Andrew Revkin asked me to provide comments on this article of his where the National Climatic Data Center was asked to respond to Watts et al 2012:
A Closer Look at Climate Studies Promoted Before Publication
Here is what I sent to him:
My comments on Thorne’s response are pretty simple.
They still refuse to get out of the office, to examine firsthand the condition of the network and try to come up with hands on approaches for dealing with station inhomogeneity, but instead focus of trying to spot patterns in data and massage it. In my view this is the wrong approach and the reason that we are in this polarization today. We are conducting a grand experiment, and like any scientific experiment, you have to carefully watch how the data is being measured in the experiment environment, or problems will invalidate the measurement. If Climate Science operated under the same rules as Forensic Science, the compromised data would be tossed out on its ear. Instead, we are told to accept it as fully factual in the court of public opinion.
Until I came along with Watts 2009, they really weren’t looking closely at the issue. The SurfaceStations photography forced them into reaction mode, to do two things.
1. Close the worst USHCN stations, such as Marysville, CA (the station that started it all), Tucson, AZ (the University Science Dept/Weather Service Office that had the USHCN weather station in the parking lot), and Ardmore, OK (the USHCN station on the street corner). There are many others that have been closed.
If they are able to correct the data gathering problems back in the office with algorithms, why do they need to close these stations? Additionally, if they think they can get good data out of these stations with the myriad of adjustments they perform, why did they need to spend millions of dollars on the new Climate Reference Network commissioned in 2008 that we never hear about?
According to communications I received from Texas State Climatologist John Nielsen-Gammon, the National Weather Service is developing plans to eliminate up to half of all COOP network stations (of which USHCN is a subset) as a potential cost-cutting measure.
Some possible reasons: (1) not central to the core mission of the NWS; (2) poor data quality; (3) too much of a public relations headache with people putting embarrassing photographs online.
I would argue not for removal of bad stations, but rather for the replacement of bad stations with well-sited stations, with simultaneous overlapping data collection so that biases can be both measured directly and permanently eliminated. I don’t see anything in what they are doing with Thorne that addresses this. To me, all they are doing is trying to put lipstick on a pig.
2. Attack me without publishing an appropriate paper intended for peer review first, such as the ghost authored “Talking points” memo issued by NCDC’s Dr. Thomas Peterson, who wouldn’t put his name on it, yet circulated it to every NOAA manager and the press. If the data from these stations is so strong, and the adjustments and corrections so valid, why the cloak and dagger approach?
Note, that in the Thorne response, they carefully avoided saying anything about station siting, preferring instead to focus on data manipulations. From my viewpoint, until they start worrying about the measurement environment in which our grand global experiment is being measured, all they are doing is rearranging data without looking at and learning from the environment and history that created it.
Perhaps they should follow the advice of the General Accounting Office report that backed up my work:
GAO-11-800 August 31, 2011, Climate Monitoring: NOAA Can Improve Management of the U.S. Historical Climatology Network Highlights Page (PDF) Full Report (PDF, 47 pages) Accessible Text Recommendations (HTML)
Finally, let’s spend a few moments looking at another network in the USA that doesn’t seem to suffer from the same sorts of magnitude of issues. The U.S. Population-Adjusted Temperature Dataset (PDAT) developed by Dr. Roy Spencer, which better handles UHI.
The following plot shows 12-month trailing average anomalies for the three different datasets (USHCN, CRUTem3, and ISH PDAT)…note the large differences in computed linear warming trends (click on plots for high res versions):
Where’s the warming?
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Revkin? Seriously? Why would you bother dealing with him?
“Where’s the warming?”
Indeed…Where IS the warming?
Thanks Anthony for everything.
Who trusts revkin to cover this impartially?
“Where’s the warming?”
*
Exactly! Well done! 🙂
Once again it basic stuff taught to any undergraduate or even high school student , that you need to use the tools of measurement in correct manner or what they tell you loses value, its actual a reality which is accepted which why there standards in the first place. But what seems to have happened is they think if they throw enough computing power at it the problem goes away. The simply fact is you cannot correct for error in any meaningful way if you neither know its magnitude nor direction. really basic stuff .this
I presume Anthony is the author of this post? I don’t see a byline.
The main point is that until these people go out and look at the HISTORIC CHANGES, not only at EACH AND EVERY site, but also in the LOCAL NEIGHBOURHOOD of each site, then they CANNOT POSSIBLY make proper allowances for local factors on the temperature trends.
If you don’t account for these local trends first, the major cause probably being the large jump in urbanisation in the 1970-2000 period, then the whole calculation of so-called “global” land temperatures is just a crock of s*** !
Roy’s PDAT and this paper by Watts et al. go some small way to addressing this issue.
Is it far enough.. probably not..
“Some possible reasons: (1) not central to the core mission of the NWS; (2) poor data quality; (3) too much of a public relations headache with people putting embarrassing photographs online.”
