the problem Danny is they are not unadulterated.
Comment on Watts et al.: Temperature station siting matters by Steven Mosher
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Comment on Watts et al.: Temperature station siting matters by Steven Mosher
The US is the worst network
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Comment on Watts et al.: Temperature station siting matters by Danny Thomas
Steven,
Okay. How have they been manipulated? My understanding is this is a subset with a long history and has been selected based on criteria not involving changes. Where did the manipulation occur, how, and how can it be stated if the data set you desire from the authors has not been reviewed by you? The impression I’m working under leads me to believe that changes (external and instrumentation) led to stations being removed leaving the balance of 410 (+/-) ‘pristine’ sites.
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Comment on Watts et al.: Temperature station siting matters by evanmjones
@David Springer
It is a very basic, simplistic example for the heat sink effect. What you mention (ventilation, etc.) lessens the effect, but here the effect is indeed much smaller: ~0.3C over 30 years.
I blew it by the group. As W. the peacemaker would say, NG got us covered.
And, yes, darkening and moisture re. CRS is indeed a part of the picture. (Like you, I’ll stick to the white line. And I figure white car will reflect more IR, which is why paint matters.)
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Comment on Watts et al.: Temperature station siting matters by captdallas2 0.8 +/- 0.3
Steven Mosher, “The US is the worst network”
Who has been in charge of this worst network?
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Comment on 2015 → 2016 by andywest2012
Happy New Year Judith, and to all the Denizens too.
I thought that the post ‘Scientists speaking with one voice: panacea or pathology?’ was a good one highlighting fundamental problems with the climate change domain, and I liked very much the post ‘we are all confident Idiots’ too. Has been a pleasure and a privilege to post here; have nothing on the deck at the moment, but hopefully will come up with more in 2016.
And thanks too for your great attempts to improve climate science integrity at the political level, via the congressional hearings. You did a great job.
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Comment on 2015 → 2016 by angech
“First Some basics.”
The algorithm will then adjust the odd balls so they look more like their neighbors.
Code for that area was too low due to cloud cover, lets adjust it to the warmer ones, We know they are right!
No room for cloud cover and 50 degree hotter or colder air pockets is there?
Not to mention making up the data for over half the sites in the USHCN
since the operators have died/ the sites are out of action/ or we need sites where there are no sites to give a grid so we will make them up from neighbouring data in the spots we want.
“We can also test the algorithm on synthetic data. You create a perfect world of data. Then you introduce all sorts of Bias.. Then you run the algorithm to see if it can move the data back TOWARD the truth.”
Please, for an intelligent man use intelligent arguments.
There is no truth in synthetic data.
there is a synthetic data base.
Then there is a synthetic data base that you have altered.
there are algorithms to try to go back to the synthetic data base.
Which is pure guesswork.
If you are applying known biases on the other hand then you are simply reversing the artificial assumptions you put in. Of course it must move back toward the original if you reverse the known bias you put in. Unfortunately Climate doesn’t follow artificial biases and has unpredictable natural variability which you have just ignored and eliminated.
” this bickering amounts to a fight over a couple of 1/10ths ”
So this would be 25% of the total temperature rise last century? [Centigrade I guess you mean?]
25% is a lot more important than a couple of tenths would you not agree?
“When we look at 30% of the world (SAT ) and apply adjustments the adjusted data is warmer than the raw data.”
No, No, No. A cute move and all but your correct statement is
“When we look at 30% of the world (SAT ) and apply adjustments the adjusted data is always cooler than the raw data in the past and equal to the raw data as collected in the present”
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Comment on Global Temperature Trends After Detrending with the AMO by ulriclyons
captdallas: “Multi-decadal “oscillations” are mainly ocean heat uptake/loss related and are extremely complex.”
Shifts in NAO regime drive the AMO.
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Comment on 2015 → 2016 by David Wojick
The real problem is that there are no SST stations. Even worsen SSTs are merely proxies. So all this talk of stations is irrelevant. The surface statistical models are crude estimates at best. No conclusion can be drawn from them.
