Explain this. Falling accumulated cyclone energy over the last 25 years. Go ahead, how does a model that predicts increasing cyclonic energy match actual measurements stating otherwise.
Too bad those assumptions and this paper do not match reality which shows the last 25 years having a decreasing trend in accumulated cyclone energy. When theory and assumptions conflict with data - data should win.
This reports is a hoax, yes. It uses "high resolution simulations" to reach its conclusions. Computer models. We have actual data that says otherwise. So which do you choose to believe? Models or data?
We have actual data that says accumulated cyclone energy is decreasing over the last 25 years. Why would you go with a simulation about what supposedly happened, when you can look at the actual data? This is part of the reason so many (including myself) are skeptical of the whole AGW things - it's based on models and projections, but the models don't match reality. If your model doesn't actually match what's happening, then I'm certainly going to give VERY little credence to your claims about what could happen.
Even then, you have to be aware of the "data" as it's presented, because often it is massaged a massive amount to turn a decreasing trend into an increasing trend. And even rewrite history. Simulations over data, data "corrected" to turn downward trends into upward trends, and historical values and records rewritten to "prove" the models. It's a house of cards built on shifting sand, and this paper is just adding another wing to that trembling structure.
One trend is from the late 19th century, the other from the late 20th century. Both have the same temperature pattern. One supposedly is caused by man's CO2 output, the other from nature. How do we know the impact of natural heating? We really can't control that level - it's a baseline change that happens and we may add or subtract from it - but we certainly can't control it...
That data is a bastardization of many alternate sites cherry-picked and blended to achieve the desired result. Just check the graph at the end of the article to see the "golden CRU data" from 5 cherry-picked trees, versus that of 34 trees from a different researcher. The former has a big upturn - the latter shows a gentle cooling.
The hockey stick that didn't exist unless you cooked your data, and then did everything possible to prevent anyone from looking at your data and examining your methods. In other words, an illusion built to support a preconceived position and distributed in a such a way as to prevent peer review.
So which dataset do we believe? Because even a single "source" dramatically edits the past. This is 1984 level stuff where data is simply outright changed with no justification, it just is - and a new crisis is manufactured out of whole-cloth that did not exist with the original data covering the exact same years.
The issue is that the models do NOT agree with the data, and that becomes problematic because the future catastrophes that are predicted (and used as justification for the latest and greatest round of taxation/regulation) rely upon the models, not the data.
So if the data doesn't show anything scary (in fact, we've had the exact same climate change in 1895 to 1943 as we saw in 1957 to 2005), then why the concern? Because the faulty models say their should be a concern. But since the models don't match reality - which do we believe? Data or models? Like the GP - I'll take the empirical evidence, thank you (and in fact, I'll take the unadulterated data that is tweaked to show a heating trend when there was, per the original data, a cooling trend).
And peer review did not catch the error, it took and independent, 3rd party individual looking at it, saying "that doesn't make sense", and running through the equations. In other words, it took a skeptic to actually check.
How about Anthony Watts? He's repeatedly shouted down as "not qualified" even though he's a meteorologist. He's shouted down because he's a skeptic. I don't know how many times I've seen links to scholarly papers AND actual checks (like from Mr. Lewis, here), on his site dismissed because "Watts is a denier and not a climatologist!:
How about Dr. Roy Spencer, an actual NASA climate researcher, who is dismissed because he's also a skeptic and religious (in particular, Christianity). But because he's a "denier" and crazy "sky god" worshiper, he's dismissed - doesn't matter about the factual nature of his data or his research.
And that "slight fault with the error bars" is a shift from +/- 0.18 to +/- 0.72, a full 400% increase in the error (meaning the error window itself is greater than the magnitude of the underlying baseline - meaning it's little more than a guess).
How much of that heating is man-made? If it's not at least 50% - then it's political, not natural. Do they address that? Does ANY model address natural climate change? The IPPC - by its very charter - ignores any natural impact on climate, assuming that all changes are man-made. If it's not man-made, but natural, then it's effectively out of our control, and thus demands we "must do something!" is simply a way of controlling what people do - because the solution is effectively out of our control.
