCDC GHCN v3 beta dataset pop over to Digging in the Clay and have a look at the following thread
http://diggingintheclay.wordpress.com/2010/09/23/ghcn-v3-beta-part-1-a-first-look-at-station-inventory-data/
Verity and I will shortly be publishing Part 2 and Part 3 in a series of threads on the subject of how the GHCN V3 dataset differs from the previous GHCN v2 dataset.
If you are interested in an ‘advanced’ look at the V3 dataset (in a much more user friendly normalised database format than the usual text files), why not pop over to Climate Applications and have a look at the TEKTemp implementation of the NCDC GHCN v3 beta dataset by clicking on the following link.
http://www.climateapplications.com/TEKTempNCDC.asp
vukcevic says:
I had a quick look at Svalbard Luft data, comparing summer & winter anomaly.
http://www.vukcevic.talktalk.net/SL.htm
Conclusion:
– Most of annual rise is due to rise in winter’s temperatures.
– Summer’s anomaly is not main contributing factor.
– Large winter oscillations are confirmation that AGW (CO2) cannot be factor.
– Low S-W correlation again confirms it is not systematic rise in warming
Nicely done!
I’d suggest going one further and looking at it by month. When I did that for stations around the world, I found different months have different trends (rising vs falling) all over the place. Often the most ‘warming’ comes at the ‘shoulder’ months between seasons. Just the places where more affluence would let folks turn on the heater a bit earlier in the season or run it a bit later (or clear the snow of the runway more …)
Oddly, stations near each other often had the same months going in opposite directions.
For me, this wide divergence of monthly trend data was a lethal thing to the CO2 thesis as there is no way for it to selectively act by month, and by slight geographical shifts.
Lots of nice graphs here:
http://chiefio.wordpress.com/2010/04/22/dmtdt-an-improved-version/
Two of my favorite graphs from it are Hobart and Darwin (where Darwin is cooling)
http://chiefio.files.wordpress.com/2010/04/hobart.png
http://chiefio.files.wordpress.com/2010/04/darwin.png
The original work:
http://chiefio.wordpress.com/2010/04/15/dmtdt-climate-change-by-the-monthly-anomaly/
Australia got it’s own posting:
http://chiefio.wordpress.com/2010/04/18/australian-anomaly-walkabout/
Though one of my favorite graphs is Japan, from this posting:
http://chiefio.wordpress.com/2010/04/26/dmtdm-a-northern-view/
that looks at northern hemisphere countries and regions.
http://chiefio.files.wordpress.com/2010/04/210_japan.png
Where it looks like the trends alternate rising vs falling on alternating months… but with February and July nearly dead flat trendless.
Magical stuff this CO2 …
I don’t understand your joke about branches of mathematics. But unless you’re using Karl Popper as a prescription not to think, you’d realize that an event having low probability under the assumption of no causal effect is (potentially) evidence of some causal effect.
Invoking Shannon-Nyquist, I think, is distracting. We’re trying to recover the first moment from spatial data, not perfectly reconstruct a temporal signal. At least please explain why the hypotheses of the theorem are satisfied in this case.