Temperature Adjustments In Ohio
By Paul Homewood
I make no apology for returning to the topic of USHCN temperature adjustments, this time in Ohio. Apart from any other reason, I have been specifically requested to take a look at Ohio.
This time, rather than just looking at one month, January, I have looked at the annual adjustments, again comparing 1934 with 2013. This will give a much more comprehensive view.
The results are below.
By a combination of reducing temperatures in 1934, and increasing last year’s, an extra 1.8F of warming has been added to the year on year comparison.
Readers will recall that, according to NOAA, the overall effect of temperature adjustments was approximately a one-half degree Fahrenheit warming in the annual time series over a 50-year period from the 1940′s until the last decade of the century.
Steve McIntyre reassures me that he has checked NOAA’s calculations and finds them to be reasonable.
I keep being told that the “half a degree” is only an average, and that TOBS adjustments, in particular, can be much greater, depending on individual circumstances. This will, however, mean that for every State I find that, like Ohio, where the adjustment is much greater, there must be many more that are lower than the average, or even negative.
I would be grateful then if these could be flagged up to me, as I have great difficulty finding them myself.
Estimates/Zombie Stations
It’s also worth noting that there are eight stations which have been shut and have estimated data for 2013. In addition, there is one station, Kenton, which has estimated data for the year as one month of raw data was missing. This means that fully 39% of the stations included in the USHCN Final dataset have been estimated.
It has been suggested that I should not publish these sort of posts.
On the contrary, whether these adjustments are right or not, I believe people have a right to know just how much temperatures have been manipulated. I find it difficult how anybody could disagree.
Sources
1) Raw data for 2013 from State Climatological Reports
http://www.ncdc.noaa.gov/IPS/cd/cd.html
2) Raw data for 1934 from USHCN
http://cdiac.ornl.gov/epubs/ndp/ushcn/ushcn_map_interface.html
3) Adjusted data from USHCN Final dataset
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NOT A LOT OF PEOPLE KNOW THAT 
One wonders, if there are folk who do not wish you to publish these sorts of posts, why they read your blog! You continue to do an excellent job and I for one, being a mere amateur, have learned an awful lot by reading your posts and following links. Thank you, Paul.
To snatch victory from the jaws of defeat, AGW skeptics probably need to acknowledge that mainstream scientists honestly felt justified in 1945 in joining Stalin’s call to deceive the public in order to save the world from nuclear annihilation.
Joseph Stalin and the scientists who followed his advice in 1945 are now dead, but science deceit may continue until mainstream scientists have an honorable way to escape.
See this video of Lord Monckton’s interview on the topic of totalitarian world governance.
Thread bomber.
Your blog. Post what you like. Many of us find it interesting and have the same questions.
Once again, your straight-up look at the numbers confirms that the adjustments are more than claimed.
Maybe I should have put this comment here:
Paul, it looks to me like Lubos Motl has done a world-wide analysis similar to your sampling of USHCN in Alabama, Kansas and Texas, and now Ohio. His approach avoids all the homogenizing because he compares slopes without averaging or anomalizing.
How about a statistical analysis of land surface temperatures where each site is treated as a distinct microclimate. I have always been uncomfortable with the adjusting, anomalizing and homogenizing of land surface temperature readings in order to get global mean temperatures and trends. Years ago I came upon Richard Wakefield’s work on Canadian stations in which he analyzed the trend longitudinally in each station, and then compared the trends. This approach respects the reality of distinct microclimates and reveals any more global patterns based upon similarities in the individual trends. It is actually the differences between microclimates that inform, so IMO averaging and homogenizing is the wrong way to go.
In Richard’s study he found that in most locations over the last 100 years, extreme Tmaxs (>+30C) were less frequent and extreme Tmins <-20C) were less frequent. Monthly Tmax was in a mild lower trend, while Tmin was strongly trending higher , resulting in a warming monthly average in most locations. Also, Winters were milder, Springs earlier and Autumns later. His conclusion: What's not to like?
Now I have found that in July 2011, Lubos Motl did a similar analysis of HADCRUT3. He worked with the raw data from 5000+ stations with an average history of 77 years. He calculated for each station the trend for each month of the year over the station lifetime. The results are revealing. The average station had a warming trend of +0.75C/century +/- 2.35C/century. That value is similar to other GMT calculations, but the variability shows how much homogenization there has been. In fact 30% of the 5000+ locations experienced cooling trends.
Conclusions:
"If the rate of the warming in the coming 77 years or so were analogous to the previous 77 years, a given place XY would still have a 30% probability that it will cool down – judging by the linear regression – in those future 77 years! However, it's also conceivable that the noise is so substantial and the sensitivity is so low that once the weather stations add 100 years to their record, 70% of them will actually show a cooling trend.
Isn't it remarkable? There is nothing "global" about the warming we have seen in the recent century or so.The warming vs cooling depends on the place (as well as the month, as I mentioned) and the warming places only have a 2-to-1 majority while the cooling places are a sizable minority.
