On the scales of warming worry magnitudes–part 1

A few weeks after my paper came out I have received quite unexpected but greatly appreciated offer from Anthony to write a summary of the paper for his blog site. The paper’s title is:

Should We Worry About the Earth’s Calculated Warming at 0.7OC Over Last the Last 100 Years When the Observed Daily Variations Over the Last 161 Years Can Be as High as 24OC?

Guest post by Darko Butina

The paper is unique and novel in its approach to man-made global warming in many respects: it is written by experimental scientists, it is published in journal that deals with data analysis and pattern recognition of data generated by a physical instrument, it treats the Earth atmosphere as a system where everything is local and nothing is global, and it is the first paper that looks for temperature patterns in the data that is generated by the instrument designed to and used by experimental scientists since early 1700s – calibrated thermometer. What is also unique is that every single graph and number that I have reported in the paper can be reproduced and validated by reader using data that is in public domain and analyse that data using simple excel worksheet. There are two main conclusions made in the paper:

1. That the global warming does not exists in thermometer data since it is impossible to declare one year either warmer or colder than any other year

2. That the Hockey Stick scenario does not exists in thermometer data and therefore it must be an artefact observed in a purely theoretical space of non-existing annual global temperatures

The paper is long 20 pages and analyses in great details a single weather station of daily data, dataset collected at Armagh Observatory (UK) between 1844 to 2004, one of very few datasets in public domain that have not been either destroyed, corrupted or endlessly re-adjusted by the curators of the global thermometer data at East Anglia University or NASA.

Before we start to analyse this paper, few points need to be made about experimental sciences for my paper to be properly understood. ALL our knowledge and understanding about the physical world around us comes from analysing and learning from data that has been generated by an experiment and measured or recorded by a physical instrument. Let me demonstrate this point by a very simple example of what happens when we record air temperature by some fixed-to-ground thermometer:

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Thermometer reading of 15.1 has several links attached to it that cannot be broken: it is linked to a unique grid point, unique date and time stamp, unique instrument – thermometer and that thermometer to unique symbol (OC). So if someone wants to analyse any temperature trends those trends have to come from thermometer readings; it follows that if thermometer to be used is calibrated using Celsius scale, no datapoint can be older than 1743, follow link to Anders Celsius. Since we know for a fact that the annual temperature ranges will depend on the location of that thermometer, and since mixing different datasets are not allowed in experimental sciences, it follows that if there are, say 6000 weather stations (or fixed thermometers) in existence and across the globe, the first step before raising an alarm would be to analyse and report temperature patterns for every single weather station. That was what I was expecting to see when I started to look into this man-made global warming hysteria three years ago, following the revelations of Climategate affair. But I could not find a single published paper that uses thermometer-based data. So we have situation that the alarm has been raised, the whole world alarmed, suicidal economic policies have been taken while totally ignoring the data generated by the only instrument that has been invented to measure temperature – the thermometer. Instead, thousands of publications have been written looking for temperature trends in purely theoretical space that does not and cannot exist, the space of annual global temperatures. Two key papers have been published earlier, both arguing and explaining why global temperature as a single number does not exists, Essex et al., in 2007, using statistical arguments and written by recognized statisticians, while Kramm and Dlugi in 2011 have shown why the Earth’s atmosphere cannot be treated as a homogeneous system but should be perceived as a network of local temperature systems, from astrophysics point of view.

The starting point for my paper was based on facts that it is impossible to have arguments and ambiguity when it comes to thermometer. If you have two readings, only one outcome is possible: T2>T1 or T2<T1 or T2=T1. So if one wants, for some bizarre reason, to compare two annual patterns then one year can be unequivocally declared as warmer only if each daily reading of that year is larger than each corresponding daily reading of another year:

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This artificially created graph above has real year in Tmax-Tmin space from the Armagh dataset while the year ‘y2100’ was result of adding 15C to each daily reading of y1844. My point here is that everyone seeing that graph would come up with an identical conclusion – y2100 is unambiguously warmer than y1844. So my perfectly valid question was – why would anyone went to trouble to invent something that does not exists while ignore obvious source of temperature data – the thermometer data? My 40 years of experience in experimental sciences offered a most obvious answer to that question – because nothing alarming could be found in thermometer-based data. There is a quite simple rule when it comes to interpretation of data – if more than a single conclusion could be made about any given dataset it means one of two things: either that dataset is of right kind but more data is needed to understand the data, or the data is of the wrong kind. Every single graph and number that is found in my paper can be independently reproduced and validated and therefore the thermometer data is the right-kind of data to use but we need more of it to fully understand temperature patterns observed on our planet.

