So... because I don't like the EIA projections, I have to defend the IPCC?
Try again.
That wasn't my argument at all. I argued not to simply dismiss them on accuracy issues for prediction.
Also, while there's a lot of useful stuff in economics, I wouldn't call it a science. The EIA is not science, it's economics. Economics is HORRIBLE at predicting the future.
So are long-term climate projections. That doesn't mean we can't use either as an example of what's wrong with what we're doing right now.
Which is the whole point of even discussing the predictions. To get an idea of how our current practices will likely affect the future. As time passes and our practices change, something economics and climate science both aptly demonstrate, the predictions lose accuracy. Which is why they are constantly revised as we get new data. And why it is that denialist arguments about IPCC accuracy as a way of discrediting climate science completely miss the point.
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There's a joke that has always stuck with me.
A physicist, a chemist and an economist are trapped on an island. Luckily a crate of food washed ashore, but unfortunately it's all canned, and they don't have a can opener. So the three debate over the best way to open the cans.
The physicist says, "I think we should build a mechanical arm to smash the cans open, revealing their contents."
The chemist says, "No, we have to build a container and fire, which will boil the contents and make the cans explode. Letting us reach the food."
The economist says, "Well, suppose we had a can opener...."
@CBDunkerson
@Irontruth
Welp, QB is on my side. I fold.
It's kinda hard to argue with overwhelming evidence that I'm in the wrong.
You're debating the viability of models with a person who has repeatedly claimed that models are incapable of giving an accurate picture of what the world will look like, while referencing the output of models that agree with his own predictions.You keep saying that and it’s still not true.
I cite contrary models because they are better than the average-of-all-models that the folks at the Paris Agreement (and elsewhere) have used to make major decisions. Averaging in a bunch of bad models with a few better ones won’t get you a superior answer.
That and the models for testing ideas about AGW won’t get you a usable answer 30 years out, often not even 10 years out, let alone to the year 2100 and beyond. But then I wouldn’t expect people ignorant of the Three Forms of Ignorance to parse this concept correctly. So, yeah…
Also Kirth... while you may do this for a living, QB read a book about it by a guy who does a lot of math. QB clearly knows more about this.You’ve not read his book or anything else by him yet you disparage his ideas? Really?
Srsly though I’m not amazed at your behavior because… people.
If you dare challenge your ignorance on this surf on over to these places and be amazed.
Mathematica and Wolfram Alpha.Wolfram is the key instigator of scientifically “worthless” stuff like that. So, yeah, what does he know? <snort-guffaw>
Where did I say that Stephen Wolfram wasn't a smart guy?
If Mr. Wolfram came into this thread and told Kirth he didn't understand a model, I'd be inclined to listen to Mr. Wolfram.
His ideas are brilliant, and his attempts at a computational model of the universe are groundbreaking and have helped reexamine how the whole concept of science is approached.
I highly suspect though, if Mr. Wolfram were shown how you were applying his concepts to this discussion, he'd have a few things to say to you. I don't think many of the would be congratulatory.
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And this is far from the first time I've seen people say we're going to run out of fossil fuels. Far from the first time we've been on the brink of it, too. Every time we get there, someone comes up with a new technique or a new technology to drill what we knew was there, but could not currently reach. And then the price falls on oil and demand goes up.
Setting aside the fact that nobody DID say "we're going to run out of fossil fuels"... new extraction technologies are almost always more expensive. Fracking, as the most obvious example, costs much more (and yields lower quality results, requiring more expensive refining) than traditional drilling... and thus can only exist at a higher (not lower as you suggested) price point. Ergo, once alternative options fall below the cost of oil it is unlikely that some new extraction technology will change that.
That said... we obviously WILL run out of fossil fuels eventually. The size of the Earth is finite. Ergo, the amount of fossil fuels it contains is also finite. Even the highest end pie in the sky estimates of extracting and converting every imaginable fossil fuel resource would barely get us to 2200 before they'd run out. More plausibly we'll hit a wall some time before 2100.
