” . . . discretely sampled continuous signals are subject to arbitrary choices of sampling interval that can introduce aliasing and other artifacts in the time series.”

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sky,

I appreciate your dialog.

The GST time series of widespread use from GISS and HadCRU span the periods of 1881 to present and 1850 to present, respectively. The sampling frequency is fixed and historical. Given that, there is no arbitrary sampling frequency. It is a given. Therefore I find your point confusing. I also note the time period covered by the data is not insignificant.

Now, again, this is actual empirical data from a physical system (our climate). The increasing collaboration and interest of professional statisticians in the data has shown that there have been/are significant statistical misapplications/errors in major climate research papers and in IPCC analysis. So, continued focus on the question of whether that data contain certain statistical properties (such as unit roots) will likely persist. Likewise, verifying correct inference statistically is now highly visible in the scientific community.

So, what model best describes the DGP imbedded in the data? That is now an interesting thrust of climate research.

We now have the luxury of a growing set of independent professional statisticians performing audits of past climate research. That is a wonderful development.

John]]>