put your money where your mouth is. Any idiot can generate hysteria in 2026.
Make your prediction about any HDI metric -- Real GDP, Child Mortality, Life Expectancy, Poverty, Malnutrition (hunger) and give me your prediction for 2030 (or any year < 2035). If your doom prediction doesn't come true, Announce to the world, "I'm pretty much clueless about how the universe works and will stop posting hysteria on Social media"
Why 2030? CO2 persists in the atmosphere for hundreds of years. This doesn't end in 2030.
The goal is not to generate hysteria; but to avoid it. Hitting one or more tipping points [1] is orders of magnitude more destructive than prioritising phasing out fossil fuels, and impossible to undo.
But I do understand that some people have reasons not to care about impacts that have an outsized effect on future generations, so to your request: a recent example of a list of impact predictions is the UK Government joint intelligence committee's national security assessment [2].
They use an established methodology (https://doi.org/10.1088/1748-95
9326/6/4/044022 - the methodology retains the average warming rate over the period since 1970 while smoothing fluctuations) to remove predictable temperature variations so they can isolate the effect they are trying to measure.
Just because they don't know exactly what past global temperatures would have been in the absence of El Niño doesn't mean it's statistically invalid to try and account for it.
Besides, temperature data to 2024 already shows accelerated warming with a confidence level that "exceeds 90% in two of the five data sets".
Add another year or two and it's likely we won't even need to smooth the curve to show accelerated warming at 95% confidence.
They used a published methodology. That doesn't mean the methodology is uncontroversial, and it certainly doesn't mean that they used it in a way that makes sense in the current context. One can commit an almost infinite number of horrible abuses via bog-standard linear regression.
Even setting aside the dubious nature of the adjustments, doing a regression on a 10-year window of a system that we know has multi-decade cycles -- or longer -- is just blatantly trying to dress up bad point extrapolations as science. Then, when they don't get the results they want to see from that abuse, they start subtracting the annoying little details in the data that are getting in their way.
> Just because they don't know exactly what past global temperatures would have been in the absence of El Niño doesn't mean it's statistically invalid to try and account for it.
You can't go back in time, invent counterfactual histories by subtracting primary signals, and declare the net result to be "significant". This isn't even statistics -- it's just massaging data via statistical tools.
> Besides, temperature data to 2024 already shows accelerated warming with a confidence level that "exceeds 90% in two of the five data sets".
If you were trying to determine if the quantity of daylight increased over a week in spring, would you account for the differences caused by day and night? What about cloud cover? Or is that just massaging the data?
p.s. the cited methodology has >300 citations in peer reviewed publications, ref Web of Science
> If you were trying to determine if the quantity of daylight increased over a week in spring, would you account for the differences caused by day and night? What about cloud cover? Or is that just massaging the data?
Just to draw a better analogy to the low quality of the current work, let's say you wanted to compare average daylight last week, globally, to all of recorded history. Then you made a model that had terms for (say) astronomical daylight, longitude, latitude and, I dunno...altitude of the measurement. Then you made a regression, subtracted three terms, and claimed that the residual was still "significantly darker". Then you run around waving your arms and shouting that if we only extrapolate forward N weeks from last week, soon we'll be living in a fully dark world!
You'd be rightfully laughed out of any room you were in.
I think you are missing my point, and the point of the article: they are demonstrating that global temperature change that is not driven by volcanism, solar variation or El Niño is (in all likelihood, given the data) accelerating. They can do this because the effects of volcanism, solar variation and El Niño on global temperature can all be predicted from external measurements.
> Hyperbolic growth is what happens when the thing that's growing accelerates its own growth.
Quibble: when a growth rate of a metric is directly proportional to the metric's current value you will see exponential growth, not hyperbolic growth.
Hyperbolic growth is usually the result of a (more complex) second order feedback loop, as in, growth in A incites growth in B, which in turn incites growth in A.
The view I hold is that, as bad as the situation is, it's not hopeless and there is a lot that can be done that will make the situation better. "All we can save". I've heard it said in the context of the polycrisis that understanding leads to grief, which leads to action which leads to (solidly founded) hope.
People (and so societies) are hard-wired to be loss averse, which means the facts about what is at stake are more effective drivers of action than the promises of techno-optimism.
Not saying that there are not good optimistic views out there, just that I personally find a realistic view renders many of them quite flat. I think embracing false hope leaves us with a myopic lens through which to frame decisions and probably underprepared to deal with the future.
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