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Anthony Watts and his WUWT blog are regularly attacked in this forum by AGW proponents. Watts has been called dishonest in every way imaginable. Personally, I disagree with those claims, but I thought Watts' critics might be interested in an episode when he lays down the law to an errant skeptic.
eace
". . . To the uninitiated observer, this “revelation” by Goddard could look like NCDC is in fact “fabricating” data. Given the sorts of scandals that have happened recently with government data such as the IRS “loss of e-mails”, the padding of jobs and economic reports, and other issues from the current administration I can see why people would easily embrace the word “fabrication” when looking at NOAA/NCDC data. I get it. Expecting it because much of the rest of the government has issues doesn’t make it true though.
What is really going on is that the FILNET algorithm, design to fix a few stations that might be missing some data in the final analysis is running a wholesale infill on early incomplete data, which NCDC pushes out to their FTP site. The process gets to be less and less as the month goes on, as more data comes in.
But over time, observers have been less inclined to produce reports, and attrition in both the USHCN and and the co-op network is something that I’ve known about for quite some time having spoken with hundreds of observers. Many of the observers are older people and some of the attrition is due to age, infirmity, and death. You can see what I’m speaking of my looking through the quarterly NOAA co-op newsletter seen here: NWS Cooperative Observer Newsletter
NOAA often has trouble finding new observers to take the place of the ones they have lost, and so, it isn’t a surprise that over time we would see the number missing data points rise. Another factor is technology many observers I spoke with wonder why they still even do the job when we have computers and electronics that can do the job faster. I explained to them that their work is important because automation can never replace the human touch. I always thank them for their work.
The downside is that the USHCN and is a very imperfect and heterogeneous network and will remain so; it isn’t “fixable” at an operational level, so statistical fixes are resorted to. That has both good and bad influences. . . ."
On ‘denying’ Hockey Sticks, USHCN data, and all that – part 1
Posted on June 25, 2014 by Anthony Watts
One of the things I am often accused of is “denying” the Mann hockey stick. And, by extension, the Romm Hockey stick that Mann seems to embrace with equal fervor.
While I don’t “deny” these things exist, I do dispute their validity as presented, and I’m not alone in that thinking. As many of you know Steve McIntyre and Ross McKitrick, plus many others have extensively debunked statistics that went into the Mann hockey stick showing where errors were made, or in some cases known and simply ignored because it helped “the cause”.
The problem with hockey stick style graphs is that they are visually compelling, eliciting reactions like whoa, there’s something going on there! Yet, oftentimes when you look at the methodology behind the compelling visual you’ll find things like “Mike’s Nature Trick“. The devil is always in the details, and you often have to dig very deep to find that devil.
Just a little over a month ago, this blog commented on the hockey stick shape in the USHCN data set which you can see here: Continue reading →

". . . To the uninitiated observer, this “revelation” by Goddard could look like NCDC is in fact “fabricating” data. Given the sorts of scandals that have happened recently with government data such as the IRS “loss of e-mails”, the padding of jobs and economic reports, and other issues from the current administration I can see why people would easily embrace the word “fabrication” when looking at NOAA/NCDC data. I get it. Expecting it because much of the rest of the government has issues doesn’t make it true though.
What is really going on is that the FILNET algorithm, design to fix a few stations that might be missing some data in the final analysis is running a wholesale infill on early incomplete data, which NCDC pushes out to their FTP site. The process gets to be less and less as the month goes on, as more data comes in.
But over time, observers have been less inclined to produce reports, and attrition in both the USHCN and and the co-op network is something that I’ve known about for quite some time having spoken with hundreds of observers. Many of the observers are older people and some of the attrition is due to age, infirmity, and death. You can see what I’m speaking of my looking through the quarterly NOAA co-op newsletter seen here: NWS Cooperative Observer Newsletter
NOAA often has trouble finding new observers to take the place of the ones they have lost, and so, it isn’t a surprise that over time we would see the number missing data points rise. Another factor is technology many observers I spoke with wonder why they still even do the job when we have computers and electronics that can do the job faster. I explained to them that their work is important because automation can never replace the human touch. I always thank them for their work.
The downside is that the USHCN and is a very imperfect and heterogeneous network and will remain so; it isn’t “fixable” at an operational level, so statistical fixes are resorted to. That has both good and bad influences. . . ."
On ‘denying’ Hockey Sticks, USHCN data, and all that – part 1
Posted on June 25, 2014 by Anthony Watts
One of the things I am often accused of is “denying” the Mann hockey stick. And, by extension, the Romm Hockey stick that Mann seems to embrace with equal fervor.
While I don’t “deny” these things exist, I do dispute their validity as presented, and I’m not alone in that thinking. As many of you know Steve McIntyre and Ross McKitrick, plus many others have extensively debunked statistics that went into the Mann hockey stick showing where errors were made, or in some cases known and simply ignored because it helped “the cause”.
The problem with hockey stick style graphs is that they are visually compelling, eliciting reactions like whoa, there’s something going on there! Yet, oftentimes when you look at the methodology behind the compelling visual you’ll find things like “Mike’s Nature Trick“. The devil is always in the details, and you often have to dig very deep to find that devil.
Just a little over a month ago, this blog commented on the hockey stick shape in the USHCN data set which you can see here: Continue reading →