Guest Post by Willis Eschenbach
Buoyed by the equal parts of derision and acclaim for my previous post, “CEEMD vs Joe Fourier“, I thought I’d take a look at a place where we know there is a solar effect.
How do I know there’s a solar effect somewhere? Because I’m a ham radio operator. Here’s my license, my call sign is H44WE, “Hotel 44 Whisky Echo”.
I got my license in the Solomon Islands at age 41, part of my commitment to life-long learning … plus I was living on a very remote tropical island and that was one of my few means of communication …
And any ham will tell you that long-distance ham radio transmission is strongly affected by the sun’s activity. Solar energy affects the ionosphere, the layer of the atmosphere that reflects radio waves back to the earth. So we know that the sun affects the very top of the atmosphere … but what about the lower levels?
To investigate this question, I thought I’d take a look at the solar effects at different layers of the atmosphere. The UAH MSU satellite temperatures cover four different levels of the atmosphere.
Figure 1. Regions of the atmosphere covered by the UAH MSU satellite temperature measurements. T—Temperature. LS—Lower Stratosphere. TS—Tropopause. MT—Middle Troposphere. LT—Lower Troposphere.
I started at the highest altitude, the lower stratosphere data, because that’s where I expected to find the solar signal. And indeed, both CEEMD and Fourier analyses verify that the sun affects the temperature of the lower stratosphere.
Figure 2a. CEEMD empirical mode containing any cycles around 11 years, for both the SILSO sunspot data and the UAH MSU lower stratospheric temperature data. Sunspots are in yellow, MSU stratosphere in red.
Figure 2b. Fourier periodograms for both the SILSO sunspot data and the UAH MSU lower stratospheric temperature data.
As you can see, both the CEEMD and the Fourier data clearly establish a relationship between variations in solar activity and variations in the lower stratospheric temperature. Both show peaks at around six and 11 year cycles, and the CEEMD data shows the effect on temperature varies with the strength of the solar signal and that the temperature variations lag the solar variations.
From there, I moved to the next lower layer, the tropopause. This is the layer dividing the stratosphere from the troposphere.
Figure 3a. CEEMD empirical mode containing any cycles around 11 years, for both the SILSO sunspot data and the UAH MSU tropopause temperature data. Sunspots are in yellow, MSU tropopause in orange.
Figure 3b. Fourier periodograms for both the SILSO sunspot data and the UAH MSU tropopause temperature data.
Here at the tropopause, while we still see the temperature peaks in the Fourier periodogram at six and eleven year cycles, they are much smaller than up in the lower stratosphere. Plus there are more cycles, at three and four years. And the CEEMD analysis shows that temperature and solar activity are much more loosely related.
Now, there’s not much atmospheric exchange between the stratosphere and the troposphere. They experience different winds and weather. Here’s the same analysis as above, but this time for the middle troposphere.
Figure 4a. CEEMD empirical mode containing any cycles around 11 years, for both the SILSO sunspot data and the UAH MSU middle troposphere temperature data. Sunspots are in yellow, MSU middle troposphere in blue.
Figure 4b. Fourier periodograms for both the SILSO sunspot data and the UAH MSU middle troposphere temperature data.
Once we’ve crossed the tropopause and are in the troposphere, the solar signal is basically gone. The CEEMD analysis shows no relationship between the two, and the Fourier periodogram shows the strongest temperature peak at four years. There’s no signal at either the six or the eleven year periods.
Finally, here’s the lowest level of the UAH MSU data, the lower troposphere.
Figure 4a. CEEMD empirical mode containing any cycles around 11 years, for both the SILSO sunspot data and the UAH MSU lower troposphere temperature data. Sunspots are in yellow, MSU lower troposphere in cyan.
Figure 4b. Fourier periodograms for both the SILSO sunspot data and the UAH MSU middle troposphere temperature data.
Total disconnect. Here, there’s absolutely no relationship between the lower tropospheric temperature data and solar activity. There’s no sign that the variations in the sun are having any effect on the atmosphere near the surface.
CONCLUSIONS
First, this verifies that the two methods I’m using, CEEMD and Fourier analysis, are both able to reliably find a solar signal in climate data if one exists.
Second, this shows that the solar signal decreases as we move lower in the atmosphere, and by the time we reach the lowest level of the troposphere, the solar signal has disappeared entirely.
Further affiant sayeth not.
Best to everyone,
w.
This makes good sense, because as the sun’s energy gets closer to the surface of the earth, in particular the water on the surface and in the troposphere substantial energy exchanges occur without temperature change. In particular, the phase changes of water from ice to liquid to vapour, and vice-versa at different pressures and temperatures.
Science is not about making sense. The effect on the stratosphere is due only to the UV part of the solar electromagnetic spectrum on the ozone layer. That the UV part of the spectrum changes by 3% instead of 0.1% for the total solar irradiance during the solar cycle is one of those things that doesn’t need to make sense, it just is what it is.
Climate science is about scaring people about CO2
Or claiming CO2 does not matter
No compromise is allowed.
“We don’t know” is not allowed.
