Interesting Analysis Of UK Temperature Trends
In part 4 of this series we discovered that Heathrow Airport runs a little hotter than the Royal Naval Air Station at Yeovilton (pictured) and seems to be warming at a greater rate.
The same analysis also indicated that things are not as straightforward as climate science and alarmists would have us believe since there have been periods without warming and periods of cooling since 1965 despite a near exponential increase in human carbon consumption.
I promised an analysis of monthly data at these two locations and here it is…
We are now looking at the same data series as used for my previous newsletter but at the higher resolution of monthly means of daily maxima and minima. The annual variation in temperature is pretty much evident, jiggling as it does from around zero degrees to +20°C or thereabouts with the series mean of 10.37°C being denoted by a red dashed line.
Folk will ask, ‘but is it warming?’ and so I have fitted one of those OLSR trendlines whose point estimate for the warming rate is 0.00187°C per month (p=0.033), which translates into 2.2°C per century, this being a tad lower than the 2.4°C estimate derived using annual means.
As before, it is worth thinking about the wiggly black line, which is picking out subtle changes within the overall upward trend. There’s a spot of rapid cooling just after 1985 and again around 2010, and a spot of rapid warming around 1990. The series starts to tail off toward 2020 and it remains to be seen whether this is the start of a cooling period or a blip as before.
The Darnedest Thing
It sure looks like it is warming down at RNAS Yeovilton, doesn’t it? So let us derive the overall mean of the most recent 60 months from Jul 2017 – Jun 2022 (11.16°C), then derive the overall mean of the earliest equivalent period of Jul 1965 – Jun 1970 (9.86°C). If we bung these into a stats test (ANOVA) it throws out a non-significant difference of p=0.118.
Ain’t that the darnedest thing? This comes about because the monthly variation in the mean temperature for each of those 5-year periods is large compared to the warming rate between them, so that subtle long term trend gets lost in the seasonal variation.
If we now extend our study period to 240 months the overall mean for Jul 1993 – Jun 2022 becomes 10.81°C and the overall mean for Jul 1965 – Jun 1985 becomes 9.93°C and we detect a statistically significant difference of p=0.034. This comes about because our total sample size has increased from n=120 to n=480 and we can thus detect that small long term difference despite significant monthly variation.
Hot Gnat Farts
This raises the issue of statistical power in climate change studies. With a large enough data sample we can detect the impact of a single hot gnat fart on the temperature profile for Greater London. Climate science is chock-a-block with massive datasets and lengthy series so we can generally detect anything we wish even though it may not have any real world meaning.
Back in SR15 the IPCC declared a warming rate of 1.5°C per century. OK, so we can detect this rate with a high degree of confidence but does it actually mean anything? This is where we have to stop looking at temperature and start looking at weather events to see if rainfall, drought, wind speed, hurricanes, sea ice, glaciers and the rest are being affected by a very modest long term warming trend or whether they are simply doing their own thing.
I shall be wheeling out several truckloads of analysis on all of these topics and more so it may be prudent to invest in a large tin of biscuits. Meanwhile, we better finish off with a quick squint at Heathrow’s monthly series…
Global Warming At Heathrow Airport!
There it all is. Warming is more evident down in the concrete jungle, with OLSR revealing a warming rate of 0.00285°C per month (p=0.004), which translates into 3.4°C per century, this being a tad lower than the 3.6°C estimate derived using annual means.
The wiggly black line mirrors the dance at RNAS Yeovilton so we can be assured that this is a genuine climate thing rather than something peculiar and rather local. The tail off after 2015 is rather intriguing!
Univariate Analysis Of Variance
In our pot we’ve got 2 airfields, 12 months and (almost) 6 decade’s worth of temperature data. Seems to me like we ought to stuff this through a statistical crunching machine called univariate analysis of variance (a.k.a. ANOVA). What this should do is confirm the temperature differences between the two airfields, confirm temperature differences between months and confirm temperature differences between decades. It will also reveal any interactions between these three factors.
I shall start by pasting a screenshot of the key output from a rather pleasing ANOVA and then talk folk through this…
Ignore everything and look at the column headed ‘Sig.’, these being the p-values that reveal whether a factor is statistically significant or not. We see a whole bunch of ‘.000’, which equates to p<0.001 and high statistical significance. High statistical significance means the differences we see are very unlikely to have arisen by chance.
