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Do Models Run Hot or Not?... Nerding Out on Models


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Do Models Run Hot Or Not? A Process Control View

 

Introduction

 

This short essay was prompted by a recent article regarding improvements to uncertainty in a global mean temperature estimate.[1] However, much bandwidth has been spilt lately in the related topic of error propagation [2, 3, 4], and so a small portion of this essay in its concluding remarks is devoted to it as well.

 

Manufacturing engineers work to improve product design, make products easier to manufacture, lower costs, and maintain or improve product quality. Among the tools they use to accomplish this, many are statistical in nature, and these have pertinence to the topic of the surface temperature record and its interpretation in the light of climate model projections. One tool I plan to present here is statistical process control (SPC).[5]

 

https://wattsupwiththat.com/2019/09/21/do-models-run-hot-or-not-a-process-control-view/

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Do Models Run Hot Or Not? A Process Control View

 

Introduction

 

This short essay was prompted by a recent article regarding improvements to uncertainty in a global mean temperature estimate.[1] However, much bandwidth has been spilt lately in the related topic of error propagation [2, 3, 4], and so a small portion of this essay in its concluding remarks is devoted to it as well.

 

Manufacturing engineers work to improve product design, make products easier to manufacture, lower costs, and maintain or improve product quality. Among the tools they use to accomplish this, many are statistical in nature, and these have pertinence to the topic of the surface temperature record and its interpretation in the light of climate model projections. One tool I plan to present here is statistical process control (SPC).[5]

 

https://wattsupwiththat.com/2019/09/21/do-models-run-hot-or-not-a-process-control-view/

Too many great points in that paper to elaborate on them all. Science has upheld that (at least in my view) that the earth's temps have remained steady with exception to 2 super Nino events in 1997-98 and again in 2015-16. As the article states it takes an immensely profound event, it seems to actually accomplish what the models are trying to output and when it does, it goes right back to below projections. Human manipulation is the only way to get the answer to the equation that they are looking for.

 

"The coloured lines are 5 different ESTIMATES of the global mean annual temperature from weather stations and sea surface temperature observations….”

 

This is a quote from the article as well. I have capitalized the word "ESTIMATES" for a reason. It appears to me, that the 5 major modern running global temperature records themselves, (per Gavin Schmidt's own language) cannot call themselves factual data but estimates.

 

Does one not find that a bit odd? I sure do. So our current global temperature after wasting billions upon billions of dollars and having land and sea observations going back many many years now is an ESTIMATE? They've only had 40 years to figure this out and all they can do is manipulate the lower end of a "setpoint" so that the trend doesn't drop below it. Gotcha. Sounds like pseudoscience and manipulation to me.

 

Ironically, I ran a computer controlled milling process that was based directly off of the engineering control charts highlighted in the beginning of the article. I knew how to manipulate the system to get what I wanted out of it also. The ONLY way to change what comes out of it is to shear off the lower end variances or restrict them or manipulate what actually goes into the system at the onset. I/E, change the setpoint, change the results or output goal. Those are the only ways to get a time/distance result outside of the realm of natural variance like that. Only way. I promise.

 

That is the best article I have read in a long time that explains what I already knew.

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