Note Solar is down in that graph. That's matching closer to EIA projections than the graph you posted.
Ummm... you mean the single year dip in the partial 2017 US figure coming off the 2016 record high? Note that is also only as a percentage of the whole... in absolute terms US solar has grown in 2017 also. A single year in a single country does not define a trend.
...and no, that DOESN'T match what EIA is projecting. The graph you posted is new additions. The EIA graph I linked was total installed. In order to match the flat EIA projection the new additions would have to fall to ZERO... not the 25% of all new capacity shown.
Think about that for a moment. Each year the EIA projects that solar growth is about to flat line for 15 to 20 years. Not that solar installation rates will stop increasing, but rather that there won't be ANY new solar installations at all. Then over the course of the following year solar actually grows to a level they hadn't projected for 30 years. So they update to the new actual solar capacity... and again project no further growth for 15 to 20 years... and solar again shows massive growth over the next year. Over and over the same nonsensical assumption that solar is about to stop growing and stay that way for more than a decade. Do YOU believe that there are going to be virtually no new US solar installations from 2018 thru ~2035? Because that's what the projection you are touting assumes.
Coal saw a production increase in the U.S. in 2017. Still closer to EIA projections than your own.
From the page you linked: "Estimated U.S. coal production for the first 11 months of 2017 is 719 million short tons (MMst), 54 MMst (8%) higher than production for the same period in 2016. Annual production is expected to be 791 MMst in 2017, falling to 771 MMst in 2018 because of lower exports and no growth in coal consumption."
So... an 8% uptick this year, followed by a 3% decrease next year. Again, for the US only.
It helps to rely on current data, not outdated information, when making a projection as to how things will go. This is the current data: Solar is down and coal production is increasing in the United States.
Your own 'current data' says coal will decrease next year. Meanwhile, pretending that a single year in a single country is indicative of global trends is just... ludicrous.
Current data clearly shows that solar is growing and coal is shrinking... even in the US. Relying on one year fluctuations to claim otherwise is the logical equivalent of claiming that global warming is over because it was cold yesterday.
Also, I noticed you only addressed one nation in your reply, while mine covered the entire world. If you are right that they are massively wrong, then alternative energy is about to be dealt a massive blow as far as growth is concerned; they show China going heavily alternative energy.
Yes, they are wrong about China too... they are still underestimating Chinese alternative energy growth.
So, you've argued yourself into a Morton's Fork by arguing the EIA is consistently wrong:
A: I haven't "argued" that the EIA is consistently wrong about renewable energy growth. Rather, I provided documentation proving that to be the case.
B: You are using the term Morton's fork incorrectly. It is a type of logical fallacy where you state that two contradictory observations lead to the same conclusion.... your erroneous claim that I am wrong whether the EIA is correct or not is itself an actual Morton's fork. Without the error in your conclusion... no fork.Nope. I'm countering the argument that if a source is wrong once, it's wrong all of the time.
The EIA was not "wrong once". They have been wrong about renewable energy growth each and every year for the past decade... and always in the same direction (i.e. underestimating growth).
And showing how, in this particular case, that line of logic has painted the person I'm dealing with into a corner.
Except... you didn't show that. You made a number of false statements (e.g. if I say EIA is consistently wrong about one thing that means I am saying they are consistently wrong about other things) built on those with false assumptions (i.e. if EIA is wrong about China that must mean China will develop LESS renewable energy... ignoring the possibility that they could be wrong because it will develop MORE) and thus arrived at an incorrect conclusion.
That is what the EIA knew when making their projection about natural gas growth challenging renewables. The fossil fuel companies have not been gearing up for switching over to sell solar panels or wind, but have instead been leveraging the past twenty years of science to sell a different type of fossil fuel. And their sales continue to grow.
Natural gas is doing well in the US... and very few other countries. Factor out the US and there is no global growth in natural gas. It should also be noted that most coal companies have no investment in natural gas and indeed have been being driven out of the market by it for the past 20 years. So the idea that coal will stick around because of natural gas clout is just wrong.
