‘Show Your Work’ Challenge to Government Climate Scientists
It is good to see constructive dialog among colleagues. To further such discussion it is necessary to keep to PSI’s commitment to open public debate, when the science demands it. John O’Sullivan – https://principia-scientific.com
Well said John. Your point was exemplified in the traditional math exam instructions “Show your work.” In fact it is more important in real science because without it reproducible results are not possible. 
But there is another important point and that is what led me to support what the Slayers were doing. As you know, as a climatologist I had very limited training in physics and math, however, I knew enough to know that the diversity of answers I was getting from a limited number of physicists indicated problems with official IPCC science. This is partly on display here but is dealt with through discussion and at least an attempt to keep an open mind.
It occurred to me during a radio interview, when being harangued once again about claim that 97{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of scientists agree, and as is my style, came out as a semi-spontaneous response, that it is likely that 97{154653b9ea5f83bbbf00f55de12e21cba2da5b4b158a426ee0e27ae0c1b44117} of scientists have never even looked at what the IPCC write in their reports. Specialists in one area assume that specialists in another wouldn’t lie or cheat, especially in science.
The retired editor-in-chief of The Lancet put the cat among the pigeons with a recent claim:
“The case against science is straightforward: much of the scientific literature, perhaps half, may simply be untrue. Afflicted by studies with small sample sizes, tiny effects, invalid exploratory analyses, and flagrant conflicts of interest, together with an obsession for pursuing fashionable trends of dubious importance, science has taken a turn towards darkness.” http://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(15)60696-1.pdf
I know that this is an understatement about what has and is going on in environmental research, and it is even worse for climate research. I know most of you have seen this quote before but it bears repeating.
“Ten years ago I simply parroted what the IPCC told us. One day I started checking the facts and data – first I started with a sense of doubt but then I became outraged when I discovered that much of what the IPCC and the media were telling us was sheer nonsense and was not even supported by any scientific facts and measurements. To this day I still feel shame that as a scientist I made presentations of their science without first checking it.”
Here is the original German source for Puls’ quote: https://www.eike-klima-energie.eu/2012/05/08/dafuer-schaeme-ich-mich-heute/
It was translated here: http://notrickszone.com/2012/05/09/the-belief-that-co2-can-regulate-climate-is-sheer-absurdity-says-prominent-german-meteorologist/#sthash.5LpKcJv0.dpbs
It must also become a goal of all of us in PSI to get other scientists to read the IPCC Reports. Not the summaries, but the original “The Physical Science Basis” Report of Working Group I” – .
http://ipcc.ch/report/ar5/wg1/
Here is an interesting comment (Box 2.1) in that work, that speaks to the Lancet question about 5 Sigma:
Box 2.1 | Uncertainty in Observational Records
The vast majority of historical (and modern) weather observations were not made explicitly for climate monitoring purposes. Measurements have changed in nature as demands on the data, observing practices and technologies have evolved. These changes almost always alter the characteristics of observational records, changing their mean, their variability or both, such that it is necessary to process the raw measurements before they can be considered useful for assessing the true climate evolution. This is true of all observing techniques that measure physical atmospheric quantities. The uncertainty in observational records encompasses instrumental/ recording errors, effects of representation (e.g., exposure, observing frequency or timing), as well as effects due to physical changes in the instrumentation (such as station relocations or new satellites). All further processing steps (transmission, storage, gridding, interpolating, averaging) also have their own particular uncertainties. Because there is no unique, unambiguous, way to identify and account for non-climatic artefacts in the vast majority of records, there must be a degree of uncertainty as to how the climate system has changed. The only exceptions are certain atmospheric composition and flux measurements whose measurements and uncertainties are rigorously tied through an unbroken chain to internationally recognized absolute measurement standards (e.g., the CO2 record at Mauna Loa; Keeling et al., 1976a).
Uncertainty in data set production can result either from the choice of parameters within a particular analytical framework—parametric uncertainty, or from the choice of overall analytical framework— structural uncertainty. Structural uncertainty is best estimated by having multiple independent groups assess the same data using distinct approaches. More analyses assessed now than in AR4 include published estimates of parametric or structural uncertainty. It is important to note that the literature includes a very broad range of approaches. Great care has been taken in comparing the published uncertainty ranges as they almost always do not constitute a like- for-like comparison. In general, studies that account for multiple potential error sources in a rigorous manner yield larger uncertainty ranges. This yields an apparent paradox in interpretation as one might think that smaller uncertainty ranges should indicate a better product. However, in many cases this would be an incorrect inference as the smaller uncertainty range may instead reflect that the published estimate considered only a subset of the plausible sources of uncertainty. Within the time-series figures, where this issue would be most acute, such parametric uncertainty estimates are therefore not generally included. Consistent with AR4 HadCRUT4 uncertainties in GMST are included in Figure 2.19, which in addition includes structural uncertainties in GMST.
To conclude, the vast majority of the raw observations used to monitor the state of the climate contain residual non-climatic influences. Removal of these influences cannot be done definitively and neither can the uncertainties be unambiguously assessed. Therefore, care is required in interpreting both data products and their stated uncertainty estimates. Confidence can be built from: redundancy in efforts to create products; data set heritage; and cross-comparisons of variables that would be expected to co-vary for physical reasons, such as LSATs and SSTs around coastlines. Finally, trends are often quoted as a way to synthesize the data into a single number. Uncertainties that arise from such a process and the choice of technique used within this chapter are described in more detail in Box 2.2.:
Note that the only record given credence is that from Mauna Loa. Charles Keeling, who built the site and instruments and made all the assumptions, was an ardent promoter of the AGW story from the start and patented the equipment and the measurement technique which is held by his family. He also convinced the IPCC to make only stations using his equipment as the sole measure of atmospheric CO2 levels.
Read more from Dr Tim Ball at drtimball.com
Download Dr. Tim Ball’s Curriculum Vitae in PDF format by clicking here.
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