Modelling Madness

Complex computer models are continually being used to generate incessant alarms about the future for our environment and resources -- climate, weather, minerals, oil, food, water, pollution and the oceans.

Every year the computers get more expensive, and the models more complex, but their doomsday forecasts still fail.

Models are simple in principle. They have a formula linking two or more variables, such as rainfall in a catchment area and the water level in a dam. The model can tell us that 200mm of rain will fill the dam. But a few failed forecasts will result in a more complex model that tries to take account of obvious complicating factors such as ground cover in the catchment area and the rate of precipitation. Then more rainfall recording stations will be needed, and more complicating factors will be identified . . . needing a bigger computer.

Imagine the complexity of a mathematical model designed to forecast something as simple as next Wednesday’s weather in Brisbane, Birmingham or Boston.

The British Met Office owns Britain's most powerful super computer. It can make 1,000 billion calculations every second while consuming more electricity than a small town. The Met claimed that it “will enable the Met Office to deliver more accurate forecasts, from hours to a century ahead.”  Some 400 climate high priests attend this electronic monster. But it has totally failed to forecast several frigid European winters because the model makers believe their own story and have programmed the models with a global warming bias. They assume without proof or evidence that carbon dioxide controls global temperature.

The global models of IPCC climateers also have a warming bias and have failed spectacularly to date -- their global temperature predictions have been wrong for 17 years straight. When do they give up?

In 2000, the UK Met Office told us that snow was a thing of the past; in 2007, Australian Climate Commissioner Tim Flannery predicted cities such as Brisbane would never again have dam-filling rains; in 2008, Al Gore predicted “The entire north polar ice cap will be gone in five years”.

Are the people who work on the climate models smarter, wiser, more ethical and more experienced than the people who worked on financial models for governments, central banks, commercial banks, hedge funds, brokers and investors and who failed to predict the global financial crisis?

The atmosphere and the oceans are far more complex than the currency markets.

And yet there are still “experts” claiming that if they had bigger computers they could forecast global climate for a century ahead!

If the assumptions in the models remain wrong, then more powerful computers will just produce wrong answers faster.

Doing the same thing, and expecting a different result, is proof of climate modelling madness.

For those who would like to read more:

Al Gore: Entire north polar ice cap will be gone in 2013 (and many other forecasts of doom):
http://anhonestclimatedebate.wordpress.com/predictions/

73 climate models fail:

http://www.drroyspencer.com/2013/06/still-epic-fail-73-climate-models-vs-measurements-running-5-year-means/

NASA predicts Arctic Ice Free by 2012:
http://stevengoddard.wordpress.com/ice-free-arctic-forecasts/

James Lovelock, BBC: “I don’t think anybody really knows what’s happening. They just guess. And a whole group of them meet together and encourage each other’s guesses.”:

http://www.thegwpf.org/james-lovelock-nobody-really-knows-whats-happening-with-climate-change-theyre-just-guessing/

 

Complex computer models are continually being used to generate incessant alarms about the future for our environment and resources -- climate, weather, minerals, oil, food, water, pollution and the oceans.

Every year the computers get more expensive, and the models more complex, but their doomsday forecasts still fail.

Models are simple in principle. They have a formula linking two or more variables, such as rainfall in a catchment area and the water level in a dam. The model can tell us that 200mm of rain will fill the dam. But a few failed forecasts will result in a more complex model that tries to take account of obvious complicating factors such as ground cover in the catchment area and the rate of precipitation. Then more rainfall recording stations will be needed, and more complicating factors will be identified . . . needing a bigger computer.

Imagine the complexity of a mathematical model designed to forecast something as simple as next Wednesday’s weather in Brisbane, Birmingham or Boston.

The British Met Office owns Britain's most powerful super computer. It can make 1,000 billion calculations every second while consuming more electricity than a small town. The Met claimed that it “will enable the Met Office to deliver more accurate forecasts, from hours to a century ahead.”  Some 400 climate high priests attend this electronic monster. But it has totally failed to forecast several frigid European winters because the model makers believe their own story and have programmed the models with a global warming bias. They assume without proof or evidence that carbon dioxide controls global temperature.

The global models of IPCC climateers also have a warming bias and have failed spectacularly to date -- their global temperature predictions have been wrong for 17 years straight. When do they give up?

In 2000, the UK Met Office told us that snow was a thing of the past; in 2007, Australian Climate Commissioner Tim Flannery predicted cities such as Brisbane would never again have dam-filling rains; in 2008, Al Gore predicted “The entire north polar ice cap will be gone in five years”.

Are the people who work on the climate models smarter, wiser, more ethical and more experienced than the people who worked on financial models for governments, central banks, commercial banks, hedge funds, brokers and investors and who failed to predict the global financial crisis?

The atmosphere and the oceans are far more complex than the currency markets.

And yet there are still “experts” claiming that if they had bigger computers they could forecast global climate for a century ahead!

If the assumptions in the models remain wrong, then more powerful computers will just produce wrong answers faster.

Doing the same thing, and expecting a different result, is proof of climate modelling madness.

For those who would like to read more:

Al Gore: Entire north polar ice cap will be gone in 2013 (and many other forecasts of doom):
http://anhonestclimatedebate.wordpress.com/predictions/

73 climate models fail:

http://www.drroyspencer.com/2013/06/still-epic-fail-73-climate-models-vs-measurements-running-5-year-means/

NASA predicts Arctic Ice Free by 2012:
http://stevengoddard.wordpress.com/ice-free-arctic-forecasts/

James Lovelock, BBC: “I don’t think anybody really knows what’s happening. They just guess. And a whole group of them meet together and encourage each other’s guesses.”:

http://www.thegwpf.org/james-lovelock-nobody-really-knows-whats-happening-with-climate-change-theyre-just-guessing/

 

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