A .5 C reduction to data in 2000 would appear to line up with Anthony Watts’ surface station survey. http://surfacestations.org/

I had to copy/paste the link definition into my browser to get it to work (the first document link), but I got there…

All that document says is that the reason for the gradual shift to morning readings is: “to support operational hydrological requirements”.

So in the end… it’s not really helpful. What kind of “operational requirement” asserts itself gradually and evenly only over a 50 year period? It is still very much a puzzle.

“fact. sorry.”

Look, I am not searching for a particular answer… no apologies are needed… it is just a mystery that I have questions about. Whatever the real truth turns out to be.

The job that all three outfits had was quite simple. Apply quality control to the data, prior to going to work with it with the statistical techniques. Then they ought to have been using the satelite/balloon data to test their output.

Neither of these three supposedly scientific outfits have reached so much as a Sesame Street level of ability in logical inference. If you look at all three of the ground data amalgamations, well they don’t agree with each-other perfectly. But they disagree far more with the satellite and the balloon data then they do with eachother.

So we have the balloon data. We have the satellite data. Both of which agree with each-other. Convergent evidence. Good data. If the two sets of data were not good data they would not confirm each-other.

Then we come to the ground data aggregations. And suddenly we find that “One of these things is not like the others. One of these things just doesn’t belong. Can you tell me which thing is not like the others………..”

http://www.youtube.com/watch?v=0WhuikFY1Pg

So we see that these people are not scientists of any sort but total failures. And an ideology has crept in that you just throw in all the data together, no quality control and then you go to work on it. Aggregate it all and don’t let anyone else check your work if you can help it.

Well how about if the Soviet Union collapses and we aren’t getting their Siberian data all of a sudden? If they just throw everything in how is that going to affect things? Its going to make the 90’s warming look a lot higher than it ought to have looked. Siberia being cold right? If I’m not going too fast for the fraud side of the argument.

What about if areas in Africa or other hotter-than-average regions are steadily coming on board over time? How is that going to rig the figures? Its going to produce a rising gradient of temperature on to of what ups and downs are already there. Thats what its going to do. And did revelations of the heat island effect and inappropriately placed measuring stations lead to a massive culling of historical data? I think we all know the answer to that don’t we?

So all of them, and just Goddard, are failures. They had the balloon and satellite data that would have allowed them to see if they were on the right track. Then when they had nutted out their methodology and exercised enough quality control over the data they had, they could have worked backwards to the pre-Satellite error.

Its no use getting any of this same crowd to try and reform their act. Each country ought to just sack them all. No need to replace them either. We know what needs to be done. Full steam ahead on governmental cost-cutting and clearing the road free of obstructions to synthetic diesel and nuclear power. Just release all the raw data onto the internet and let people argue it out. No conclusion anyone came up with could change the fact that we need to move quickly to make nuclear and synthetic diesel investor-friendly prospects. Billions of lives are counting on us doing just this.

We have to understand that something has happened in the English-Speaking world with our public servants. There was a time where, for the most part, they were reasonably content with merely getting a free ride on their hosts. Now the parasite has turned nasty. And it wants to actively damage its host for no reason. Just out of spite and nihilism or so it seems. We see this tendency rearing its head at every turn.

THE UNITED STATES HISTORICAL CLIMATOLOGY NETWORK
MONTHLY TEMPERATURE DATA – VERSION 2

Figure 3 shows that since about 400 out f 1000 stations changed from pm to am observation time, and that it was a gradual change.

fact. sorry.

I had JUST SAID that I had read something about it… (and I did).

And then all I said was that it *seemed funky*, and asked a simple question, based on what I had already read.

Read for yourself:

“Ah, this still seems very funky. how come this software sees fit to generate gradual 50 year upward trends?”

sod goes apoplectic:
—————————
all this uneducated posts about TOB are simply stupid. please read something about the subject, before you comment on it!!!!
—————————

BTW, your first link seems broken.

I am finding it a little hard to believe that it is taking 50 years to get observers to change to morning readings. They must be stubborn old b*stards. 50 weeks maybe… but regardless:

I checked the Peilke article…. and there is scant information about the TOB adjustment… just a cite of a paper that claimed it is robust.

SO, the idea that as more and more stations added the same biases to their data…. the overall shift represents an accumulation of error for the entire dataset… now, in reference to what? Is the bias being normalized to the first year in the data? What year is considered to be a year where there is no bias?

all this uneducated posts about TOB are simply stupid. please read something about the subject, before you comment on it!!!!

http://ams.confex.com/ams/pdfpapers/141108.pdf

The systematic time of observation bias would be of
little concern with regard to temperature trends provided
that the observation time at a given station did not
change during its operational history. As shown in Fig.
3, however, there has been a widespread conversion
from afternoon to morning observation times in the
HCN. Prior to the 1940s, for example, most observers
recorded near sunset in accordance with U.S. Weather
Bureau instructions. Consequently, the U.S. climate
record as a whole contains a slight positive (warm) bias
during the first half of the century. A switch to morning
observation times has steadily occurred during the latter
half of the century to support operational hydrological
requirements. The result is a broad-scale reduction in
mean temperatures that is simply caused by the
conversion in the daily reading schedule of the
Cooperative Observers. In other words, the gradual
conversion to morning observation times in the United
States during the past 50 years has artificially reduced
the true temperature trend in the U.S. climate record
(Karl et al. 1986; Vose et al. 2003; Hubbard and Lin
2006; Pielke et al. 2007a).

figure 3 clearly demonstrates the continuing change from afternoon to morning observation.

if you don t understand or believe the articles, you can make a simple test in a excel or calc sheet. generate two random columns of numbers, low min in the first (0-5, for example) and high max in the second (20-25).
a measurement at the “best” time of observation, those two numbers are the min and max value of the day. (generate a day average from them)
to simulate a worst case scenario, simulate a n observation time close to the maximum, by calculating the day maximum as the as the higher number between this day max and thelast day max value.
do the same for minums. the difference is massive!

————————

if you on the other hand prefer to believe a denilaits, just check the Pielke article

http://ccc.atmos.colostate.edu/pdfs/Pielke-etal_BAMS_Jun07.pdf

you will find that even he comes to the conclusion:

However, the
evaluation of these TOB biases has indicated that the
time-of-observation bias adjustments in USHCN
appear to be robust (Vose et al. 2003).

Ah, this still seems very funky. how come this software sees fit to generate gradual 50 year upward trends?

And since it is supposed to be correcting the data to look like the “midnight summary period”, which one might assume is a cold part of the daily temp cycle, and the observations probably made during warmer times of day… then the corrections should be *downward*.