So… there’s a statistically significant difference between airfield temperatures (p<0.001), between monthly temperatures (p<0.001) and between decadal temperatures (p<0.001). This much we already know, but just hang on one moment for the table of repeated contrasts reveals a fly in the decadal ointment! Here it is:
You’ll see a number of contrasts labelled ‘level 1 vs level 2’ etc. These are factor levels for decade defined as follows:
- Level 1: 1965 – 1974
- Level 2: 1975 – 1984
- Level 3: 1985 – 1994
- Level 4: 1995 – 2004
- Level 5: 2005 – 2014
- Level 6: 2015 – 2022
Now look at the rows labelled ‘Sig.’ starting with p=0.088 for level 1 (1965-1974) vs. level 2 (1975-1984). That there change in overall mean temperature of 0.204°C between these two decades fails to reach statistical significance at the 95 percent level of confidence (p>0.05) so this difference may easily have arisen by chance.
In plain English there wasn’t any significant change in temperature, which is rather odd given AGW is supposed to be a thing.
Now look at that p=0.132 for that difference of 0.180°C between level 2 (1975-1984) and level 3 (1985 – 1994). No statistically significant change in temperature there either! This is supposed to be settled science is it?
It is only when we get to level 3 (1985-1994) vs. level 4 (1995-2004) that we see a decadal warming of 0.601°C reach statistical significance at p<0.001. Suddenly we appear to have some genuine AGW… or is some other form of warming going on that gives an impression of AGW?
Shouldn’t we be debating this point instead of branding scientists with alternative theories as climate change deniers and denying them media coverage and/or careers and/or grant funding? Should all our eggs be in one highly political basket given the importance of the matter|?
If alarmists were smiling contentedly at level 3 vs. level 4 they won’t be smiling at level 4 (1995-2004) vs. level 5 (2005-2014) since there’s absolutely no change in decadal means!
To be precise there was a warming of +0.0002°C (p=0.999) between these two decades.
The final contrast of level 5 (2005-2014) vs. level 6 (2015-2022) should give alarmists some relief, with a highly statistically significant rise of 0.499°C (p<0.001). Thus we observe AGW popping in and out of existence at the decadal level despite our carbon consumption continuing to rise at a giddy rate.
This is not exactly a robust theory, to say the least!
Three Crusty Bits
There are three crusty bits to this analysis that deserve another cuppa and chat, these being the three interaction terms of airfieldmonth (p<0.001), airfieldPeriod10 (p=0.125) and Month*Period10 (p<0.001). The first of these tells us that the temperatures recorded at RNAS Yeovilton and Heathrow differ according to month and I reckon a simple slide is in order to show this visually:
Isn’t that lovely? We now see that both airfields record pretty similar temperatures during the colder part of the year but as the sun returns Heathrow heats up more than RNAS Yeovilton because there is more tarmac, more concrete, more air traffic and more folk arriving in vehicles etc etc.
During July the mean temperature at Heathrow is 1.67°C hotter than RNAS Yeovilton on average; a feature that we can attribute to the urban heat island effect that the Met Office quietly ignores. How confident are we that Stevenson screens around the globe have been put in sensible places, and if they were once in a sensible place (leafy green stuff) then is that place still sensible?
The second interaction of airfield*Period10 fails to reach statistical significance (p=0.125) and this indicates long-term warming rate differences between the two airfields are too small to be detected in a decadal analysis of variance. A larger sample will fix this but we’ve already nailed an estimate in part 4 of this series.
The third interaction of Month*Period10 is rather interesting in that it indicates that months of the year have not warmed at equal rates over the six decades under study. This can be seen in the colourful plot below as a narrowing of decadal differences during the autumn and a broadening of differences in high summer.
The greatest difference we observe is for the month of July, with the months of July during 2015-2022 being 2.1°C hotter on average than Julys during 1965-1974. The smallest difference we observe is for the month of October, with Octobers during 2015-2022 being only 0.7°C hotter than Octobers during 1965-1974.
This is worth coffee and cogitation because it means decadal warming rates are not consistent across the calendar year, as we might expect if the process was being driven by atmospheric carbon dioxide alone. I would suggest that something else must be going on but this would make me a ‘denier’ or ‘nutjob’ etc etc.
