Moving away from fossil fuels could create thousands of jobs, improve public health, and increase overall economic activity by nearly $14 billion in Wisconsin, according to a new study.

[…]

The study, done at the request of La Crosse County, is hypothetical and doesn’t address technological challenges.

“The impetus for this whole study was just to figure out whether producing our energy in-state would be beneficial to the economy and people and the environment of Wisconsin,” said David Abel, a UW energy researcher and lead author of the study.

Ahhh, to be an academic…

Transitioning to non fossil fuel energy sources sounds great until the temperature drops below zero.

…. and the sun doesn’t shine and the wind doesn’t blow.

In Madscow, where ignoramous Prof. Abel resides, the sun shines (defined as up to 70% cloud cover) on avg. 54% annually. Green Bay, Milwaukee, same. From November through March Madscow averages just 12 days a month of sun.

In Dane county, where ignoramous Prof. Abel resides, the average wind speed is 14.6 mph. Windmills require 30mph +/- for rated output.

Question: how many of those “created” 162k jobs ignoramous Prof. Abel claims are actually just replacements for those that would be displaced by shuttering gas and coal?

To answer MjM’s question, you’ll need to create a lot more than 162,000 jobs to replace the shuttering of gas and coal (and Boeing…and GM…and Ford…and the rest of the automobile and aviation industries). But don’t worry – in the Left’s world, you’ll be paid to not want to work (until the OPM runs out).

Maybe it would “work” with a global population of no more than 75,000,000, but even most of the Left won’t want to be Renewed to get there.

Umnnhhh….during the recent COLD spell, residents of central Minnesota were asked to turn down their heat to 60 degrees and stop using hot water. Reason?

Excel is in transition to Green!! So the utility depended on windmills to provide electricity, not the gas-fired turbines. UN-fortunately, the wind failed to blow after the cold front passed through; thus, the gas-fired turbos had to be started, requiring a bunch of natgas–so the customers’ furnaces and hot water became third of two priorities.

Oh, well. Excel had to pay for a lot of hotel rooms, too.

Perhaps Prof. Abel will invent the batteries which will store the electricity needed to run houses, etc., remembering that current Li batteries CANNOT be charged at temps below freezing, and are only 40% effective at temps below zero.

Minor technical challenge, I’m sure.

Ugh, more liberal academic tripe.

If we eliminated academic hot air, wouldn’t that fixed alleged global warming?

Yup, those darn academics. You guys would rather be living a hut, burning peat and walking everywhere. Medicine, who needs it.

“The ultimate ignorance is the rejection of something you know nothing about, yet refuse to investigate”. Fits you neanderthals perfectly.

The bad news: we’re into Global COOLING and will be there for the next 20-50 years. Sadly, we’ll have to keep the academic hot-air machine going, and prolly all the politicians, too.

But at least they’ll be a little more useful than they are today.

dud:

Those pesky scientists and their facts keep tripping you up.

https://www.nytimes.com/interactive/2019/02/06/climate/fourth-hottest-year.html

This is your periodic reminder that “Logan’s Run” is a warning, not a how-to manual.

Leeeeeeeeeeeeeeroy, you take the bait like a guppy.

Look very hard at the numbers and notice that they are WELL within the margin of error. Look again, and you’ll notice that “warming” stopped a few years ago–perhaps 10–with only margin-of-error variations since.

Suck on that bait while you’re chopping firewood.

In fact, LeeeeeeeeeeeeeeeeeeeRoy, if you look a third time, you’ll find that the atmospheric numbers are flashing “COLD COLD COLD”–and that the projections–even accepting NASA data–are downward temps. Crashing downward.

Firewood! Faster!!!

Nord,

NYTimes? Are you kidding?

I love that temperature chart, which has an alleged variance of only 1.2 degrees over 125 years is made to look like a mountain has been moved with its super skewed scale!

We cannot even take the variance as more than a rounding error because temperature measurement was “barbaric” relative to precision today prior to 1950.

Sometimes you arrogant elitists think you are so smart, but then you post something so dumb with no critical eye whatsoever.

Besides, we have been told by warming cultists that a 1-2 degree warming is the apocalypse. We have had an alleged 1.2 degree warming and no apocalypse, assuming it is not a rounding or bias measurement error Where is the apocalypse?

Where is the apocalypse?

Better question: what, exactly, is the ideal temperature? Support your answer with documentation, focusing on benefits while addressing harms. Be sure to provide footnotes.

Since you flat-earthers are too lazy to look this up yourself I’ll do your work for you again.

dud: Maybe you could show your work. How did you determine the margin of error? And show how you interpreted the results. And what crystal ball did you use to come up with that “crashing downward” nonsense?

k: NYT provided the data per the NASA release. If you feel you are smarter and more knowledgeable that NASA in terms of this release, please provide the data to prove your point.

https://www.nasa.gov/press-release/2018-fourth-warmest-year-in-continued-warming-trend-according-to-nasa-noaa

Nord,

NASA did not present a skewed chart to be alarmist to serve a radical cult agenda like The NY Times.

