About 6 months ago I provided an update on the state of global temperature anomalies as well as the CO2 concentration in the atmosphere and I think it’s time to do another one. You’ll see that the Anthropogenic Global Warming (AGW) hypothesis, which states global temperatures will rise with increasing atmospheric CO2 concentration, falls apart by a simple graphing of the data.
As a reminder, here is how I obtain the data:
“I look at two  well respected data sets to obtain the global temperature anomalies: The University of Alabama Huntsville (UAH) and the Climate Research Unit (CRU). The atmospheric CO2 data is obtained from NOAA website but uses the data from Mauna Loa which has been measuring CO2 concentrations (ppm) in the atmosphere since 1958.”
The graph for atmospheric CO2 concentration, measured in parts per million (ppm), is shown below.
Here are the graphs of global temperature anomalies for CRU and UAH.
Now let’s graph those same two data sets but just include temperatures since 1998.
Looks pretty flat to me over the past 13+ years and this isn’t due to a reduction in atmospheric CO2 concentration which continues its steady march upwards.
At the risk of belaboring the point – If the AGW hypothesis is correct then we should be able to see a positive linear trend (correlation) when we graph atmospheric CO2 concentration on the x-axis and global temperature anomaly on the y-axis. The graph using the CRU data is shown below.
Something breaks down when atmospheric CO2 concentration hits around the 370 ppm point and we see that increased atmospheric CO2 concentration didn’t increase global temperatures.
So there is not much change in the graphs since the last time I posted them and in actuality, the temperature anomalies are on a downward trend for the last few years.
Couple this inconvenient data with the recent hacking activity of climate scientist Peter Gleick and the recent desperate and out-of-touch-with-reality headline; you can see that it is tough being an AGW cult leader trying to peddle your propaganda to the public.
That’s because the relationship isn’t linear, it’s logarithmic. Nice work.
In honor of Fearless Leader, whose never-ending efforts to return us to those halcyon days of yore (you know, before the Industrial Revolution), I penned this bit of doggerel:
Four years of Obama have us on pace
To power our lives with aquarium waste;
He’ll distill & refine the odiferous green
and mandate we use it in every machine;
With windmill and pond scum the future he’ll seize
And make a new nation dependent on breeze.
Bob, You are a lyrical genius!
CO2 is actually cooling the atmosphere as it displaces water vapor. The upper troposphere at about 400 mbar shows decreased humidity. We know the water vapor is much more of a GHG than CO2. The net result is cooling. Not warming. As CO2 increases, the greater the upper troposphere cooling. This is why during one of the ice ages the CO2 was 10x today’s. Chilled the he** out of the upper troposphere! CO2 does have a warming effect, but it’s way less than water vapor. Because of this decrease in upper Troposphere water vapor, I don’t think the total GHGs with water vapor included has increased in over 60 years.
Thanks for posting CptWayne! I think you are right and water vapor is indeed a larger GHG than CO2. I’ve written a little on this in another post (pasted below) but you bring up great points here.
Hi, CptWayne! Help me out here, please! Which Ice age had a CO2 reading 10X todays? None of the Vostok or Epica data sets I have access to has a value even close to what we have today.
Your displacement observation may be a factor in the 15 year disconnect between rising CO2 and flatline land surface temperatures. The ocean surface temps are still rising, but that lag is to be expected.
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Contact NASA and tell them of your revelation! Might as well fix their climate change algorithms while you are at it.
That is an excellent idea. I really wish they would.
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“Something breaks down when atmospheric CO2 concentration hits around the 370 ppm point”
Oh my, you don’t know how linear regression and Pearsons coeffocient of coorelation work. For that matter, science and statistical analysis The tail end is still within the expectation of variance. All that tail does is slightly lower the slope of the regression line.
Ypou might just as well have said, “All the dots aren’t perfectly lined up.”