Extreme weather

[Alan Klein]

Who needs Paris?
GM to invest $2.2B in first all-electric vehicle plant, create 2,200 jobs
https://www.nbcnews.com/business/autos/gm-invest-2-2b-first-all-electric-vehicle-plant-create-n1124086

[Peter McLennan]

Who needs Paris?

You do.  Ever been there?   The City of Light.

Kudos to GM for seeing the light.  Sustainable energy will create zillions of high paying quality jobs.  Better, even, than coal mining.

[Alan Klein]

You do.  Ever been there?   The City of Light.

Kudos to GM for seeing the light.  Sustainable energy will create zillions of high paying quality jobs.  Better, even, than coal mining.

Building electric cars doesn't create electricity.  It needs electricity, likely from fossil fuels. 

[LesPalenik]

In Ontario, January 2020 has been wet and mild, 2-5 degrees Celsius warmer than average January. The month is not over yet, so it might turn out as the wettest and warmest January yet. 

"Much of southern Ontario has seen 150 to just over 200 percent of the normal or average precipitation for the month of January," Sonnenburg adds. "But with the warmer temperatures, a lot of that precipitation has fallen as rain."

Currently, this is Toronto's second rainiest January on record with 105.6 mm of rain reported so far. Total precipitation for the month as of January 26 is sitting at 130.6 mm.

STAYING MILD AND ABOVE SEASONAL INTO EARLY FEBRUARY
"The first few days of February will bring a continuation of what we have seen during January -- changeable weather," says meteorologist Dr. Doug Gillham. "But overall above seasonal temperatures are expected to dominate, though the pattern looks to be much more active and unsettled than how we are ending January this week."

https://www.theweathernetwork.com/ca/news/article/ontario-mild-and-wet-january-lack-of-arctic-air-but-with-above-average-precipitation-for-the-month

[Bart_van_der_Wolf]

Building electric cars doesn't create electricity.  It needs electricity, likely from fossil fuels.

Only for the laggards ...

[kers]

Building electric cars doesn't create electricity.  It needs electricity, likely from fossil fuels.

Building oil cars doesn't create oil.  It needs oil, likely from fossil fuels.

In a few years you have cars and oil cars...

btw
https://www.pik-potsdam.de/news/press-releases/climate-costs-smallest-if-warming-is-limited-to-2degc
the Potsdam institute for climate Impact research has figured out:

“We did a lot of thorough testing with our computers. And we have been amazed to find that limiting the global temperature increase to 2°C, as agreed in the science-based but highly political process leading towards the 2015 Paris Agreement, indeed emerges as economically optimal.”

[Slobodan Blagojevic]

... “We did a lot of thorough testing with our computers...

 

[Bart_van_der_Wolf]

It's called modeling. How else do you propose to test different scenarios and anticipate what future outcomes are possible?

Climate costs smallest if warming is limited to 2°C

27/01/2020 - Climate costs are likely smallest if global warming is limited to 2 degrees Celsius. The politically negotiated Paris Agreement is thus also the economically sensible one, Potsdam researchers find in a new study. Using computer simulations of a model by US Nobel Laureate William Nordhaus, they weight climate damages from, for instance, increasing weather extremes or decreasing labour productivity against the costs of cutting greenhouse gas emission by phasing out coal and oil. Interestingly, the economically most cost-efficient level of global warming turns out to be the one more than 190 nations signed as the Paris Climate Agreement. So far however, CO2 reductions promised by nations worldwide are insufficient to reach this goal.

[RSL]

I wrote this in an essay in 1980, Bart. Nothing has changed since then:

"The efficacy of any correct algorithmic process depends on two things: the validity of its premises and the validity of the data fed into it. The premises almost always are unprovable. They are arbitrary perceptions of reality arrived at through a mind leap that suspiciously resembles faith. The data need not only be accurate, they need to measure what the algorithm purports to deal with. Without valid premises and valid data a process may be quite valid and work perfectly well, but at the same time produce garbage.

