Guest post by John Goetz
As noted in the previous post, GISS has released their monthly global temperature summary for June, 2009. This month’s whopping anomaly of 0.63C is once again much higher than that of RSS, UAH, and even NOAA, which is the source of the GISS temperature data. Not only is the anomaly higher than the other metrics, but it is trending in the opposite direction.
Temperature data from 1079 stations worldwide contributed to the analysis, 134 of them being located in the 50 US states. Data from essentially the same few stations have been used for the past twenty-four months. Many, many hundreds of stations that have historically been included in the record and still collect data today continue to be ignored by GISS in global temperature calculations.
Once again, the bulk of temperatures comprising the present-day worldwide GISS average come from airports – in this case 554 airports, according to the NOAA metadata from the V2 station inventory. In the US, the ratio of airports to total stations continues to run very high, with 121 out of the 134 reporting stations being located at airports.
Why worry about airports? Aside from recent posts on this site documenting problems with airport ASOS equipment in the US, WUWT has also documented a number of equipment siting problems, notably the typical close proximity of the equipment to a tarmac heat sink. Airports can introduce a mini-UHI effect where one would otherwise not be found.
The NOAA metadata is not entirely accurate, and several stations located at airports are not noted as such. Some examples include Londrina and Brasilia in Brazil, Ely / Yelland in Nevada, and Broome in Austrailia. Those stations were easy to find because they had “airport” (or some variant) in the station name. A check of coordinates using Google Earth confirmed the airport locations.
Let’s examine the metadata a little further, shall we?
NOAA says that 345 of the stations it passes on to GISS are rural and presumably free of UHI influence. Fifteen of those stations are located in the US. However, only 201 of those rural stations are not located at an airport, and therefore presumably free of UHI effects (including tarmac heat sinks). In the US, only one of the fifteen stations is listed as both rural, and not located at an airport: Ely / Yelland in Nevada.
Doh!!! As noted above, that station is located at an airport – confirmed not just by Google Earth, but also by NOAA’s NCDC website as well! This means that all of the US temperatures – including those for Alaska and Hawaii – were collected from either an airport (the bulk of the data) or an urban location.
As for the rest of the world, some of the stations listed as being rural and not at an airport have metadata indicating they are located in an area of “dim” or “bright” lights. Filtering those out, we find a total of 128 stations that are rural, not at an airport, and “dark”.
Why are “dark” stations important? Recall that GISS uses dark stations to adjust for UHI in the urban stations. With only 128 dark stations available, none being in the US, it would seem this is an impossible task.
Fortunately, GISS adjustment rules allow old data to be used in adjusting new data. The older “non-reporting” rural weather stations continue to adjust reporting urban stations, even though the most recent two years of overlap is missing.
Thankfully, the algorithms are robust enough to calculate adjustments to the 100th of a degree even when data is missing.
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The GISS has the following table of surface station locations:
http://data.giss.nasa.gov/gistemp/station_data/v2.temperature.inv.txt
Colum 68 has a header of “P” which stands for “Population” and is described as follows:
P =R if rural (not associated with a town of >10,000 population)
S if associated with a small town (10,000-50,000 population)
U if associated with an urban area (>50,000 population
Colum 82 has a header of “A” which stands for “Airport” and is described as follows:
A =A if the station is at an airport; else x
The table is easily loaded into Excel as fixed fields and contains much useful information. Sub-totals can be generated which yields the following table:
Rural Airport, 975
Small-town Airport, 504
Urban Airport, 911
Subtotal Airports, 2390
Rural Non-airport, 3021
Small-town Non-airport, 905
Urban Non-airport, 1048
Subtotal Non-airports, 4974
Total Surface Stations, 7364
The GISS surface station table has 7,364 entries of which 2,390 are airports, so one-third of the GISS stations are at airports. Of the 2,390 surface stations described as airports, 975 are in rural locations. There are a total of 3,996 rural surface stations of which 975 are at airports so one-fourth of all rural stations are really not rural.
If anyone wants a different analysis of the data just post a request.
Mike
Reply: The list you are referencing is the complete list GISS starts with. The GISStemp software culls some of the stations from the overall herd. The list of stations actually used can be found here.