Let’s begin with NASA lies. https://www.americanthinker.com/articles/2018/01/nasas_rubber_ruler_an_update.html

How, indeed? By lying like Hell. The same author (one B.S. Eng’g and TWO M.S. Eng’g degrees) found similarly cooked (heh) books:

When I find it–if I’m so inclined–I’ll get back to you about NASA’s margin-of-error scare mongering.

k:

Could you explain in kevinese how the NYT chart is skewed to be alarmist and the NASA one isn’t? Betcha can’t.

Kevin,

The variance is not 1.2 degrees Celsius. The difference between the starting temperature and the ending temperature is 1.2 degrees Celsius. Variance is the expectation of the square minus the square of the expectation. That probably does not help, let me try another way.

Understand that numbers are abstract ideas that take on meaning when they enter the real world. When this happens units are assigned to numbers. Units are things like inches, centimeters, minutes, dollars, degrees Centigrade or degrees Fahrenheit.

Humans can quantify things using numbers with units. For example it may be 0 degrees Celsius or 100 degrees Celsius. Those quantities have specific meaning, at those temperatures water freezes or boils at 1 atm of pressure. Such definitions are objective, since they are the same for everyone.

Humans can also subjectively describe heat and the measurements that define heat. They can say that on a summer day it is hot or that 40 degrees Celsius is hot. The temperature at which a person says it is hot varies with each person, but at some point we generally agree.

It is true that if you or I were in a room it is unlikely that we could perceive a difference of 1.2 degrees Celsius. But scientists are not concerned with our subjective experience. Scientists and statisticians study things objectively. They collect data, conduct experiments, and make predictions. They want to know is a 1.2 degree Celsius difference statistically significant or is it random variation?

Let me explain. Suppose you were playing a dice game against a friend where you both rolled one dice and the person with the higher number won (If you tie you roll again). Suppose you played the game many times. You would expect that you would win approximately half the time. Now suppose you played the dice game a thousand times and never won. While it is possible that your friend is very lucky the more probable conclusion is that he cheated. The result of winning 0 and losing 1000 games is what is called a statistically significant result. However if you play only 4 times and win 1 time, even though you only won 25% we would expect that this is the result of chance (random variation).

That 1.2 degree difference is significant. Statistician know this in the same way that they know that someone who won the dice game mentioned above cheated. They have mathematical formulas that can prove this, it is not certain, in the same way that your friend could have gotten really lucky with his dice rolls.

Without advanced mathematics here is a way that you can see that the data is statistically significant. Write down each temperature from the Times graph. Take the arithmetic average of the first half of the temperatures and the arithmetic average of the second half of the temperatures. Then compute the difference between them.

Then write each temperature on a note card. Mix up the cards, shuffle them real good. Then put them in a pile. Draw the first fifty of them. Write down the average of those fifty cards and the average of the second fifty cards and subtract the averages. Try and repeat his process at least 25 times. Do you have many differences greater than the first difference you computed? If you do then you know it is random, if not than you know it is not random.

Maxwell,

1.2 degrees is significant how? (Assuming it is not a rounding error or biased measurement by improving measuring technology.)

Because you say so, but cannot prove it is significant?

Nord,

It is obvious the NYTimes chart is “compacted” to give the rounding error more significance.

You should read book “How to lie with Staistics”. One of the great works that renders most academics idiots. I especially ripped all statistics of Sociology professors. One professor re-did her entire class curriculum after I tore it a new one clas after class.

Your post was a classic case of lying with statistics by making the data look more significant than it really was.

Kevin,

I tried very carefully to explain it to you. Take the first half of the data compare it to the second half of the data. I proposed a randomization simulation that you could actually run yourself. The mathematical formula I avoided for your sake is called the student t-test.

I have read the book, “How to Lie with Statistics”. Do you know how to use a student t-test or conduct a randomization simulation?

Climate change is real. It’s consequences are real.

Max:

Great job !! I haven’t given much thought to student t in 40+ years. You did a great job simplifying it for k. Dr Barger would be proud of you. Keep up the good work ! Do you teach math?

k:

If “compacted” were the criteria for the validity of the chart, perhaps you could demonstrate how the NYT chart is misleading compared to the one from NASA. Or perhaps you could expound on why it was misleading to you whereas it wasn’t to others?

“renders most academics idiots”. And once again you proclaim yourself smarter than everyone else.

FYI: The word you were searching for is “Statistics”.

Nobody disagrees with that. The change is related directly to variations in the sun–specifically, sunspot activity. Of the other causes, water vapor is the most significant.

And sunspot activity is predicting climate change to the COLD side.

dud:

Could you provide the source for your claims (try something better than the Zharkova nonsense) ? Or are you conducting your own independent research?

Oh glory be, the disciples have testified to the warming!

That should be good enough for all of us to fall in line with the Marxist commandments…I mean agenda.

And all that man has done, couldn’t possibly have an effect on climate, exactly why?