Of course, if you calculate the change of the global mean temperature, you get a positive sign – you had to get one of the signs because the exact zero result is infinitely unlikely. But the actual change of the global mean temperature in the last 77 years (in average) is so tiny that the place-dependent noise still safely beats the "global warming trend", yielding an ambiguous sign of the temperature trend that depends on the place."
http://motls.blogspot.ca/2011/07/hadcrut3-30-of-stations-recorded.html
Paul,
Excellent work. Concentrate on the numbers, don’t let the adhoms get to you, and don’t do adhoms yourself, and you’ll be fine.
This blog is a clear space in the debate, and long may it continue.
Silence peon! The algorithm is working as designed
Paul,
Keep up the good work – I never tire of reviewing the data.
Your stand on this matter is specifically why I am willing to donate to keeping this website alive with what money I can spare. Those who are engaged in arguing against bald truth do not deserve contributions of any kind to support noisy distortions.
How can it be scientific debate when there are known facts involved? When original temperature data has been changed to produce a different result the “why” doesn’t matter anymore, particularly when a corrupt political agenda is involved. That agenda should be enough for reasonable people to stand back and study before they make rash excuses for a government that is obviously out of control in so many areas.
Temperature adjustments made so far serve only one purpose. They allow government regulators to close down perfectly clean energy sources to force our population to do without the bountifulness the American experiment has produced. We are being drug down to poverty, along with the rest of the world, for a religious belief enforced by government control. It is the opposite of what the writers of The Constitution of the United States of America intended in the first amendment.
I just wanted you to know that we laymen out there understand what is being done by the federal government, and probably, some state governments. Donating is one way to say “we stand beside you” in an ugly war.
Sorry, this mis-posted because I followed the link without realizing I had changed sites. It was mean for Tony Heller. However, thank you Ron C for all that information as well as Paul Homewood. Reading reasoned approaches to real data always gives me confidence that this fight is winnable.
CO2 is not a pollutant…
Oil??…It’s the new clean energy
I am left wondering if all these adjustments are also smoothing-out the extremes of variablity of the past (say before 1980) and so making the current period look unusually variable.
This would assist in adding credence to the ‘team’ claim of weather getting more extreme.
The Google Maps gadget here (scroll down) may save you some time. It shows the effect of GHCN adjustments on 60 year trends (the most recent 60 year period available for each station). You can select to show which ones exceed a prescribed value. etc. Click on the markers to get the info.
You disappoint me Nick.
I thought you were going to give me a list of 10 States, with negative adjustments.
What I did post, a couple of months ago, was a here of the US total average. It’s a simple average – should be area-weighted.
The spike at 2014 is an artefact of the part-year.
That’s interesting, Nick. It actually comes to about the 1F figure I have been suggesting.
Have you any figures by state, as I have the area numbers for weighting?
Paul, is there even one State with negative adjustments?
Not found one yet
Paul,
I have just posted a complete set of plots for the various states, and also an average of these for the USA, weighted by state area. The large states have a moderating effect. The national adjustment now varies by less than 1 °F.
I want to see that list too.
Churchill is alleged to have once claimed – there are lies. damn lies and statistics.
A famous Australian politician is alleged to have uttered – Sir – the greatest travesty in the abortion debate is that in your case it isn’t retrospective.
How can anyone justify changing data recorded almost a hundred years ago – they have NO IDEA if their adjustments should be up or down.
I have studied and respect statistical analysis but to use it as a justification for altering data ??
I’m not sure I trust this data altering process at all !
By reporting that last year’s temperature is higher than it actually was, the fiddlers’ make a rod for their own back.
Because next year, if the temperature remains the ‘same’ as this year, then it’ll actually have ‘cooled’ compared with their own figures.
[eg last year actual (say) 50F, but reported as 51F; next year actual (say) 50F, so it’s 1F lower!]
By publishing this information the experts have to explain themselves sooner or later.
Their explanation probably isn’t particularly convincing. It’s also difficult to call something settled science when it depends on a judgment call of ‘correcting’ data.
Sure seems suspicious how current adjustments always increase temperature. .. While the past is cooled via this same “calculation”…
Yea… Hmmmmmm…. right.
Steve,
That would disappoint me about Steve Mc. Do you have a link to where he’s said that he thought the adjustments reasonable?
Steve? Err…sorry – “Paul”!
Who, exactly, does not want this published?
Right, TOBS adjustments …. but, that doesn’t explain the discrepancy in adjustments done in 2013. http://suyts.wordpress.com/2014/07/06/infilling-interpolating-and-temp-adjustments-as-seen-on-individual-stations/
If you examine any of the contemporary literature on the subject, the presumption that our ancestors were too stupid to take temperatures for distinct days and not confound overlapping readings blows to smithereenees. Current TOBS adjustments are duplicitous arrogance, and arrogant duplicity.