IIUC, if observations are multivariate normal (with possibly some additional hypotheses)-- which is consistent with many proposed
stationary stochastic processes (iid, AR (1), MA (1), ARMA (p, q), FARIMA (p, d, q), etc.)-- then the first and second differences will also be multivariate normal (note that the reverse is not generally true).
The climate system is not
a stationary stochastic process.
MM2005 model
a stationary stochastic process but the MBH98 algorithm somehow detects what you describe as a non-stationary forcing attributed to CO2.
«From
a stationary stochastic process the MBH98 algorithm detects a non-stationary signal: just how does it do that and still get described as robust?»
From
a stationary stochastic process the MBH98 algorithm detects a non-stationary signal that is then attributed to CO2 forcing (the «hockey stick»).
Not exact matches
If one assumes that a
stochastic process is
stationary (Hurst's Hunit root test), which would be consistent with DrK's Hurst - Kolmogorov pragmaticity, then the
process has a finite mean.
If we continue this type of thinking (means varying at a cascade of time scales, in an unpredictable manner), the eventual result is a
stationary (yes,
stationary)
stochastic process with LTP.
Of course any finite realization of a
stochastic process,
stationary or not, has a finite mean (you can always compute the average of a bunch of numbers).
Nevertheless, the salutary aspect of the GISP 2 data is the clear indication it provides of a gentle, truly secular cooling trend since the Holocene optimum, overlain by weakly
stationary, strongly structured, quasi-Gaussian
stochastic variations whose ordinate distribution and power - spectrum both diverge from anything resembling a Poisson
process of abrupt jumps.