The opposite is true when we look at the calculated and not measured data called annual global temperatures. Nobody knows where the data comes from, since data is calculated the only way to validate it is to use another set of calculations, it has been constantly adjusted, modified and different trends have been generated on daily bases using ever-changing arguments. When you dissect this very complex looking scientific problem of man-made global warming to its basic components, what you find is that the whole concept of global warming and climate change has nothing to do with science but everything to do with a very desperate attempt to connect temperatures with a few molecules of CO2 that have been generated by burning fossil fuels, while ignoring vast majority of CO2 molecules that have been generated by nature itself. It must follow that if those alarming trends could not be found in thermometer data, than that data must be removed and new data created, type of data that cannot be either proved wrong or right and allow proponents of man-made global warming to generate any trend they need and to enable them to claim that they know everything about everything when it comes to our planet. But, the only problem with that approach is that you cannot cheat in experimental sciences and slowly but steadily, retired scientists like me, with bit of free time will start to look into this problem and use their respective expertise to critically evaluate the supposed science behind this man-made movement.

So even before I started to collect daily data that are available in public domain, I was almost 100% confident that I will not find any alarming trends in thermometer data. And I was proven right.

Let us now start with the experimental part of the paper, the part where all the details of the dataset and dataset itself are presented. The paper is 20 pages long and all conclusions are based on detailed analysis of the Armagh (UK) dataset that covers period between 1844 and 2004. Dataset can be downloaded from the Armagh Observatory website as two sets of files, Tmax and Tmin files:

http://climate.arm.ac.uk/calibrated/airtemp/tccmax1844-2004

http://climate.arm.ac.uk/calibrated/airtemp/tccmin1844-2004

Depending on the software that one wants to use to analyse data, it is important to format all datasets in the same way. Since all commercial software expect as default data to be read in row-wise manner, reformatted Armagh dataset was created as a matrix containing 161 rows (1 row for each year) and 730 columns (1 column for each day-night readings):

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BTW, all the graphs and tables from my paper are presented as JPG image and once I made my paper available free of charge on my own website you will be able to match all those graphs presented in this report to the original ones in the paper.

As a result, we now have annual temperature pattern, let us call it ‘annual fingerprint’, as a 730-bit fingerprint with the first 365 bits assigned to Tmax 1 to Tmax 365 (Jan1 to Dec 365 daytime readings) followed by 365 bits assigned to Tmin 1 to Tmin 365 (Jan1 to Dec 365 night-time readings). So, the annual fingerprint space can be seen as a 161 (years) x 730 (daily readings) matrix. Looking at the table above column-wise, we have ‘day fingerprints’, each of them 161-bits long representing the history of each day-night readings over period of 161 years. Once this table is created, we need to decide what to do with the missing values and with the extra day in February in leap years. We delete that extra day in February, but with great care not to get rest of the year out of the sync. There are two options when dealing with the missing datapoint – either replace it with some calculated one or remove the whole column.

The danger of replacing missing value with some calculated one is that we are contaminating instrumental data with some theoretical data, and unless we really understand that data the safest way is to remove all columns that contain even a single missing datapoint. Once you remove all columns with missing data you end up with 649-bit annual fingerprints, 89% of the original data, i.e. loss of 11% of total information content that is contained in that dataset, but with knowledge that the starting set is not contaminated by any calculated data and all datapoints are generated by thermometer itself.

Now we have our table in excel, table containing 161 years of data where each year is collection of 649 day-night readings and we can ask the data that 64 million worth question: Can we detect unambiguous warming trend over 161 years at Armagh (UK) in thermometer data? All we need to do is to take difference between the youngest (2004) and the oldest (1844) annual fingerprints and display it as a histogram:

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Let me briefly digress here to make the following point – when you analyse instrumental data you have to know accuracy or error levels of the instrument that is used to generate the data. If we assume accuracy of thermometer used in 1800s at +/- 0.5C that means that for two readings to be declared as different, the difference between them should be larger than 1.0C. For example, if T2=10.0 and T1=10.8 we have to declare those two readings as same, i.e. T2=T1, since those two readings fall within the error levels of that instrument. If T2=10.0 and T1=20.0 then the difference is real since it is way outside the error levels of the instrument.