Yes, natural gas been growing rapidly in the US for a couple of decades now. However, that growth is slowing in the US and not being replicated elsewhere.
Due to political changes, 2017 was a comparatively good year for fossil fuels >in the US<. In the rest of the world, not so much... and there is no logical reason to believe that the single year shift in a single country signals the end of ongoing global trends. Renewables will grow. Fossil fuels will not.
Of the major sources, Bloomberg has underestimated the growth of renewables the least thus far;
Personally, I think they're still giving fossil fuels (and nuclear) too much credit, but that graph should at least be roughly in the ballpark. Nothing the EIA has produced will even come close.
And this is far from the first time I've seen people say we're going to run out of fossil fuels. Far from the first time we've been on the brink of it, too. Every time we get there, someone comes up with a new technique or a new technology to drill what we knew was there, but could not currently reach. And then the price falls on oil and demand goes up.Setting aside the fact that nobody DID say "we're going to run out of fossil fuels"... new extraction technologies are almost always more expensive. Fracking, as the most obvious example, costs much more (and yields lower quality results, requiring more expensive refining) than traditional drilling... and thus can only exist at a higher (not lower as you suggested) price point. Ergo, once alternative options fall below the cost of oil it is unlikely that some new extraction technology will change that.
That said... we obviously WILL run out of fossil fuels eventually. The size of the Earth is finite. Ergo, the amount of fossil fuels it contains is also finite. Even the highest end pie in the sky estimates of extracting and converting every imaginable fossil fuel resource would barely get us to 2200 before they'd run out. More plausibly we'll hit a wall some time before 2100.
Note Solar is down in that graph. That's matching closer to EIA projections than the graph you posted.Ummm... you mean the single year dip in the partial 2017 US figure coming off the 2016 record high? Note that is also only as a percentage of the whole... in absolute terms US solar has grown in 2017 also. A single year in a single country does not define a trend.
...and no, that DOESN'T match what EIA is projecting. The graph you posted is new additions. The EIA graph I linked was total installed. In order to match the flat EIA projection the new additions would have to fall to ZERO... not the 25% of all new capacity shown.
Think about that for a moment. Each year the EIA projects that solar growth is about to flat line...
Scroll up a bit. I got a wake-up call about exactly which side of the discussion I was unwittingly on.
I hope you at least had fun with this.
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So...I skimmed a lot the last few pages, but did want to throw in a few comments
Regarding Terrinam's earlier stuff, at the government level I think he is exactly correct. Viewpoints development a certain inertia once they get into the political sphere, and get pushed even when the industry is no longer supportive of them. We have seen that in the recent wave of deregulation in areas such as the food industry, and were seeing that in how coal powered plants and renewable energies are being treated. Even when the industries are no longer really actively opposed to something, a cultural lay-group can still be advocating it, and politicians can exploit it (which is also what TheJeff was talking about).
For models...Kirth is right in that modeling is pretty much everywhere, but most people don't realize it. Beyond his own field, as someone who works in human anatomy, I can vouchsafe that modeling is used all the time in the creation of new drugs or how drugs/cancer/viruses move through the body as well as human populations, as well as in the design of prosthetic and surgical techniques. No one really disputes these models, not because they are any less accurate than many climate change modeling, but because there are no major industries that are inconvenienced by there results.
Stating the core issue in one sentence (and risking being misunderstood again):
If a given question is “too hard to model”, the question is ipso facto “not worth asking”.
I don't see how that follows at all. "Too hard to model," to me, just means either "insufficient input (quality and/or quantity) and/or insufficient processing power." Neither seems particularly insurmountable, except in the short term.
The thing about non-complex mathematics working for a great many human endeavors overlooks the fact that most questions about nature cannot be answered by that approach to modeling.
If you want to respond to something I’ve posted, this^ repeated and very salient point is a good one to get us to a better discussion.
I keep responding to this with variations on, "The word 'most' doesn't mean what you seem to think it means."
