Posted on 02/08/2018 11:05:05 AM PST by Academiadotorg
A Princeton physicist has shared an inconvenient truth of his own--climate change models are based on an alternate reality. "And I know they don't work," Princeton University physicist William Happer says in a video produced by Prager U. "They haven't worked in the past."
"They don't work now. And it's hard to imagine when, if ever, they’ll work in the foreseeable future."
"In the video, Happer argues that even supercomputers used to predict the weather and forecast future global warming aren't strong enough to capture the complexity of Earth's atmosphere, including cloud cover and natural ocean cycles," Michael Batasch, who wrote about the video in The Daily Caller, writes.
"That's why, over the last 30 years, one climate prediction after another -- based on computer models -- has been wrong," Happer says. "They're wrong because even the most powerful computers can’t solve all the equations needed to accurately describe climate."
As Batasch recounts, Happer's are not the only observations within the scientific community that break with current wisdom: "We haven’t seen that rapid acceleration in warming after 2000 that we see in the models," Myles Allen, a geosystem scientist at the University of Oxford, stated in 2017. "We haven't seen that in the observations."
Ping.
Here is the link to the Prager U. video
https://www.prageru.com/playlists/what-science-reveals-about-climate-change#1
“They’re wrong because even the most powerful computers can’t solve all the equations needed to accurately describe climate.”
—
Seems to me that in order to construct “all the equations needed to accurately describe climate”, you would first have to know everything there is to know about climate. So when did all climate research end with the conclusion there is nothing more to learn?
There is further albeit obscure the possibility that the atmosphere consists of hexagonal cells linked one to the other and they communicate. Until someone does further research to prove or disprove that idea, then climate will never be successfully modeled among many other reasons.
OK!! Everybody pay attention!
Lesson for today:
1. The sun is 1,300,000 times as big as the earth.
2. The sun is a giant nuclear furnace that controls the climates of all its planets.
3. The earth is one of the sun’s planets.
4. The earth is a speck in comparison to the size of the sun.
5. Inhabitants of the earth are less than specks.
Study Question: How do less-than-specks in congress plan to control the sun?
Climate Change fraud bump for later....
Well, if the observed data fails to match the models, they can just wait a few years and adjust it then. Problem solved. /s
If the mesh is too dense then you quickly run out of computing resources.
If the mesh is too sparse then the predictions you get from running the model are worthless.
Not to mention the amazing variety of boundary conditions that have to be included... boundary conditions that are changing and moving around to boot like:
- Cloud cover
- Sea temps
- Sea emissions
- Plant cover
- Snow/ice cover
- Volcanic venting
.
.
.
- Human generated emissions
Does a great job of boiling down a voluminous debate into a five minute video.
Seems to me that in order to construct “all the equations needed to accurately describe climate”, you would first have to know everything there is to know about climate. So when did all climate research end with the conclusion there is nothing more to learn?
XLNT. That would be analogous to acting on the conclusions of an investigation while the investigation is still underway.
he really does
In the words of Bob Dole, you said it, I didn’t;>)
They are wrong because they are based on one simple, but limited and faulty assumption. As CO2 increases in the atmosphere the temperature will increase a set amount in response. The problem is the climate is nowhere near that simple. CO2 has been increasing since the beginning of the industrial revolution. The problem is that temperatures have gone up and down during this time, but never as high as the models have predicted,
Actually, they even use hypothetical variables to “predict” past temperatures and never get it right. They brag if they get closer to the actual than they have been, or, as my late boss, M. Stanton Evans put it, “so they’re getting better at predicting the past.”
A model is a small-scale imperfect reproduction of a full-sized original.
The model runs equations that imperfectly describe the actions of the small-scale model.
The equations are a guess as to how things actually function in real life. The equations take short cuts, and make assumptions where no one knows how things function.
Collection of data is far from perfect. The Earth is huge, and there is no way to take enough measurements to obtain usable readings.
Small errors in the input data lead to major errors in the results. This is the meaning of the stupidly-named “butterfly effect.”
Lorentz: Chaos: When the present determines the future, but the approximate present does not approximately determine the future.
A rational scientific community would conclude that CO2 concentrations do not cause atmospheric warming.
Well sure, but the point of the author was that these models for one thing cannot model water vapor which is 98% or so of all the so-called greenhouse gasses.
That's called "testing" or "ground truth". Start a model with 1980 data and see how well its results compare with 2010 data. For example.
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