So, what is this simple graph (Figure 5) telling us? First thing to notice is that year 2004 cannot be declared either as warmer or colder than 1844 since every few days there is this switchover occurring making 2004 few days warmer than few days colder than 1844. Second thing to notice is that the size of those switchovers can be as large as 10C in one direction and 8C in another, i.e. 18C in total – way above the error levels of thermometer and therefore those switchovers are real. To make sure that those switchover patterns are not some artefacts unique to those two years, I wrote a special program (in C) to systematically compare every year to every other year (161 * 160 = 25760 comparisons) and on average each year is 50% of time warmer and 50% of time colder than any other year in the Armagh dataset. What make things even more complex is that there is no obvious pattern in terms when the switchover occur and magnitude of it, as it can be seen when two different year pairs are plotted on the same graph:

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So far, all I did was to plot the original data, without any adjustment and without making any prior assumptions. I did not start this exercise to either prove or disapprove existence of global warming, but to see what the actual data is telling us. And what the thermometer is telling us is that the sheer magnitude of those apparently random and chaotic switchovers are due to natural forces that we do not understand, yet, and the anti-scientific process in which all complexity of annual temperature patterns is removed, replaced by a single number and suddenly we ‘see the light’ cannot be used to acquire any knowledge. If we use a simple logic the following logical construct could be made: dataset that is based on thermometer readings contains 100% of information content when it comes to temperatures. If we reduce that 730-dimensional space into a single number, we reduce the information content of that dataset from 100% to 0% – i.e. there is no information there left to gain any knowledge. Let us do the following question/answer exercise to compare two datasets – one that has day-night thermometer readings for a single year and one where 1 number represents 1 year

Q. What is total range of temperatures observed in Armagh?

A. Lowest temperature observed was -15.1C on February 7 1895, the highest temperature +30.3C recorded on July 10 1895; Total range 45.4C

Q. What is the largest and the smallest natural fluctuations observed for individual days?

A. Day that has the most variability is May 4 (Tmax125) with total observed range of 23.8C, while day with least amount of variability is October 29 (Tmax302) with the observed range of ‘only’ 9.9C

In contrast, each year is presented as a single number in the annual temperature space, number obtain by averaging all daily data to a single number, and there are not too many questions that you can ask about that single number. Actually there are none – not a single question could be asked the number that has no physical meaning! For example, if two years have identical annual average we don’t know why they are the same, and if they have two different annual averages, we don’t know why they are different. If we do the same exercise in daily data, we know exactly which days are moving in a same direction and which days are moving in opposite direction.

Let us now ask the most obvious question – are those patterns, or rather lack of patterns, observed in Armagh unique to UK, i.e. are they local or do they reflect some global patterns? Scientific logic would suggest that the same random/chaotic switchover patterns observed in Armagh should be observed across the globe with the only difference being the size and magnitude of those switchovers, i.e. local variations. To test that I took two annual temperature samples from two weather stations on two different continents, one in Canada and one in Australia:

Waterloo (Canada):

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Melbourne (Australia):

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Please note difference in both, patterns and magnitude of switchovers.

Let me make a very clear statement here – the choice of Waterloo and Melbourne weather stations was driven by the ease to find weather stations with relatively easy-to-download formats and I did not get involved in method of cherry picking weather stations that fit patterns found in Armagh, as it is normal practice in man-made sciences. To prove that last point and to challenge readers to start looking into the real measured data and stop looking into non-existing and calculated data like annual global temperatures, I will offer a modest financial reward of £100.00 (UK) from my pension, to first person who finds a single example of year pair where one year has every single daily thermometer readings larger than another year. Any weather station that is not on permanent ice or sand (I don’t know what to expect in those cases) and any gap between two years. Obviously, the winner will have to give the link to the original data and contact either Anthony or myself at darkobutina@l4patterns.com to claim the award.

The way I see it, I am here in win-win situation. If nobody can find weather station that shows unambiguous warming trend, and if we keep record of all those analysed weather stations I saved the money but gain large number of additional information that should finally kill any notion of the man-made global warming hypothesis, since the proponents of that hypothesis would have to explain to general public those patterns observed in thermometer data. In strictly scientific terms and using null hypothesis that either all weather stations count or none does, I have already proven that those patterns are real and observed on three different continents, and therefore prove that the global warming trend does NOT exist in thermometer data. On other hand, if someone does find clear and unambiguous warming trend in thermometer data, that work will again make the same point – all temperature patterns are local and ONLY way to declare that trends are global is if ALL individual weather stations are showing the same trends.

This concludes this Part One report in which I explained how the first conclusion “That the global warming does not exists in thermometer data since it is impossible to declare one year either warmer or colder than any other year” in my paper has been reached.