The BIG Stuff
Up to now I’ve taken subscribers through some very basic analysis of temperature data at two UK airfields to illustrate how unsettled the science really is.
Critics will invariably spit out “that’s no big deal, that’s just two airfields!”; hence, in the next few newsletters we are going to go really BIG – were are going to go GLOBAL and we are going to go NASA, NOAA, GISS, Berkeley, CRU, Hadley and beyond.
We’re going to scrutinise top notch anomaly data for land and sea surface temperatures and I’m going to reveal a few hidden tricks of the climate trade.
See more here: substack.com
Header image: gov.uk
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Jerry Krause
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Hi John Dee and PSI Readers,
I went to (substack.com) to see more. And there I read: “It takes an investment of 40-50 hours per week to crank the handle and this is made possible through voluntary donation. Your support is greatly appreciated.” I believe the 40-50 hours per week because being a SCIENTIST requires more than a 40 hour per week commitment regardless of what topic (system) one is studying.
And I do not find John commenting about the observed fact that during the 1995-04 decade the average temperature for August increased about 0.7C from July’s average temperature when during 5 other decades the August’s average temperature usually decreased about 0.2C.
We should not forget this average is for 10 years. Hence, as a SCIENTIST, I would focused my attention upon the yearly trends of each of these 10 years to better see how, or when, this decadal anomaly occurred. Which, if one had already invested 40 hours per week, really should not require more than a hour. For the monthly averages for a decade had to have been calculated from the daily average temperature (maybe maximum and minimum temperature of a day divided by 2) for each day of a month. That is if one has experience with accessing this data as it seems John Dee has.
Have a good day, Jerry
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Jerry Krause
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Hi John Dee and PSI Readers.
(https://raws.dri.edu)
While the Remote Automated Weather Stations (RAWS) are only for stations in the USA states and territories, they provide graphical representations of fundamental climatic data for about 2000 weather stations for at least two years.T. All one has to do is click on the this link. Click on the specific station desired. Click on the Time Series Graph, Set the Starting Date, Set the Ending Date, Select the Elements to List. Click on Submit Information and wait while your computer down loads the graphs to the screen for you to study.
Have a good day, Jerry
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lloyd
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SCIENTIST. So the rest of us are just dweebs???
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Andy Rowlands
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Hi Jerry, I knew ‘John Dee’ on social media before he started writing for Substack, and he is as he claims, a retired former G7 level British government scientist, who now spends many hours combatting the climate fraud using the actual data and his experience of being an analyst.
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Jerry Krause
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Hi Andy,
My question to you and John Dee is: are either of you aware of the RAWS project and its data?
Have a good day, Jerry
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Jerry Krause
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IN THE BEGINNING—Part 1 (Philosophers and Alchemists)
Preface: I begin a series of brief comments (with links to essays; which are not as brief), based upon the wisdom: “The most obvious is most difficult to see.” Hence, we humans have had made many mistakes.
Comment: The first three words, IN THE BEGINNING, begin most all English translations of the Holy Bible. Does one need to be told that these three words should be where one should always start.
EARTH, WATER, AIR, FIRE Four words. This is where some ancient PHILOSOPHERS, who studied their world, began. Which some alchemists, who accepted the wisdom of these philosophers (who had only reasoned) failed in their experimental attempts to convert earth, water, air, fire into GOLD But in the process of their experimental efforts, the alchemists concluded their world was composed of the three phases of matter—SOLID, LIQUID, GAS. And it seems that some alchemists of Robert Boyle’s time still attributed the failure to create Gold was not enough HEAT. For even at the time of Boyle, alchemists were still meeting to discuss FURNACES.
Today many scientists, chemists even, consider alchemists to have been STUPID to try to make Gold as they ignore that at a much more ANCIENT time, than that of Boyle and Newton, alchemists had made glass (a liquid) from sand (solid earth) using furnaces that alchemists had invented long before. And glass, since ancient times, has been a more practical product than GOLD. Which (gold), for a very long time, was only important because of its esthetic and economical (due to its rarity) values. And it seems that alchemists, Newton and Boyle, ignored the practical importance of the glass flasks, beakers, and thermometers of their time made with ‘furnaces’ invented nearly two thousand years earlier.