I keep responding to this with variations on, "The word 'most' doesn't mean what you seem to think it means."The thing about non-complex mathematics working for a great many human endeavors overlooks the fact that most questions about nature cannot be answered by that approach to modeling.
If you want to respond to something I’ve posted, this^ repeated and very salient point is a good one to get us to a better discussion.
The doubly amusing aspect is that Stephen Wolfram (QB's new hero I guess) actually built a career on non-complex modeling. One of Wolfram's greatest contributions to science was taking the abstract idea of "simple rules can produce great complexity" that was born out of the advent of computers and discovery of DNA, but was able to demonstrate it in the early 80's with his "rule 30".
Wolfram's current life-long project is examining simple mathematical models that can replicate the universe. Which is why I find QB's assertion that Wolfram thinks models can't give us useful information kind of hilarious.
It's like claiming that Isaac Newton would consider gravity to be a largely irrelevant scientific idea.
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Also Kirth... while you may do this for a living, QB read a book about it by a guy who does a lot of math. QB clearly knows more about this.You’ve not read his book or anything else by him yet you disparage his ideas? Really?
Srsly though I’m not amazed at your behavior because… people.
If you dare challenge your ignorance on this surf on over to these places and be amazed.
Mathematica and Wolfram Alpha.Wolfram is the key instigator of scientifically “worthless” stuff like that. So, yeah, what does he know? <snort-guffaw>
So, did I "dare challenge" my ignorance?
So, did I "dare challenge" my ignorance?No.
Wolfram’s models are nothing like the climate models used by virtually every major researcher in climate science over the past 40 years.One thing you overlooked about Wolfram’s approach is the fact that the Third Form of Ignorance:
3) Computational irreducibility (some things... well, some things you just can't calculate however well you can measure them)
Is the basis for the type of modeling that Wolfram does.Your new homework is to look up the implications for “computational irreducibility” and current climate models (models not used by Wolfram but by the hoard of climate scientists the world over).
Hint: Our global climate is its own shortest description
Also, I already linked to Mathematica and Wolfram Alpha up-thread – in short, I know what Stephen Wolfram is up to.
So, you're claiming that the definition of computational irreucibility is the inability to calculate something, regardless of how well it can be measured.
If that sentence is wrong, please reply with a revised sentence. I'm not asking you to explain it, I'm asking if that is what you think it is. I'm rephrasing slightly, to make sure I understand what you're saying.
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I don't see how that follows at all. "Too hard to model," to me, just means either "insufficient input (quality and/or quantity) and/or insufficient processing power." Neither seems particularly insurmountable, except in the short term.LOL! Did you not see my example about weather forecasting?
Tell me, which is it? Are we missing quality/quantity data or is it insufficient processing power? A combination of the two maybe?
This leads directly back to my supposed misuse of “most” in regards to questions about nature that cannot be answered the standard way.
Because they cannot be answered they are considered either unimportant questions to ask and/or non sequiturs by old school scientists.
Tellingly you haven’t answered the questioned I’ve posed twice now:
Today ‘Britany Forecaster’ at Local News TV gets the same grade as the top brains of 1967 in forecasting the weather.Why?
Your example of the weather forecasters is incorrect and completely a fabrication on your part. Weather forecasting HAS improved significantly since 1967.
When weather forecasting was done by hand, the models used to have 7 vertical layers, and was only able to detect atmospheric disturbances that were 500 miles or larger. Forecasters would modify the model based on local data, sometimes correctly, sometimes not.
Now, the models have approximately 60 vertical layers and have an atmospheric resolution 10 miles wide. They can much more accurately predict rain/snow lines (whether precipitation will be rain or snow) and models are accurate to a much longer duration than they used to be 40 years ago. 3-day forecasts are as accurate as 1-day's from 1967, while 7 day forecasts are as accurate as the old 5 day ones.
After a storm in 2000, the National Weather Service created the infrastructure to compare multiple models to each other and create an ensemble forecast. Because of this, they were able to accurately predict the DC area blizzard in January 2000 up to 5 days ahead of time.