The second conclusion in my paper which explains why the Hockey Stick scenario does not exist in thermometer data will be reported in a separate report. In Part Two report I will introduce two different bits of software, my own clustering algorithm and k Nearest Neighbours algorithm, or kNN, both used in sciences like pattern recognition, datamining and machine learning and apply them to annual temperature patterns observed in Armagh. The overall conclusions will obviously be the same as we have reached so far, but I will demonstrate how the observed differences between different annual patterns can be quantified and how we can use those computational tools to detect ‘extreme’ or unusual annual temperature patterns, like annual patterns of 1947 which is the most unique not only in Armagh but also in the rest of UK.

==================================================================

Dr Darko Butina is retired scientist with 20 years of experience in experimental side of Carbon-based chemistry and 20 years in pattern recognition and datamining of experimental data. He was part of the team that designed the first effective drug for treatment of migraine for which the UK-based company received The Queens Award. Twenty years on and the drug molecule Sumatriptan has improved quality of life for millions of migraine sufferers worldwide. During his computational side of drug discovery, he developed clustering algorithm, dbclus that is now de facto standard for quantifying diversity in world of molecular structures and recently applied to the thermometer based archived data at the weather stations in UK, Canada and Australia. The forthcoming paper clearly shows what is so very wrong with use of invented and non-existing global temperatures and why it is impossible to declare one year either warmer or colder than any other year. He is also one of the co-authors of the paper which was awarded a prestigious Ebert Prize as best paper for 2002 by American Pharmaceutical Association. He is peer reviewer for several International Journals dealing with modeling of experimental data and member of the EU grants committee in Brussels.

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Lance Wallace

“Essex et al., in 2007, using statistical arguments and written by recognized statisticians, while Kramm and Dlugi in 2011”
Links?

There is a funny paradox:
1) Earth has warmed by 0.7 deg C during the last 100 years, article says
2) but Earth has already warmed by 0.7 deg C during the 1910-1945 period
http://www.woodfortrees.org/plot/hadcrut3vgl/from:1910/to:1945
3) Where is the modern warming then? ?:D
Always remember, that only the post-1970 warming is attributed to “greenhouse gases”. Never forget, that practically all the warming occurred before the “greenhouse gases” were invented as an issue.

oldseadog

Brilliant.
And probably very important.

Alan Clark, Paid shill for Big Oil

I’m sorry. I don’t know if you intended the humour but I simply laughed out loud when I read: “So we have situation that the alarm has been raised, the whole world alarmed, suicidal economic policies have been taken while totally ignoring the data generated by the only instrument that has been invented to measure temperature – the thermometer.”
Priceless.

dataset collected at Armagh Observatory (UK) between 1844 to 2004, one of very few datasets in public domain that have not been either destroyed, corrupted or endlessly re-adjusted by the curators of the global thermometer data at East Anglia University or NASA.
But has been corrected and adjusted by other people in putting together the dataset:
“1844-1882 Data corrected for thermometer errors by ADSC and North Wall Screen/Stevenson Screen
differences by CJB (cjbmet15b) except for 7 Dec 1860-31 May 1863 when raw data corrected for
NWS/SS only
1883 data from Self Recording Thermograph of Automatic Weather Station, corrected for NWS/SS diff
1884 data corrected before entry, corrected for NWS/SS diff.
1885-1899 data corrected before entry. Exposure in Stevenson Screen from 1 Jan 1885 …
So if someone wants to analyse any temperature trends those trends have to come from thermometer readings; it follows that if thermometer to be used is calibrated using Celsius scale, no datapoint can be older than 1743,
So what? if the thermometer is calibrated to any other scale [Fahrenheit, Reamur, etc] the readings can be readily converted to Celsius. The main point is that the thermometer must be calibrated. As long as it is, everything is fine. BTW, I doubt that the Armagh data was measured by thermometers on the Celsius scale. Fahrenheit would be more likely [but I have not checked; have you?]

Darko Butina:
Thankyou.
That is science. And it is how science should be done.
Thankyou.
Richard

Lance Wallace

Google search for Kramm and Dlugi 2011 turns up several discussions. Science of Doom makes a few rather dry comments:
http://scienceofdoom.com/2012/01/05/kramm-dlugi-on-dodging-the-greenhouse-bullet/

milodonharlani

Can we detect unambiguous warming trend over 161 years at Armagh (UK) in thermometer data? All we need to do is to take difference between the youngest (2004) and the oldest (1844) annual fingerprints and display it as a histogram
Nonsense.