Have a good day, Jerry
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Jerry Krause
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IN THE BEGINNING—Part 1 (Philosophers and Alchemists)
Preface: I begin a series of brief comments (with links to essays; which are not as brief), based upon the wisdom: “The most obvious is most difficult to see.” Hence, we humans have had made many mistakes.
Comment: The first three words, IN THE BEGINNING, begin most all English translations of the Holy Bible. Does one need to be told that these three words should be where one should always start.
EARTH, WATER, AIR, FIRE Four words. This is where some ancient PHILOSOPHERS, who studied their world, began. Which some alchemists, who accepted the wisdom of these philosophers (who had only reasoned) failed in their experimental attempts to convert earth, water, air, fire into GOLD And in the process of their experimental efforts, the alchemists concluded their world was composed of the three phases of matter—SOLID, LIQUID, GAS. And it seems that some alchemists of Robert Boyle’s time still attributed the failure to create Gold was not enough HEAT. For even at the time of Boyle, alchemists were still meeting to discuss FURNACES.
Today many scientists, chemists even, consider alchemists to have been STUPID to try to make Gold as they ignore that at a much more ANCIENT time, than that of Boyle and Newton, alchemists had made glass (a liquid) from sand (solid earth) using furnaces that alchemists had invented long before. And glass, since ancient times, has been a more practical product than GOLD. Which (gold), for a very long time, was only important because of its esthetic and economical (due to its rarity) values. And it seems that alchemists, Newton and Boyle, ignored the practical importance of the glass flasks, beakers, and thermometers of their time made with ‘furnaces’ invented nearly two thousand years earlier.
Have a good day, Jerry
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Jerry Krause
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Hi Andy,
Sorry, I double submitted. Because of MattH’s problem I have figured out what PSI has done to hopefully solve a problem,. I certainly appreciate your efforts.
Have a good day, Jerry
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Jerry Krause
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IN THE BEGINNING—PART 2 (Feynman’s Blunder and My Blunder)
Preface: I began this series of brief comments (with links to essays; which are not as brief), based upon the wisdom: “The most obvious is most difficult to see.” Hence, we humans have had made many mistakes. I will alway post the link to the previous comment to maintain a continuity (https://principia-scientific.com/interesting-analysis-of-uk-temperature-trends/#comment-75779 ) so an interested PSI Reader can track back to the beginning.
Comment: My blunder concerns Feynman’s blunder (https://principia-scientific.com/feynmans-blunder-part-1/) and (https://principia-scientific.com/?s=Feynman%27s+blunder). My blunder was that I did not go back to Feynman’s ORIGINAL blunder because I did not see it until I started this series of comments.
Feynman attempted to help his students to imagine how tiny, tiny atoms, or molecules, were by magnifying them many, many times. However, Feynman original blunder was that at the same time Feynman magnified the molecules he did not magnify the lecture room, or the students, or himself. There is no problem with his effort until he began to switch the students from water molecules in the drop of water molecules in the air of the lecture room. The air molecules of the lecture room had been magnified but the size of the lecture room had not.
THE FEYNMAN LECTURES ON PHYSICS Vol I was published in 1963 and I eventually purchased the three volume set of his lectures when it became available. For many years (decades) about the only things I really “understood” was “all things are made of atoms—little particles that move around in perpetual motion, attracting each other when they are a little distance apart, but repelling upon being squeezed into one another.” For I was a chemist and this was elementary chemistry which I had been taught and understood even in high school chemistry.
So, I question: Why did no Freshman physics student in Feynman’s class immediately correct him when he stated: “This picture of steam fails in one respect; at ordinary atmospheric pressure there might be only a few molecules in a whole room, and there certainly would not be as many many as three in this figure.”???
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Jerry Krause
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Hi Andy and PSI Readers,
I prepared this for (https://principia-scientific.com/another-botched-experiment-the-tricks-of-pseudoscience/) but I find someone has totally botched the format of that article.
IN THE BEGINNING—PART 3 (I Believe Feynman’s Knowledge Of Physics)
Preface: I began this series of brief comments (with links to essays; which are not as brief), based upon the wisdom: “The most obvious is most difficult to see.” Hence, we humans have had made many mistakes. I will alway post the link to the previous comment to maintain a continuity (https://principia-scientific.com/interesting-analysis-of-uk-temperature-trends/#comment-75787) so an interested PSI Reader can track back to the beginning.