So my car(evil gas powered IC) breaks down on the side of the road, because I put the wrong size tires on, and instead of replacing with the right ones, I just burn it there,and tell my insurance company everything is honkydory, because the offending vehicle has been removed from the system.
Must have been a long day. Can’t seem to wrap my head around this logic.
“They still refuse to get out of the office, to examine firsthand the condition of the network”
And there you have it in a nutshell. Crap in = crap out (albeit highly processed crap. Those computers make it nice and smooth)
What is the yearly cost of a COOP station? Given computer and internet technology today, shouldn’t it be coming down?
Why with the price of technology getting cheaper
and information handling costing next to nothing
and so much at stake in the Climate Change debate,
is NOAA not ADDING to the COOP station network instead of shrinking it?
Sounds like enlarging COOP is a good use of “Stimulus” funds, to me.
Here’s my own take:
we’re all in the blue.
Excellent response for reasonable people but not for those with bias as the main agenda
NOAA’s attitude to data is akin to the Titanic’s crew rearranging the deckchairs, sadly NOAA hasn’t realised it’s sinking yet…
Or it’s like cooking with garbage, doesn’t matter what recipe you try the results are still going to taste of garbage…
Fine….they cook the books and numbers…..but it still shows the
temp-plateau since 2000 we are on. And this plateau will continue…..
no more warming to come…..
What has been exposed is a total lack of governance, quality control and configuration management. Instead of quick easy ‘fixes’ to data because one station looks odd man out then run the standard algorithm on many thousand observations; each station needs a full quality record.
The quality record would provide siting issues and local information. Any adjustments would be applied specifically to that one station, be justified with fully documented details of why and how the adjustment was being made and who by, be signed off by a QA and Configuration Manager as being appropriate for that station. The signatories would then be responsible for that change. Any subsequent ‘adjustment’ to that one station would again have to be agreed and justified and the reason that the previous adjustments were not correct gully documented. This way stations that are odd ones out because of their geographic position or whatever will not be homogenized out as their readings are accurate. The entire worship of the average that climatologists seem to like is not borne out in reality.
Its not like there are a huge number of stations, even worldwide. It is perfectly possible for government funded agencies to run a quality system without great expense. But they do not want to, as the repeated massaging of the data by compliant climate scientists plays to their confirmation bias.
It’s not Revkin so much as it’s the New York Times. They are “the paper of record.” Unfortunately.
I refuse to subscribe. I do subscribe to the WSJ.
Last post directed at Sean Peake:
http://wattsupwiththat.com/2012/07/30/my-response-to-ncdcs-op-ed-in-the-new-york-times/#comment-1048064
Puzzling. We can launch satellites to try to measure temperatures. We have the Argo network. We’re surrounded by ‘smart’ things, including ‘smart meters’ for loads of stuff.
Yet on the ground, where it should be easiest, we have a mess which requires constant ‘adjustment’ by sedentary statisticians.
Well done Anthony!
Apropos of nothing but accuracy, but didn’t the General Accounting Office (GAO) change their name to Government Accounting Office?
Plain, simple, and straightforward. In a word, brilliant. Keep their feet to the fire. They are not empiricists and will fight to the death rather than admit that temperature stations should be classified according to the physical characteristics of the heat sinks in which they exist.
Actually that’s wrong too. Government Accountability Office is closer.
Once in my career, I was principal investigator on an IR&D project at a major defense contractor. The project had already started when I was assigned, and the results from the lab were abysmal, huge standard of deviation from multiple experiments that should have been measuring the same thing. I got myself down to the lab full time, rolled up my sleeves, and set about finding out what the problems were. After a couple of weeks I solved a lot of contamination and experimental technique issues, and we got down to SDs of about 5-10% of the mean with very repeatable results from experiment to experiment.
Who knew that I could have stayed in my office and just made up “adjustments” to the data instead of getting my hands dirty in the lab? What a dummy I was!
Ah, yes…”manipulation”.
It is insightful to define what “manipulation” means, as in “data manipulation”.
First, to the root word “manipulate”:
ma·nip·u·late (me-nip`ye-lat)
tr.v. ma·nip·u·lat·ed, ma·nip·u·lat·ing, ma·nip·u·lates
1. To move, arrange, operate, or control by the hands or by mechanical means, especially in a skillful manner: She manipulated the lights to get just the effect she wanted.
2. To influence or manage shrewdly or deviously: He manipulated public opinion in his favor.
3. To tamper with or falsify for personal gain: tried to manipulate stock prices.
4. Medicine To handle and move in an examination or for therapeutic purposes:
I’ve highlighted the two definitions that apply (although the first one has potential in a devious way, too). How can anybody claim to be a scientist and be in favor of “data manipulation”?
If so, the definition “scientist” no longer applies.
Well said Mr Watts !!!
Exactly what I was saying 24 hours ago on another forum. Shift the measuring sensors into approved locations following the sighting guidelines set out by your own countries (Australia?UK/USA/Europe etc) and international standards and we won’t see this corrupted data being used to manipulate the entire worlds opinion on global warming.