Fig 4a UAH TLT blue curve looks different from Spencer’s published inWUWT
Comment please
Alastair, I’ve never seen Dr. Roy publish any CEEMD curves, either on WUWT or elsewhere. Link?
w.
Sorry, I did not fully read the caption to Fig 4a and so did not realise that the temperature curve was CEEMD. Maybe you could publish the complete set of UAH Lower troposphere modes, and then just for comparison a straightforward bandpass filter of the raw data set
No worries. Here are the modes and the periodograms.
I don’t do “straightforward bandpass filters” because they force me to decide on the bands. The CEEMD is essentially an empirically selected bandpass filter based on the data itself, leaving my personal prejudices and beliefs out of the equation
My best to you and yours,
w.
Fascinating. Thanks for supplying the modes. As a former seismic interpreter, I recognise the maths , and the power of Fourier, and decomposition methods, although quite rusty now.
2 points of interest.
1) You show in your analysis a long term downward trend in stratospheric temperature which according to blackbody theory would imply a decrease in radiation from stratosphere to space from which the CO2 brigade would say is a consequence of increasing greenhouse gases.
2) This CEEMD business is a lot like principal component analysis which applied to tree rings led M E Mann and the world at large down a monstrous rabbit hole. Mann’s mistake as I see it was not being robust enough in the determination of his modes. Can you be sure that you are not dining on carrots and lettuce
Thanks, Alastair.
1) The decrease in stratospheric temperatures is an expected result from increased CO2 absorption of upwelling longwave radiation in the troposphere.
2) CEEMD is nothing like PCA. And Mann didn’t even understand how to use PCA. It was not PCA which led him down a rabbit hole. It was his total misunderstanding of PCA. He didn’t center the data before applying PCA, which leads to meaningless resorts.
Regards,
w.
So you think Mann just made an honest mistake?
He used a method he didn’t understand to achieve a result he wanted, and presented it as reasoned analysis. That doesn’t fall into the category of honest mistake in my book.
Obviously he worked just enough to get the answer he/they wanted. Mistakes weren’t any consideration.
Yeah, I think Michael Mann is crooked as a dog’s hindleg.
I didn’t get that impression from Willis, so I asked the question.
Willis,
Your analysis is very interesting and leads me to the conclusion that the troposphere (the mixing layer) of Earth’s atmosphere is dominated by mass motion energy transport and not by radiative opacity.
A similar conclusion can be drawn from our ongoing study of the troposphere of Mars.
A Short Note on the Comparison between the Tropospheres of Venus and Mars
It’s all about resonance. If a system is inherently stable then it will resonate in harmony with an external forcing. If a system is inherently unstable then it will not resonate in harmony with an external forcing. The troposphere is inherently unstable on multiple scales and so any resonance will be overwhelmed by the chaotic motion of atmospheric convection.
Philip,
Resonance requires wavelengths of magnitudes that can interact with each other. Strongest resonance is when both source and receiver are at same wavelength, next strongest with one at half wave. Is this matching present for your examples? Geoff S
Geoff,
I take your point. Willis has identified a signal in the ionosphere and tropopause that is not seen in the troposphere. My conjecture is that this is related in some way to stability.
Willis,
How about a color scale or other legend for the graphs?
Thanks, Clyde. I’ve added notes to the captions in each case.
w.
To what would you attribute the periodicity >3 years in the middle and lower troposphere temperatures?
I’d suspect that they are related to El Nino, or to the QBO, but those are just guesses.
w.
No disrespect intended, but that sounds like kicking the can down the road. I realize that no one has a good model for explaining the timing of El Nino, but it seems to me that ENSO must have a forcing that moves energy around. The biggest elephant in the room is the sun.
What we do know is that sun spots are a proxy for changes in the intensity and spectral composition of light reaching Earth, along with the occasional Coronal Mass Ejection adding energy to the atmosphere and perturbing the geomagnetic field.
Clyde Spencer:
“no one has a good model for explaining the timing of El Nino”
Try this on for size:
“The Definitive Cause of La Nina and El Nino Events”
https://doi.org/10.30574/wjarr.2023.17.1.0124
I tried it on for size. I couldn’t find any information about a) how you defined an El Nino, b) which El Nino index you used, and c) which temperature record you’re using.
And of course, that renders your paper less than useful because it is impossible to replicate.
Despite that, I did my best to replicate it. Here are the dates of the eruptions and the El Nino years.
Rather than just wave my hands at the data and declare the case “proven” as you did, I calculated the time elapsed between the nearest previous eruption and the subsequent El Nino. Here are the elapsed times from eruption to El Nino, in months.
34, 1, 60, 28, 2, 14, 14, 26, 10, 8, 44, 8, 10, 2, 12
Eight of these are more than a year from eruption to El Nino. Five are more than two years. Two are more than three years.
And this is supposed to “prove” that volcanoes cause El Ninos? Really?
w.
PS—Starting a somewhat vague climate science paper about El Ninos and eruptions by claiming that “it has been proven that all La Ninas and El Ninos are caused by the increase or decrease of reflective SO2 aerosols” is a scientific faux pas. Little is provable in science in general, and even less is provable in climate science. It makes you look like a braggart.