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Comment on 2015 → 2016 by David Springer
“Then we go one more step. We look at the data for Jumps and radical changes.”
A step too far. These should average out. If they don’t then the detection is almost certainly problematic. If they do then it’s unnecessary to do it.
An oft repeated claim of yours is that many of the adjustments, station selection criteria, etcetera have no effect one way or the other on the resulting trend. If “the fix” isn’t fixing anything then why are you doing it?
I suspect at this point that gradual deterioration (read darkening) of exterior surfaces of cotton region shelters introduces a long term warming bias into that station’s record. When a CRS is replaced, cleaned, or painted it appears in the record as a “jump or radical change” in the cooling direction. That cooling should be incorporated into the record as it compensates for the undetected long term warming bias. But it isn’t.
This is all more or less moot in any case because GAT is dominated by SST measurements and those are seriously messed up in other ways.
The bottom line is there’s nothing really trustworthy enough to use in surface station measurements with the exception of ARGO and USCRN and those are both too new to reconstruct a record going back far enough to discriminate between multi-decadel natural oscillations and human-driven effects.
The satellite record is where to look for the best data and at 36 years long now it’s becoming useful for a true GAT trend.
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Comment on 2015 → 2016 by David Springer
Thanks AK. +1
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Comment on 2015 → 2016 by David Springer
@Horst
Total yield is up more than protein per unit of yield is down. Therefore total protein production rises. Carbohydrate production rises faster. Pick your ambrosia there is no poison.
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Comment on Watts et al.: Temperature station siting matters by Arch Stanton
Remember, Phil Jones said that he is sure that the original old stuff he ‘dumped’ would have looked just about the same to him today as if it were yesterday. Was it a long list, I still can’t find it on the net?
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Comment on 2015 → 2016 by David Springer
Steven Mosher | December 31, 2015 at 10:15 pm |
“The notion that there is an optimum is kinda silly. nobody assumes that.”
Who died and made you speaker for everyone? Teh hubris, it burns!
You’re patently wrong in any case. Vast hordes of Birkenstock-wearing flower children, free spirits, bohemians, and other assorted moonbats believe the optimum is 280ppm or in other whatever mother nature does absent human influence.
If you think about what you write before you write it may I suggest a New Year’s resolution for you: think harder.
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Comment on Watts et al.: Temperature station siting matters by Arch Stanton
Until this ‘dump’ thing is cleared up with the facts…
we have all been wasting electrons. The servers are heating the TOA.
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Comment on Watts et al.: Temperature station siting matters by Steven Mosher
it was mostly volunteer for a long time
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Comment on Watts et al.: Temperature station siting matters by Steven Mosher
nobody argues the estimate is good to 1/10th
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Comment on Watts et al.: Temperature station siting matters by Steven Mosher
NOAA didn’t make a decision to over sample. Stop making stuff up
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Comment on 2015 → 2016 by bigterguy
Judith, congrats on the best scientific blog on the Internet. Happy New Year!
Someday there will be a JudithCurty Prize for scientific integrity.
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Comment on Watts et al.: Temperature station siting matters by Steven Mosher
“Okay. How have they been manipulated? My understanding is this is a subset with a long history and has been selected based on criteria not involving changes. Where did the manipulation occur, how, and how can it be stated if the data set you desire from the authors has not been reviewed by you? The impression I’m working under leads me to believe that changes (external and instrumentation) led to stations being removed leaving the balance of 410 (+/-) ‘pristine’ sites.”
1. your claim is that they are unadulterated. THAT is the claim that requires proof.
2. Evan did not use the entire Leroy classification system which would
have included “shading”
3. The only evidence you have is what the site looks like “Today” or at the date of the last photo. So a site that was shaded by trees 30 years
ago that has the trees chopped down today.. will be “undisturbed” using
evan’s criteria.
In short, You cant claim they are unadulterated. Extraordinary claims require extraordinary proof. All that can be proved is that Given
a belief in metadata, given a belief that some of LeRoy criteria DONT matter, the stations show no signs in that metadata of being changed.
and check your numbers again.
Further, the first time Anthony and Evan published this they published maps of the stations. guess what you can do?
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