Author Archives: Willis Eschenbach

A New Metric for Amplification

ABSTRACT: A new method is proposed for exploring the amplification of the atmosphere with respect to the surface. The method, which I call “temporal evolution”, is shown to reveal the change in amplification with time. In addition, the method shows which of the atmospheric datasets are similar and which are dissimilar. The method is used […]

Can’t See the Signal For the Trees

ABSTRACT: A new method is proposed for determining if a group of datasets contain a signal in common. The method, which I call Correlation Distribution Analysis (CDA), is shown to be able to detect common signals down to a signal:noise ratio of 1:10. In addition, the method reveals how much of the common signal is […]

When Good Proxies Go Bad

Many of the good folks who write the papers and keep the databases seem not to use their naked eyeballs. By that I mean, they seriously think that you can invent some new procedure, and then apply it across the board to transform a group of a thousand datasets without looking at each and every […]

Data Smoothing and Spurious Correlation

Allan Macrae has posted an interesting study at ICECAP. In the study he argues that the changes in temperature (tropospheric and surface) precede the changes in atmospheric CO2 by nine months. Thus, he says, CO2 cannot be the source of the changes in temperature, because it follows those changes. Being a curious and generally disbelieving […]

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