Guest essay by Johannes Herbst
There is a much discussed graph in the blogosphere from ‘Tamino’ (Grant Foster), which aims to prove that there is no delay or pause or decline in global warming.
He states: Twelve of sixteen were hotter than expected even according to the still-warming prediction, and all sixteen were above the no-warming prediction:
Let’s get a larger picture:
- We see the red HADCRUT4 graph, coming downwards a bit from 1960 to 1975, and inclining steeper beyond 2000, with a slight drop of about the last 10 years.
- We see a blue trend, rising at the alarming rate of 0.4°C within only one decade! This was the time when some scientists started to worry about global warming.
- We see the green trend, used by the blogger Tamino in the first graphic, rising less than 0.1°C per decade.
- Below we see the Sunspot Numbers, pulsing in a frequency of about 11 years. Comparing it with the red temperature graph, we see the same pattern of 11 years pulsing. It shows clear evidence that temperature is linked to the sunspot activity.
Tamino started his trend at high sun activity and it stopped at low activity. Therefore the weak increase during 18 years.
Which leads us to the question: How long should a time be for observing climate change? If we look at the sunspot activity and the clear pattern it produces in the temperature graph, the answer is: 11 years or a multiple of it.
Or we can measure from any point of:
·high sun activity to one of the following
·low sun activity to one of the following
·rising sun activity to one of the following
·declining sun activity to one of the following
to eliminate the pattern of sunspot numbers.
Let’s try it out:
The last point of observation of the trend is between 2003 and 2014, about 2008. But even here we can see the trend has changed.
We do not know about the future. An downward trend seems possible, but a sharp rise is predicted from some others, which would destroy our musings so far.
Just being curious: How would the graph look with satellite data? Let’s check RSS.
Really interesting. The top of both graph appears to be at 2003 or 2004. HADCRUT4 shows a 0.05°C decline, RSS a 0.1°C per decade.
A simple way for smoothing a curve
There is a more simple way for averaging patterns (like the influence of sunspots). I added a 132 months average (11 years). This means at every spot of the graph all neighboring data (5.5 years to the left and 5.5 years to the right) are averaged. This also means that the graph will stop 5.5 years from the beginning or the end. And voila, the curve is the same as with our method in the previous post to measure at the same slope of a pattern.
As I said before the top of the curve is about 2003, and our last point of observation of a 11 years pattern is 2008. From 2008 to 2003 is only 5 years. This downtrend, even averaged, is somehow too short for a long time forecast. But anyway, the sharp acceleration of the the 1975-2000 period has stopped and the warming even halted – for the moment.
Note: I gave the running average graph (pale lilac) an offset of 0.2°C to get it out of the mess of all the trend lines.
If Tamino would have smoothed the 11years sun influence of the temperature graph before plotting the trend like done here at WFT, his green trend would be would be the same incline like the blue 33 year trend:
Even smoother
Having learned how to double and triple smooth a curve, I tried it as well on this graph:
We learned from Judith Curry’s Blog that on the top of a single smoothed curve a trough appears. So the dent at 2004 seems to be the center of the 132 month’s smoothed wave. I double smoothed the curve and reached 2004 as well, now eliminating the dent.
Note: Each smoothing cuts away the end of the graph by half of the smoothing span. So with every smoothing the curve gets shorter. But even the not visible data are already included in the visible curve.
According to the data, after removing all the “noise” (especially the 11 year’s sun activity cycle) 2004 was the very top of the 60 years sine wave and we are progressing downwards now for 10 years.
If you are not aware about the 60 years cycle, I just have used HADCRUT4 and smoothed the 11 years sunspot activity, which influences the temperature in a significant way.
We can clearly see the tops and bottoms of the wave at about 1880, 1910, 1940, 1970, and 2000. If this pattern repeats, the we will have 20 more years going down – more or less steep. About ten years of the 30 year down slope are already gone.
