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You wrote so much, it’s a shame you insist on claiming the models are not wrong. The right answer is that, just like COVID models, of course the climate models
by zaroth 7y ago
You wrote so much, it’s a shame you insist on claiming the models are not wrong.
The right answer is that, just like COVID models, of course the climate models will turn out to be completely wrong in the exact details, in the scale, in the timeframe, and possibly even in the endpoints.
COVID is actually supremely easier to predict than climate. The two fundamental problems with most COVID models are that 1) the positive test counts don’t mean what you think they do, and 2) because of that, everything that is based on positive test counts being relatively meaningful is therefore totally wrong.
The climate models, since they were created by humans and not God, will likewise have almost innumerable errors which will cause all sorts of problems both minor and major with their predictions. This is universally true with all models of complex systems, and therefore should be totally uncontroversial, unfortunately the models have become like sacred cows.
Personally, just like I was with COVID, I am confident that paradigm-shifting events will intercede that will totally invalidate the model one way or another.
For COVID the paradigm shift was that the majority of cases are asymptomatic. Most people are still coming to terms with this. I heard it recently best described to think of SARS-CoV-2 as actually two viruses. One, much less prevalent, is serious and deadly. The other, much more prevalent, is mild to the point of being unremarkable. Getting one confers immunity to both. This is, I stress, a mental model, not a scientific explanation of what’s actually happening (which does not presently exist).
The point is that the things that make models wrong are often “external” to the model, the unknowables. For Kelvin it was radioactivity. His model was total “sound” just like the climate models are “sound” in terms of everything that is presently knowable. But complex systems, particularly ones with humans in the loop, have a way of surfacing curveballs the model did not, and could not, anticipate which have outsized effects in the endpoints.
The lesson with climate, just as it is being shown with COVID, is that dramatic action to address the problem (“flatten the curve”) with almost incomprehensible direct costs does not pay off.
With climate, just like with COVID, a less blunt instrument will achieve a better outcome for orders of magnitude less cost.
The sad part is that the top 2% couldn’t give a fuck about the cost either way. It’s the bottom 75% which will suffer from terrible policy.
- nl 7y agoThe lesson with climate, just as it is being shown with COVID, is that dramatic action to address the problem (“flatten the curve”) with almost incomprehensible direct costs does not pay off. Surely the lesson from Covid-19 is "early intervention works". Compare for eg the number of deaths in Japan/Australia/South Korea with Italy/US/UK.
- zaroth 7y agoI guess I’m not sure what definition of “works” you are using? Humans have a tendency to see the thing in front of them and claim, I did X, and then Y happened, so X must have helped cause Y. When in fact no such thing has been proven. I think there are a lot of things different about those examples you gave, and absolutely no scientific way to draw a conclusion about a particular intervention having a particular effect. Here’s an interesting comparison between Australia and Canada for example, who both responded similarly but have ended up in markedly different situations. [1] So instead I would offer a different framework for the discussion. In the end there are only two simple questions with COVID. 1) When we hit the endpoint, what is the total prevalence in the population, and is it lower than the natural saturation point? So my guess for #1 is that at the endpoint, we will see that basically everyone who could have gotten it did get it. To put it another way, I suspect only the highest risk population taking the most extraordinary precautions will end up not having antibodies to SARS-CoV-2, everyone else at some point being naturally exposed. In other words, I assume we will reach whatever the top of the S curve for COVID would naturally be based on the biological nature of the virus. Essentially, I am assuming that vaccines will not play a large role, because it will have played out before they become available, and/or because we don’t have any coronavirus vaccines and it’s probably harder to make one than we think. 2) How long do we stretch things out to get to that endpoint, and therefore, how many lives are saved through increased availability of medical care and, on the flip side, how much economic cost is incurred? My hope here—based on some very preliminary data—is that we are actually much further along than the testing might indicate (e.g. 5% overall prevalence and much higher in certain metros, vs 0.2%) From a health care perspective I think that the only effective treatments we have today are minimally invasive and extremely scalable — oxygen therapy and frequent repositioning. We are learning that ventilators have proven to be basically lethal to COVID patients, therefore increased availability and usage of ventilators presumably just increases the death rate. There have been no controlled studies either way at this point so no one can say for sure. At this point because we have no effective cure or treatment, and because initial antibody testing seems to indicate COVID is extremely widespread despite the shutdown, I am very skeptical of the current approach paying off both in terms of delaying spread & saving lives through higher availability of care. [1] - https://www.theglobeandmail.com/opinion/article-canada-and-australia-a-tale-of-two-covid-19-responses/ https://www.theglobeandmail.com/opinion/article-canada-and-a...