Readers may recall I wrote in this article about my family memorial day excursion to Crater Lake:
Crater Lake happens to have a USHCN weather station, and it is one of the few stations that GISS excludes (they have an exclusion code for it in their software Mosher located some time ago).
Steve Mosher commented in detail about that:
Thanks for remembering that Anthony.
In addition to crater Lake there were 4 other northern california stations that GISS had removed from the data. In the paper Hansen merely says this:
‘
The strong cooling that exists in the unlit station data in the northern California region is not found in either the periurban or urban stations either with or without any of the adjustments. Ocean temperature data for the same period, illustrated below, has strong warming along the entire West Coast of the United States. This suggests the possibility of a flaw in the unlit station data for that small region. After examination of all of the stations in this region, five of the USHCN station records were altered in the GISS analysis because of inhomogeneities with neighboring stations (data prior to 1927 for Lake Spaulding, data prior to 1929 for Orleans, data prior to 1911 for Electra Ph, data prior of 1906 for Willows 6W, and all data for Crater Lake NPS HQ were omitted), so these apparent data flaws would not be transmitted to adjusted periurban and urban stations. If these adjustments were not made, the 100-year temperature change in the United States would be reduced by 0.01°C”
Well, I wanted to see the analysis, the code, that was used to make this determination that these stations were flawed. Gavin basically said the paper documented everything, but these words don’t tell me HOW it was done. It just says THAT it was done. Any way that was pretty much why I wanted the code released. When it finally was released, you will see that there is no analysis supporting the removal of these stations. Upon inspection you can see some flakey stuff with the stations, but I was looking for math that quantified the flakiness. In the end, these were excluded by hand.
The argument of course is that including them or excluding them amounts to a tiny difference. That argument never held much water for me. The question, in my mind, was how many other flakey stations were there and was there math that could detect it? I think thats a good question. It doesnt make me doubt the record, I just think its a good question.
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I agree. I don’t know that Crater Lake data is flawed or “flakey”, it just may reflect the snow pack hanging around longer, creating a cool bias into summer. With the snow pack as heavy as it is this year, it will be interestign to see if that has an effect of suppressing mean temperature.
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Hansen: “If these adjustments were not made, the 100-year temperature change in the United States would be reduced by 0.01°C”
Mosh: “The argument of course is that including them or excluding them amounts to a tiny difference.”
Way I’ve been reading AGW is that “tiny” is the critical word, or event, right through.
Wouldn’t this mean that the data isn’t “flaky” but representative of an area with extended snow pack and therefore a cooler environment? So, does that mean GISS eliminates stations that stay cool because they are in alpine regions and don’t fit the “model”?
Meanwhile, Kepler did not discard Tycho’s Mars data, even though it was “flakey” and did not dovetail neatly with the assumed perfection of the heavens.
The Hansen excerpt cited comes from this 2001 paper. They seem to be talking about a particular study; it isn’t clear that what they say applies to an ongoing index.
Crater Lake is listed in GISS’ station data in the normal way
here. It’s on line 4522 of their inventory file. I think you should show the evidence if you think it has been excluded from the index calculations.
You can take a strong bet that if those stations had consistently higher temps rather than lower, then rather than reject them as ‘flakey’ they would install even more stations nearby.
Why not use some sort of a statistical outlier test to determine whether to throw out data points like we’re taught in Analytical Chemistry (even at the undergrad level, it’s not rocket science)? Another example of these clowns making it up as they go?
HF
It doesn’t show enough warming. Exclude it.
Amazing. Anomalous data is still representative of that little bit of reality that is part of the big picture. Presumably there are instances of stations being removed from the record because of the opposite effect. . . ? It’s shenanigans such as this that provoke distrust in the whole temperature record.
I wonder how many similar removals were made for stations that exhibited a warm bias?
Cherry picking at its finest, with justification of course. Forget the ground stations and just stick to the satellite record.
“inhomogeneities with neighboring stations”
They couldn’t whip and beat them into line with each others ???
Flaw=Since these non-urban sites don’t reflect urban heating and would decrease the average temp (although slightly), and therefore don’t support the Global Warming alarmist’s agenda, they decided to exclude them.
So if these few stations would affect the 100 year average by .01 degrees, how many other sites have been excluded from the average for the same reason.
Even if Crater Lake is snow packed all through summer creating a cool spot, what does that matter? Isn’t the point of climate statistics to include all weather spots, warm or cool, lest you want to create a bias in the data from the get go.
Nick Stokes, thanks for the link to Crater Lake. Do you see any trace of AGW in that record?
“Well, I wanted to see the analysis, the code, that was used to make this determination that these stations were flawed. Gavin basically said the paper documented everything, but these words don’t tell me HOW it was done. It just says THAT it was done. Any way that was pretty much why I wanted the code released. When it finally was released, you will see that there is no analysis supporting the removal of these stations. Upon inspection you can see some flakey stuff with the stations, but I was looking for math that quantified the flakiness. In the end, these were excluded by hand.”
Yes, GISS documentation standards leave a LOT to be desired…
“The strong cooling that exists in the unlit station data in the northern California region is not found in either the periurban or urban stations either with or without any of the adjustments. Ocean temperature data for the same period, illustrated below, has strong warming along the entire West Coast of the United States. This suggests the possibility of a flaw in the unlit station data for that small region.”
Couldn’t it also suggest that the broad assumptions that climate in an area will be consistent may not be accurate and that any meaningful “global” measurement needs to be far finer grained than they assume, rather than smeared together like a charcoal picture?
Hiding a decline?
It gets stranger. Here is a long term data string that is in need of adjustment. Does anyone know how GISS would approach adjustment? It is definitely rural, no lights on here.
http://www.geoffstuff.com/troublesome.jpg
Just as a reminder, Crater Lake is in Oregon, not Northern California.
All data are created equal, but Hansen is smart enough to know when and where some data are more equal than others.
How Progressive of him.
Mosh …’The question, in my mind, was how many other flakey stations were there and was there math that could detect it? I think thats a good question. It doesnt make me doubt the record’
It is a good question and it does make me have doubts about the record.
But maybe that’s easier for me because I am not a lukewarmer,.
I am, and probably always will be, agnostic.
This is more evidence of systematic editing of the historic record to groom analysis to show a modern warming trend. The keepers of the data base make a minor change here, another minor change there (hoping no one will notice) until the results point in the desired direction. When the warming trend cannot be sustained by these targeted editing practices, a sharp cooling will be noted, which will result in yet another ‘catastrophe’ for the alarmists to exploit.
No clearer example of cherry picking I can think of.
GPlant
This is cherry-picking. It obviously affects something or they wouldn’t choose to exclude it.
Andrew
Gee, snow hanging around later and later in the season, cooling the local temperatures. Isn’t that how glaciers get started? But of course, what’s 0.01 deg C among friends when we’re talking about the difference between the trend of 0.58 dec C/century instead of the 2-6 degree C rise projected by the inscrutable GCM’s. Death by a thousand cuts!
Bill