One more pattern
There is also a double bump visible at the downward slopes of about 10/10 years up and down. By looking closer you will see a hunch of it even at the upward slope. If we are now at the beginning of the downward slope – which could last 30 years – we could experience these bumps as well.
Going back further
Unfortunately we have no global temperature records before 1850. But we have one from a single station in Germany. The Hohenpeissenberg in Bavaria, not influenced from ocean winds or towns.
http://commons.wikimedia.org/wiki/File:Temperaturreihe_Hoher_Pei%C3%9Fenberg.PNG
Sure, it’s only one single station, but the measurements were continuously with no pause, and we can get somehow an idea by looking at the whole picture. Not in terms of 100% perfection, but just seeing the trends. The global climate surely had it’s influence here as well.
What we see is a short upward trend of about ten years, a downward slope of 100 years of about 1°C, an upward trend for another 100 years, and about 10 years going slightly down. Looks like an about 200 years wave. We can’t see far at both sides of the curve, but if this Pattern is repeating, this would only mean: We are now on the downward slope. Possibly for the next hundred years, if there is nothing additional at work.
The article of Greg Goodman about mean smoothers can be read here:
Data corruption by running mean ‘smoothers’
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Johannes Herbst writes at: http://klimawandler.blogspot.de/
By the way, the equipment I used to create the tone pips used in my research gated and filtered the high frequency signal coming from the signal generator to create a narrow high frequency set of tones set at a sudden onset and a certain dB level used to evoke auditory brainstem potentials. So I know how to find the signal I want. My dear Bart, puuulllease!!!!
Or should that be Bartie. LOLOL!
Bart says:
February 10, 2014 at 9:10 am
Bart, I always get nervous when someone starts using electronics as an analogue for the climate world. Why?
Well, because we can do scads of things in electronics that have no corresponding real-world counterpart. For example, we can make materials with negative refraction indexes that are invisible to microwaves … something which to my knowledge doesn’t exist in nature.
In addition, electromagnetic waves are not like heat waves, in that electromagnetic waves have an inherent frequency which they generally maintain through thick and thin. As a result, we can pick them apart and find the tail of the elephant … perhaps you could point to the frequency of a given heat wave, and how we can use that frequency to distinguish it from some other heat wave?
Heck, we don’t even need mathematics to separate out the different electromagnetic frequencies. We can use something as simple as a prism to divide the electromagnetic waves of different frequencies … perhaps, since this is your analogy, you can point us to the “climate prism” that will allow us to separate heat waves by their inherent frequency …
But wait, there’s more. In the electromagnetic world, we rarely have to deal with turbulence. You can mix dozens of light signals in a single fiber, and separate them back out again at the other end with near 100% fidelity … try that using pressure waves in a pipe, however, and the turbulence will defeat you every time.
But wait, there’s more yet. In electronics, we rarely have to deal with emergent phenomena, where in the climate they are the rule rather than the exception … and emergent phenomena are famously hard to model or even understand. Heck, despite our deep understanding of electricity in the laboratory, we still don’t have a complete theory of how lightning is generated.
But wait, there’s even more. Climate is generally held to be a chaotic system, one which is highly sensitive to initial conditions … and in general electronics is the opposite.
Let me summarize. In electronics, there is:
• very little turbulence
• very little chaos
• very few emergent phenomena, and
• every player is conveniently tagged and can be separated out by its inherent unchanging frequency.
In climate, not one of these things are true … and as a result, while in electronics we can “find the elephant” as you point out, this means NOTHING about the corresponding problem of attribution in climate.
And that’s why I get nervous when people say something like identifying the elephant is so dang simple that we do on an “everyday basis” in electronics … so what? When you can point me to the “climate prism” that works on climate like a prism works on electromagnetic waves, you might have something to discuss.
But until then, all you have is a false and misleading parallel.
w.
