Why it doesn't matter what the climate-models tell us about the global warming

  • Is climate change real? Are the damaging effects foreseen by scientists real? Are we - humans - really responsible for a climate change? Are CO2 emissions the cause of the problem? What if the scientists' models are wrong? What if climate change is a Hoax after all?

    We need reliable evidence of harm, before we take any action, right?

    What if it's all wrong perspective and we are asking the wrong question? What if it's not about the accuracy of the models and it's rather about the scale of the possible damage?

    What if uncertainty about climate models should lead us to a more conservative, more cautious, "greener" stance, even if one disbelieved the models?

    Welcome to precautionary principle.

    I strongly encourage you to read the a short statement by Joseph Norman, Rupert Read, Yaneer Bar-Yam, and Nassim Nicholas Taleb. Read the statement below or download the article as PDF from Taleb's website

    Climate models and precautionary measure

    THE POLICY DEBATE with respect to anthropogenic climate-change typically revolves around the accuracy of models. Those who contend that models make accurate predictions argue for specific policies to stem the foreseen damaging effects; those who doubt their accuracy cite a lack of reliable evidence of harm to warrant policy action.

    These two alternatives are not exhaustive. One can sidestep the "skepticism" of those who question existing climate-models, by framing risk in the most straightforward possible terms, at the global scale. That is, we should ask "what would the correct policy be if we had no reliable models?"

    We have only one planet. This fact radically constrains the kinds of risks that are appropriate to take at a large scale. Even a risk with a very low probability becomes unacceptable when it affects all of us – there is no reversing mistakes of that magnitude.

    Without any precise models, we can still reason that polluting or altering our environment significantly could put us in uncharted territory, with no statistical trackrecord and potentially large consequences. It is at the core of both scientific decision making and ancestral wisdom to take seriously absence of evidence when the consequences of an action can be large. And it is standard textbook decision theory that a policy should depend at least as much on uncertainty concerning the adverse consequences as it does on the known effects.

    Further, it has been shown that in any system fraught with opacity, harm is in the dose rather than in the nature of the offending substance: it increases nonlinearly to the quantities at stake. Everything fragile has such property. While some amount of pollution is inevitable, high quantities of any pollutant put us at a rapidly increasing risk of destabilizing the climate, a system that is integral to the biosphere. Ergo, we should build down CO2 emissions, even regardless of what climate-models tell us.

    This leads to the following asymmetry in climate policy. The scale of the effect must be demonstrated to be large enough to have impact. Once this is shown, and it has been, the burden of proof of absence of harm is on those who would deny it.

    It is the degree of opacity and uncertainty in a system, as well as asymmetry in effect, rather than specific model predictions, that should drive the precautionary measures. Push a complex system too far and it will not come back. The popular belief that uncertainty undermines the case for taking seriously the ’climate crisis’ that scientists tell us we face is the opposite of the truth. Properly understood, as driving the case for precaution, uncertainty radically underscores that case, and may even constitute it.

    There's more about the principle on Taleb's website. Also, read this Taleb's document on skepticism.

    photo: Nassim N. Taleb;link: https://gallery.windy.com/albums/a/Nassim-Nicholas-Taleb-skepticism.png;desc: The more uncertain or skeptical one is of "scientific" models and projections, the higher the risk of ruin, which flies in the face of the argument of the style "skeptical of climate models". No matter how increased the probability of benefits, ruin as an absorbing barrier, i.e. causing extinction without further recovery, can more than cancels them out. This graph assumes changes in uncertainty without changes in benefits (a mean-preserving sensitivity) –the next one isolates the changes in benefits.;

  • I believe all of this 100%. However I won't pass along to the many deniers I know because the language is too scientific and will turn them off. It would be great to have this written in a way that the man on the street would sit up and take notice.

Windyty, S.E. - all rights reserved. Powered by excellent NodeBB
NodeBB & contributors, OSM & contributors, HERE maps