Also note that the majority of stations actually used did not report a June 2009 temperature. – John
Has anyone else noticed the AMSU-A satellite readings lately? The readings at 14,000 feet show temperature has suddenly headed north. As I understand it, the 14,000 foot level is what Roy Spencer uses to compile his monthly global average temperature plot. As of July 13, the satellite was reading 0.73 F above last year’s reading on that date and 0.81 F above the 20-year average.
That’s a pretty radical departure from last month’s average.
>>>Every afternoon at about 3:15 a KLM “heavy” (a 747 combi)
>>>loaded with frreight would pass directly over our headquarters
>>>building and I swear that you could count the rivets on the
>>>landing gear doors.
You mean like this…
Its those crazed Cloggies, they are not used to enormous great hills near to runways (ie, anything more than 2 meters high).
And if you want to see how far all that hot gas can go…
http://www.youtube.com/watch?v=RILkG2yhAAM
.
Well, Steve, eyeballing is not enough. Here is a graph showing the difference between UAH and GISS
http://noconsensus.files.wordpress.com/2009/01/giss-uah-difference-no-trend.jpg
The average is obviously very close to zero…
Sorry to be pedantic, but I think it useful when talking about UHI effects to be more accurate and use the term Delta UHI over time (using Delta in the calculus sense meaning change). UHI doesn’t matter if it hasn’t changed over time. eg, if the surrounding population hasn’t changed.
The team can argue that UHI ‘doesn’t matter’ if they can point to locations where it hasn’t changed over time.
Obviously, for a host of reasons, airports are very likely to have changed over time, and thus demonstrated Delta UHI which contaminates the temperature record. Delta UHI can and should be measured by comparison with truly rural sites some 10km or so away, far enough not to be affected by the UHI effect.
As I understand it, ‘Rural’ is defined as towns where less than 10,000 people live. Anyone with a thermometer reading outside temperature can prove to themselves that small towns most certainly do have a UHI effect, and it can be quite pronounced. The real question though is how the UHI has changed over time, since the Delta UHI could be the main contributer to the reported temperature increases.
Thankfully, the algorithms are robust enough to calculate adjustments to the 100th of a degree even when data is missing.….Too robust perhaps?
I should have said. ‘Anyone with a thermometer reading outside temperature IN THEIR CAR can prove to themselves that small towns most certainly do have a UHI effect, and it can be quite pronounced.”
>>>Every afternoon at about 3:15 a KLM “heavy” (a 747 combi)
>>>loaded with frreight would pass directly over our headquarters
>>>building and I swear that you could count the rivets on the
>>>landing gear doors.
You mean like this?
Its those crazed Cloggies, they are not used to great hills in front of the runway (anything more than 2 meters high).
And if you want to know how far all that hot gas will go, then take a look at this…
http://www.youtube.com/watch?v=EpPJdDNHRKc
.
It’s NOAA’s 0.63C of separation.
Michael Ronayne (09:56:45)
If anyone wants a different analysis of the data just post a request.
I live in RWO:
I have a preference for this table
http://www.climateaudit.org/data/ghcn/brazil.population.xls
Sorry… It’s GISS’s 0.63C of separation.
Must have been a self-biased error.
Nogw (08:26:00) :
Our time will be called the “confused data era”.
…or perhaps the “error era”? (Sounding like a Kennedy)
>>>“Tarmac” is not a generic term for solid surfaces at an
>>>airport (ok may it is now but it shouldn’t be). The airport
>>>runways are made of concrete.
Not in the UK or much of Europe – runways here are all tarmac, its much smoother. We don’t like bone-shaker takeoffs.
Except for Luton, some years ago, where a crazed civil engineer decided to use bricks at the threshold (like a house driveway). But those all disappeared after the first heavy take off, and they are back to tarmac now.
I know that UHI exists and even our little car thermometer proves it.
Our car thermometer yesterday reported 111 degrees at a McDonalds in an area where heat was radiating off of bricks, cars right next to us, and the pavement, and our home thermometer corrected for bias was 103-104.
That’s a 7-8 degrees heat bias right there, maybe I should notify NASA that the McDonalds drive through near the building surrounded by cars and pavement would be a good place to put a climate station 😛
Newark Airport and NYC used to have the same daytime temperatures. However, in the past 20 years or so, Newark has become much warmer than Central Park in spring and summer, typically 3 – 4 degrees on sunny days.
