I tell you statistics is a legitimate field of science. Many of you doubt it because of incoherent answers given by climate “scientists” in response to reasonable questions. Answers such as, “weather is not climate” when asked why climate models can supposedly predict temperatures 100 years out but cannot predict the weather two weeks out.
In statistics this is nonsensical.
When a statistician (or pseudo-statistician in the case of climate scientists) says they have a model that explains any kind of outcome what they mean in simple English is they have a mathematical representation (model) of explanatory (independent) variables that capture the magnitude to which these explanatory variables hold a causal relationship (not “correlation”) to an outcome (dependent variable).
It is not necessary at all for a statistician to draw conclusions from a model. “Results are inconclusive” is a perfectly acceptable way to close out a scientific study.
But the Greens have drawn a conclusion – the science is settled.
The scientific conclusion they have settled on, in English, is:
- Global Warming (AGW) is occurring.
- They have measured the effect of various atmospheric influences (independent variables) on climate temperatures (the dependent variable).
- Explanatory variables impacting climate include changes in solar flare activity (changes which are currently impossible for NASA astronomers to predict in advance), ocean currents, those much maligned carbon levels, etc…
- Out of all variables, they have concluded man made carbon emissions have the most effect on projected climate conditions.
- The effect of carbon emissions, and other atmospheric influences, on climate are mathematically and accurately represented in their climate models.
- The degree of impact carbon has on climate is projected to have catastrophic consequences.
Skeptics, targeting how much explanatory power the models actually have, go on to question how representative these models are of real trends by asking how they can predict climate but not weather.
To this, the mainstream anti-carbon crackpots squawk back – weather is not climate!
We call this talking point and those who make it crackpot because weather is informationally relevant to climate.
Or, in mathematical language, the explanatory variables that impact weather and climate overlap with each other.
From this it follows if explanatory variables for climate and weather overlap, and, if climate “scientists” do understand the actual scientific relationship between carbon and climate, then it should be possible for climate “scientists” to convert their statistical models of climate into accurate statistical models of weather conditions using climate variables that climate shares with weather.
At least, if weather cannot be projected out on a day by day basis, on a decade by decade timescale.
The fact they would not dare to predict weather beyond two weeks, let alone a century, using explanatory factors similar to the factors used in their climate projections indicates they do not have serious confidence in their expression of the relationship between the forces governing these highly complex atmospheric feedback loops.
And if they do not understand these relationships, there is no reason to act on their anti-carbon recommendations.
Weather is indicative of information about climate.
At a minimum, not being able to predict weather using models similar to climate models seriously calls into question their “settled” position on climate.
For them to insist that “weather is not climate” is as mathematically ridiculous as an economist saying –
- They have a regression model that predicts national consumer spending trends over 5 years using inflation, wages, unemployment rates, etc., as explanatory variables.
- The conclusion drawn from this economic model is that inflation is the most important variable.
- But their model cannot be adjusted to explain quarterly consumer spending on the state level.
This, too, is ridiculous for the same reasons “Climate is not weather” is: Explanatory variables of national consumption rates overlap with many explanatory variables of consumption rates at the state level.
Any economist who tacked on this lousy caveat about state spending at an academic conference of economists would immediately be bombarded with hostile questions about how he can conclude anything about national spending if his statistical reasoning cannot be converted to handle state spending.
But this is precisely what climate “scientists” are saying by “Weather is not climate!”.
No legitimately “settled science” spends so much energy evading questions with analogies this flimsy.