Robuk

I knew there were some honest scientists out there,

Joe Public

So your data analysis proves beyond doubt that the £millions ‘wasted’ on limiting CO2 production in Armagh has had zero impact upon the local temperature.

bw

Your methodology could be applied to other stations. There are a few others here
http://hidethedecline.eu/pages/ruti/europe/western-europe-rural-temperature-trend.php
The emphasis that missing data can NOT be “interpolated” or “homogenized” must be repeated loudly and often on those interested in the AGW issue. Quality of data, sampling, methodology are crucial to any experimental design. The surfacestatons.org project just shows how easy it is to show that bad data exists. I think that there are still NOAA stations located in the path of air conditioner exhausts even today.
Other surface temperature stations may have good data but it’s best to do it right in the first place. Eg. the Antarctic stations Vostok, Halley, Amundsen-Scott and Davis are well maintained. They show zero warming since they were established.
If the US Climate Reference Network had been established in 1890 then we would have better data. If it were possible to establish a global network with methodically fixed ocean buoys and reliable recording thermometers in 1890 then we would have a better idea of what the various global climates are doing. But good instrumentation costs money.
There is no “global climate”

M Courtney

Empirical evidence. Thank you.
Yet I fear that those who “know” will only believe evidence that matches their ideal world.
We “know” CO2 causes warming so your thermometer must be broken.
You are denying science with primitive looking at things.
You must recognise that the historical records are stored by industry-funded (fossil-fuel-funded) institutions…
Does that need a /sarc?

richard telford

Did the author consider how much mean annual temperature would have to increase before no overlap between temperature in different years could be expected?
Since for May 4th, there is “total observed range of 23.8C”, we can conclude that the an enormous warming is required (probably over 10C) before the authors test can be expected to yield a positive result. This means that this paper has zero statistical power.
A link to the paper would be appreciated.

M Courtney

By the time I’d typed my third line of urinetaking Leif had actually jumped on a variant of number 3.
lsvalgaard at April 15, 2013 at 12:29 pm.
How embarrassing (for someone).

Eight comments so far and what do we have?
‘Brilliant’
‘Nonsense’
I await the outcome of this debate to see where the balance of opinion lays.

Zeke Hausfather

So I take it that the interpolated CONUS temperatures presented in Fall et al were spurious?

John Edmondson

Your £100 is safe. The warming signal (be it natural or otherwise) is an order of magnitude smaller than the seasonal and daily variability.

milodonharlani

http://solarscience.msfc.nasa.gov/papers/wilsorm/WilsonHathaway2006c.pdf
I hope “correction” refers only to calibrating thermometers & not to “adjustments” of the Hansen/Schmidt variety.

Rob Potter

An interesting approach: People have often pointed out how much information is lost when one calculates averages of one kind or another from a data set, and yet we don’t seem to be able to avoid doing it! For example, in order to compare different sites and show that any observation is seen at more than one site, the almost ubiquitous anomaly is used. However, this is just another way of introducing an average figure and, in the process, losing a great deal of the data as described here.
One point I would like to make is that temperatures are strictly observational data as opposed to experimental data and this is where us experimental scientists get so frustrated (with both the temperature data itself and the ‘scientists’ who manipulate it)! With observational data, the gaps are always there; they can’t be filled by more observations because the time of the observation has passed. This leaves people with the problem of having to either do what is done here (drop years) or introduce a calculated value – and risk contaminating the data with a biased calculation.
A similar issue surrounds dealing with the known issues in observational time series, such as changes in methodology or drift in the measuring equipment. I don’t know if the Armagh series is unique in this respect, but from what I understand there are very very few temperature records made at the same place with the same piece of equipment. This introduces discontinuities into a data set and are commonly addressed by “adjustments” which are supposed to be value neutral, but which everyone can argue about. And, even supposing that a single piece of equipment was used at one site for the whole period, what is the potential for drift in the accuracy of the instrument? Another opportunity for bringing in a calculation to “correct” for a “known” issue, but at what cost?
So, while I applaud this approach, I fail to see that it will really change too many minds. With observational data it is very very hard to keep out some kind of correction for (accepted and agreed on) problems with data collection or manipulations in order to compare the time series to other time series. And it is these corrections upon which everything rests as they can be (and are) argued over incessantly because – as has been shown here – it is the corrections that either produce a trend or don’t, or produce a trend that correlates to another (corrected observational) times series which is then given some kind of causal status.
Oh dear, I have written a thesis instead of a comment. I do apologize to Dr Butina for hijacking his piece which I do think is worth the effort of reading.

