I thought I’d have a bit of fun today. As we all know, most of the climate alarm hinges on the correlation between CO2 and its effect on our global temps. One of the problems we have, is that there isn’t much in the way of historical CO2 measurements. Sure, we can go back to about 1959, but, given the recent whines about trend lines and the duration they cover, we don’t really have 60 years of information to do proper comparisons. Well, I’ve sort of fixed that for the moment. But first, let me lay down some back ground. As I’ve mentioned before, I see no reason to be excessively redundant. So, I use our friend Paul’s app when I can. (WoodForTrees) Looking at the CO2(Mauna) We see this……
There are two things I’d like to call to your attention. First, 1958.21 is as far back as the data goes. Secondly, we see a near linear increase. It is really exponential, but near linearly. So, to remedy the lack of data, I’m going to back-cast what our CO2 levels would be. As long as I keep it a short time period, say 14 years or so, I should be able to stay reasonably close. I’ll use the first 19 years of data, (from 1958-1980) to get a linear trend and back-cast from there. To make it easier, I’m only going to use annual data. (I see no reason to replicate the squigly line.) So, basically, I’ll be back-casting from this, using the trend line shown here.
Obviously, this won’t be perfect, but then without actual measurements, nothing else would be either. I suppose I could add 1 or 2 ppm to remain consistent with the near-linear-but-really-exponential-trend, but for our purposes, this won’t make any difference. For the anal people, just imagine really hard that the line really curves up 1 ppm at the end. So, using Excel’s “Forecast” function I get the values, (ppm) of
| 1957 | 1956 | 1955 | 1954 | 1953 | 1952 | 1951 | 1950 |
| 313.39 | 312.51 | 311.62 | 310.73 | 309.84 | 308.96 | 308.07 | 307.18 |
| 1949 | 1948 | 1947 | 1946 | 1945 | 1944 |
| 306.30 | 305.41 | 304.52 | 303.63 | 302.75 | 301.86 |
Everyone with me? Sadly, from here on, we’ll have to leave the WFT graphs and go to Excel’s. So, with my back casted yearly data, we get this…….
Ok, before any alarmist gets to screaming about how the graphs look different, it is because the base is different, thus rendering the scale different. I think this should be easier to show temps and their correlation with this view. Now, I could go through the time and effort to put the temps and the trends on this graph, but doing that is a bit of a pain. So, we’ll just pop back to the WFT’s graphs and trends. We’ve got 66 years worth of CO2 data. I’ll do the first 33 and then the next 33.
Go here to get started at WFT.
Now, what does this tell us about the CO2 theory? So, for 33 years, seeing a 40% increase in atmospheric CO2 from the magical 280 ppm, the temps generally and slightly decreased. And then for the next 33 years, we see a larger increase in the temps. But, this is counter intuitive. The closer to the baseline of CO2 the more it is suppose to increase the temps. This defies the logarithmic effect that is widely accepted.
I think it is past time for people to realize the “scientists” working on our climate don’t know what they are talking about. And it’s past time to scrap what we thought we knew about how CO2 effect our climate and start again. The theory continues to be falsified.
suyts space 
First a linear CO2 trend line is impossible…you only get that with math
How can they say that warming and cooling of the oceans effects CO2 levels…and we know the oceans have warmed and cooled…and get that straight line
and whatever happened to the +400 ppm levels that were measured in the 1800’s?
Right, I just put this up to show the posit that the current “CO2 driving the climate” theory is bunkum.
As to what happened to the +400 CO2 levels, obviously, we industrialized. 😀
What is “CO2 theory”?
Hmm, I was specifically referring to the posit that CO2 was driving our temps up. And that atmospheric CO2 correlates well with the temp increases we saw a few years ago. Perhaps, I could have worded it a bit differently……
How’s Smokey?
The pCO2 empirical effect on temperature fits very nicely with a 2XCO2 of about 0.6-0.7 C.
Basically use Butler & Johnston 1996 with the CET and goalseek the value of 2XCO2.
I only used 250 years of data because the best SCL dataset starts in 1755 and the Maunder stuffs things around before then.
Thanks Bruce, I’m not sure using only CET data would tell us enough, but I do appreciate the effort you put into your model. So, are you saying 33 years isn’t long enough to make the proper distinction?
I wouldn’t go back much further than 250 years, because current thought is that the 280ppm was fairly persistent, prior to industrializing. (Though, I have my doubts) You’d probably want to show how the ppm were lower than 280 ppm to achieve your 0.6-0.7 degree increase.
The equation for pCO2 is an exponential regression fit of the Mauna Loa data assuming 280 ppmv in preindustrial times.
I used CET because Butler & Johnston 1996 is for Armagh in Northern Ireland – arguably pretty close in climatic conditions and latitude. If you look at the other Flickr photostream graphs you will see the slopes for CET and HadCRUT v3 are similar when graphed vs previous solar cycle length.
Been a while since I last read B&J 1996 but I assume they used corrections for volcanoes etc. I haven’t done this – so the CET & HadCRUT graphs start after the volcanic eruptions of the Dalton period. The volcanic forcings used by climate scientists is in the other graph.
I’m not saying any length of time is necessary – all I was doing in this exercise was to see if the low sensitivity or high sensitivity hypothesis made the most sense. I had seen the B&J paper and thought recreating the CET (or not) using it would be an interesting way of checking this question out. Pretty clearly low sensitivity wins. My background includes lots of modelling of datasets, statistical and iterative, so this is the way that seemed appropriate to me. I’m a working scientist – my attitude is you should always go see what the data itself says if you can.
