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Rahmstorf et al. 2007 Update

Filed under: Uncategorized, Climate Change, Rahmstorf — admin @ 7:14 am

Well it is almost 24 hours since I posted the comment below to RealClimate at the post by Stefan Rahmstorf, about the inconsistency in the methodology used in their Science Brevia article to show that climate is trending higher than IPCC models. As yet the post has not appeared. I can’t see how it breeches their moderation policy, so I guess I am being told to go pound sand.

Update: Stefan Rahmstorf replied at the post here.

To provide a bit more clarity, I have drawn a couple of lines on the figure at issue to illustrate possible trajectories of the trend. The thin red line is where I think the trend should have gone if the method described in the figure caption had been used — SSA+MRC. The thin blue line is where I think the trend line should have gone if SSA only had been used.

Slide1.png

Figure: Annotated Rahmstorf et al. 2007 Science Brevia figure showing global temperatures and trend line. SSA is where the trend line should be for SSA method only, SSA+MRC is the trend line for SSA with the ‘minimum roughness criterion’ applied. The published trend line passes between these possible outcomes.

The actual trend on the figure passes between these two obvious choices. So at this stage I don’t know what method was used. It seems clear that if they had used the method SSA+’maximum roughness criterion’ as described, the trend line would not have supported their argument that ‘temperatures may be responding more quickly to climate change than our current generation of models indicates’.

Below is my post to RealClimate.org:

Stefan

I would be grateful if you would clarify for me a puzzling aspect of your Rahmstorf et al. ‘07 Science paper. You state in the figure caption that the ‘minimum roughness criterion’ was used to get the temperature trend line. Use of this method of data padding as described by Mann 2004 should ‘pin’ the trend line to the 2006 temperature value. However, while the 2006 value lies in the center of the IPCC range, the trend line shown on the figure lies above the 2006 value, in the upper IPCC range.

I would like to clarify this apparent inconsistency. This an important paper for the case that ‘the climate system is responding more quickly than climate models indicate’ and it is important to verify its technical correctness. More details and graphs can be found here:

http://landshape.org/enm/rahmstorf-et-al-2007-ipcc-error/

1 Comment »

  1. […] To show this I looked at three different methods with slightly varying end points. Two are causal smoothers (SSA and spline) and one is an acausal (moving average). Causal smoothers do not use future data to create a trend to the end point of the series. Acausal smoothers (such as moving averages) need past and future data, and so stop half a window short of the endpoint (see wiki) All data are global temperature data from GISS from 1973 to 2006. 1. Singular Spectrum Analysis. Below is the figure of the result of two approaches to CaterpillerSSA, with 11 year embedding period. The red curve resulted from padding the end with data reflected around the final 2006 value, the so-called ‘minimum roughness condition’. The blue one is without padding. The two different approaches differ throughout the whole length, except where the two curves meet at year 1999. The last seven points deviate quite a lot, illustrating uncertainty at the end. 2. Smooth spline The figure below is a smooth spline method of fitting and another approach to estimating uncertainty. This fits a higher order non-linear regression line to the points, with 11 degrees of freedom. In this graph, the last point 2006 has been altered to either the top or bottom of the 95% channel range. That is, the last point covers the range of random variation that might reasonably be expected. The two curves differ again, but this time they flex about the 11th point from the end. Further discussion of this method here. 3. Moving average The final figure below shows the result of running a moving average with an end point at 2006 of 0.6 and 0.3. The moving average stops 5 points short of the end of the series, and the last point varies as a result of the variation at 2006. […]

    Pingback by Niche Modeling » Examples of simple smoothers — April 17, 2008 @ 6:31 pm

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