Willis:
Regarding how I defined an El Nino, and which El Nino index I used, this is covered in my first reference.
For temperature data, I used Hadcrut5, which has its faults, but is not as extreme as NASA/GISS
The elapsed times from the date of an eruption to its El Nino is also given in my Table 2. (which varies wildly from your listing). My times were determined by using Hadcrut5 data.
An eruption first produces a La Nina, due to the injection of SO2 aerosols into the stratosphere. These aerosols eventually settle out, then an El Nino can follow, because of the less polluted air, if there are no intervening eruptions, which will quench the El Nino.
And of course, an El Nino can also form without an eruption, due to idled factories, foundries, etc. during an American Business recession, causing decreased Industrial SO2 aerosol emissions. An El Nino can also form if there are extended periods between volcanic eruptions usually 7 years or more, giving time for ALL of their SO2 aerosols to settle out of the atmosphere.
And a couple have formed due massive reductions in SO2 aerosol levels due to global “Clean Air” efforts.
Rather than being a scientific fau pas, my abstract is 100% correct
Thanks, Burl, I’ll take a look when I have time.
I used the Smithsonian eruption dataset for volcanoes and the NOAA list of El Ninos to get my list of lag time …
More as time permits.
Regards,
w.
You are using the word “solar” and “sunspot” to mean the same thing. They are not the same thing.
To claim that there is little or no “solar” signal at surface level is outlandish nonsense. My solar panels show the effect every day.
I used “solar signal” to mean “the small variations in solar output related to sunspots”. Sorry for the confusion.
w.
The signal disappears, only the “DC” component reaches your panel?
Practically everyone knows what he means.
Thermal IR emitted from atmosphere below 10km depends almost exclusively on heat brought there by turbulent convection (mass flux). Conversely, thermal IR emitted from above 10km depends almost exclusively on SW absorption there. These are very different processes, with different heat transfer modes.
“Here, there’s absolutely no relationship between the lower tropospheric temperature data and solar activity.”
That’s because the LT significantly responds to the ocean with a 2 month lag:
While the ocean temperature significantly responds to 120 total years of solar activity:
Thanks, Bob. I took a look at the data. I can verify the two-month lag between SSTs and MSU TLT, R^2 = 0.60.
However, your method in the second instance, comparing a 30-year boxcar smooth with a cumulative sum of sunspots, suffers from several huge problems.
First, the cumulative sum (integral) of the sunspots depends on whatever you are using for a zero point. A different choice of zero point will give you a totally differently shaped curve. So you could fit it to almost anything.
Second, both data series are so heavily autocorrelated that the effective N in both cases is … one data point. N=1.
Which is why calculations using smoothed curves are very strongly discouraged. See the post from the professional statistician William Briggs entitled “Do Not Smooth Time Series, You Hockey Puck“, and more specifically his post Do NOT smooth time series before computing forecast skill.
Last, a “boxcar” filter such as you used is a horrible choice. It easily turns peaks into troughs and vice versa. Here’s an example:
Look for example at the period 1920 to 1930—the boxcar filter, the kind you used, has totally inverted the signal.
Regards,
w.
“I can verify the two-month lag between SSTs and MSU TLT, R^2 = 0.60.”
You have already messed up by not time-shifting TLT 2 months to get the correct R^2.
“Second, both data series are so heavily autocorrelated that the effective N in both cases is … one data point. N=1.”
N=1. Right, sure Willis.
“Last, a “boxcar” filter such as you used is a horrible choice. It easily turns peaks into troughs and vice versa. Here’s an example”
More unrelated gaslighting from the anti-solar activist Willis Eschenbach.
“Which is why calculations using smoothed curves are very strongly discouraged.”
At this point I realize you are nothing but a BS artist.
Bob Weber February 22, 2023 4:59 am
Just went back and checked my calculations. You’re correct, my error. Time-shifted R^2, 0.71. Mine doesn’t agree exactly with your value of 0.70, likely a slight difference in the data used.
Bob, if you disagree, please show your calculations. I’ve used the method of Koutsoyiannis for estimating effective N. What method are you using? What do you get for the effective N?
I gave you a clear example of the difficulty with boxcar filters. Ask any statistician, they’ll tell you they have very bad qualities, including “ringing”. There’s a good discussion of these issues here.
In any case, calling my words “gaslighting” is an evidence-free attack. Get back to the science. Point out where my graph is wrong. It clearly shows how a boxcar filter can turn troughs into peaks.
You truly don’t seem to understand how debate is done. Calling your opponent names in a scientific debate is a sure sign that you have no scientific arguments. I gave you not one but two posts from William Briggs, a professional statistician, showing exactly why using smoothed datasets in calculations of statistical significance is a grievous error.
In response, you have not shown that Briggs is incorrect in any way, shape, or form. In fact, you haven’t even tried. Instead, you think you win the debate by calling me a “BS artist”??? That’s your idea of how to show Briggs and I are wrong?
