Marcott – Proxy errors and conclusions

There has been a lot of discussion (see here) about the treatment of errors by  Marcott et al. through  their  Monte Carlo analysis. Since I  avoided any interpolation or Monte Carlo by using only the measured values for each proxy, the error analysis for my reconstruction is straightforward. I have calculated the standard deviations, the error on the normal  and the anomaly error for each proxy between 5000 and 4500  years BP.  The results are given here.

The typical statistical error for a 100 year bin  for a single anomaly measurement is 0.6. The statistical error on the  overall global mean can be  derived from sigma(mean) = sigma/srqt(n) where n is the number of proxy contributing to  the bin.  This numbers contributing to each bin are shown here.

Figure 1 shows the data with a 90% confidence level shading based on a 2 sigma error. The smooth curve is an FFT filter smoothing. Figure 2 shows the same result overlaid with the published graph in Science.

Global averaged temperature  anomaly of 73 proxies with 100 year binning. Show in Yello is the 2 sigma 90% confidence level.

Fig 1: Global averaged temperature anomalies of 73 proxies with 100 year binning and redated. Shown in Yellow is the 2 sigma 90% confidence level.

Fig2; Comparison with published Marcott et al. based on Monte-Carlo derived errors.

Fig2; Comparison with published Marcott et al. based on Monte-Carlo derived errors.

Conclusions

The statistical errors are about 50% larger than those derived by  Marcott’s Monte Carlo analysis. However, there is  good agreement between the two approaches for  the long term trend. The previous post demonstrated that the data are insensitive to any rapid temperature variations of duration less than ~400 years.  For this reason alone there is also no evidence in the data for a 20th century uptick. A perfect renormalisation of anomalies from 5500-4500 YBP to 1961-1990 is also needed to splice on the instrument data.

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