Your assertion that forecasting hasn't changed in either procedure or accuracy is patently false. If you want to claim it again, you should provide evidence.
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Suspect the Chinese road is cheaper because in China, unlike France, they have no unions.
China has unions. They also have a much more robust solar manufacturing industry than anyone else. In any case, they are using a different design.
Also, what's the carbon footprint of "transparent concrete" roadway?
Should be a little less than other concrete since it generally incorporates clear resins and optical fibers that don't have the same high manufacturing emissions as regular concrete (or asphalt).
The last sentence save one in my previous post (quoted here-in). The one that starts out "Hint:".So, did I "dare challenge" my ignorance?No.
Wolfram’s models are nothing like the climate models used by virtually every major researcher in climate science over the past 40 years.One thing you overlooked about Wolfram’s approach is the fact that the Third Form of Ignorance:
3) Computational irreducibility (some things... well, some things you just can't calculate however well you can measure them)
Is the basis for the type of modeling that Wolfram does.Your new homework is to look up the implications for “computational irreducibility” and current climate models (models not used by Wolfram but by the hoard of climate scientists the world over).
Hint: Our global climate is its own shortest description
Also, I already linked to Mathematica and Wolfram Alpha up-thread – in short, I know what Stephen Wolfram is up to.
So, you're claiming that the definition of computational irreucibility is the inability to calculate something, regardless of how well it can be measured.
If that sentence is wrong, please reply with a revised sentence. I'm not asking you to explain it, I'm asking if that is what you think it is. I'm rephrasing slightly, to make sure I understand what you're saying.
You do this constantly. I ask you a straightforward question, and you don't answer. The consistency with which you do it implies that you either don't take the conversation seriously, or you don't understand what you're talking about. I personally lean towards the latter until I'm presented with evidence otherwise. For example, you just defined the term "computational irreducibility" wrong, and then pointed at an example that is technically correct, which tells me you know that climate is computationally irreducible, but you don't know why, because you don't know what the term actually means.
And you can tell me to go back to read your previous posts... but that is how I arrived at that conclusion, so if you tell me to just go read them again, you're telling me that this conclusion is correct.
Of course... you could have just avoided this by actually presenting the definition of computational irreducibility (which if you look it up, is different from how you've presented it).
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China has unions.In name only.
Thank you for conceding that your claim that "they have no unions" was false.
As to 'in name only'... this is also literally false (e.g. the unions have members... ergo, more than just a name). Figuratively, you likely meant that the unions are in some way inferior... but as that is subjective/unstated your position lacks sufficient substance to evaluate.
Yes but the concrete base (i.e. 99.9% of the concrete on the roadway) is the same. Adding “transparent concrete” as a veneer does not reduce the cost or add to the roadway’s expected lifetime. One wonders in fact if it effectually protects the solar cells for more than a few weeks/months or real use.
Most roads are made of asphalt. Concrete, including transparent concrete, is significantly more durable than asphalt. Therefore no, people who have any idea what they are talking about do not wonder if concrete will break down within a few weeks. Transparent concrete roads will last longer than asphalt roads, and thus offset some of the increased construction cost with decreased maintenance.
You didn’t read my argument very closely. Up thread when I first posted this assertion I said,Your example of the weather forecasters is incorrect and completely a fabrication on your part. Weather forecasting HAS improved significantly since 1967… <snip> …
Your assertion that forecasting hasn't changed in either procedure or accuracy is patently false. If you want to claim it again, you should provide evidence.Look at it this way. Fifty years ago the best weather forecasters could do an “A+” job three days out, a “B-“ job five days out, a “C” at seven days and “F-“ for a ten day forecast.
Today ‘Britany Forecaster’ at Local News TV gets the same grade as the top brains of 1967 in forecasting the weather.
Why?
Weather satellites, super computer modeling, NOAA resources freely available, plus all the assorted stuff that allows those first three things to be (with the Internet being foremost among them).