I put up a post a while back called “Agreeing to Disagree“. Here’s the graphic:
You’re down at the very bottom level, “Name Calling”. Let me encourage you to up your game by ascending the pyramid …
w.
“First, the cumulative sum (integral) of the sunspots depends on whatever you are using for a zero point. A different choice of zero point will give you a totally differently shaped curve. So you could fit it to almost anything.”
You can start the 109y SN average calculation at any month after I did and still recover the essential relationship up to the minimum N number of months for statistical significance, and doing so will not result in a totally different curve, just a shortened curve with the same but truncated shape.
You are wrong that I could “fit almost anything”. Your comments are off the mark.
I see I haven’t been clear. An integral is the area under a curve. This varies greatly depending on what the zero point is. Here’s the area under the sunspot curve, with the zero point being no sunspots.
As you can see, because the number of sunspots is always positive, the curve can never decrease in amplitude. However, your curve does decrease …
Next, here’s the exact same data, but with the zero point set to the mean of the data.
And finally, again the same data, but this time with the zero point set to 1.2 time the mean of the data.
As I said, integrals can be fit to most things by simply selecting the zero point.
Hope this clarifies things.
w.
Will you cult-of-personality worshippers please man up and state your complaints.
I think. Here again. I did some measuring myself. To see something of the heat coming through, you have to look at Tmax. TMax follows the GB cycle, a sine wave with a wavelength of 86.5 years, but that wavelength is variable, depending on the available centrifugal and gravitational power (from the planets, mostly) you could a miss a beat (DeVries?)
To understand Willis’s measurements – undoubtable he is a genius with maths – you must grasp that TSI can be constant, but the bottom line (x-scale) of wavelengths being let loose, may vary a bit. When the field strengths on the sun get lower, more of most energetic particles can escape. This causes more O3, NxOx and HxOx, being formed TOA. In its turn this causes that less UV can come through, which means less energy in the oceans. Actually, it is the UV (and < wavelengths) part that warms most of the oceans. It can bring the top layers easily to boiling point, forming clouds. Eventually, lower magnetic fields on the sun will therefore lead to a cooler atmosphere. But it is not the sun that gets ‘cooler’.
Learn to forget about spots. Look at the actual measurements of the solar polar magnetic field strengths.
Henry, for one the UV is such a small component of the spectrum, and the UV changes while larger than TSI changes as a percentage, are still small numbers compared to the rest of the spectrum that penetrates to depth:
I don’t buy your theory because tropospheric UV was very high (inversely related to ozone) over the tropics during the depths of the recent La Nina, but it wasn’t warming up. It is warming up now due to the increase in TSI according to my work.
Don’t you ever think I’d ever forget about sunspots and their relationship to TSI, and their long-term effect on climate change.
You have to look at the absorption spectrum of water. I think you cannot even warm a drop of water with normal white LED light. When I get the time I will check again, but I think water only has strong absorption in the UV and in de IR. While the IR heats deep, it cannot bring the top layers of the oceans to the evaporation point. Cloud formation is therefore strongly dependent on the amount of UV (A,B and C) and shorter wavelengths coming through.
You understand what I am saying? Where a molecule has absorption, there is obstruction. It cannot let that wavelength through so it starts radiating back. But now, in the water there is mass, so here this emission is eventually converted to heat.
Note very high absorption up to 180 nm. Then only in the near Infra Red absorption goes up again a bit. The big heat that causes skin burn, water evaporation and CO2 in the air is coming from the UV.
Surely, it must be possible to plot UV Index Today – National and Local UV Index Forecasts at a number of places against time?
If somebody can help us?
Ultraviolet index – Wikipedia
Eishhh. Semper idem. They always get stuck in spots here.
Willis, you didn’t perform any physics like I did that confirmed my results, see below. Oh and why don’t you whine some more about being called a BS artist. You have called us solar people “sun worshippers” for years so your name-calling complaints fall on deaf ears.
Who is it that cries out in pain while abusing someone else? You’ve abused us long enough.
I can no longer entertain your statistical claims about the sun-climate relationship, as I have demonstrated below using the Stefan-Boltzmann Equation that the climate as represented by the 30-year HadSST3 is predicted perfectly in the year 2010 using sunspot numbers and TSI.
The fact that I could perfectly predict the climate in 2010 with physics shows everyone physics trumps your concepts of what is statistically valid. I won’t trust your conclusions as a result.
Your auto-correlation method would “prove” the summer sun doesn’t cause summer weather.
The results of my investigation stand, the sun controls the climate, absolutely.
Bob Weber
This is exactly why I ask people to QUOTE MY EXACT WORDS. As far as I know, I have NEVER called anyone a “sun worshipper”, much less “for years”. That’s a damn lie.
Piss off. I have absolutely no interest in debating someone like you who is willing to lie about me. Falsus in uno, falsus in omnibus.
w.
Willis,
Any thoughts on the several year lead/lag in the lower stratosphere between the temperature and activity series?
The gas density way up there is rather low, inferring that it takes not much energy change to change temperature, compared to (say) lower troposphere.
