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Comment on State of the blog discussion thread by Joshua
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Comment on State of the blog discussion thread by Joshua
For some reason I can’t post the part of my comment where I quote you. Bizarre. So I won’t quote you and just give the rest of my response:
Your discussion of the vaccine is irrelevant. The data he presents show that your conclusions about trust in scientists are meaningless because they are absent any context. Where is your evidence to show a drop in trust in scientists over time? For any drop in the public’s assessment of scientists’ integrity you can show, you need to show some evidence for the causality you described. If there was a change, who was it among? If it was among some demographics and not others, why is that the case? Did it increase in some while it decreased in others? Where do you show the assessment of integrity relative to other groups? Where do you show a change for scientists relative to change for other groups – wouldn’t you need that to support your stated causality? Has it dropped but still remains higher than in any other group? You don’t know. You don’t know any of that. Not one little bit of it.
You got nothin’’, yet you don’t allow that to stop you from formulating a conclusion. Never let the facts get in the way of a good story, eh?
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Comment on Asymmetric responses of Arctic and Antarctic by Wagathon
Climate research is a good example of science fiction (pop science?) in that the story always ends the way the author wants–i.e., in the service of the of reigning academic paradigms.
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Comment on Climate data and financial data: Part I by GaryM
What other graphs would show a steady rise, right to left, from the mid-19th century to the present?
Population
GDP of most western countries
Average building height in downtown Chicago
CO2 levels
Global average temperature
and many more.
Now try to come up with an investment strategy based on any of them, and invest to your heart’s content.
Selling such “information” in newsletters strikes me as evidence the author doesn’t have much confidence in his own product. Last I checked, Warren Buffett keeps his investment analyses pretty close to the vest.
As for the timing issue, my eyeballing of the last chart suggest this method shows some correlation between 11 of the last 20 drops in the S&P 500. Indistinguishable from a coin flip.
I am reminded of the old front page feature the Wall Street Journal used to have – three stock pickers each week against darts thrown at a dart board.
No analyst ever beat the darts regularly, nor would this method.
But I will say newsletters are safer than investing your own money, and far safer than using the same types of graphs to actually sell stocks and generate brokerage commissions – no fiduciary duty and less chance of getting sued for breach of such a duty, or fraud.
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Comment on Climate data and financial data: Part I by JCH
Rule 157 forced companies to mark to market in a panic. This was really really not too bright. This would be akin to playing Russian roulette with 6 bullets in the revolver. Macho, but point-blank stupid.
When they adjusted rule 157 so it made a bit of sense, the people who were panicked were really ticked off because, to be honest, they love to be panicked. And they’re probably still ticked off. I think it’s safe now to forever more ignore their ignorant butts.
And yes, one can claim that 157 went in place at the top of the market and was adjusted at the bottom of the market. They took 5 bullets out of the revolver and holy cow, people suddenly started surviving.
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Comment on Climate data and financial data: Part I by bpstojkovic
I have been running quant models for almost 14 years: “seeing” a correlation is dangerous since it is easy to trick yourself. It’s exactly as you said: you cannot trust it until you backtest it, i.e., until some number confirms it.
Once again, only a correlation in detrended data is meaningful: for any two data sets which can both be decomposed into trend + noise, there will always be a correlation, due to the correlation between the underlying trends. Thus, what you are proposing, with your “timing” of price direction, is precisely correlating the noise: let’s see how much, if any, of the correlation is preserved after detrending. The correlation does not depend on the volatility, so the overall amplitude of the noise term does not matter, but if you are worried, you can go non-parametric and compute rank correlation. In fact, if you want to point me to the data, I will do it myself.
Personally, I agree with one of the previous commenters: it may make more sense to look into the the correlation between the climate and the price of energy derivatives (heating oil, nat-gas) or grains. Or if one can predict the number of hurricanes in a season, than that may be used to forecast the profitability of the insurance companies.
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Comment on Asymmetric responses of Arctic and Antarctic by bpstojkovic
Is the geothermal heating in the Antarctic increasing for some reason? Why wasn’t it observed before?
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Comment on State of the blog discussion thread by thisisnotgoodtogo
John Carpenter said:
“It’s not an either or situation. There can be multiple utilities for tools. A hammer is useful for pounding nails, but it could also be used as a weapon. ”
Of course. But you were specifically replying as to that utility, and either you were hitting nails into wood or or hitting heads with hammer. So you can’t have it both ways at once. But nice try.
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Comment on Asymmetric responses of Arctic and Antarctic by Pierre-Normand
“Secondly, the second graph in the link I gave shows that the decline in ozone minimum ended around 1987, which is before the Montreal Protocol came into force.”
You responded “balderdash” to the claim that there was a dramatic depletion of stratospheric ozone in Antarctica since the late 70s. But now you are retreading to the claim the change is the depletion rate doesn’t coincide with the implementation of the Montreal protocol. The stratospheric chlorine ozone correlation seems very strong to me and your trying to exactly match inflection points is the noisy data is overfitting. But that changes nothing to the OP claim anyway. You also suggest that it’s more of a shift than a lineal decline. But the article cited in the OP also invokes the depletion as the cause of a shift in climate. So, that doesn’t contradict the OP either.