Here’s my explanation, and maybe some research can bear me out:
The weather station was located just to the west of Parking Lot C, that big lot which abuts Route 1 – 9. Up until recently, that parking lot was full night and day, and you really had to circle around to find a space. The parking lot, in fact, was expanded, and the weather station is just to the west of the expanded lot. My hypothesis is that when the lot expanded, that’s when the discrepancy started to occur.
Now, this year, an amazing thing happened. The Port of NY – NJ Authority, which runs the parking lots, raised the rates to $24 a day. Coupled with the soft economy, this has let to Parking Lot C being almost empty. In fact, the monorail no longer serves the most distant of the two stops.
Let’s see if the temperature discrepancy between NY and Newark Airport (EWR) has narrowed. If so, it would indicate that the Newark temperatures have been spiked by automobile traffic nearby. Of course, the lot is still paved, and the concrete has a lot to do with it, too.
Jeff Wiita (06:17:31) : You are spot on regarding O’Reilly’s ignorance on environmental matters. His rants about Big Oil are equivalent to those concerning AGW. He seems to believe that we can achieve independence from foreign Oil producers with windmills and solar sources.:
I sent an e-mail to Bill O’Reilly informing him that he is out to lunch on global warming. I suggested he have a “come to Jesus meeting” with Steve Milloy, who is a regular contributor to Fox News. Sadly, O’Reilly’s ego is too much for him to overcome.
urederra (09:07:01) : “Excuse my ignorance, what does ROW mean?”
http://www.acronymfinder.com/
Of 56 returns for ROW, “Rest of World” is number 2. This is a handy site to put in your favorites list. Also, Steve McIntyre provides a list of acronyms common on climate related sites:
http://climateaudit101.wikispot.org/Glossary_of_Acronyms
Anthony: If GISS knows that the underlying assumptions and structure of GISTEMP are flawed and producing erroneous data and continues to put forth that data with the intent to mislead the public, that is fraud. The proof is there to observe. I understand your concerns, but submit that your silence is better than making excuses for GISS.
“Reply: ……Also note that the majority of stations actually used did not report a June 2009 temperature. – John”
Isn’t that the problem? If there is a valid algorithm that can predict temperatures within an X mile radius, then I am sure that we would understand weather a lot better than we do. As it is, there can be a huge variance between a distance of ten miles. I can think of one such example from here in Ohio back in June where it was at least 5ºF warmer downtown than it was at my house. Cloud cover and precipitation were the main reasons for this, but how does an algorithm adjust for that, and why would you want it to?
bob paglee (09:12:28) : “Isn’t there an abundance of CO2 being spewed close to the ground . . .”
As Tina Turner might sing “What’s CO2 got to do with it?”
Ans: Extremely little when thinking of the extra over the background concentration.
I propose GISS software engineers spend a couple of million dollars to write a computer program that will provide an answer to the following probability problem:
What is the probability that to further the AGW agenda an individual who advocates and participates in civil disobedience as a means of disrupting coal mining operations will if given the opportunity knowingly distort temperature data to further that agenda?
On second thought, we can save a couple of million dollars. The answer is 0.99999999999 give or take a couple of 9s.
As George Carlin said: “Why measure the temp at the airport? Nobody lives there!”
A Tarmac could be a good example of Kirchhoff’s law of thermal radiation, or black body experiment. I would suspect that the increased thermal emission from the dark construction materials are from the increased UV radiation reaching Earth’s surface.
Reed Coray (11:43:28) :
I agree that any activist can never be an independant scientist.
HadSST2 June is out at 0.5C, warmest June also since 1998. So such a warm temperature in GISTEMP can only be expected. No doubt HadCrut3 will also show a warm June too, it’s quite evident from the sea surface temperatures over the past month that it was very warm.
Why have the satellite records shown cooling? Because the lower troposphere is evidentally not in sync with the surface. In fact it’s pretty obvious from even a cursory inspection of the records that the lower troposphere temperature lags behind the surface temperature by several months.
In other words the surface records are showing what is happening at the surface now, while the satellite records are still showing what happened at the surface months back when we were in La Nina conditions.
So why oh why is a comparison between the satellite and surface records for a single month being made as if they should be in sync? They aren’t even measuring the same thing.
I also have a nice prediction that the satellite records will show strong warming in coming months due to the El Nino conditions filtering up into the satellite records.