I continue to think it is unrewarding to study correlations with sunspots, unless the study is to clarify their physics and mechanisms. Geoff S
Good question. It may be because the largest solar variation is in UV. This is absorbed in the UV layer, and due to the low density of the stratosphere, it may take a while for the energy to be mixed throughout the stratosphere.
But that’s just a guess …
w.
Cool!
What a disappointment this article must be to the “sun worshippers” here. I’m not one of them, but I was sure this 26th Willie E. article on sunspots was going to refute his first 25 sunspot articles, based on my Rule of 26. Which I am now revising to the Rule of 27.
Just wait, folks, and in Willie E’s 27th article on sunspots and climate, which I expect in a few days, the “sunspotters” will finally win. Right now they don’t get no respect. And I predict all 26 prior Willie E. sunspot articles, which is a world record for scientists named Willis, will all be retracted, with the excuse that “my dog ate the papers”.
Everyone knows sunspots must be important — that’s why people attempted to count them. And once there is a count, and then a revised count, some people are going to attack the numbers like a junkyard dog attacks your ankle. And after enough data mining and mathematical manipulation they will find something.
My own analysis, on another subject, found that eating potatoes leads to a life of crime, based on a survey of prisoners in Michigan’s Jackson Prison. That’s why I asked my Congressperson to sponsor a bill banning potato eating. Guns don’t cause crimes — potatoes do. That’s what we can all learn from science.
Once again a Willie E. article — this one — will be the first on my list of up to 24 read and recommended climate science and energy articles tomorrow, at Honest Climate Science and Energy
In my opinion Willie E. is a gold star author who has earned my trust, and. that is a short list. He also responds to the negative comments calmly, which is probably tougher than writing the articles !
This is a serious comment, not intended to be funny.
Now let the sunspot wars begin:
I’m making popcorn.
Worshipping has nothing to do with science. It is just the opposite of science. I thought you should know in case you are worshipping something. Accusing somebody of worshipping is accusing them of anti-science, something not to be taken lightly by a scientist.
It’s called humor, Javier
And most people (48.9%) will laugh
But not the sun worshippers
They get upset.
Which is it Richard?
“This is a serious comment, not intended to be funny.”
or ‘It’s called humor, Javier”
Are you sure it isn’t 48.931415296%?
Thanks, Richard. Humor is too often missing in discussions, especially scientific. It doesn’t degrade the conversation if done reasonably. Makes it better if done w/cleverness.
Still the wrong tool within the wrong paradigm.
Karin Labitzke demonstrated in 1987 in a paper cited 500 times that the temperature of the polar stratosphere during the winter was determined by the solar cycle and the quasi-biennial oscillation.
Labitzke, K., 1987. Sunspots, the QBO, and the stratospheric temperature in the north polar region. Geophysical Research Letters, 14(5), pp.535-537.
Research updated 20 years later
Labitzke, K., Kunze, M. and Brönnimann, S., 2006. Sunspots, the QBO and the stratosphere in the North Polar Region-20 years later. Meteorologische Zeitschrift, 15(3), pp.355-364.
A year after her first paper, Labitzke and Van Loon analyzed the dynamical effects on the atmosphere in a paper cited over 700 times.
Labitzke, K. and Van Loon, H., 1988. Associations between the 11-year solar cycle, the QBO and the atmosphere. Part I: the troposphere and stratosphere in the northern hemisphere in winter. Journal of Atmospheric and Terrestrial Physics, 50(3), pp.197-206.
I know you are not very good with solar stuff, so you might not know there is no sunlight in winter over the North Pole so the effect is not due to sunlight. The solar cycle induces dynamical changes in the atmosphere for which you are completely blind because you use the wrong tools within the wrong paradigm and you are bias-driven to not find an effect.
That ain’t science. Science is based on what others have discovered before. Does the phrase “dwarfs standing on the shoulders of giants” mean anything to you? If you don’t want to stand as a dwarf you have to study what the giants have discovered.
Javier Vinós February 21, 2023 11:28 pm
Let me get this straight. Both Labitzke and I found sunspot-related effects on stratospheric temperatures, and I’m wrong? How does that work?
Let me note that we have almost no information about stratospheric polar temperatures at an altitude of ~ 30 km (~100,000 feet). So instead, Labitzke used the output of a reanalysis climate model. It seems you actually think that is data. Bad news.
Yes, you are right—in modelworld lots of things happen. You seem to actually think that means they perforce happen in the real world. Bad news. Sometimes yes … but also, sometimes no.
Let me invite you to gently place your ugly insults as far up the distal end of your esophagus as your arms will reach. I’ve spent time in the Arctic in the winter. You are just making things up so you can stand on tiptoe to try to bite my ankles. Protip. It’s not working.
That’s a wonderful evidence-free accusation. You’ve already said that Labitzke and I agree that the stratosphere contains a clear solar signal. So what are you whining about? Since I agree with Labitzke, how could I be using the “wrong tools”?
Sorry, but giants I stand on the shoulders of use OBSERVATIONS, not the results of shoddy climate models.
w.
“Sorry, but giants I stand on the shoulders of use OBSERVATIONS, not the results of shoddy climate models.”