milodonharlani says:
April 15, 2013 at 12:34 pm
Dr. Svalgaard: http://climate.arm.ac.uk/publications/484.pdf
does not say which scale was actually used. But the following is a good indication that the thermometers were calibrated to the Fahrenheit scale:
From section 4.1 of http://www.arm.ac.uk/preprints/445.pdf
“This thermometer was still in use at the observatory in 1823 when Thomas Romney Robinson arrived to take up his employment as Director, a position he retained for 59 years. Robinson (1859) remarked of the thermometer It appears to have been made with great care, the freezing and boiling points are exact, and by comparison of the points within the annual range of temperature, I have not found an error greater than 0.2° (F). When the meteorological series was continued in January 1834, after the break since June 1825, the same thermometer was employed until it was broken on 24 May 1859. The series continued using a ‘Kew standard’ thermometer, which, when checked by Mr R.H. Scott from Kew in October 1890, was also found to be accurate to 0.2°F. In view of the reported accuracy of these two thermometers, most likely the only ones employed for the series, and the absence of any more detailed calibration information, we decided etc etc…”
So, what is all that emphasis on the Celsius scale? Completely irrelevant.

milodonharlani

Dr. Svalgaard:
This book, “The Role of the Sun in Climate Change”, by your colleagues Hoyt & Schatten, is probably old hat to you, but was new to me. I found it following up on the first link I posted above, re. Armagh & the solar cycle. It might be of interest to readers here:
http://books.google.com/books/reader?id=EBTZ4LdSfhwC&printsec=frontcover&output=reader&source=gbs_atb&pg=GBS.PA9.w.1.0.0
Your comments would be valued & appreciated. Thanks.

milodonharlani

I wondered also why the author went on at such length re. C. v. F. Conversion is just arithmetic.

milodonharlani

PS: From your valuable link, I see that one of the corrections was for exposure.

Mike Bromley the Kurd (this week)

Mixing of data sets? Now who would do a tom fool thing like that? Oh….wait….right….sorry….I was fantasizing there for a second…..

So if one wants, for some bizarre reason, to compare two annual patterns then one year can be unequivocally declared as warmer only if each daily reading of that year is larger than each corresponding daily reading of another year:

I appreciate the argument that Dr. Butina makes that by keeping the daily min-max data, his dataset has 729 more dimensions than some arithmetically contrived single annual mean value. His point is that even if the annual means between two years are equal, the two years can be very different in the daily measures.
Two complex numbers, C1 and C2, can be said to be equal, but it is not possible to say that C1 > C2 even when C1=a1+b1i , a1>a2, and b1>b2. You can only say |C1|>|C2|. Dr. Butina is not even allowing this. Tell my why Dr. Butina has not created a strawman be creating a condition nearly impossible to meet.
If A(i)>B(i) for all i=1 to 365 we can say that A is “unequivocally” warmer than B. For what “bizarre reason” would we avoid saying A is significantly warmer than B if A(i)>B(i) for all i=1 to 365 except for i=255?
I am all in favor to retaining Tmin and Tmax and the daily ranges that will contribute to an increased statistical mean standard error. But we are not looking for unequivocal evidence in a chaotic system. We are looking for strong statistical significance that the behavior of that chaotic system has changed over time or between periods of study.

james griffin

The natural temp variability since the Holocene Climatic Optimum over the last 10,000 years is
+/- 2.5C. The debate is over 0.7C…..not even close enough to cause any concern. What a waste of time and money the last 20 years has been.

milodonharlani

Mr. Griffin:
Some date the Holocene Optimum from c. 9000 years BP; others from after the 8200 BP event.
http://en.wikipedia.org/wiki/File:Greenland_Gisp2_Temperature.svg
But your point is valid, whatever the precise T variation +/-.

Who knew that it wasnt any cooler in the LIA. Thanks. the sun therefore does nothing.
hahaha
Ah Leif thanks for beating me to the comment about the adjustment in the observatory data.
I thought that perhaps Willis and I were the only ones to have studied that closely enough to wave the Bullshit flag on this guy.. so kudos.

milodonharlani says:
April 15, 2013 at 12:59 pm
This book, “The Role of the Sun in Climate Change”, by your colleagues Hoyt & Schatten, is probably old hat to you, but was new to me.
is well worth a read [and a re-read].

Doubting Rich

“… thousands of publications have been written looking for temperature trends in purely theoretical space that does not and cannot exist, the space of annual global temperatures … the Earth’s atmosphere cannot be treated as a homogeneous system but should be perceived as a network of local temperature systems, from astrophysics point of view.”
I teach a 40-hour course on meteorology and world climate aimed at people with no scientific background, with no minimum academic requirement, so this is a very basic course. This fact becomes entirely obvious during the course. In fact if the student came out of the course not knowing enough to recognise that averaging the climate is ludicrous, and recognise 9 climate zones (in a vastly simplified system, symmetrical about the ITCZ) showing 5 different climates they are likely to fail the course.
So why is it that my students have to know this, yet a climate scientist does not?