So how about the best weather forecasters of today? How do they rate? Well, right in there with ‘Britany Forecaster’.
I boldified the most salient point for the present turn of discussion.
So you see I acknowledged that weather forecasting at Local TV News has gotten better but the of today are not appreciably better prognosticators than their progenitors, namely the of 1967.
The average forecast? Well yeah that’s seen some improvement, almost entirely through brute forcing incredible amounts of data and freely distributing the results to mostly mimic what only the top forecasting minds once knew.
For much the same reason a typical senior in pre-college math today at Local High School is about as good at doing the same 12th-grade math as 1967’s version of Sheldon Lee Cooper.
You yourself mention the enormous increase in data aggregation and complexity of analysis involved in forecasting, yet the net improvements have been...
Show evidence that the best forecasters today are doing the same as small town forecasters in 1967. You are making the claim, back it up. Don't just say that it is true, show that it is true.
For example, you'd want to highlight how far off forecasters are on temperatures 3 days out. Of course, you don't actually want to highlight that statistic, because it wouldn't back up your point. In 1972, they averaged being off 6 degrees Fahrenheit, while currently forecasters are only off 3 degrees (which is a significant reduction in errors).
Another one you could look at would be predicting where a hurricane makes land fall. Though again, its not a statistic you want to highlight, because 25 years ago national forecasters were on average off by 350 miles. Those predictions now average 100 miles off (again, significant improvement). But that is a massive improvement and has led to a dramatic reduction in the number of people killed by hurricanes in the US.
Show evidence that the best forecasters today are doing the same as small town forecasters in 1967. You are making the claim, back it up. Don't just say that it is true, show that it is true.Today ‘Britany Forecaster’ at Local News TV gets the same grade as the top brains of 1967 in forecasting the weather.
So how about the best weather forecasters of today? How do they rate? Well, right in there with ‘Britany Forecaster’.
So you see I acknowledged that weather forecasting at Local TV News has gotten better but the of today are not appreciably better prognosticators than their progenitors, namely the of 1967.
To be fair to Quark, that's not what he's saying. He's saying that the best forecasters of today aren't much better than the local ones and they're around the same level as the best back in 67.
Basically because the local forecasters of today are basically reading the forecasts prepared by the best today - working off that brute forcing of data. Back then it was more of an art.
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Formatting seems to be going through weird.
Except the top forecasters of today ARE better than the top forecasters of 1967. Historical hurricane data shows us that they are.
I suspect that Jeff was just clarifying Quark's point, not agreeing with it...
FWIW as far as I am concerned the info provided upthread seems sufficient to refute the claim that high-end forecasting has not improved since the sixties. Though not the only persuasive example, the hurricane example seems particularly persuasive since it's not a matter of local forecasting vs. top forecasting and since accuracy has clearly and dramatically increased.
A potential Quark fallback position might be that the forecasts have improved, but not because the models have improved. This seems plausible, as there are have been a number of other improvements that would affect forecasting (weather satellites giving better observational data to plug into the models, for example).
Happily, it seems that scientists are also in the business of studying what factors contribute to the overall improvement they have achieved. From cursory initial research, the European Center for Medium-Range Weather Forecasting's (ECMWF's) model is widely cited as presently one of the premier world forecasting models. Among other things it is heavily used in the hurricane forecasting mentioned above.
This model didn't even exist in the sixties (ECMWF wasn't established until '75, and I imagine they had to build their models for the first few years after they were established), but various sources note that it has improved substantially over its lifetime and some state that the improvement was especially marked in the decade of the 2000s.
I reproduce below the abstract from a 2013 paper studying these improvements. Bolding mine.