Comment: In my last comment I was somewhat critical of Feynman when he taught about chemistry; so I want to make it clear that I totally respect his teaching of physics.
“Einstein assumed that Planck’s final formula was right, and he used that formula to obtain some new information, previously unknown, about the interaction of radiation with matter. His discussion went as follows: Consider any two of the many energy levels of an atom, say the mth level and the nth level (Fig. 42–2). Now Einstein proposed that when such an atom has light of the right frequency shining on it, it can absorb that photon of light and make a transition from state n to state m, and that the probability that this occurs per second depends upon the two levels, of course, but is proportional to how intense the light is that is shining on it. Let us call the proportionality constant Bnm, merely to remind us that this is not a universal constant of nature, but depends on the particular pair of levels: some levels are easy to excite; some levels are hard to excite. Now what is the formula going to be for the rate of emission from m to n? Einstein proposed that this must have two parts to it. First, even if there were no light present, there would be some chance that an atom in an excited state would fall to a lower state, emitting a photon; this we call spontaneous emission. It is analogous to the idea that an oscillator with a certain amount of energy, even in classical physics, does not keep that energy, but loses it by radiation. Thus the analog of spontaneous radiation of a classical system is that if the atom is in an excited state there is a certain probability Amn, which depends on the levels again, for it to go down from m to n, and this probability is independent of whether light is shining on the atom or not. But then Einstein went further, and by comparison with the classical theory and by other arguments, concluded that emission was also influenced by the presence of light—that when light of the right frequency is shining on an atom, it has an increased rate of emitting a photon that is proportional to the intensity of the light, with a proportionality constant Bmn. Later, if we deduce that this coefficient is zero, then we will have found that Einstein was wrong. Of course we will find he was right.
“Thus Einstein assumed that there are three kinds of processes: an absorption proportional to the intensity of light, an emission proportional to the intensity of light, called induced emission or sometimes stimulated emission, and a spontaneous emission independent of light.” (THE FEYNMAN LECTURES ON PHYSICS Vol I 42-5 ‘Einstein’s laws of radiation’)
I make this comment so a PSI reader can see how Feynman taught physics without going into great mathematical detail as he summarized a relatively long paragraph with four lines..
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Jerry Krause
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IN THE BEGINNING—PART 4 (Another of MY Blunders)
Preface: I began this series of brief comments (with links to essays; which are not as brief), based upon the wisdom: “The most obvious is most difficult to see.” Hence, we humans have had made many mistakes. I will alway post the link to the previous comment to maintain a continuity (https://principia-scientific.com/interesting-analysis-of-uk-temperature-trends/#comments) so an interested PSI Reader can track back to the beginning.
Comment: My blunder this time is I did start IN THE BEGINNING of Richard Feynman’s book THE MEANING OF IT ALL. So Chapter 1, FIRST SENTENCE: “I want to address myself directly to the impact of science on man’s ideas in other fields, a subject Mr. John Danz particularly wanted to be discussed. In the first of these lectures I will talk about the nature of science and emphasize particularly the existence of doubt and uncertainty.” I skip over his review of the next two lectures to the beginning of the first lecture.
“In talking about the impact of ideas in one field on ideas in another field, one is always apt to make a fool of oneself. In these days [1963] of specialization there are too few people who have such a deep understanding of two departments of our knowledge that they do not make fools of themselves in one or the other. And IN THE BEGINNING—PART 2 (Feynman’s Blunder and My Blunder),
Feynman and I illustrated how easy it is to make a fool of one’s self.
“The ideas I wish to describe are old ideas. There is practically nothing that I am going to say tonight that could not easily have been said by philosophers of the seventeenth century. Why reap all this? Because there are great ideas developed in the history of man, and these ideas do not last unless they are passed purposely and clearly from generation to generation.” Here Feynman gives the reason for my PSI essays and my PSI comments.
“Many old ideas have become such common knowledge that it is not necessary to talk about or explain them again. But the ideas associated with the problems of the development of science, as far as I can see by looking around me, are not of the kind that everyone appreciates. It is true that a large number of people do appreciate them. And in a university particularly most people appreciate them, and you may be the wrong audience for me.”
I try to keep these comments brief because they not only need to be read to be of any value; they also need to be read and pondered.
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