And then I had to filter the noisily huge cortical chaotic brainwaves to find just the tiny evoked auditory brainstem potentials coming from the 1st synaptic junction through to the 6th along the auditory nerve. So again, terrible analogy posted to the wrong thread. ROTFLMAO!!! So this sweetie does indeed know what she is talking about. Bartie.
@Pamela
the first position I looked at was a station in somewhere in the Alps. Leif gave me the data. It had good data going back to the beginning of the century. I did some some best fitting (with a polynomial) and saw a clear bending point (downwards) in 1951 and another one (upwards) in 1995. Here, the difference between the low (1995) and high (1995) was about 10%
the second position was a graph I looked at from the the SS (the baddies) relating to a place in the southern SH. It only had data from the beginning of the eighties, but there was an unmistaken trend upwards since 1995. The ozone was very low here, so the increase of the past two decades represented almost 50-100%!!
clearly the composition TOA differs, hence the differnce between my own first (global) graph and the second one below it (Alaska), here,
http://blogs.24.com/henryp/2012/10/02/best-sine-wave-fit-for-the-drop-in-global-maximum-temperatures/
sadly, we have no measurements on peroxides and nitric oxides TOA. I think this is where Trenberth’s missing energy is hiding. He never considered the peroxides and the nitric oxides.
I, OTOH, think that the peroxides are dominating the SH (above the oceans) and thatb is why the ozone is less here. There never was a “hole” other than the natural holes that God put up in the sky. It is worthwhile noting though that without the ozone and the peroxides and the nitric oxides we’d all be dead.
.
sorry
Here, the difference between the low (1995) and high (1995) was about 10%
should be
Here, the difference between the low (1995) and high (1951) was about 10%
W you bring up an important point. Synaptic brain potentials are similarly tagged. We know about how long it takes an electronic signal to travel between synapses along a known nerve. Our filters can be set to these parameters and presto! We find the particular regularly evoked synaptic signal we are looking for embedded in the chaotic and much larger background noise. Thanks for tickling my brain about tagging.
Bart says:
February 10, 2014 at 9:50 am
If it is Watts, it is power. Plain and simple. Energy is Joules. Power is Joules/sec = Watts. Do I really have to explain this to you?
You have to learn [and perhaps explain to Greg] that the term in common usage in atmospheric physics is ‘energy input’ and not ‘power’. I gave you a couple of links. Did you consult them? Prove that you did, e.g. by providing the page number where the phrase ‘energy input’ occurs.
So HenryP, based on your logic, Atmospheric CO2 increase is HUGE and therefore should have a devastating, measurable affect on global temperature! Which means you believe in AGW based on the increase in CO2.
Logic. She’s a bi*ch but she’s my bi*ch.
My gosh. I have outdone myself. If solar enthusiasts are considering tiny increases in solar parameters as having been the driving source behind the warming trend, they will not be able to reject their null hypothesis (it being CO2 as the source). I wonder if they know why?
Could this be the reason why you no longer hear much from them about the solar-driven warming trend? The conversation has subtly changed to reasons for the pause. Since CO2 continues to climb they are in safer territory. As long as they ignore the HUGE monster blowing wind up their skirts. And it is pretty darned easy to show that CO2 does not create atmospheric pressure. So no wonder the solar cacophony has gotten louder.
Pamela Gray says:
February 10, 2014 at 9:53 am
You are proving my point. You need specialized equipment and analysis techniques to find the signals of interest.
Yes, it is straightforward to do when you know what you are looking for. What are we looking for here? We are looking for an input driving the transmission from input power to stored energy, and resulting in long term variability of the mean surface temperature. Do you know what that transmission function is? How well has the input been characterized? Answers: No. Not very well.
Bart says:
February 10, 2014 at 9:26 am
Yes, it is true that cos(a) + cos(b) is equal to 2 cos((a+b)/2) cos((a-b)/2). We’re in agreement on that question. However, that is a mathematical relationship, not an analysis of how interference patterns, aka “beat frequencies”, are generated.
