Please show an example of that. Link please. All I have seen is pundits lying about what papers say. Did you actually read such a paper, or read what some pundit claimed the paper said?...um, it's in the paper.
I was familiar with the paper, but the instrument data in that paper is cited as being fromUnrelated.
You asked about confidence intervals. I provided you examples of distributions.
It is clear from Fig. 5 that the best fit is obtained for a sensitivity below the 1.5°C lower bound of the 90% confidence range.
I disagree with that perspective. My perspective on science is that we take a hypothesis, and do our best to disprove it. When all failures to disprove it fail, then we are getting somewhere.
Why are people constantly trying to deny the works of others that they don't like? Do you believe that to be science?
Please show an example of that. Link please. All I have seen is pundits lying about what papers say. Did you actually read such a paper, or read what some pundit claimed the paper said?
I was familiar with the paper, but the instrument data in that paper is cited as being from
Wigley, et al
Which Wigley found was below 1.5C for the best fit....and AGAIN I cannot stress this enough, that 90% confidence figure is not just based on the "opinion" of the researchers. It is calculated from the distribution itself.
Which Wigley found was below 1.5C for the best fit.
That's their conclusion based on the information they used. Do you think they believe that's absolute?...um, it's in the paper.
That's their conclusion based on the information they used. Do you think they believe that's absolute?
NO figure 3 instrument section came from Wigley, or at least that is what the citation said.So you are just going to ignore Figure 3?
As a guide only.I get the feeling I'm slamming my head against a brick wall here. What do you mean "absolute"? Do you have no familiarity with statistics and data distributions? I don't understand your question.
When you have a distribution of data you can, from that, calculate estimates of the mean, median, standard deviation, etc. It is calculated based on the data.
Statistics is a critical skill to have for a scientist.
NO figure 3 instrument section came from Wigley, or at least that is what the citation said.
As a guide only.
That is too general of a question. A hypothesis has to be able to be challenged. I'm not sure where you are going with this statistic idea, except to think you must rely too much of statistics.Huh? I'm not following. So, barring statistics, what is the best way to determine the most likely accurate hypothesis based on the data in your experience?
only the instrument data counts with any accuracy, models and opinions ,Fig. 3 has MANY different methods of measurement. The entire article goes over a wide variety of methods. Fig 3 shows confidence intervals.
Look,man. These guys are ‘sort of engineers’. They obviously sort of know what they’re talking about.I get the feeling I'm slamming my head against a brick wall here. What do you mean "absolute"? Do you have no familiarity with statistics and data distributions? I don't understand your question.
When you have a distribution of data you can, from that, calculate estimates of the mean, median, standard deviation, etc. It is calculated based on the data.
Statistics is a critical skill to have for a scientist.
That is too general of a question. A hypothesis has to be able to be challenged. I'm not sure where you are going with this statistic idea, except to think you must rely too much of statistics.
A reminder. Facts make statistics. Statistics do not make facts.
only the instrument data counts with any accuracy, models and opinions ,
PS expert elicitation is the synthesis of opinions of authorities of a subject where there is uncertainty due to
insufficient data or when such data is unattainable because of physical constraints or lack of resources.
in short their opinion!
I am guessing that you do not understand how statistics are applied to merging climate data and climate model results.You keep saying that, but I sense it is because you are not one who utilizes statistics. Statistics is the BEST and, as of now, the ONLY tool we have to estimate error and eliminate bias.
I don't know what kind of magical thinking you are undertaking about the nature of an hypothesis but when you work with data statistics becomes VERY important.
I've seen people take graphs and draw best fit lines through the data and wave their hands and say "Look, here's a trend!" But in reality unless there's an F-test done on that trend to show with some confidence that there is actually a REAL trend and not just a random noise artifact then one would be best NOT to accept the claim that there is a trend. That's just sloppy.
Most of the ones not under the instrument listing are so subjective as to be opinion.-sigh-
THE CONFIDENCE INTERVALS IN FIGURE 3 are NOT, repeat, NOT based on "opinion".
Here's how confidence intervals are calculated on normal distributions: http://www.stat.yale.edu/Courses/1997-98/101/confint.htm#:~:text=For a population with unknown,for the standard normal distribution.
And here's how one works with non-gaussian distributions (CI on the median): https://online.stat.psu.edu/stat415/lesson/19/19.1
(There are whole host of non-parametric statistics as well)
I am guessing that you do not understand how statistics are applied to merging climate data and climate model results.
The empirical climate data has an actual confidence interval and standard deviation, the model outputs do not really have that because
each simulation can have very different input variables.
Most of the ones not under the instrument listing are so subjective as to be opinion.
Please show an example of that. Link please. All I have seen is pundits lying about what papers say. Did you actually read such a paper, or read what some pundit claimed the paper said?
Agree or disagree...
Do you agree with the Orwellian type censorship?
If the used exactly the same initiation condition, combined with exactly the same variable selection, they would likely get very close to the same results.You are saying that model outputs cannot have variability in successive runs? That does not sound right. I believe Monte Carlo methods are used in some aspects of climate science, do you think their output is not statistically describable? Why not?
In fact there are stochastic climate models which, pretty much by definition, are described by statistics.
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