Summary Of Statistical Evidence Against Global Warming

One of global warming's more prominent supporters.
One of global warming’s more prominent supporters.
This is from my Classic Posts page, but seems appropriate to highlight in the wake of the latest gloom and doom from the IPCC.

If you’re looking for just one thing (statistically oriented), see the series on how to reconstruct and homogenize temperature series. The IPCC’s pictures, in particular their “confidence bounds” are too narrow, far too narrow. Yet another instance of the old “parameter-based” view of statistics (parameters reified as reality) and the new, predictive approach (where observables rule).

Meaning—as I’ve been saying for years—these fellows (and fellowettes!) are far too sure of themselves. If you’re on a desert isle, you can surf over to the same CP page (woefully behind in updating) and look at the statistical articles.

On the other hand, if you’re like me, you might skip reading everything. Is there any political will left for action on global warming? You can only scream so long before the fear of your audience turns to boredom and, finally?, to hostility. I find the whole area tedious; my heart sinks each time I see some earnest true believer trying to explain how the sky is falling, even though year upon years of observations shows it rising. And if you don’t like that screwy backwards metaphor, I’ve got plenty of others.

The number of blown forecasts have been so many you’d guess climatologists would go into hiding instead of trumpeting how accurate are their beliefs. I can’t even be upset with them, the poor dears. Do you know how gut wrenching it must be to even contemplate admitting to the world—the whole world which has been following your every word—that you have been wrong? Imagine the loneliness they’ll soon feel. Sad.

My eyes now glaze over, almost literally, whenever I see yet another whatever-they’re-calling-global-warming-this-week story. Maybe yours will do the same when scanning these old posts. I wouldn’t blame you.

So, this post, and tomorrow’s, may well be the last you hear from me on this subject.

Global Warming & The Environment

The BEST project: I (what it means), II (methods), III (politics).

How to think about time series (temperature example). Part I, II, III, IV, V.

What Probably Isn’t: Heat Waves and Nine Feet Tall Men: Prelude, I, II. 1 in 1.6 Million Heat Wave Chance: I, II

A Citizen’s Guide to Global Warming Evidence, Use And Abuses Of Decision Analysis: Global Warming Example, The Data Is The Data, Not The Model

Bad Astronomer Does Bad Statistics: That Wall Street Journal Editorial

How To Cheat, Or Fool Yourself, With Time Series: Climate Example, Anthropogenic Forcing Signals Not Significant?

What is—and what isn’t—evidence of global warming, Overview, I, II, III, IV, V, VI

The EPA, Dust, And The Ecological Fallacy Example: Criticism of Jerrett et al. CARB PM2.5 And Mortality Report

Do not smooth times series, you hockey puck! I, II, III

Climate Model Uncertainty: I, II

Homogenization of temperature series I, II, III, IV, V

Hurricanes have not increased: misuse of running means I, II

Proper statistical description of temperature (parameter-based versus predictive statistics): I, II.

Lewandowsky’s Faked Moon Landing


8 Comments

  1. A timely compilation. I have not read them all, but I will try to correct that now. Statisticians as a tribe come out quite well from the sordid mess that ‘climate science’ has become over the past 30 years or so, with the odious IPCC helping accelerate the descent into a kind of faith soup awash with easy money for toeing the party line. William M. Briggs has been a good man on the side of reason, reasonableness, and calm appraisal of theory and observations. Very well done!

  2. Happy to see that this is the your last post on the topic because you obviously dont know what you are talking about.

  3. Gustav,

    Oh! You got me! Your incisive, deep comments have convinced me that I’m wrong. Should I withdraw all those links which you haven’t read? Or leave them as examples of how people can be wrong?

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