Just to expand a little on the pCO2 thing, what I did was regression fit to the log of the Mauna Loa dataset minus 280 ppmv then used the regression equation to give me calculated values of pCO2 for 1659-1950 before Mauna Loa dataset started. And yes you’re right – the equation takes about 200 years to go from 280 to 281 ppmv. : )
Ok, like I said, I like what you’ve done, but I’m a bit confused. Reading your graph, it seems to indicate a 0.6 ° C increase per doubling CO2. And your graph shows at least that increase in temps. Accepting the 280ppm per-industrial level, how did we achieve the > 0.6 increase without getting to 560ppm? Or am I reading the graph wrong?
Most of the variance is solar indirect warming. That’s what Butler & Johnston found with previous solar cycle length as the proxy for overall solar effect (presumably magnetic + UV + TSI). CO2 is just the icing on the cake quantitatively speaking. Picking 2000 as a random year & reading off the spreadsheet: CO2 is worth +0.24 C (since 1659), the Sun is worth +0.49 C and ocean oscillations are +0.13 C. The ocean cyclic component is based on the 64-odd year periodicity you see in ENSO, PDO, AMO and the HadCRUT data. Not many people like the cyclic stuff, but I’m an old fashioned empirical scientist type so I chucked it in to see what happens. It makes a big difference on short timeframes eg satellite era 1979-today, but less over long term. If you leave out the ocean cycle component it bumps up the calculated value for 2XCO2 to about 0.8 C. Which is still harmless.
Because of the time period if you use 2XCO2 of 0.7 instead of 0.6 C you only get a slight difference in the trend slope, I think 0.00004 C/yr. Excel R^2 equation on graphs only reports to 4 decimal places. The graph is from my first effort, I just threw in the 0.6 C/doubling number from Spencer & Braswell 2010 and that is the graph that came out. Doing a goalseek to calculate 2XCO2 it comes out 0.69 C/doubling. Nowhere near the IPCC’s 2.5-4.5 C range.
Suyts – you know all this stuff from umpteen solar posts etc on WUWT. I did this for my own conscience to ask the question is the IPCC right. Answer is they ain’t.
Yes, I do. And Bruce, I thank you for your patience. You’ve articulated your effort quite well. And now, if some warmista comes by to attack this effort, the refutation of the warmista will be self-evident.
Excellent work! Bruce, thanks again,
James
Bruce, I should also add, any time you wish to do something similar and present as a post, you’d be more than welcome to use this blog. Thanks again.
James – Thanks I’ve thought of doing one but really there are lots of loose ends that would need to be tied up, and I don’t wish climate science as a new career as I’m content doing chemistry. I hadn’t meant to put any of it on the web until a CAGW person asked me sarcastically:
Please explain why YOU expect the climate models to fit ALL OF THE DATA, when no climate scientists would expect such an incredible feat.
Secondly, please present your own models that describe the observed warming without taking into account greenhouse gas forcings.
Thirdly, don’t direct me to more blog-science crap.
So I stuck the graph on Flickr and did as he asked. Somehow I don’t think he was expecting that.
lol, no he probably wasn’t. Climate science…… where models aren’t expected to be correct, but used as gospel anyway……. you have to love it.
I will get back in touch with you as soon as I’m off 85+ hour work weeks…..
Good money – But it leaves no time for anything but breakfast, travel out to work, work, lunch, work, mid-watch break, work, supper, (plus laundry sometimes) and travel back to the motel.
K, just let me kow….
Good analysis – I like the logical extrapolation into the near-past of pre-CO2 data.
Care to address (debunk ?) the Arctic-Icecap-death-spiral next? I have some raw data of solar exposure up there, that, once combined with the actual Arctic Ocean’s geography compared to the solar exposure each day contradicts this CAGW exaggeration.
I need your help with the graphs to make it more clear.
Robert
I’d be happy to help, if I can.
Go to Climate4You 12 mo change of CO2 at
http://www.climate4you.com/
Greenhouse Gases
Why has the growth rate of atmospheric Co2 remained at 2 ppm/yr when CO2 emissions have grown from 25 to 33 over the same time period, about 35%? All the time temp has been FLAT!
http://www.desdemonadespair.net/2011/10/steep-increase-in-global-co2-emissions.html
CO2 surely must be the Houdini of Gases? (google and study that paper)
Then what’s really odd, temps as you have shown above were flat from 1943 to 1978 – 35 yrs while CO2 emissions were skyrocketing.
Obviously there are forces at work that are more powerful than CO2.
Absolutely. Mine was just a quick and easy. It’s clear CO2 doesn’t run anything.
What’s really interesting in the Houdini paper is that the IPCC theory says that the oceans absorb half of our emissions. But if they absorb half the emissions now, then they would have absorbed ALL the emissions in 1950, CO2 emissions have increased exponentially from 1500 MMT in 1950 to 7000 now, so the oceans couldn’t be absorbing 1/2 the emissions all that time. Something doesn’t fit. What doesn’t fit is the IPCC has no idea how much of human CO2 emissions are absorbed. Also, CO2 growth rate is very variable, it should be steady. It’s variable because the ocean temp cylces are likely playing a huge role in the constantly varying CO2 absorption and growth rate. This is all a big wacky theory, with more unknown than known.
Why has the growth rate of atmospheric Co2 remained at 2 ppm/yr when CO2 emissions have grown from 25 to 33 over the same time period, about 35%?
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That alone is the biggest elephant in the room for me……
The oceans have warmed and cooled, CO2 emissions have gone up and down…
….yet that little CO2 line is as steady as it can be