Lying with data, statistics, conclusions and predictions = climate "science:

I've been compiling a list of common ways people lie with data, statistics, and predictions for over 20 years.

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The list is based on my climate change reading since 1997.

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Climate "science" is based on a climate physics theory that is wrong.

That's why there have been 40 years of grossly inaccurate climate predictions!

The theory is wrong because it ignores climate history knowledge, and claims 'it's different this time', with little evidence that's true, and a lot of evidence it's not true.

The theory (CO2 is the climate controller) is simply assumed to be correct, and used to make inaccurate predictions.

This scheme starts with government employees scaring people using computer game predictions of a coming climate change catastrophe.

Scared people want their government to prevent the "crisis".

The government claims the "solutions" are more taxes on corporate energy use, and more regulations.

It's surprising this imaginary "crisis" still scares people after 40 years of consistently  wrong climate predictions!

There is no crisis -- Earth's climate has barely changed in 150 years, and is better than it has ever been in at least 500 years.

People who question climate catastrophe predictions are ridiculed and character attacked by 'believers".

Following is a generic list of lying by climate change "believers" that I have identified and discussed in the EL Climate Change Blog since late 2014:

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How to lie with data, statistics, and predictions:

 

               DATA  COLLECTION  BIAS

Efforts to support pre-existing beliefs and predictions, or to support desired conclusions:

--- ignore 99.999% of historical data,

--- ignore most accurate source of data,

--- data mine -- cherry pick data from each data source,

--- make arbitrary "adjustments",

--- make frequent, small 'same direction' "adjustments" that stay 'under-the-radar',

--- hide the raw unadjusted data,

--- truncate available data,

--- ignore contradictory data,

--- ignore best available measurement methodology,

--- use estimates, computer model data, or proxy data, when real data are available,

--- never discuss biases of people who collect & analyze data, and

--- never discuss biases of organization(s) that pays for data collection.

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            STATISTICS  &  CHARTS  BIAS

-- use averages that hide important details,

-- show anomalies versus an arbitrary base period, rather than actual data,

-- use charts with small vertical axis range to exaggerate tiny anomalies,

-- confuse correlation with causation,

-- extrapolate short-term trend into future,

-- mistake random variations for a meaningful trend,

-- splice together data from unrelated sources on one chart, without explanation,

-- don't show predictions vs. actual results on the same chart,

-- false precision: too many decimal places shown,

-- false precision: too small margins of error claimed, and

-- false precision: statistics applied to poor quality source data.

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   PREDICTIONS & CONCLUSIONS  BIAS:

- state predictions & conclusions with unjustified confidence,

- never admit "I'm not sure.", or "I could be wrong.",

- ignore consistently inaccurate predictions in past four decades,

- make such long term predictions they can never be proven wrong in your lifetime,

- claim a strong consensus of experts, when there's no consensus at all,

- jump to conclusions not supported by the data,

- ignore different conclusions by other subject matter experts,

- claim that historical cause-effect relationship suddenly reversed 180 degrees,

- refuse to debate: Attack character and motives, ridicule alternative theories, and

- predict a crisis to get a government grant to study the "crisis".

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Example of the most important bias:

Governments employ almost all climate modelers

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Governments want a crisis, real or imaginary.

 

Politicians use the imaginary climate crisis to seize more control over the private sector, with new regulations and taxes.

 

They claim they need more power to "save the Earth".

 

But our climate is actually better than it has ever been in at least 500 years -- Earth does not need to be saved -- there's only good news for humans (slightly warmer nighttime low temperatures) and plants (Earth is greening with more CO2 in the air).

 

Meanwhile, a multi-trillion dollar 'green' industry has been built on government subsidies, and government loans to "connected" crony capitalists.

 

The most important bias of all is large organizations, from cigarette companies to central governments, buying whatever data, statistics, conclusions, and predictions they want, simply by paying scientists, economists, consultants, etc. for what they want.