As a migraine sufferer I just want to express my sincere thanks for your previous work! 🙂
“He was part of the team that designed the first effective drug for treatment of migraine […] Sumatriptan”
As to this argument I would agree with a single number used to describe “climate” over a year being meaningless – but claiming that every single day over the year would need to be warmer than every single day another seems to stretch things a bit. If “day”, then why not “hour”, “millisecond” or “three week period”? It becomes quite arbitrary.

Troed Sångberg says:
April 15, 2013 at 1:56 pm
but claiming that every single day over the year would need to be warmer than every single day another seems to stretch things a bit. If “day”, then why not “hour”, “millisecond” or “three week period”? It becomes quite arbitrary.
More than arbitrary: nonsense. Why not “century”, or “decade” as well? There is no doubt that Houston, TX is hotter than San Diego, CA, but there are every year days with temperatures below 25F in Houston, but never in San Diego.

dynam01

I too wish to thank Dr. Butina, both for his research here and on behalf on migraine sufferers. I have taken Treximet on and off (that’s how it works for migraine meds, unfortunately) for years and it has been the more consistently effective medication out there.

davidmhoffer

I’ve been a long time critic of the notion of an average temperature that means anything and I think averaging anomalies is worse. But those methods being wrong doesn’t make this one right. If I applied this method to my bank account, I could prove that I don’t have any more money now than I did a year ago. But I do.
Besides which, GHG theory doesn’t say CO2 changes temperature, it says it changes w/m2 which is only indirectly related to temperature. All the methods in the world can’t change that fact. We need to measure and trend w/m2. Degrees just won’t do it.

Lance Wallace

milodonharlani says:
April 15, 2013 at 12:31 pm
I found these:
http://www.uoguelph.ca/~rmckitri/research/globaltemp/GlobTemp.JNET.pdf
Thanks to milodon for linking the Essex & McKitrick paper on the mathematical aspects of the “global temperature” concept. An oldie (2007) but a goodie. If you haven’t read it, you are in for a treat.

jorgekafkazar

The notion of a “global” temperature based on air temperatures is…what was Leif’s word? Oh, yeah. Nonsense. The atmosphere has 1/1100 the thermal capacity of the oceans, so measuring air temperatures (in °F, °C, °R, °K, or whatever) is examining the tail instead of the dog. Air temperature devices (thermometers, etc.) ignore humidity, barometric pressure, wind velocity, and precipitation. Osterizing all those temperatures taken under disparate conditions results in a meaningless fruit smoothie, never an apples-to-apples comparison.
Moreover, in looking at trends, remember that pointwise high temperatures are T⁴ heat-shedding mechanisms and are losing heat faster than cooler areas. Averaging those high temperature areas with other areas just helps us lose sight of that fact. Estimating “global” temperature by averaging regional temperatures is like estimating a city’s population by counting the number of cars on the freeways. Some of those roads lead out of town.

See - owe to Rich

I’m with Stephen Rasey. And Leif. And Mosher, etc.. Just because the author doesn’t like averages or means does not imply that such concepts and measures have no validity regarding climate.
In the Armagh data 2004 does look, on average, warmer than 1844. What caused that? Is that a pattern that is repeated around the world – on average? Is that what global warming means, howsoever it may be caused?
Rich.

Werner Brozek

Should We Worry About the Earth’s Calculated Warming at 0.7OC Over Last the Last 100 Years
To put this number into perspective, the yearly variation is 3.8 C. It may not exist, but if we assume a place that is completely average during the whole time, and even if we assume it also went up 0.7 C, then the July average in 1844 would have been 3.1 C higher than the January average in 2004. See:
http://theinconvenientskeptic.com/2013/03/misunderstanding-of-the-global-temperature-anomaly/

AndyG55

In Figure 5, what is the net average of the daily differences?
It looks to me that there is quite a bit more above the zero line than below.
same with the un-named red/yellow graph.