So then, the claimed defense of "it's a peer reviewed report!" means little, and in fact a paper that is published - regardless of peer-review or not - should carry the same weight.
And that science - as we find with this report - is highly variable, with wide tolerances, and often reported incorrectly because of a desire to be political. When you look at the 95% confidence levels of most of these studies, you find the error bands are literally 2-3 times wider than the claimed "average" change. Meaning the same study that is used to "prove we have to do something!" really also states that there may not be any heating, but actually a small chance of cooling. We just don't know.
It it easier to say that the "temperature is up 0.23 deg C!" but it doesn't sound so bad when you say "the temperature is up between -0.1 deg C and 0.56 deg C!", does it?
The benefit of SS is also capped, based upon your contributions. Or are you saying we should continue increasing taxes but not increasing the benefits, more like a normal tax rather than a mandatory contribution retirement plan?
Which State is that? The most expensive is Vermont, and the average nationwide is $10,000 for tuition and fees. Live at home, or share an apartment/house for a few hundred a month.
$20K for college? What State do you live in? That's about double or more of what you can find. And a decent part-time job can cover a lot of the other costs...
And note that Social Security runs out of money by 2034 - just before the ratio reaches its lowest level, meaning that SS taxes will have to be significantly increased (fewer workers paying in AND no more "trust funds" available) because it will be political death to cut benefits.
I wish that Congress would lift the limits on IRA contributions - that would go a LONG way to making it easier to slowly reduce SS benefits over the next 20-30 years as people would be encouraged to save more of their own money up-front...
Slashdot Mirror
As Dr. Roy Spencer said, 95% of climate models agree the observations must be wrong. When data and models disagree - it shouldn't be the data that's tossed aside...
Explain this. Falling accumulated cyclone energy over the last 25 years. Go ahead, how does a model that predicts increasing cyclonic energy match actual measurements stating otherwise.
Too bad those assumptions and this paper do not match reality which shows the last 25 years having a decreasing trend in accumulated cyclone energy. When theory and assumptions conflict with data - data should win.
This reports is a hoax, yes. It uses "high resolution simulations" to reach its conclusions. Computer models. We have actual data that says otherwise. So which do you choose to believe? Models or data?
Cyclone energy isn't increasing. Tornadoes are trending down. And the temperature record only shows an increasing trend after heavy editing and "adjusting". The data doesn't support your claims or conclusions, but the models do. So which do you trust - data or models?
We have actual data that says accumulated cyclone energy is decreasing over the last 25 years. Why would you go with a simulation about what supposedly happened, when you can look at the actual data? This is part of the reason so many (including myself) are skeptical of the whole AGW things - it's based on models and projections, but the models don't match reality. If your model doesn't actually match what's happening, then I'm certainly going to give VERY little credence to your claims about what could happen.
Even then, you have to be aware of the "data" as it's presented, because often it is massaged a massive amount to turn a decreasing trend into an increasing trend. And even rewrite history. Simulations over data, data "corrected" to turn downward trends into upward trends, and historical values and records rewritten to "prove" the models. It's a house of cards built on shifting sand, and this paper is just adding another wing to that trembling structure.
One trend is from the late 19th century, the other from the late 20th century. Both have the same temperature pattern. One supposedly is caused by man's CO2 output, the other from nature. How do we know the impact of natural heating? We really can't control that level - it's a baseline change that happens and we may add or subtract from it - but we certainly can't control it...
That data is a bastardization of many alternate sites cherry-picked and blended to achieve the desired result. Just check the graph at the end of the article to see the "golden CRU data" from 5 cherry-picked trees, versus that of 34 trees from a different researcher. The former has a big upturn - the latter shows a gentle cooling.
The hockey stick that didn't exist unless you cooked your data, and then did everything possible to prevent anyone from looking at your data and examining your methods. In other words, an illusion built to support a preconceived position and distributed in a such a way as to prevent peer review.