"Many who claim “scientific” methodology seem utterly uncritical about the premises upon which their methodology is based, and seem unable to distinguish between what can be quantified and what cannot. Most of what these people produce is garbage. Yet, it seems, our society has been taught to accept the results of any methodology provided it’s sufficiently complex and mysterious to hide the question of faith buried in its premises. Process itself has become our religion. Revelation and mathematics have become synonymous."

[Bart_van_der_Wolf]

I wrote this in an essay in 1980, Bart. Nothing has changed since then:[...]

Russ, may I suggest to read up on modern technology? A lot has changed since then.

The models used now, were not available then. The amount and quality of input data has improved, since then.

And while I'm sceptical of many economists, it looks like William D. Nordhaus did a thourough job that after 40 years culminated into this 2018 Nobel Memorial Prize in Economic Sciences for him and Paul M. Romer in this shared honor.

2018 Nobel in Economics Is Awarded to William Nordhaus and Paul Romer
https://www.nytimes.com/2018/10/08/business/economic-science-nobel-prize.html

WASHINGTON — The Yale economist William D. Nordhaus has spent the better part of four decades trying to persuade governments to address climate change, preferably by imposing a tax on carbon emissions.

His careful work has long since convinced most members of his own profession, and on Monday he was awarded the 2018 Nobel Memorial Prize in Economic Sciences in recognition of that achievement.

But Professor Nordhaus sadly noted that he hadn’t convinced the government of his own country.

“The policies are lagging very, very far — miles, miles, miles behind the science and what needs to be done,” Professor Nordhaus said shortly after learning of the prize. “It’s hard to be optimistic. And we’re actually going backward in the United States with the disastrous policies of the Trump administration.”

Professor Nordhaus shared the prize with Paul M. Romer, an economist at New York University whose work has demonstrated that government policy plays a critical role in fostering technological innovation.

The award was announced just hours after a United Nations panel said large changes in public policy were urgently needed to limit the catastrophic consequences of rising temperatures. The prize committee said its choice of laureates was meant to emphasize the need for international cooperation.

“The message is that it’s needed for countries to cooperate globally to solve some of these big questions,” said Goran K. Hansson, the secretary general of the Royal Swedish Academy of Sciences.

Professor Romer, for his part, offered a more optimistic take on the challenges confronting society, saying that his work showed that governments could drive technological change. He noted the success of efforts to reduce emissions of ozone-depleting chlorofluorocarbons in the 1990s.

“One problem today is that people think protecting the environment will be so costly and so hard that they want to ignore the problem and pretend it doesn’t exist,” Professor Romer said at a news conference after the announcement. “Humans are capable of amazing accomplishments if we set our minds to it.”

[Alan Klein]

GIGO=Garbage in. Garbage out.

[Bart_van_der_Wolf]

GIGO=Garbage in. Garbage out.

You mean fossil fuel ...

[Alan Klein]

GIGO=Garbage in. Garbage out.

"It was popular in the early days of computing, but applies even more today, when powerful computers can produce large amounts of erroneous data or information in a short time. The first use of the phrase has been dated to a November 10, 1957, syndicated newspaper article about US Army mathematicians and their work with early computers,[4] in which an Army Specialist named William D. Mellin explained that computers cannot think for themselves, and that "sloppily programmed" inputs inevitably lead to incorrect outputs. The underlying principle was noted by the inventor of the first programmable computing device design:

On two occasions I have been asked, "Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?" ... I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.

— Charles Babbage, Passages from the Life of a Philosopher[5]"

https://en.wikipedia.org/wiki/Garbage_in,_garbage_out

[Robert Roaldi]

Models don't have to be perfect to be useful.

The argument that because things have been wrong in the past means that they are wrong now is specious.

What ARE you people afraid of?

[Slobodan Blagojevic]

... What ARE you people afraid of?

That you are going to f&*ck up our way of life for your crazy delusions. We are afraid of your totalitarianism that inevitably follows any left rule. We are afraid of you shoving down our throats your preconceptions of what we shall think, say, eat, and do.

