Earth to warm more quickly, new climate models show (By 2100, could rise 6.5C)
phys.org
phys.org
I was speaking to an organization about reducing its flying. In the spring they wouldn't consider it. One 16-year-old girl, Greta Thunberg, sailing across the Atlantic put the initiative on the table.
She didn't plan to influence that organization but she did.
We all have that potential.
I've given one TEDx talk on environmental leadership http://joshuaspodek.com/my-tedx-talk-is-online-find-your-del... with a second in a few weeks https://www.tedxwaltham.com/tedxwaltham-2019. My podcast http://joshuaspodek.com/podcast is creating role models among globally renowned people.
I've become somewhat of a role model -- in my fourth year of not flying, I haven't filled a load of trash in over a year, I pick up litter every day -- and people write me to tell me they're doing it, as are their friends.
These results aren't enough, and some disasters will happen, but each person's actions contribute, including yours -- mostly by leading others to contribute too.
Does anyone have a good explanation as to why it’s prudent to attempt to predict anything about anything 80 years in the future?
Also curious if there is evidence of predicting the future in any field. If so, I’m wondering what the accuracy rate is one month out, one year out, five years out, etc.
I’ve done some modeling with sales data, trying to predict demand in a given market based on a series of variables. The issue is how much weight to put on each variable. With lots of market research and historical data, we were able to get decent estimates a couple of months in the future. Beyond that? It was complete speculation. Especially if we missed an important variable, which is common, since its impossible to know what variables will (and won’t) be relevant in the future.
I imagine climate modeling is more complex than my sales models, meaning more variables that were included, more variables that were excluded (especially the ones that are unknown unknowns), and a much larger margin for error (especially as time increases).
I raise this as I haven’t seen any push back from the HN community on articles like this. Not sure if I’m missing something, if it’s political bias, or a fear of ostracized for questioning these reports. Either way, I’d be fascinated to see some deeper analysis on the topic from the minds on this forum.
Have humans ever created a complex model that has enabled us to predict the future with any degree of accuracy? If so, how far into the future and with what degree of accuracy? If not, what is the purpose of a model extrapolated out to 2100?
Trying to imagine when technology will reach X milestone (AGI, for example) reminds me that it’s probably wise to be less sure of our predictions. The last US presidential election reminded me of this too.
Here is some analysis of how the predictions made by some climate models have done: https://www.carbonbrief.org/analysis-how-well-have-climate-m...
They have done a remarkable job since the 1970s.
https://www.env-econ.net/2017/07/cherry-picking-results.html
https://ori.hhs.gov/videos/case-study-list/3037
https://www.pnas.org/content/pnas/early/2018/03/08/171075511...
The inputs, the models themselves, and the main way to compute an output had mostly not been invented.
This is a fundamentally unfair comparison. If it couldn’t be computed analytically, it wasn't really possible to compute it 80 years ago. That absolutely doesn’t mean we should just ignore these predictions. Are we supposed to always wait some arbitrary time before listening to long term prediction?
I never said we should ignore any prediction. My calculation is purely Bayesian: how much prior trust should you place in a model (or class of models) with no long-term track record of success?
Why attempt to predict future conditions decades out? We do it all the time even though we absolutely know our predictions will not be exactly right. A prediction, even if imperfect, is useful if the prediction contains some bounds or probability estimates. People individually and society collectively makes best estimate judgements based on imperfect data every day, all day.
You've done some modeling of sales data, and the difficulty of predicting human whims leads you to suspect that modeling physics is an impossible and useless task? "I imagine climate modeling is more complex than my sales models" is an understatement of supreme folly. Even if you are a genius, the amount of work invested by tens of thousands of researchers spending their lives on this problem is incomparably more robust that some sales data modeling you tossed off.
> Have humans ever created a complex model that has enabled us to predict the future with any degree of accuracy?
Eclipses and solar positions can be computed to extreme accuracy centuries out. There is no closed solution -- it is all modeled and computed numerically.
The IPCC reports do get revised upward just about every release because the estimates are always conservative. Despite what is widely claimed by doubters, the IPCC reports have not been alarmist, and we can go back 30 years now.
Go back 40 years to Exxon's own modeling of climate change and considering the limited amount of data as compared to today, their estimates are not far off.
https://www.theguardian.com/environment/climate-consensus-97...
Maybe I am misunderstanding your statement, but to which period of time are you referring to? Your lifetime? 3 generations?
The long now includes a non-zero probability of a collapse of atmospheric oxygen, and complete human extinction within ~3600 years. [0]
We haven’t had a hypoxic atmosphere in the history of the earth since the evolution of photosynthesis (that’s a 2 Billion Year track record). The support for the plausibility of the author's hypothesis is that if you fit a parabola to the data over a certain time window, you get 100% decrease in atmospheric oxygen in a few thousand years??
That model is just nuts. By the same token it predicts we will have negative oxygen shortly thereafter.
However, you said:
> We haven’t had a hypoxic atmosphere in the history of the earth since the evolution of photosynthesis (that’s a 2 Billion Year track record).
This research seems to disagree, doesn't it? [0]
> Climate change triggered by volcanic greenhouse gases is hypothesized to have caused the largest mass extinction in Earth’s history at the end of the Permian Period (~252 million years ago). Geochemical evidence provides strong support for rapid global warming and accompanying ocean oxygen (O2) loss, but a quantitative link among climate, species’ traits, and extinction is lacking. To test whether warming and O2 loss can mechanistically account for the marine mass extinction, we combined climate model simulations with an established ecophysiological framework to predict the biogeographic patterns and severity of extinction. Those predictions were confirmed by a spatially explicit analysis of the marine fossil record.
[0] https://science.sciencemag.org/content/362/6419/eaat1327
[0]https://www.pnas.org/content/pnas/96/20/10955/F2.large.jpg
[1]https://en.wikipedia.org/wiki/Anoxic_event#Anoxic_events_in_...
It may be fit with a line+trigonometric to get some approximation for the next few years (10? 100?). With a line you get 50000 years to the 0 oxygen level, that is less alarmist than 3600 years.
Also, without a good model it's a bad idea to extend these projections too much. There are a lot of natural process that depend on the concentration of oxygen and will change. For example, under 15%-10% concentration of oxygen you can't burn wood so you solve the problem of forest fires https://en.wikipedia.org/wiki/Limiting_oxygen_concentration
How do we convince all investors to walk away from a nearly guaranteed and superb return?
This is the main problem which we currently face in my view.
www.forbes.com/sites/howardgleckman/2018/10/10/bill-nordhaus-the-nobel-prize-climate-change-and-carbon-taxes/
The real barrier is making something like this policy imo
But the whole world has to participate...