Why does your graph looks so different to the official graph provided by the REMSS website for their V3.3 TLT data (theirs shows a clear warming trend)? http://images.remss.com/papers/other...sion_Notes.pdf (Page 3).
I would be interested to know how RSS fit their model (which doesn't seem to be in the document, pity.)... I doubt that a simple LS linear regression is the best approach -- given it's a time series (non-independence of points), and it's also got clear periodic effects...
Clementine Grace (07-04-2014)
Well -- I am referring to the statistical model (LS) you are applying to the data to determine the warming (or in your case, no) trend. I must admit, there are probably way more complicated ways of statistically modelling global warming in the current peer-reviewed literature, but with time-series you usually use an auto-regressive model. Just as a disclaimer, I know *some* stats for my work, but I am not a card-carrying statistician nor am I a climate scientist...
This lecture has alot of info on how to analyse time-series (in R though, you look like your using Excel..?), and even has that Moa series as an example.
You may be interested in Nicola Scafetta's harmonic model. It is going much better than the IPCC's models. His paper is here:
A key graph:
But a linear model assumes that the error-terms are iid (independent and identically distributed) -- which it is clearly not the case in your data. You violate the model assumptions by fitting a basic LSLR.
I appreciate the link to the paper -- but it's not really from a peer-reviewed journal is it? (I had a quick look at what SPPI was...). I also read that the author declines to make his software available to the public which is always a good sign *cough*. Anyhow -- let's just say my argument is with your use of statistics... I don't really care enough to read up on either side of this argument...
Last edited by goshawk; 09-04-2014 at 13:13.
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