During the past 30 years the skill in ECMWF numerical forecasts has steadily improved. There are three major contributing factors: 1) improvements in the forecast model, 2) improvements in the data assimilation, and 3) the increased number of available observations. In this study the authors are investigating the relative contribution from these three components by using the simple error growth model introduced in a previous study by Lorenz and extended in another study by Dalcher and Kalnay, together with the results from the ECMWF Re-Analysis Interim (ERA-Interim) forecasts where the improvement is only due to an increased number of observations. The authors are also applying the growth model on “lagged” forecast differences in order to investigate the usefulness of the forecast jumpiness as a diagnostic tool for improvements in the forecasts. The main finding is that the main contribution to the reduced forecast error comes from significant initial condition error reductions between 1996 and 2001 together with continuous model improvements. The changes in the available observations contributed to a lesser degree, but the authors note that all the ERA-Interim forecasts are from the satellite era and here the focus is on the midtroposphere in the extratropics. Regarding the jumpiness in the forecasts, this is mainly a function of the error in the initial conditions and is therefore an insufficient tool to investigate improvements in the full forecasting system.
Barring a misunderstanding on my part (always possible in amateur research) or the production of more-convincing contradictory evidence, this seems sufficient to dismiss both the actual contention ("high-end weather forecasting has not meaningfully improved since the sixties") and the obvious fallback position ("okay, but the improvements are due to other factors, the models themselves haven't meaningfully improved") as false.
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For the record;
History of weather model forecast accuracy
As those 36 and 72 hour forecasts have improved we now get 5 and 10 day forecasts... which would have been completely random in 1967.
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Think about that. It costs less to build and run a new wind or solar power plant, with battery storage, than it would to continue running any coal plant in the state. Thus, as those wind and solar plants get built and put downward pressure on the cost of electricity those coal plants are going to be operating at a loss... and will perforce shut down. Nuclear has even higher operating costs and thus faces the same problem. Not only will no NEW coal or nuclear plants be built... but many of the existing ones will shut down before 'end of life' because they'd lose money if they didn't.
The same is happening, though not as dramatically, throughout North America. If electric vehicles proliferate then the same thing happens to gasoline. Which would leave natural gas as the only fossil fuel standing... until renewable prices undercut it too.
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I agree with the general economic math you always promote.
Glad to see you come around.
However, what you seem to miss is these changes are about two decades too late to prevent a +2.5°C global temperature in the year 2100.
Nope, I don't 'miss' that. I just know that it is far from certain. If the absolute worst case high end climate sensitivity estimates are correct then that is true. If more middle of the road estimates are correct then we still have time. I happen to think that we'll come out at about +2.5°C warming (assuming an early 20th century baseline since that is the metric used in most of the international agreements), but only because we are still emitting massive amounts of CO2 now and will continue to do so for decades as the transition to renewable energy unfolds. Not because we already emitted too much CO2 ~20 years ago.
You also overlook that there are entire economies that will sell oil at unsustainably low prices (over the long term) until the government collapses in an attempt to buy enough time so they can safely transition to the new and better ways to generate electricity and move things about.
Yes, I overlook incomprehensible gobbledigook as a matter of course. Why would governments pay more for dirtier energy? So that they can collapse? What?
So cheap oil will be around for many years longer than a mere number-crunching Economics 101 exercise would predict.
Errr... no, I'm gonna go with economics on determining whether something will be "cheap" or not... given as how that's, you know, economics.
A thin veneer of “transparent concrete” is needed to protect the solar cells. I doubt its durability vis-à-vis that need.
It isn't that thin and, as already pointed out, concrete is more durable than asphalt.
If solar roof tiles are (not yet) cost effective, and won’t be for at least a decade it looks like, I doubt solar roadways will be cost effective before the year 2050.
Solar roof tiles are inherently a 'vanity' item. If you want the most cost effective you just put regular solar panels on your roof. You only use the tiles if you are willing to pay extra for 'aesthetics'. Thus, the fact that the solar roof tiles only cost slightly more than comparable roof tiles (e.g. $57k vs $41k in one estimate by Bloomberg) makes them seem fairly 'cost effective' now... let alone in ten years. If and when solar roadways will become cost effective is still to be determined, thus the need for these research projects.