Surely most things scientific are by necessity models, which should be modified to match observations. What is wrong is that models are not modified to match observation, particularly in climate related topics.
At the end of the day the fusion reactor that is 93 million miles away must have an effect on all of the planets in the solar system, and any changes must be reflected in that effect, whether it’s changes in the EM spectrum or the magnetic fields. We see auroras on Earth, Jupiter and Saturn.
From my prior comment:
“In my opinion Willie E. … responds to the negative comments calmly, which is probably tougher than writing the articles!’
Revised version:
“In my opinion Willie E. … TRIES TO respond to the negative comments calmly, which is probably tougher than writing the articles!”
This is a Willie E. blowing his top classic:
“Let me invite you to gently place your ugly insults as far up the distal end of your esophagus as your arms will reach. I’ve spent time in the Arctic in the winter. You are just making things up so you can stand on tiptoe to try to bite my ankles. Protip. It’s not working.”
The Climate Howler Global Whiner’s have effective climate change propaganda, climate scaremongering, and confuser models, because they operate like the Star Trek Borg: Leaders with huge carbon footprints and useful idiot trained parrot followers. That’s politics, not science.
Real science is down and dirty.
The scientists:
— Skepticism is a primary attribute of a good scientist.
— Never start with a conclusion, like the IPCC did
— Never trust or defend the current consensus, like the IPCC does
— Observe the present and past without bias, rather than making wrong predictions of the future like the IPCC does
— Challenge the quality of your data, and analyze whether it is of sufficient quality to reach the conclusion
The “peer” reviewers should:
— Challenge the quality of the data, and whether it is of sufficient quality to reach the conclusion.
— Never trust long term predictions, which must be data free speculation because there are no data for the future. Humans have a terrible track record for predictions, yet climate science peer reviewers never seem to notice that fact.
— Never trust a scientist who has unreasonably high confidence in his work, never admits to potential weaknesses in his conclusions, or never admits “I don’t know that”.
— Challenge any conclusion that is not logical, even if you can’t prove it wrong right away — ask tough questions to see if the author
has answers, even if you don’t.
— Challenge other scientists and try prove them wrong with one or more exceptions to their hypothesis
Good comment. 🙂
Thanks I was trying to make three points with my comments, and to be funny too, which is always a challenge for me.
(1) Willis has written a large number of articles on the subject and maybe ought to move on to other subjects,
(2) It’s possible that Willis’s article #27 would have different results than the prior 26 articles, although I doubt it, and
(3) Somewhat unruly debate is NORMAL for real science.
Good scientists try to falsify the work of others.
How do you know that? is a key question often asked.
No position of authority, or popularity, gives a scientist free rein to make any claim.
It is the Star Trek Borg-like behaviors of the Climate Howler Global Whiners that is abnormal for real science.
But perfectly normal for leftist politics.
Nothing believed can be falsified.
Mainly because leftist climate beliefs are mainly predictions for far into the future.
How do you know that? questions are forbidden.
A scientist in a position of authority, or popularity, is automatically assumed to know just about everything.
Every time you speak you show your ignorance. Labitzke worked under prof. Richard Scherhag, the discoverer of stratospheric warmings, at the Freie Universität in Berlin. They used balloons to record polar stratospheric temperatures, and continued doing so until the program stopped in 2013 when she retired. The data (not reanalysis output) is archived at the Institute of Meteorology of the Freie Universität in Berlin.
https://www.geo.fu-berlin.de/en/met/ag/strat/produkte/northpole/index.html
Saying that you are ignorant on these issues is not an insult is a simple statement of fact. Seeing how you react gives little hope that you will stop being ignorant.
Javier, I know that balloons have been used to record polar stratospheric temperatures, as they’ve been used to record atmospheric temperatures all over the world.
The problem is that the world is a VERY big place. There are only a few stations putting up weather balloons in the Arctic: Svalbard, Bear Island, Danmarkshavn, Eureka Station, Jan Mayen, Luleå, and Sodankylä. They release two balloons per day, for a total of 14 balloons per day.
Now, the surface area above the Arctic Circle is ~ 62,000 sq. km. That means we have two measurements per day for each ~9,000 sq. km. But it’s worse than that, far worse. This is because the measurements are not spread evenly across the Arctic. They are only measuring a region within about 200 km of each station. And we have almost no balloon measurements over the entire Arctic Ocean, which covers about a quarter of the Arctic.
Now, it’s true as you say that the NCEP/NCAR Reanalysis model incorporates this balloon data as input to their model. It then outputs daily estimates of all variables every six hours on a 2.5° x 2.5° grid. For the Arctic, that’s 5,760 estimates per day.
So every day, the NCEP/NCAR reanalysis model is turning something on the order of 14 irregularly scattered observations of e.g. 30 hPa Arctic temperatures, with almost no observations over the entire central Arctic, into 5,760 daily estimates of the same variable covering the entire area.
That means that the actual observations are something on the order of 14 / 5,760 = 0.24% of the output, and the computer infills all the rest. Heck, even if there were four times as many balloon flights, actual observations are still less than 1% of the output.
