L&S11′s “A 21st Century forecast suggests that climate may remain approximately steady until 2030-2040″ was originally (unlike the IPCC) an alternative scenario to the continuing quadratic trend in Scafetta10 taking in to account the last decades hiatus. That scenario is now consistent with the astrophysics prediction of a solar grand minimum except theirs includes the possibility of steady or cooler climate until further out to 2080.

Excelent article (bentham), very impressive and very convincing on background 60/20 year cycles. Amazing that the troposheric aerosols completely disappear.

On page 78/79 he breaks out the elements of his model being a 60 year cycle + a 20 year cycle + a long term natural linear trend of 0.2C per century + a linear trend post 1942 trend of 0.66C per century. It produces a remarkable good fit and each element is well justified from external observation. After removing the cycles the total post 1942 rate of warming he has at 0.86C per century but linear. The quadratic has become linear in this later work.

Worth noting though that the 0.66C per century he refers to as anthropogenic includes any heat island or measurement problems. He mentions that other sources calculated from 0.3C per century to all of it as attributable to measurement problems. Therefore he concludes that this is the top end of the possible range for actual anthrogenic warming.

Nicola Scafetta and Craig Loehle have since put out a paper based on Scafetta 2010. From WUWT:-

Loehle, C. and N. Scafetta. 2011. Climate Change Attribution Using Empirical Decomposition of Historical Time Series. Open Atmospheric Science Journal 5:74-86.

The study is available via free open access at http://benthamscience.com/open/toascj/articles/V005/74TOASCJ.htm (links to full paper and supplemental information, both PDF, follow at the end of this post)

http://wattsupwiththat.com/2011/07/25/loehle-and-scafetta-calculate-0-66%C2%B0ccentury-for-agw/

He was less than impressed. A sample:

“Looking at their figure showing global temperatures with the El Nino, volcanic and solar effects removed I must say that I don’t think their removal has been very good, as many of the features associated with El Nino and volcanic effects are still very obvious in the processed data. What’s more, these effects are large, tenths of a degree to many tenths of a degree, and I have no great confidence that inadequately removing them to reveal a tiny ‘natural’ trend of between 0.014 deg C and 0.018 deg C a year is a robust result.

Curiously, the authors’ analysis shows that in their adjusted data set 2009 and 2010 are the hottest years. 2010 was warmer (though not statistically significantly so) than some previous years because of an El Nino. Taking it away (and adding a linear trend) seems to have made it even warmer!”

I see where both series come from now and it is a good approach to what happenned over the last 100 years – well done.

The temptation would be to use these series for future predictions. While your CO2 polynomial would probably work well for quite a while I do not believe that was why Scarfetta developed his quadratic. I also doubt whether he would claim it as a useful tool for prediction of future temperature.

http://www.fel.duke.edu/~scafetta/pdf/scafetta-JSTP2.pdf

Might save you some time.

http://dl.dropbox.com/u/52688456/CO2%20vs%20GAT%20R2.xls

I’ve got a backup of the original in case changes to the Dropbox “R2″ version by collaborators means there’s several different versions of it. Not sure how this works yet.

The CO2 curve is my own best fit 4th order polynomial. I could have just plotted the raw data but the poly is as good a fit as you will get I think because it follows the Keeling curve almost perfectly and certainly good enough to make the comparison plus it makes for a good looking plot

Don’t worry about criticism – I invite it, it’s the sceptical way. BTW, you will probably have an easier time if you can get to the Workbook in Dropbox.

Sorry, I wasn’t being critical just wanted to know the background.

It looks like the CO2 curve is a best fit type quadratic. There is a lot of good data available to build such a curve and I presume it does not have built in bias. I am going to do some testing on it over the weekend.

However the temperature equation is a simple function of time squared ie parabolic. I can see no reason for the equation being other than linear. That series artificially builds in acceration in projected temperature with no obvious logic.