As an R&D project to test the limits and have fun (if you’re an engineer) I’m not against them. If they are promoted as a way to help us meet the Paris Agreement goals, solar roadways are just plain stupid.
You, and plenty of others, made similar statements about solar power, wind power, and battery storage just a few years ago. Some people seem unable to perceive trends. There is every reason to believe that if R&D efforts continue ways will be found to rapidly decrease the costs of solar roadways... in which case they could indeed have a major impact on meeting the Paris Agreement goals.
You do this constantly. I ask you a straightforward question, and you don't answer…If you say so. I’ll repeat it plainly for you, though I seriously doubt this will help. The “definition of computational irreducibility” can be faithfully encapsulated in what I’ve already said:
Hint: Our global climate is its own shortest description.
Evidently you didn't understand my question. I'll reword it for you.
Why is global climate computationally irreducible? Explain it.
Hint:
(some things... well, some things you just can't calculate however well you can measure them)
Would be incorrect... at least according to Stephen Wolfram, and be an incorrect application of the term "computational irreducibility".
A positive hint: look at rule 30 and why it is computationally irreducible. Both rule 30 and climate are computationally irreducible for the same reason, but it isn't a reason you have actually talked about in regards to models.
It's because you haven't talked about that reason which indicates to me why you might be having some confusion about the concept of computational irreducibility and attributing to it meaning that it doesn't have.
@ Irontruth
As for the computational irreducibility of climate:
Stephen Wolfram (and others) believe certain pervasive aspects of the global climate are that class of problem. You’ll have to argue the finer points with Stephen and company.
I'm not arguing anything right now. I'm just asking if you are capable of explaining why global climate meets the definition of computational irreducibility. Essentially, all it would take to satisfy that would be a single sentence definition of the term.
By the way, if you go back and read that Jan 3rd post, that's all I asked for. A one sentence definition. Not an example, a definition.
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It’s the veneer of transparent “concrete” I’m talking about.
Yes, I know... and the fact that "veneer" is your word, and inaccurate to this case, is what I was talking about. You just decided in your own mind that it was some thin ineffective layer... reality be damned.
And I don’t care how durable it is compared to asphalt. My point is that, when used as a part of a roadway, it won’t do the job of protecting the solar cells for long.
Ummm... if you don't care to understand how durable concrete is, how can you make conclusions about how long it will last? You're just saying things you want to believe rather than having any understanding of how they really work.
A solar roadway is just a very expensive way to make a solar panel with a greatly reduced lifespan.
There is nothing to suggest that the lifespan of the panels will be reduced at all, and solar roadways are significantly more than just solar panels.
Yes by all means paint me with the “climate change denier” brush...
Not only is that a false quotation... it isn't even a remotely plausible paraphrase of what I wrote.
Countries, such as Saudi Arabia, that have invested a great deal of their economic viability in the extraction of fossil fuel and exporting it will continue to sell oil as long as they can.
Obviously.
However, that doesn't explain why countries would BUY the stuff once it becomes cheaper to use renewables.
Heck... even Saudi Arabia is making a big effort to convert to renewables, because it doesn't make sense for THEM to continue spending more to use oil either.
So again... how does the fact that countries will want to continue selling fossil fuels force anyone to buy them when there are cheaper alternatives?
I believe human improvements in CO2 emissions will be too little too late to prevent a +2.5°C year 2100, because in the aggregate humans always ease into major changes in behavior, unless and until it becomes a recognized crisis.
Funny, you had been claiming that it was impossible to avoid +2.5°C year 2100 because we had already emitted enough CO2 to hit that level 20 years ago.
Your new position above is much more plausible.
The average global atmospheric temperature in the year 2100 being +2.5°C (or worse) is another.
Not the least because (e.g) we spent a lot of #### effort making solar roadways. Fiddle with decadal ROI investments after we have CO2 emissions under control! What a craptastic waste of research effort.
And... you're back to crazy town. We're not going to be able to control global warming because we have spent 'so much' on solar roadways?
'Do not invest R&D into possible solutions to the problem until the problem has been solved!'