However, there is a deeper problem with relating your equation to Greg’s claims. In your equation, 8.55 and 9.3 are the frequencies of the waveforms, typically in cycles per second or cycles per year.
Greg’s claim, on the other hand, involves two waves with periods of 8.55 and 9.3, which in this case are measured in years per cycle.
I know that your 8.55 and 9.3 are frequencies, because if your numbers 8.55 and 9.3 were periods (say years per cycle) then multiplying them by t (time) gives us units of years2/cycle … no bueno. So they are frequencies.
You see why I asked Greg above what he meant by “cos(9)” and “cos(10)”? It was for this very reason, to clarify the discussion … which is why I quit interacting with Greg when he replied with an insult instead of answering a simple request.
w.
PS—The frequency of the “beat” or interference pattern of two waves of frequency F1 and F2 is given by abs(F1 – F2), the absolute value of the difference of the frequencies. This fact was utilized in early “heterodyne” and “superheterodyne” radio receivers, heterodyne being a fancy word for beat frequency.
Rather than tune the radio to receive different frequencies, which is inefficient, the radio was tuned to give great fidelity at one frequency. Then the incoming signal was mixed (beat) against an oscillator which was adjusted so that the beat frequency, F2 – F1, was the frequency for which the radio was perfectly tuned … neat trick in my opinion.
Now, Greg is working with periods, not frequencies. To get the period of the beat frequency from the periods of the underlying waves is a matter of simple math. The frequency of the beat is the difference in frequencies of the underlying waves, or
Fb = F1 – F2
where Fb is the beat frequency, and F1 and F2 are the frequencies of the signals being added.
Using the relationship that F = 1/P, which is to say that the frequency is equal to one divided by the period (and vice versa), this can be written as:
Fb = 1/P1 – 1/P2
Putting the right side on a common denominator, we get
Fb = P2 / (P1 * P2) – P1 / (P1 * P2)
which simplifies to
Fb = ( P2 – P1) / (P1 * P2)
Inverting both sides, we get:
1/Fb = (P1 * P2) / ( P2 – P1)
But since the beat period is one over the beat frequency, that is to say
1/Fp = Pb
this gives us the period of the beat frequency. In planetary terms, this is called the “synoptic period”.
Note, however, that there is nothing in all of that to support Greg’s claim about how you get a beat frequency which has the average period of the two underlying periods … as far as I know, that doesn’t happen when you mix two signals.
Willis Eschenbach says:
February 10, 2014 at 9:56 am
“I always get nervous when someone starts using electronics as an analogue for the climate world. Why?
Well, because we can do scads of things in electronics that have no corresponding real-world counterpart. For example, we can make materials with negative refraction indexes that are invisible to microwaves … something which to my knowledge doesn’t exist in nature.”
I also get slightly nervous, but in the opposite direction. When people say you cannot use techniques from radio, audio, mechanical, etc. in Climate.
Power is power and loads are loads.
Input from the source, Solar, will ‘match’ into a complex load such as the Earth with a constantly varying acceptance ratio TOA down to surface with absorption and reflection along the way.
You could probably model the world quite well with a rotating globe of semi-absorbent, semi- reflective material in a micro-wave oven illuminated from one side and sitting in a vacuum.
Pure Mech Eng with some radio stuff thrown in.
And subject to all the known stuff used in those disciplines all the time.
So please don’t be so quick to cast off things from other disciplines. They have their place if properly used.
Bart says:
February 10, 2014 at 10:39 am
We are looking for an input driving the transmission from input power to stored energy, and resulting in long term variability of the mean surface temperature.
We are looking for how the energy input drives temperature. The empirically determined lag is only one month, so the ‘long-term’ variation should follow the variation of the energy input [e.g. as measure by TSI]. And it does not.
