Would that the "corrections are documented for each dataset". Each researcher has his own understanding of the adjustments so whoever processed the raw data applies his corrections and goes away. The datasets do not indicate which of hundreds of algorithms are applied to the data. Some of the changes seem almost like an institutional bias, but we know that doesn't happen.
"The time series" do not "suffer from misalignment" they suffer from optimistic interpretations of the dead band. If a dataset has an uncertainty of +/-10 years then any value from 20 years to 40 years is exactly the same number. Treating the values in any other way will range from wishful thinking to criminal intent.
One argument about cause and effect of this issue stirs up debate about which came first CO2 or warming, but as any climate scientist will explain the two are linked in feedback so this question is moot by itself. Either will elicit the other.
If you reject the Greenhouse Gas hypotheses out of hand, then the feedback loop doesn't happen. The earth warms. The permafrost retracts (measurable physical phenomena that was measured during the warming period in the 1990s). The frozen organic material becomes available for biological activity. Atmospheric CO2 increases within a year. This is a complete hypotheses that doesn't require computer models. It could be as wrong as the GHG hypotheses looks to me. It does plausibly fit the uncertainty in the data sets better than the GHG hypotheses. And don't say that GHG is a
FACT as though shouting will make it so. I've heard the shouting and am not impressed.
As to "Principle Component Analysis" I did my Masters in Fluid Mechanics. In doing research for my Theses I reviewed several hundred PhD Theses documents and many other learned writings. Many of which went to great lengths to describe their "orthogonal vectors", "Eigenvalues" and "Eigenvectors". One sticks in my mind. After this verbose choom went on for over 300 pages about his Analysis he said that the results of it ended up with a system of empirical equations that would "match actual flows within +/-35% almost 22% of the time". In other words he felt that 1/5 of the time he could predict a 100 ft/sec flow stream as having a velocity between 65 and 135 ft/sec, the other 4/5 of the time he was less accurate. He and his PhD committee saw this as a huge win. Now he's teaching our children.
I've never heard the fluid and thermodynamic forces in the environment described as "freshman physics" before. Maybe I should have paid more attention. I got good marks so I thought I was paying attention, but maybe I missed that day. It really is not simple. It is kind of complicated actually. Much more complicated than any fluid system that has ever been successfully analyzed. The climate models with grid blocks the size of Colorado make me think of doing Engineering drawings with a paint roller. The model that was developed for my new separator has 1/10 the number of grid blocks than are used for the entire earth and the separator has a volume of 0.17 m^3 not 4.2 billion cubic kilometers. In any given one cubic meter control volume of the earth's atmosphere there are flow forces, rotational forces, gravitational forces, electrical forces, magnetic forces, nuclear forces, forces due to heat transfer, and other forces too numerous to mention. These all interact in amazingly complex and beautiful ways that absolutely defy closed form solutions. That is in a cubic meter. There are 4.2x10
18 cubic meters in the atmosphere. Every one has a potential to effect every other one. My pissant model takes 28 hours to run to completion on the fastest computer array at Los Alamos National Laboratory (it is a long story). That model does a great job of explaining observed measured parameters. We let it extrapolate 20-25 time cycles into the future, and each time step is 20 seconds. I think that the results are useful. I don't think I'd let it go 200 time steps (just over an hour) into the future. Climate models are trying to tell us about the year 2500. Utter and complete tripe.
I've taken the time to write this because the meeting I'm in the office for today got canceled and I'm bored. Not sure when I'll be able to get back to a response if one is needed.
David Simpson, PE
MuleShoe Engineering
"Belief" is the acceptance of an hypotheses in the absence of data.
"Prejudice" is having an opinion not supported by the preponderance of the data.
"Knowledge" is only found through the accumulation and analysis of data.
The plural of anecdote is not "data"