[Alan Klein]

Models don't have to be perfect to be useful.

The argument that because things have been wrong in the past means that they are wrong now is specious.

What ARE you people afraid of?

There are more things wrong today because there are more people inputting data and having opinions about things that they can spread around on the web.  So it's actually harder to distinguish truth from BS.  That's what so scary about AI.  All it is is people imputed data and algorithms using their own flaws and prejudice that slants the results.  It's one of the concerns about climatology.  But it really extends to all social and hard sciences, economics, politics, etc.  You can;t trust anything you read today and have to be very discerning about trying to extract the truth. 

[Robert Roaldi]

That you are going to f&*ck up our way of life for your crazy delusions. We are afraid of your totalitarianism that inevitably follows any left rule.

Relax, that sounds frantic. You're letting ideology rule your thinking, much like all those "student radicals" do.

Every environmental policy in the last 50 years has improved our lives. It has nothing to do with totalitarianism, you just insist on seeing everything through the same lens. It's a bizarre notion, that designing systems that conserve resources are viewed as "left-wing rule" on your part. Time for you to step back and re-analyze. Most of the corporate world started doing exactly that several decades ago. You're stuck in a meme.

Nobody is destroying your way of life. If anything, the rest of the world is rushing to adopt it, with occasional hiccups along the way as per normal.

There are moves in the coal belt to prevent agencies from collecting disease data. From the rantings on these threads, it sounds like many people want to stop climate modelling, presumably because it doesn't produce the results they favour. Do you really think that kind of strategy can work? Don't you think that people will notice that strip coal mining produces air pollutants than make people sick? Do you think that making it more difficult for people to sue when they get sick is actually a good thing for society?

Just because people you don't like who supports a policy does not make the policy bad. You're not thinking straight.

[Robert Roaldi]

There are more things wrong today because there are more people inputting data and having opinions about things that they can spread around on the web.  So it's actually harder to distinguish truth from BS.  That's what so scary about AI.  All it is is people imputed data and algorithms using their own flaws and prejudice that slants the results.  It's one of the concerns about climatology.  But it really extends to all social and hard sciences, economics, politics, etc.  You can;t trust anything you read today and have to be very discerning about trying to extract the truth.

One the weirdest things I've read on this thread.

[kers]

"It was popular in the early days of computing, but applies even more today, when powerful computers can produce large amounts of erroneous data or information in a short time. The first use of the phrase has been dated to a November 10, 1957, syndicated newspaper article about US Army mathematicians and their work with early computers,[4] in which an Army Specialist named William D. Mellin explained that computers cannot think for themselves, and that "sloppily programmed" inputs inevitably lead to incorrect outputs. The underlying principle was noted by the inventor of the first programmable computing device design:

On two occasions I have been asked, "Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?" ... I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.

— Charles Babbage, Passages from the Life of a Philosopher[5]"

https://en.wikipedia.org/wiki/Garbage_in,_garbage_out

Some people here got stuck in 1957 cq 1980... for them after that nothing has changed ....
Science is not to be trusted ... after 1980.... ??
only argument seems to be: believe you me: I am old and wise...    ... or getting senile... ?

Today, input that goes into computers for calculations in observing our climate and our economy is very precise and comes from multiple sources and satellites that were not available in 1980, or 1957. In the early days of computing there was often no relevant data.
Today there is so much more relevant data that can be used in calculations, also for cross checking.
Now computers can be fed with more relevant and precise data than ever before, and computers can deal with more complex calculations than ever before...

There should be MORE trust in science, than ever before...

[RSL]

Russ, may I suggest to read up on modern technology? A lot has changed since then.

The models used now, were not available then. The amount and quality of input data has improved, since then.

But the premises behind the algorithms, premises that resemble faith haven't changed, Bart. The data may be more accurate (though you'd have to prove that somehow), but the potential fallacies built into the "models" are no less disastrous than they were "then." I did software engineering for thirty years after I retired from the Air Force. I understand the problems involved, and I understand that the problems, like the oceans, always will be there.