So which dataset do we believe? Because even a single "source" dramatically edits the past. This is 1984 level stuff where data is simply outright changed with no justification, it just is - and a new crisis is manufactured out of whole-cloth that did not exist with the original data covering the exact same years.
The issue is that the models do NOT agree with the data, and that becomes problematic because the future catastrophes that are predicted (and used as justification for the latest and greatest round of taxation/regulation) rely upon the models, not the data.
So if the data doesn't show anything scary (in fact, we've had the exact same climate change in 1895 to 1943 as we saw in 1957 to 2005), then why the concern? Because the faulty models say their should be a concern. But since the models don't match reality - which do we believe? Data or models? Like the GP - I'll take the empirical evidence, thank you (and in fact, I'll take the unadulterated data that is tweaked to show a heating trend when there was, per the original data, a cooling trend).
And peer review did not catch the error, it took and independent, 3rd party individual looking at it, saying "that doesn't make sense", and running through the equations. In other words, it took a skeptic to actually check.
How about Anthony Watts? He's repeatedly shouted down as "not qualified" even though he's a meteorologist. He's shouted down because he's a skeptic. I don't know how many times I've seen links to scholarly papers AND actual checks (like from Mr. Lewis, here), on his site dismissed because "Watts is a denier and not a climatologist!:
How about Dr. Roy Spencer, an actual NASA climate researcher, who is dismissed because he's also a skeptic and religious (in particular, Christianity). But because he's a "denier" and crazy "sky god" worshiper, he's dismissed - doesn't matter about the factual nature of his data or his research.
And that "slight fault with the error bars" is a shift from +/- 0.18 to +/- 0.72, a full 400% increase in the error (meaning the error window itself is greater than the magnitude of the underlying baseline - meaning it's little more than a guess).
How much of that heating is man-made? If it's not at least 50% - then it's political, not natural. Do they address that? Does ANY model address natural climate change? The IPPC - by its very charter - ignores any natural impact on climate, assuming that all changes are man-made. If it's not man-made, but natural, then it's effectively out of our control, and thus demands we "must do something!" is simply a way of controlling what people do - because the solution is effectively out of our control.
So then, the claimed defense of "it's a peer reviewed report!" means little, and in fact a paper that is published - regardless of peer-review or not - should carry the same weight.
And that science - as we find with this report - is highly variable, with wide tolerances, and often reported incorrectly because of a desire to be political. When you look at the 95% confidence levels of most of these studies, you find the error bands are literally 2-3 times wider than the claimed "average" change. Meaning the same study that is used to "prove we have to do something!" really also states that there may not be any heating, but actually a small chance of cooling. We just don't know.
It it easier to say that the "temperature is up 0.23 deg C!" but it doesn't sound so bad when you say "the temperature is up between -0.1 deg C and 0.56 deg C!", does it?
I seem them starting at $11,000 per year. This doesn't include living on or off campus - live at home, save some cash.
Yes. No. Sometimes. If I pay you 15% more do I get 15% more code, or 15% quicker code?
Google is your friend.
The benefit of SS is also capped, based upon your contributions. Or are you saying we should continue increasing taxes but not increasing the benefits, more like a normal tax rather than a mandatory contribution retirement plan?
Then maybe not major universities? A solid 4 year university should be considerably less...
Which State is that? The most expensive is Vermont, and the average nationwide is $10,000 for tuition and fees. Live at home, or share an apartment/house for a few hundred a month.
$20K for college? What State do you live in? That's about double or more of what you can find. And a decent part-time job can cover a lot of the other costs...
And note that Social Security runs out of money by 2034 - just before the ratio reaches its lowest level, meaning that SS taxes will have to be significantly increased (fewer workers paying in AND no more "trust funds" available) because it will be political death to cut benefits.
I wish that Congress would lift the limits on IRA contributions - that would go a LONG way to making it easier to slowly reduce SS benefits over the next 20-30 years as people would be encouraged to save more of their own money up-front...
Don't forget Senator Diane Feinstein having to be reminded by her staff if she did or did not leak the Kavanaugh accusation letter...