Pamela Gray says:
February 10, 2014 at 10:01 am
“And then I had to filter….”
Filter? FILTER! We don’t allow filters longer than a year in Climate work. They show all the wrong sort of things 🙂
http://i29.photobucket.com/albums/c274/richardlinsleyhood/Extendedtempseries-secondpass_zps089e4c7d.gif
Bart, the first step in the scientific process is observation. You then conduct various and repeated experiments to uncover the mechanics of the observation. You seem to be saying that you are still looking for an observation. If you cannot observe something correlating between a tiny solar and the temperature trend change AND that has a plausible mechanistic connection, you must acquit. IE Solar parameters are not responsible for the warming or cooling trend.
I am no fan of AGW, but at least CO2 enthusiasts observed a barely similar, but similar nonetheless, trend between warming and CO2 increase in the past. And they have observed a mechanism under lab and mathematical conditions that CO2 does indeed serve as a greenhouse gas, and can and does re-radiate LW infrared light in all directions, including towards a temperature sensor. Your solar parameter, choose one, does not have such a similarity with temperature trends nor does it have a plausible mechanism.
So indeed, using classical scientific inquiry, you must acquit.
lsvalgaard says:
February 10, 2014 at 10:44 am
“We are looking for how the energy input drives temperature. The empirically determined lag is only one month, so the ‘long-term’ variation should follow the variation of the energy input [e.g. as measure by TSI]. And it does not.”
Assuming we know accurately what the instantaneous acceptance/reflection ratio is and the storage constant times for any re-release, certainly.
RichardLH says:
February 10, 2014 at 10:52 am
Assuming we know accurately what the instantaneous acceptance/reflection ratio is and the storage constant times for any re-release, certainly.
There is good evidence that solar activity [measured by variation of the energy input, TSI] causes a 0.1 degree solar cycle variation of temperature. A similar number can be calculated from first principles, so it seems that the mechanism is reasonably well understood.
Richard, the same is true for brainwaves. Too many filters and you can find all kinds of things, including a correlation to the rising of the sun which is clearly caused by me waking up at 5:00 AM day in and day out.
Pamela Gray says:
February 10, 2014 at 10:58 am
the rising of the sun which is clearly caused by me waking up at 5:00 AM day in and day out.
Perhaps you waking up causes the Sun to rise 🙂
RichardLH needs to measure clouds. Quick!!!! Before they change!!!!!!…..hmmmmmm
Pamela Gray says:
February 10, 2014 at 10:58 am
“Richard, the same is true for brainwaves.”
Simple broadband low pass filters are what connect most people (or some anyway) to the Internet.
15 years is hardly a great stretch from decadal and ‘Gaussian’ is so much better than SSM (sub-sampled single mean) but…..
Pamela Gray says:
February 10, 2014 at 11:01 am
“RichardLH needs to measure clouds. Quick!!!! Before they change!!!!!!…..hmmmmmm”
The data and summaries of the data. Nothing more 🙂
lsvalgaard says:
February 10, 2014 at 10:56 am
“There is good evidence that solar activity [measured by variation of the energy input, TSI] causes a 0.1 degree solar cycle variation of temperature. A similar number can be calculated from first principles, so it seems that the mechanism is reasonably well understood.”
There is good evidence that we cannot model clouds very well which are a large part of the ‘instantaneous acceptance/reflection ratio ‘ so all is not that simple.
Climate Scientist: I want a tool to examine Climate Temperatures.
Geek: How do you define Climate?
Climate Scientist: Longer than 30 years.
Geek: So you want a tool that will show how the planet’s temperature responds in periods of more than 30 years?
Climate Scientist: Yes.
Geek: Well basic theory says that a Low Pass filter with a corner frequency of 15 years will do exactly what you want.
Climate Scientist: But that’s not complicated enough and anyway that does not show me what I like to see. It says that there are natural oscillations in the signal and my theory says they don’t exist.
Geek: ??????????