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Comment on Open thread by ianl8888
Until you make a prediction that requires some event or clear, measured trend that would NOT otherwise occur if CO2 < 400ppm, then AGW remains insignificant in empirical terms
Will you do so ? I didn't think so
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Comment on How ‘extreme’ can it get? by Ragnaar
What if the distribution changed in a warming climate to have a ‘snub nose’ on the right, rather than a tail?
Figure b) shows something interesting I think. The line is changing shape to give us more instability. The slopes are softening. I think it would make it more likely we can swap regimes.
The red blue distribution from the 3 graphs. Knowing the actual distribution would imply what’s going on. Has that been looked at?
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Comment on How ‘extreme’ can it get? by Matthew R Marler
Interesting post. I had not seen actual snub-nose distributions.
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Comment on Open thread by ianl8888
Thank you for your reply
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Comment on How ‘extreme’ can it get? by Matthew R Marler
A fan of *MORE* discourse: Higher temperatures *AND* higher humidity amount to a doubly-lethal consequence of climate-change, that temperature forecasts alone do not capture.
Football lunacy aside, that is an important point. Any increase in atmospheric CO2 that increases DWLWIR ought to increase both temperature and water vaporization, and the mix is to date unpredictable. With alternating warming and cooling, the 3.7 W/m^2 increase can not produce both the equilibrium temperature increase that has been calculated, and the equilibrium water vapor distribution; besides that, the hydrologic cycle increases so that heat is transported from surface to upper troposphere faster than accounted for in the models.
Empirical measurements definitely should inform this discussion.
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Comment on How ‘extreme’ can it get? by ianl8888
Pointless dilettantism, Jimmy old bean. Change is always occurring
It’s the size and attribution that matter, not your assumptions
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Comment on How ‘extreme’ can it get? by Ragnaar
Summer only unfortunately.
http://www.giss.nasa.gov/research/briefs/hansen_17/dice.gif
We do see falling stability – Snub nose.
Figure c) is the winner with more reds.
If this continues, in about 300 years the distribution will collapse.
What can make this change? That’s an interesting question.
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Comment on How ‘extreme’ can it get? by Steven Mosher
Control for obesity.
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Comment on How ‘extreme’ can it get? by A fan of *MORE* discourse
Global humidity anomalies trending upward … same as global temperature … ouch.
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Comment on How ‘extreme’ can it get? by Rud Istvan
Judith, as someone who now lives on the Atlantic in Florida, yet still runs a dairy farm in Wisconsin, these sorts of results matter a great deal.
I find them unpersuasive. There are a number of reasons. Model PDFs do not adequately describe the possible hurricanes, droughts, and late plantings I have to deal with annually using my checkbook.. They may describe the house odds in Vegas, but do little to help the practical decisions I must make annually about insurance and crops in order not to lose the farm to the ‘house’ (like hybrid corn time to maturity of the seeds we chose to plant, which ranges from 4 to 5 months (faster means less yield) but if guessed wrong means even worse yields.
And, results for NSW in Australia mean Butkus for southwestern Wisconsin.
And, as Pielke Sr has published, regional downscaling of GCMs is worse than useless.
So, when I see general statistical ideals/truisms with respect to probability distributions (as above) combined with highly uncertain model climatology, I react as farmers have always done. Hope last year won’t be that different than next year, and no matter what actually happens persevere.
A fancy way of saying that until somebody can reasonably forecast next year before it happens, us farmers will just continue with our no regrets conservative policies. Worked for hundreds of years. Even before CAGW.
And mostly ignore fancy model studies that pretend to have all this climate stuff figured out but without a lengthly historical validation.
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Comment on How ‘extreme’ can it get? by Faustino
Judith, you refer to Giles and Melbourne as “the two cities.” The following refers:
“Giles Weather Station (also referred to as Giles Meteorological Station or Giles) is located in Western Australia near the Northern Territory border, about 750 kilometres (470 mi) West-South-West of Alice Springs and 330 kilometres (210 mi) West of Uluru.[1][2] It is the only staffed weather station within an area of about 2,500,000 square kilometres (970,000 sq mi)[3] and is situated mid-continent and near the core of the subtropical jetstream. This means it plays an important role as a weather and climate observatory for the country, particularly eastern and southeastern Australia, and particularly for rainfall predictions. The station is on the Great Central Road and the nearest township is the Warakurna aboriginal settlement (population 180), 5 kilometres (3 mi) North. Giles is within the Shire of Ngaanyatjarraku and is in the foothills of the Rawlinson Ranges.
“A staff of three (reduced from 4 at the end of 2010) operate the remote station on six-monthly tours. A 1,600-metre (5,200 ft) airstrip services the station and the Warakurna community.[4]”
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