Hi Darko
About 2 years ago Tony B and I were considering historic perspective of the convergence/divergence between the CET and Armagh temperatures.
Here is part of the exchange (my contribution)
http://www.vukcevic.talktalk.net/Armagh.htm
Why the Armagh should be rising faster up to 1940 and than keeps track with the CET, in order to start falling in 1970’s?
( In this part of the nort Atlantic summer temperatures show no long term rise, all increase is in the winter time. The Armagh observatory is located on edge of the town, but only about 30 miles from heavily industrialized Belfast.) Is it possible that up to WWII industrialization of Northern Ireland was growing faster than in the CE area, (coal burning particles would increase condensation and cloudiness in the winter, and the cloud blanket reducing winters temperatures drop ?).
By 1940s industrialization reached the CE’s and for the next 30 years keeps in step with it.
But why sudden difference from 1970s?
In early 1970 Northern Ireland was hit by civil unrest, slow down in the industrial activity meant cleaner air and colder winters.
In contrast discovery of the North Sea Gas and en mass central heating installation in the English houses probably contributed to UHI effect, which not only prevented slow fall, but contributed to some rise in the CET during 1970’s. In the 1980’s the UHI effect reached a plateau, and onward both the Armagh and CET move at approximately same rate. The above difference would imply that the UHI component in the CET is of order of 0.3C.

Lot of guessing there, but it is a thought worth considering.

CC Squid

“Doubting Rich says:
April 15, 2013 at 1:32 pm
I teach a 40-hour course on meteorology and world climate aimed at people with no scientific background, with no minimum academic requirement, so this is a very basic course.”
I would be interested in a course of this nature if it were offered online. One of the problems of this or any other course is that the subject matter reflects the bias of the instructor. For example, I would not take any course from Mann because my answers would have to reflect the views of the instructor in order to obtain a great grade. Is a course like this offered online and what is the cost?
If there is not an online course please list the title of the text book used for this course.
Regards,
CC

AndyG55

Also, one might want to look at the number of days in either direction then look at in terms of a binomial probability distribution.
I suspect that either that or the average would tell a different story.

Excellent, thank you. Let’s see if we can get this into a few heads. This is exactly what should boot out the nonsense computer models, if enough people only listen and learn.
I know, I know, no one has to tell me how difficult that is, but it’s happening all the same. Just slowly.

AndyG55

ps, if the average difference is significantly positive and the number of days in one direction is significantly more that 182, then I think it may indicate a change in overall temperature.

davidmhoffer

Suppose we measured temp just twice per day. One reading at 280 K and the other at 300K. Average for the day would be 290 K. But instead of averaging temps, let’s first convert to w/m2 via SB Law P=5.67*10^-8*T^4 We’d get:
280K = 348.51 w/m2
300K = 429.41 w/m2
(348.51 + 429.41) / 2 = 388.96 w/m2
Convert 388.96 w/m2 back to temperature via SB Law and we get…. 287.8 K
So which is the right “average” temperature for the day? 290? or 287.8?
I submit that it doesn’t matter. For the purposes of determining if CO2 increases also increase the w/m2 at earth surface, measuring temperature is ludicrous. As per jorgekafkazar says:
April 15, 2013 at 2:48 pm above, there are plenty of other factors that alter energy balance and whatever number actually is correct it means diddly squat compared to the oceans.
Air temps are like a tiny child being dragged by one hand by a large adult. It may be the thrashing and wailing of the child that draws our attention, but there is little doubt in our minds that the child’s “average” direction is to simply follow the large adult.

I’m not sure that this works. Something seems a bit fishy to me. I don’t like averaging temperatures, that seems to lose too much information. But this doesn’t seem right either.

jorgekafkazar

AndyG55 says: “ps, if the average difference is significantly positive and the number of days in one direction is significantly more that 182, then I think it may indicate a change in overall temperature.”
Right, it may, but it would be ambiguous. Before I’d risk our entire civilization, I’d ask for unambiguous proof of the null hypothesis and an economic analysis not pulled out of someone’s stern.

Jarryd Beck:
I write to support your post at April 15, 2013 at 3:35 pm which says

I’m not sure that this works. Something seems a bit fishy to me. I don’t like averaging temperatures, that seems to lose too much information. But this doesn’t seem right either.

You have ‘hit the nail on the head’.
Average temperatures are nonsensical in theory and in practice.
In his above article, Darko Butina accepts this and suggests methods for comparing results of actual temperature measurements obtained at one place (i.e. Armagh Observatory).
The suggested methods are probably less than optimum, but they are clear in method and can be debated. Such debate of interpretations of real data and their indications is science. This contrasts with the methods being used by ‘climate science’.
The debate may decide that the methods suggested by Darko Butina are ideal, or need amendment, or merit rejection. But if the suggested methods are not ideal then that opens debate as to how the suggestions should be amended. If the suggestions merit rejection then that opens debate as to what alternative would be acceptable. And if there is no acceptable alternative then that is useful information because learning what cannot be known is always an important scientific finding.
I submit that the above article is among the most important which have been posted on WUWT. It takes the subject of climate change back to consideration of what is and what is not an indication of climate change. And that consideration is three decades overdue.
Richard