Now, you’re free to pretend that something that is 99%+ computer output and <1% observations is “data”. And lots of folks do just that.
Me, I’m not that blind.
Finally, you say:
Sorry, but your opinion doesn’t qualify as “fact”. It’s just one man’s opinion, and a very opinionated man at that. And that opinion adds nothing to the scientific discussion except an ugly tone. Stick to the science, there’s a good fellow.
w.
What is archived at the Institute of Meteorology of the Freie Universität in Berlin is data, not model output, not reanalysis output. Data that was collected by careful German researchers since 1955.
You keep insisting on something you have no idea about. Not very scientific.
Well, since I never said that what is archived in the Universität wasn’t data, I must assume you are talking to someone other than me.
I was referring to this quote from the Labitzke paper, emphasis mine:
You keep trying to put words in my mouth. Not very scientific.
w.
Nice try but no cigar:
No, instead no. She used real data for her 1987 paper that you haven’t read. You are trying to dismiss her important finding based on your belief that it was model data. That is not true, and you are WRONG. As usual, if I may add.
Javier, as I said above:
I did NOT “dismiss” her findings. I pointed out that both she and I found a solar signal in the stratosphere. I say we were both right, but over and over you try to make me wrong and her right.
I’m gonna pass on further discussion of this. She found a stratospheric solar signal. I used a totally different dataset and a totally different method, and I also found a stratospheric solar signal.
So sue me.
w.
Ha, comparing your findings to hers says a lot about your ego. What you found was already known and not surprising. You didn’t discover anything. What she found was completely unknown and mind-boggling. She discovered the first evidence that solar variations affect climate well beyond their difference in energy.
Javier Vinós February 22, 2023 11:10 pm
It was “already known” that a CEEMD analysis of the UAH MSU measurements of the full record of lower stratosphere temperatures would show a solar signal, that the same analysis of the tropopause would show a lesser signal, that the mid-troposphere would show almost no signal and the lower troposphere would show absolutely no signal at all?
Really? Her study showed all of that?
I thought her study involved the upper stratosphere (30 hPa, ~100,000 feet of altitude), only in the winter, and only in one phase of the QBO … not one of which had any part in my analysis.
Funny, I’ve NEVER seen my findings anywhere. But hey, since you’re so sure I “didn’t discover anything”, I’m also sure you must have a link to a study showing my findings about the differences in the solar signal in the lower stratosphere, the tropopause, and the mid and lower troposphere.
I’ll wait for a link to said study … but of course, you’ll just change the subject and find something else to nag at me about.
As to my ego, perhaps you missed this in my previous post:
Was she the first to show a solar effect in the winter in the upper stratosphere during one phase of the QBO?
Yep. No question. And I give her huge props for that. And you have my thanks for pointing out her studies to me. I’d never seen them, they’re quite interesting. And I’m glad to see that her findings don’t contradict mine.
However, the winter, the upper stratosphere, and the phase of the QBO had NOTHING to do with my analysis.
Gotta say, Javier, I don’t understand what the point of your endless carping and criticism is. I know I didn’t piss in your morning oatmeal, so why are you so determined to stand on tiptoe in a failed attempt to gnaw at my ankles? What do you get out of it?
My research is what it is. I discovered what I discovered, which was not what she discovered—so why is what I did discover so triggering to you that you are wasting your time with your meaningless whining about what my analysis showed?
Surely you must have something better to do with your time, and your record shows that you can do it. So go write another paper with Andy May, write another book, do something that moves the conversation forward. Because I gotta tell you, your actions in this thread do not redound to your credit.
w.
The effect of solar-cycle-associated changes at every layer of the atmosphere and surface was worked out in the 1990s. You can check Judith Lean’s papers for information and citations.
You haven’t discovered anything new, I’m afraid.
Do you not understand the concept of “links”? I’m not going on a snipe hunt for you or any man. Provide links to Dr. Judith’s Lean’s “papers” detailing “solar-cycle-associated changes at every layer of the atmosphere and surface” or go away.
Be clear. I’m not saying they don’t exist. I’m saying that if you are claiming them as evidence to support your argument, it’s your job to link to them, not mine.
As to “discovering anything new”, I say again, that makes no difference to me.
w.
I suspect that the Chinese military may have some recent data from 100,000 feet. 🙂
Willis;
It appears that once you leave the stratosphere, there is an “anti correlation” in the remaining periodograms that starts at about 9 years and then shifts about 15 month or so going from the tropopause, then the middle troposphere and finally the lower troposphere. In fact, it looks like there is a train of 3 peaks making that march. Any thoughts on what might be happening, or am I reading the tea leaves too closely? Curiously, the peak at 4 years remains stationary across the three levels.
Thanks again Willis. With all the negative comments on your previous post, no one ever came up w/any plausible cause for a solar-cycle effect (yeah, UV, ozone, and all the others don’t as yet have any demonstrated effect). TSI varies slightly, but a watt or two difference isn’t going to make any detectable effect, it’s just not enough change.
It is too complex stuff to be dealt with in a comment or even an article. Try reading my book. It is very cheap, but if you don’t want to pay for it, you can still get it for free at my ResearchGate page.
Never said it wasn’t complex. But I still don’t see any plausible mechanism that UV which is almost entirely absorbed WAY up in the stratosphere (which is so thin that the total “heat” it contains is practically negligible) can affect surface weather. To say a slight change in stratospheric temperature affects surface weather is the tail wagging the dog.
Thermal IR emitted from within the troposphere at any given time is almost completely a consequence of fluid dynamic motions.
There is no chance to observe any specific SW signal using techniques discussed in the headpost.
Radiation enthusiasts somehow ignore that bulk transfer within the lower atmosphere is completely by turbulent flux (whorls of fluid motion). The solar signal is completely diffused in space and time.
Upward emitted power as LW IR from lower atmosphere has already undergone many material transformations beforehand, ranging in time from minutes to centuries and millennia.
The headpost highlights this change in heat transfer mechanisms below the tropopause quite well, I think. Solar effects are smeared into various timescales in the turbulent fluid mass of troposphere-oceanic reservoirs.
The mechanism was first proposed by a fantastic Canadian atmospheric physicist called Colin Hines in the 1970s. During winter, the stratosphere goes from radiatively controlled to dynamically controlled. The alterations in the dynamic state of the stratosphere introduced by changes in UV radiation and ozone amounts alter the propagation of planetary waves originating in the winter troposphere. The changes in planetary wave flux modify the energy and momentum delivered at the stratosphere. This is where the energy difference to alter climate comes from, not from the Sun. The energy delivered alters wind speed affecting vortex strength. Now, you should know that vortex strength changes have the capacity to affect atmospheric circulation and climate in the troposphere.
The problem is this stuff is too complicated for most people, so “it’s not the Sun” is the simple but wrong answer.
It is the Sun through a complex mechanism that involves the least well-known parts of the climate system. No wonder scientists could not crack it until Karin Labitzke showed up and elegantly solved it.
The other scientist to read is Joanna Haigh. She solved the role of ozone. Without ozone and without stratosphere, solar variabilities would not affect climate. This stuff is too complicated for the Watt counters at the top of the atmosphere.
Ditto
Good comment
Either the plant kingdom is to be ignored or their efficiency is highly under rated.
Figure 3a, four temperature peaks from 1980 to 2018.
Figure 4a, five temperature peaks from 1982 to 2017.
Exactly. Neither do the Fourrier plots match. The solar data has a clear peak just under 11y ( 10.8 ?) , the TLS data has a much broader peak with a maximum at around 13y. This may be two separate peaks which are poorly resolved because of the small number of cycles in the data.
Failing to see that periods are similar but not the same, is exactly the kind of criticism Willis makes in looking at the lower tropo data but manages not to see it here.
Also no mention of the cause of MOST of the variability in TLS which is the two massive stratospheric eruptions which unfortunately occurred roughly 10y apart and were close to solar maxima. Willis is very familiar with the effects of those events , so not mentioning it deliberate omission of significant information.
Good point about the eruptions, plus the lower strat’ has been flat since around 2007.
The middle troposphere shifts out of phase with sunspot cycles from the mid 1990’s, just like AMO anomalies did. That means changes in the solar wind strength are the key solar metric, and sunspot number is a red herring.
https://www.woodfortrees.org/graph/esrl-amo/from:1880/mean:13/plot/sidc-ssn/from:1880/normalise
climategrog February 23, 2023 1:01 am
I had the same thought, so before I wrote the post, I ran just the portion of the stratosphere data post eruptions. The results were basically the same.
Which you would have known if you’d had the decency to just ASK, instead of using what you didn’t know about as some kind of an excuse to accuse me of “deliberate omission of significant information”.
Perhaps you or your friends play those kinds of underhanded games. I don’t. Period. And you are a slimy scumball for making such a vile personal accusation without a scrap of evidence, based only on your unwillingness to ask about what you don’t understand.
Piss off. I don’t deal with people who do that. You’re on my blacklist. Go whine somewhere else. I’m done with you.
w.
climategrog:
Here’s the post-1994 (meaning after the “two massive stratospheric eruptions”) Fourier analysis of the stratospheric temperature.
As you can see, the solar signal is NOT due to the eruptions, and you can stuff your accusation that I “deliberately omitted” discussing them up where solar panels don’t work.
w.
It sure looks like sockpuppets are downvoting Willis and up voting the ankle nippers.
High sunspot activity leads to increases in UV as a proportion of TSI. UV is how the oceans gain most of their heat as short-wave radiation penetrates far deeper than the skim layer which absorbs LW radiation. Sunspot activity acts through ocean heat content, which has long and variable lags in the warming of the near-surface atmosphere.
Another very worthwhile Willis post. Note that the ozone layer, which peaks above the middle of the highest layer you studied, also warms the atmosphere. The ozone layer over my Central Texas site peaks around 20-25 km, which I measure using twilight photometry at the Chappuis absorption peak at 600 nm. Forrest M. Mims III
As I said, ozone correlates or anti-correlates with the solar polar field strengths.
Does somebody know how the field strengths are developing beyond the last date here: