Marcus Hutchins Arrested – Guy Who Stopped “Wannacry”

This one has me bothered, but I’m not sure how much I ought to be.

The guy who found the “kill switch” in the “Wannacry” malware and potentially saved the world $Billions has been arrested by the FBI for “selling malware”. Now what isn’t clear is “to whom” and “for what purpose”.

This could be the moral equivalent of a master locksmith selling a pick kit to another locksmith, or it could be he sold it to a burglar. Who knows.

Since that isn’t known, and he’s been arrested anyway, the presumption must be that the US Government doesn’t care if you are working in the field of computer security and are a “good guy”, if you use or sell hacking ‘kit’ it gets you busted.

As a guy who worked in computer security, I can assure you it is essential for the “good guys” to get the ‘kit’ to understand it and defend against it. Now it looks like exchanging it with others gets you arrested.

There’s not a whole lot of good that can come out of this. One recent hero with skilz taken out of the White Hat pool, perhaps for past indiscretions or perhaps for just doing his job. How is this a good thing?

It has me wondering if I post an article saying, for example, “Do this byte shift with this code and you can take over a Windows Intel box”, am I now a criminal too? All I’ve done is show a risk to be closed, but is that exchanging “malware” and building “hacker tools”?

So guess what my behaviour, faced with that risk, will be? Right: STFU. Go dark. Take care of me and mine and screw everybody else, let them figure out how to protect themselves and what the risks are. So how is that helpful to others?

Also: Note to self – do NOT attend any hacker conferences in the USA. The USA is security guy hostile. Kiss off Las Vegas as a destination. At most, use foreign VPNs to have a telepresence from an untraceable location. In short, treat US Law Enforcement as Black Hats. Now that one really sticks in the craw as I’ve been on teams working with law enforcement against the real Black Hats.. but as of now, Law Enforcement must be treated as at least a Grey Hat, with suspicion, and only at a distance.

FBI Arrests Marcus Hutchins, Who Stopped WannaCry

Hutchins, aka “MalwareTech,” Accused of Creating Kronos Banking Malware

Mathew J. Schwartz (euroinfosec) • August 4, 2017

Many in the information security community have reacted with shock over the arrest of 23-year-old British citizen Marcus Hutchins, aka “MalwareTech.”

Hutchins was arrested Wednesday at the airport in Las Vegas by the FBI, as he attempted to return to Britain. He had been attending the annual Black Hat and Def Con information security conferences, although not presenting research at either event.

The arrest of Hutchins was an unexpected turn after he singlehandedly defused the WannaCry malware outbreak in May, after accidentally registering a domain name referenced in the malicious code. The move earned him folk hero status, not least because he’d apparently helped avert a ransomware disaster for Britain’s National Health Service. Hutchins, however, referred to himself as an “accidental hero” and said he’d preferred operating as an anonymous security researcher.

A six-count indictment, filed July 11, charged Hutchins and another, unnamed defendant – apparently based in Wisconsin – with various crimes associated with the Kronos banking Trojan.

The U.S. Department of Justice says in a statement: “Marcus Hutchins … a citizen and resident of the United Kingdom, was arrested in the United States on 2 August, 2017, in Las Vegas, Nevada, after a grand jury in the Eastern District of Wisconsin returned a six-count indictment against Hutchins for his role in creating and distributing the Kronos banking Trojan.”

Now it could be that Marcus was a Grey Hat who was working both sides of the fence. Creating malware and then profiting from defending against it. Or it could be that his “role” was that he sold copies to others for them to figure out how to defeat it, and the FBI just can’t make that fine a distinction. In my (limited) interactions with the FBI on cyber security, admittedly 30 years ago, I was not impressed. (Roughly: “We have a live attack in progress on a US Government Facility bouncing off our router. The attacker appears to be Russian.” met with “Oh, THE guy who handles that is on vacation, can he get back to you next week?” Really.) Hopefully they have improved a LOT since then.

he was arrested, relate to alleged conduct that occurred between in or around July 2014 and July 2015.” It adds that Kronos has been used to exfiltrate victims’ online banking credentials not just in the United States but also such countries as Canada, France, Germany, Poland, and the United Kingdom. In addition, it says the malware has been distributed via phishing campaigns, for example via the Kelihos botnet in late 2016.

So first off, this is from 2014 / 2015. Was he a Black Hat then, and reformed? If so, does that buy him nothing? Can no Black Hat EVER consider moving to the White Hat side?

Or was it already in existence and “circulating”, and he just set up a side business selling copies of it of known quality to others “in the business” of defending? IF that is the case, does this mean EVER using a dark net site brands you a criminal? What “get out of jail free card” do I need when doing such explorations for my employers (or LEOs or other agencies…), hmmm? I’ve run a phone number scanning operation looking for modems at a block of phone numbers including Federal Offices. That’s technically a crime. I was doing it under the direction of law enforcement officers and after filing my security clearance papers with The Fed. But what proof do I need now to show I’m not a Black Hat? If I publish the (trivial) script to do that scan, am I going to be arrested?

There’s just way more questions here than answers.

Hutchins appeared Thursday before U.S. Judge Nancy Koppe. A federal public defender, Dan Coe, told the court that Hutchins “had cooperated with the government prior to being charged,” Reuters reports.

Koppe ordered Hutchins’ hearing to reconvene Friday, to give the defendant time to retain defense counsel; he was detained overnight.

So they bust the guy, he’s cooperative and answering their questions, THEN they charge him? Note To Self: NEVER EVER COOPERATE. Say only: “Lawyer please”….

Non-profit digital rights group Electronic Frontier Foundation said it was attempting to make contact with the detained information security researcher. “This is the sort of thing that concerns us a lot,” the organization said in a statement.

Hutchins is an employee of attacker intelligence and information sharing platform provider Kryptos Logic. Officials at the company, which has not made any public statements in relation to his arrest, could not be immediately reached for comment.

Some legal experts have expressed concern at Hutchins apparently having spoken to the FBI without a lawyer present.

Concern? Concern doesn’t even come close. The FBI has now raised a giant “DANGER DO NOT ENGAGE” sign over their entire organization.

Now the details on Kronos make it unlikely, IMHO, that this is the guy who created it. It is of Russian origin and the “seller” was going by another handle. To me, it is more likely the FBI offered a ‘deal’ to the wrong guy and he’s pinning the gig on Marcus.

Kronos Banking Trojan

The indictment accuses a co-defendant – who has not been named – of having advertised and sold the Kronos banking Trojan, at least once, for $2,000 via the AlphaBay darknet marketplace.

John Miller, senior manager of analysis at cybersecurity firm FirEye, says that his firm “observed Kronos being advertised on an established Russian cybercriminal forum by the actor ‘VinnyK’ in June 2014.” But it’s not clear if that actor might be the unnamed co-defendant.

Hutchins, meanwhile, has been accused of helping to create Kronos.

Numerous details relating to the case have yet to come to light. But many in the security community have reacted with surprise over the indictment of Hutchins on charges of creating malware, since his job is to track and investigate malware, and help others stop it. The indictment’s linking of Hutchins to the Kronos malware – heavily researched by the security community – also remains an open question.

“Kronos is a Russian banking trojan, for info,” says British security researcher Kevin Beaumont on Twitter. “It looks like the U.S. justice system has made a huge mistake.”

So did “VinnyK” sell this kit in 2014, a White Hat Marcus buys it, and now is getting burned? Or did Marcus just resell something already in circulation to other White Hats?

So Russian kit, sold on a Russian forum, by a guy with a different name, now a potential ‘co-defendant’ or maybe the Black Hat tossing Marcus under the bus; this makes Marcus a bad guy how?

The original article as several links in it to more info. BTW, Wannacry was asking $300 to recover your data. It would take at least $100 of time to restore a system instead of paying the ransom. Figure 10 Million computers would likely be hit (or way more…) at $100 each and you’ve got a $Billion of costs avoided. Just for that alone the guy ought to be given a Lifetime Free Pass.

The German news has a bit different take on things, as they usually seem to do.

Arrest of ‘WannaCry’ buster Marcus Hutchins raises concern

Marcus Hutchins is credited for single-handedly stopping the WannaCry cyber attack in May, which affected computers in over 150 countries. He was detained by law enforcers before returning to London.

The 23-year-old security researcher Marcus Hutchins, who uses the online handle “MalwareTech”, was detained Thursday as he boarded a flight from Los Angeles back to the United Kingdom.

An indictment was issued against Hutchins and an unnamed co-defendant on July 12 in US District Court in the Eastern District of Wisconsin. Hutchins is accused of creating the Kronos malware, then advertising, distributing and profiting from it in activities between July 2014 and July 2015, according to the court.

So which is it: Did he write it, or was it a Russian kit?

Hutchins, who works for LA-based firm Kryptos Logic, was in Las Vegas around the time of the DEF CON and Black Hat hacking conferences, but didn’t plan to attend, according to The Outline. Hutchins and several acquaintances rented first-rate sports cars, held parties at their lavish apartment and went to a shooting range.

Hey, sounds like a typical conference in Vegas ;-)
What, you though everyone stayed in their rooms all day?

The case against Hutchins:

Orin Kerr, a professor of law at George Washington University, told the Associated Press news agency that it remains a consistent problem in legal circles when malware is only created and sold – and not for greater crimes. “This is the first case I know of where the government is prosecuting someone for creating or selling malware but not actually using it,” he noted.

Kerr also wrote a lengthy explanation in a Washington Post op-ed about the challenges for the Justice Department in presenting a robust legal case for creating and selling malware. “My sense is that the government’s theory of the case is fairly aggressive. It will lead to some significant legal challenges,” he wrote.

There are a whole bunch of Professors who ought to be crapping their pants about now if making ‘malware’ becomes a crime in its own right. The common pattern is someone finds a bug, builds and exploit, then tells all the White Hats and provides sample code. That is, by definition “building and distributing malware”. BUT, if that is forbidden, it doesn’t stop malware from happening, it stops the FIX and PATCH from happening. It leaves the door wide open for the Black Hats to exploit with no ability for the White Hats to know, or fix it.


Kronos malware downloaded from email attachments left victims’ systems vulnerable to theft of banking and credit card credentials, which could have been used to siphon money from bank accounts.

The indictment alleges that the unidentified co-defendant advertised the Kronos malware on AlphaBay, a dark web marketplace
that international authorities took offline last month. Investigators said the site allowed anonymous users to facilitate global trade in drugs, firearms, hacking tools and other illicit goods.

The Justice Department said Kronos was used to steal banking systems credentials in Canada, Germany, Poland, France, the United Kingdom and other countries.

Within the cyber security community, Hutchins was heralded as a folk hero for his apparent role in stopping the WannaCry attack, which infected hundreds of thousands of computers and caused disruptions at car factories, hospitals, shops and schools in more than 150 countries.

So someone else sold it… yet Marcus is getting the ‘take down’? Sure smells to me like a ‘deal’ cut by someone in the nutcracker to get the screws backed off. What better than to get reduced heat AND toss a White Hat under the bus too…

One would need to know that actual relationship between Marcus and “the co-defendant” to know if criminal intent existed for Marcus, or was he just sharing some ‘kit’ with a fellow White Hat who turned out to be more Grey Hat?

So much more information needed than is available. I’m reserving judgment until more is known, but my preliminary leaning is that this is a case of Legal Overreach (not quite on a par with Waco, but getting there…) with FBI Hot Dogs trying to make a name for themselves and impress the boss, while not “getting it” about how computer security culture and methods work and are distributed. We MUST engage with The Dark Side to find out what they are doing and what kit is about to hit us. We MUST share known hacks, cracks and ‘kit’ to propagate “sources and methods” faster than the Bad Guys. Hell, I’ve got a program for the Pi that is specifically designed to crack into WiFi Hot Spots. Disney had a team dispatched to roam the entire park and property looking for clandestine Hot Spots just to assure their own gear was secure against known attacks. Was the whole Disney Computer Security Team made criminals by getting and deploying that “Tiger Team” gear? If defending your own gear becomes a criminal act, the result is not going to be pretty.

Yes, I’ll be watching this one closely.

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Posted in Tech Bits | Tagged , , , , , | 9 Comments

More “data” than the Data – The Stupid, It Burns…

So in “tips” was a line from Larry (h/t Larry) that I actually ended up following from a cross post by Another Ian (h/t Ian) at Jo’s place:

pointed me back at, well, me… and this:

That sent me off to:

which is well worth reading, though I had a bit of an “upchuck moment” at:

Scientists said supercomputer modeling could have predicted the flooding. Thompson said the supercomputer “simulations provided one hundred times more data than is available from observed records.”

Oh, the Stupid, it is strong in them…

100 times more “data” than in the actual Data.

I fear there is nothing that can be done to cure that level of Stupid. Perhaps a whole generation will need to be assigned to “doggy dooly patrol” pending their recovery.

Let me make it perfectly clear:

Computer Model OUTPUT IS NOT DATA. It is not, never was, and CAN NOT BE DATA!!!. EVER.

It is a computer generated fantasy product. It is “data food product”. It is Phantasy Football Crap.

Computer fantasy IS NOT REAL.

Oh God, I feel the need for more Tequila coming on… I know of no other way to dampen the burn from this much Stupid On Parade…

To quote someone or other:
“We give these people computers and expect them to know how to use them”…

I’d also add Smith’s Math Corollary:
“We give these people math and statistics and expect them to know how to use them!”.

Is there no intelligent life in Academia?

It would seem not…

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Posted in AGW Science and Background, Global Warming General | Tagged , , | 25 Comments

Why Economists Study “Climate Science”, Uncertainty, Interest Rates, and A Crash

This is going to be a long, and somewhat complicated post. I’m going to be looking, very very briefly, at some of the more difficult topics in Economics, tying them to “Climate Science”, and then taking a look at the current state of Bond and Stock markets, then asking a pointed question about how markets crash. I’ll try to keep it as brief and attainable as possible. (That is, this is to be a ‘popular piece’ to the extent I’m able.)

Economists & Economic Theory History

I can’t imagine a heading more likely to cause folks to run away screaming. Economics is named “The Dismal Science” for more than one reason. Then “History” is often worse. Now blend in “Theory” and looking at the “History of Economic Theory” has got to sound like having your teeth pulled while being lobotomized without anesthesia. But please, give it a chance. I hope to make it clear and at least a little interesting.

The basic point is just that Economics is a Social Science in that it studies human behaviour. People are unpredictable, and sometimes irrational, so predicting them is extremely hard. When will the next dictator arise? How long until Venezuela collapses? Will the USA continue to embrace the Progressive Socialist path into a Grand Venezuela, or will Trump “turn it around”? It simply is not possible to know or predict. It is Uncertain.

This is different from a statistical distribution. We can’t be “20% New Dictator” in some country. Yet for some of it, you can have a distribution. You can get “20% Progressive Agenda”. How do you sort out the uncertainty from the probabilities, and how do you predict / project / model them? That kind of stuff has been at the core of Economic Theory for about 100 years (or perhaps even more, depending on how you look at some early Economic Theory … the problem was certainly there from the start.)

So Economics and Economists have a special perspective on uncertainty, having it thrust in their face for all of their academic training and subsequent study. When we see what is done in “Climate Science”, it just shouts to us a bit “Oh No!!! We tried that and it is WRONG! You are missing the Uncertainty Problem!!!”

From lousy error bands, to linear regression of cyclical things to linear regression of chaotic things to linear regression of unknown things to assumptions of stability in things unknown, or worse, known to be unstable; and more. It all just screams at us “We’ve been there, run away NOW! as here their be Uncertainty Dragons!!!”

Over at Judith Curry’s place, I found an excellent article on just this topic (while searching for more of Javier’s stuff… It’s generally a great place to go fishing ;-)

I don’t know as I’d call it “non-orthodox” economics, being as Keynes is involved, but hey, “New Math” is from a few hundred years ago too…

So I’m going to quote chunks of it, and add some commentary, but folks really ought to read the whole thing. It has much clue in it, just waiting for folks to pick up the gems.

The Uncertainty Monster: Lessons From Non-Orthodox Economics
Posted on July 5, 2017 | 129 Comments

by Vincent Randall

A perspective on economists’ grappling with the ‘uncertainty monster.’

In this essay I am going to try to introduce non-economists who work in fields where they are first coming into contact with the ‘uncertainty monster’ – as Judith Curry calls it – to what some economists have learned from their encounter with it. First I will try to explain why economists encountered the monster before others working in different disciplines. Then I will try to give the reader an overview of what different economists have said about it. Then finally I will briefly consider the differences and similarities between how economists are confronted with the uncertainty monster and how those working in ‘harder’ sciences, like climate science, are confronted with the uncertainty monster. There are definite differences and definite similarities.

I like that name, “The Uncertainty Monster”. It certainly is a monster. This is what Rumsfeld called “the unknown unknowns”, mostly, but to some extent also the “known unknowns”. Things like “What causes the Thermohaline Circulation to halt?”. Some folks claim it is a flood of fresh water into the northern latitudes. Perhaps for some of the halts, but not all. We know that the heat backs up in Florida and Europe freezes and it happens many many times. We don’t really know why. it is a hypothesis that glacial melt causes it. At other times there is no such event. In large part it looks like a chaotic and unpredictable switch of the Gulf Stream. Yet there are periodicities in it that may point to a tidal trigger and lunar 1800 year position changes. It is highly “Uncertain”. When, why, how. All major uncertainties. Is it happening now? The THC has slowed some; will that continue? It isn’t a probability distribution, it either will, or it won’t, and we have no basis for saying which or how much. All we have is speculation in the face of uncertainty.

In economics, and the history of it, you learn mostly what grave errors were often made by other economists in creating their theories. You learn to be very very skeptical that any of it is right, and more skeptical that what is right is precise or persistent. (I.e “things might change”… because people change…)

So yes, The Uncertainty Monster has plagued Economics and Economists for decades, maybe even centuries. We’re uniquely steeped in it. So when we see it blithely ignored by “Climate Scientists” and swept under the rug, well, let’s just say we get that creepy spider skin crawling feeling… and we want to shout “Beware Of Arrogance!”.

Keynes concludes that this means that a lot of economic activity is determined not by calculation of probabilities or anything like it. Rather it is determined by the state of confidence.

It would be foolish, in forming our expectations, to attach great weight to matters which are very uncertain. It is reasonable, therefore, to be guided to a considerable degree by the facts about which we feel somewhat confident, even though they may be less decisively relevant to the issue than other facts about which our knowledge is vague and scanty. For this reason the facts of the existing situation enter, in a sense disproportionately, into the formation of our long-term expectations; our usual practice being to take the existing situation and to project it into the future, modified only to the extent that we have more or less definite reasons for expecting a change. The state of long-term expectation, upon which our decisions are based, does not solely depend, therefore, on the most probable forecast we can make. It also depends on the confidence with which we make this forecast — on how highly we rate the likelihood of our best forecast turning out quite wrong. If we expect large changes but are very uncertain as to what precise form these changes will take, then our confidence will be weak.

You could look at “state of confidence” as “how wide are the error bands?”, but it is a bit more than that. Error bands show up when you have decent statistics. Confidence is when you are doing that, but also ‘guessing’ about the future. I make a guess that I’ll be alive in 10 years when I build a factory or decide to buy a new home in a new State, but there are no error bands known to me. The entire insurance industry is built around finding those probabilities on a herd basis, but that can tell me nothing about the only thing that matters to my decision; my actual future. It is a guess about an error band…

Yet that drives most economic activity in the long term. Over a year or two out, we are all guessing. Will North Korea nuke Hawaii? Will ISIL get their Caliphate established? Guesses all. Yet we must decide to build a factory, vacation in Hilo, or enter long term oil contracts with Iraq.

A dummies guide to uncertainty in economics

First up is Keynes himself. We have already seen how Keynes introduced the concept into economic theory. But he also did some work on the implications uncertainty had for econometric modelling – that is, the use of mathematical and statistical models to try to predict future economic outcomes. Keynes addressed this in his paper ‘Professor Tinbergen’s Method’, written in 1939. The ‘Tinbergen’ in question was Jan Tinbergen, a Dutch economist who pioneered multiple linear regression modelling. Keynes had actually written an entire book on probability and statistics where he advanced a theory of probability that integrated uncertainty. This is too complex to look at now but interested people should get their hands on a copy of ‘Treatise on Probability’.

Keynes lays out some of the issues with statistical modelling in his Tinbergen paper. For example, he makes clear that…

Put broadly, the most important condition is that the environment in all relevant respects, other than the fluctuations in those factors of which we take particular account, should be uniform and homogeneous over a period of time.

Now most people will be taught in statistics class that the coefficients in a multiple linear regression can only be taken at face value if we assume that the statistical model is complete. That is, that all relevant variables have been included in the model. But as most people know, in practice most people do not follow this rule. But they should and the fact that they do not probably means that we should take what they say with more than a pinch of salt.

So first off notice that this was a ‘hot topic’ in Economics back in 1939. We’ve been at this a while…

Next, that key line ”

the most important condition is that the environment in all relevant respects, other than the fluctuations in those factors of which we take particular account, should be uniform and homogeneous over a period of time.

Yet we know the climate environment is anything but uniform and homogeneous over time. It is chaotic (in the mathematical sense), changes in step functions for no known reasons, has modes of oscillation of scales from months to years to decades to centuries, and has a long history of dramatic and unexplained changes. From the Younger Dryas, to a few dozens (hundreds?) of stadials, interstadials, glaciations, interglacials, D.O. events, Bond Events, Heinrich Events and more.

Stadials and interstadials are phases dividing the Quaternary period, i.e., the last 2.6 million years. Stadials are colder periods and interstadials are warmer. Each phase has a Marine Isotope Stage (MIS) number, working backwards from the present, with stadial having even numbers and interstadials odd numbers. Thus the current Holocene is MIS1 and the Last glacial period is MIS2. Stages are divided into warmer and colder intervals. MIS 5e (the Eemian), the hottest of the last million years, was the oldest interstadial of MIS5, with MIS3 and MIS1 being interstadials and MIS2 and MIS4 being colder stadials. In glacials a and c are stadials and b and d are warmer interstadials. Thus MIS 6a, 6c and 6e are stadials and 6b and 6d are interstadials.

Generally, stadials endure for a thousand years or less, interstadials for less than ten thousand years, interglacials for more than ten thousand and glacials for about one hundred thousand. The Bølling Oscillation and the Allerød Oscillation, where they are not clearly distinguished in the stratigraphy, are taken together to form the Bølling/Allerød interstadial, and dated from about 14,700 to 12,700 years before the present.

Greenland ice cores show 24 interstadials during the one hundred thousand years of the Wisconsin glaciation. Referred to as the Dansgaard-Oeschger events, they have been extensively studied, and in their northern European contexts are sometimes named after towns, such as the Brorup, the Odderade, the Oerel, the Glinde, the Hengelo, the Denekamp, etc.

It just shouts at us to ask “How can that be called uniform and homogeneous over a period of time? Eh?”

At that moment, the entire edifice of “Climate Science” looks like so much hokum and bunk to anyone who has had to spend a few years wrestling with The Uncertainty Monster and wrongly done linear regressions.

IMHO, that is the sort of thing that slaps many Economists across the face and is the reason why you find many of them participating on the Skeptical side of the Climate Wars.

Another problem that Keynes highlights in the paper is as follows:

For, owing to the wide margin of error, only those factors which have in fact shown wide fluctuations come into the picture in a reliable way. If a factor, the fluctuations of which are potentially important, has in fact varied very little, there may be no clue to what its influence would be if it were to change more sharply. There is a passage in which Prof. Tinbergen points out (p. 65), after arriving at a very small regression coefficient for the rate of interest as an influence on investment, that this may be explained by the fact that during the period in question the rate of interest varied very little.

Keynes’ criticism is as fresh today as it was in 1939. Because we have no access to repeatable controlled experiments the model is limited by the actual variability in the historical data. The relationship between one variable and another variable may not be linear. The coefficient may rise massively past a certain point. The example of the interest rate is a good one. If the interest rate only move within the bounds of one or two percentage points in a sample its impact on investment will probably be minimal or non-existent. A regression would tell us this. But if the interest rate was then raised in an unprecedented way – say, by 15% — then the impact on investment could be enormous. This actually happened in 1979-1980 when the interest rate was raised from around 10% to just over 17%. Investment crashed and the economy went into recession.

CO2 anyone? Though with CO2 we do have something of a prior natural experiment. It has been far far higher in the geological past and there was no thermal runaway. Often it could get fairly cold with high CO2 levels. For most of the history of planet, CO2 levels were far higher, yet here we are. That, alone, ought to be enough to falsify the CO2 hypothesis.

But the more important point is just this: We do not know all the variables and how they interact. We can not say that something that was “always a constant” didn’t, in fact, have a mode of change we didn’t know about.

Recently, we got proof of that as a real issue. The Sun went very very quiet. Total Solar Irradiation (TSI) didn’t change much at all, but the spectrum shifted. Far far less Extreme UV and UV, a lot more red and infra-red. Then the unexpected happened: The atmosphere got shorter. Same mass, just not puffed up as much. This causes all sorts of collateral changes. We moved from a Zonal Flow to a Meridional Flow jet stream. Cloud number, size, and distribution shifted. Storm tracks moved. We’ve got much increased flooding all over the planet. Precisely timed to the solar shift (yet Climate Junkies claim it must be CO2, despite no coincident change of CO2 and no such issues in the prior 30 years of CO2 Panic Mongering). So this is an existence proof of a variable we didn’t know about, with major impacts and nonlinear interactions. Just the kind of thing Keynes was talking about.

Currently our temperature data, globally, is far far too sparse, variable in quality, full of dropouts (holes in the data) and too manipulated in a variety of ways to be usable for much. A huge effort has gone into creating statistical manipulations to try to overcome the demands of Nyquist and fabricate meaning out of nothingness. Yet that is based on a completely broken set of assumptions and even has the physics wrong. You can NOT average temperatures in different places or with different air masses and derive any meaning as a temperature or heat content from the result. It is an intensive property.

That means that even our notion of what the present “Global Average Temperature” is, or what it ever was in the past, is an unknown and unknowable thing. It isn’t a statistical probability, it can not be made more accurate by averaging. You can reduce error by averaging measurements of the same thing but only for random errors. You can not reduce error of systematic errors by averaging nor can you reduce errors in the actual temperature by averaging temperatures from different places or times (as the air mass changes physical state – things like dew point).

Yet exactly that is used as the foundation stone for ALL of the panic over “Global Warming”. A simple statistical fraud, at best, horridly failed understanding of physics at worst. (Yes, I consider it a worse failing to not know enough physics and statistics to get them right; since anyone can be paid enough to commit fraud and that is only a failure of ethics, not ability.)

But now look at it in the context of The Uncertainty Monster: It is all about attempting to erase uncertainty by false methods. You can NOT erase the uncertainty in cloud formation and extent via averaging thermometers. You can NOT erase the uncertainty in the error bands of thermometer readings from 1950 via averaging them together (intensive property, after all, and systemic error issues). It just screams out for rejection as it is claiming to have slayed the Uncertainty Monster via methods known to be wrong and failed.

Do note, in the example above, the reference to interest rates making an unexpected excursion from prior experience. We’ll come back to that in modern terms below. Then it was a spike high. Right now, we are beyond historically low. Both “Uncertainty” flags. So how to decide in that context, eh? Greenspan was on CNBC today “admiring the problem”.

Returning to the Uncertainty page. This is a long quote, but important to keep intact:

The next economist to deal extensively with uncertainty was GLS Shackle. Shackle tried to further integrate uncertainty into economic theory in books like Epistemics and Economics: A Critique of Economic Doctrine. That may not be of too much interest to non-economists but he also made some interesting points about uncertainty more generally. He was especially interested in the issue of decision-making under uncertainty – which he understood to be entirely different to decision-making in the face of a probabilistic or ‘risky’ future. He thought that decisions in the face of uncertainty were unique as they are often required but there is no definite way to approach them. From his book Epistemics and Economics: A Critique of Economic Doctrine:

To be uncertain is to entertain many rival hypotheses. The hypotheses are rivals of each other in the sense that they all refer to the same question, and that only one of them can prove true in the event. Will it, then, make sense to average these suggested mutually exclusive outcomes? There is something to be said for it. If the voices are extremely discordant, to listen to the extreme at one end of the range or the other will have most of the voices urging, in some sort of unison, a turn in the other direction. ‘The golden mean’ has been a precept from antiquity, and in this situation it will ensure that, since the mass of hypotheses will still be in disagreement with the answer which is thus chosen, they shall be divided amongst themselves and pulling in opposite directions. Moreover, the average can be a weighed one, if appropriate weights can be discovered. But what is to be their source? We have argued that statistical probabilities are knowledge. They are, however, knowledge in regard to the wrong sort of question, when our need it for weights to assign for rival answers. If we have knowledge, we are not uncertain, we need not and cannot entertain mutually rival hypotheses. The various hypotheses or contingencies to which frequency-ratios are assigned by statistical observation are not rivals. On the contrary, they are members of a team. All of them are true, each in a certain proportion of cases with which, all taken together as a whole, the frequency-distribution is concerned. Rival answers might indeed be entertained to a different sort of question, one referring to the result of a single, particular, ‘proper-named’ and identified instance of that sort of operation or trial from which the frequency-distribution is obtained by many-time repeated trials. But in the answer to a question about a single trial, the frequency-ratios are not knowledge. They are only the racing tipster’s suggestion about which horse to back. His suggestions are based on subtle consideration of many sorts of data, including statistical data, but they are not knowledge.

I have quoted Shackle at length to give the reader a sense of how reading his work might be a useful guide to making certain decisions that are encountered with some regularity in climate science. Epistemics and Economics is partly about economic theory but it is also a book devoted to how rational people can make decisions under uncertainty.

The key bit being the punch line at the end:

But in the answer to a question about a single trial, the frequency-ratios are not knowledge. They are only the racing tipster’s suggestion about which horse to back. His suggestions are based on subtle consideration of many sorts of data, including statistical data, but they are not knowledge.

That is exactly the problem with Climate Models. They are just automated tip sheets.

The next economist that may be of interest is Paul Davidson. Davidson highlights the fact that economics is a ‘non-ergodic’ science. By ‘non-ergodic’ he means that the future does not necessarily mirror the past; just because x happened in the past does not mean that x will happen in the future. He writes:

Logically, to make statistically reliable probabilistic forecasts about future economic events, today’s decision-makers should obtain and analyze sample data from the future. Since that is impossible, the assumption of ergodic stochastic economic processes permits the analyst to assert that the outcome at any future date is the statistical shadow of past and current market data. A realization of a stochastic process is a sample value of a multidimensional variable over a period of time, i.e., a single time series. A stochastic process makes a universe of such time series. Time statistics refer to statistical averages (e.g., the mean, standard deviation) calculated from a single fixed realization over an indefinite time space. Space statistics, on the other hand, refer to a fixed point of time and are formed over the universe of realizations (i.e. they are statistics obtained from cross-sectional data). Statistical theory asserts that if the stochastic process is ergodic then for an infinite realization, the time statistics and the space statistics will coincide. For finite realizations of ergodic processes, time and space statistics coincide except for random errors; they will tend to converge (with the probability of unity) as the number of observations increase. Consequently, if ergodicity is assumed, statistics calculated from past time series or cross-sectional data are statistically reliable estimates of the statistics probabilities that will occur at any future date. In simple language, the ergodic presumption assures that economic outcomes on any specific future date can be reliably predicted by a statistical probability analysis of existing market data.

Or, simply put, the assumption is that “past is prologue”… yet we know it isn’t. This puts the kibosh on the whole modeling deal.

Did the past predict the Younger Dryas? How about “1800 and froze to death”? The hot 1930s, did they predict the cold 1970s? Those cold 1960s and 70s when we were being told to “Be Afraid, Be VERY AFRAID of the coming Ice Age Now!!!”; did they predict the hot 90s and the flat ’00 (oughties or naughties? ;-) ?

The simple fact is that climate, like weather, has a large chaotic component, so it is not ergodic.

Past is not prologue, and time series analysis does not predict the future. This matters rather much more than has been considered.

He also makes the case – and this is of interest to those in other sciences – that non-ergodicity may apply to systems that are very sensitive to initial conditions. That is, systems which are commonly referred to as ‘chaotic’ today.

That is a rather classic description of weather, climate, and climate models: “very sensitive to initial conditions”. Now mix in that the computer models have lots of tuned parameters, have feedback loops of unproven accuracy – so subsequent steps “initial conditions” can have lots of stochastic jitter in them compared to reality – and you have a recipe for the statistical junk that are the present “Climate Models”.

Think “statistical junk” is too harsh? Well, it is based on good theory and a long history of bad practices:

The next economist that merits mention is Tony Lawson. Lawson has gone right back to basics to try to tackle the aspect of uncertainty in economics. He makes the case that recognising uncertainty requires the economist/scientist to occupy an entirely different ontological position – that is, they have to view the world in an inherently different way to the way their uncertainty-free colleagues do. Lawson’s work is massively complex and attempts to build up new epistemological and ontological foundation through which scientists can access truths in the face of uncertainty. I will try to give the reader something of a flavour here. Much of this rests on Lawson’s attack on mathematical modelling as the end goal of science. Lawson claims that only ‘closed systems’ – that is, systems that are both deterministic and in which we fully understand the determinates driving the system – can be mathematically modelled in any serious way.

At this point I’ll leave off the long quotes. Since “massively complex” not being well suited to “simple and attainable”. Folks wanting a deeper dive can hit the link and read more. At this point I think it is pretty clear that Economists are not just looking at pennies and trade, and have a long history of looking at math and models.

When I chose Econ as my major, there was no “Computer Science” degree offered at UC. There as Electrical Engineering – heavy in hardware and thermo, Math Major – with a minor in computer stuff but mostly dense math theory, or Economics – that had a lot of accounting, data collection, and econometric modeling use of computers and some pretty easy theories to learn. I chose Econ (since it can sort of be sold as a quasi-business degree) and proceeded to take a slew of computer classes. FORTRAN, ALGOL, COBOL, Biomedical Applications of Computers, and more. The point? Economists have been at this whole computer modeling thing way longer than “Climate Scientists”, even before there were Computer Science Majors from UC…

The “put downs” of Economists who look into the math and modeling of “Climate Science” just shows how ignorant they are of Economics AND the history of computing. And how entirely devoid of appreciation of the Uncertainty Monster they really are. They have about 75 years of catching up to do to get where Economists are today on Uncertainty and modeling. (A good first step would be dropping the hubris and arrogance and doing a bit of modest introspection… thinking “perhaps, just maybe, I might be wrong. What alternatives are there?”)

Interest Rates

Remember that up above, there was mention of a time when US interest rates suddenly and unexpectedly moved up to near the 15% to 17% level. Prior to that, historical considerations said interest rates ought to be stable and dull. “Something changed”, but it isn’t clear really just what.

Sure, Volker raised rates, but The Fed is a reactive organism. It was reacting to “inflation”. But what caused the inflation? Was it going off the gold standard? Massive spending on the Vietnam War? The Baby Boomers creating giant demand in excess of supply? The end of the post W.W.II “Economic Miracle” as the rest of the world got into the manufacturing business too? Some mix of it all?

It really IS an interesting question of just what, or who, sets interest rates. Right now, The Fed is saying they are “data driven”, so have left interest rates near zero for a fairly long time. The BOJ (Bank Of Japan) has had a ZIRP (Zero Interest Rate Policy) for longer, and the EU with more volatility ended up in the same place. IF interest rates were really determined by Central Banks, why have they varied so much and why have they ended up in the same place?

I would assert that The Fed is just a slow and warped mirror of general economic productivity. More economic growth and consumption lead to more demand for money so higher interest rates to convince folks to “save more, consume less” right now. When folks have lots of spare cash (due in part to not consuming) interest rates drop as they all try to buy the same limited investment instruments. In both cases, the Central Bank reacts.

Now that reaction can be good or bad. They might prints tons of money (literally, tons of it…) and cause lots of excess demand leading to shortages and inflation, and eventually higher interest rates. They might be “austere” and keep money tight, leading to a drop of building, hiring, and eventual deflation and lower interest rates. But can they really change the starting base to which they must respond?

The accepted theory is the Keynesian (in some variations) that the level of money and interest rates can change the real economy, but even Keynes himself said it was only in a short 1 or 2 years that could work, then the real economy would dominate the monetary. Assuming Keynes was more right about his own theory than the folks who have followed him (and ignored his advice about short term only); this implies strong limits on what Central Banks can ultimately achieve. Which implies similar limitations on how much they can ‘set’ interest rates.

Is it enough to change an established trend? I think the most we can say is “maybe”. Volker did many things, and interest rates was only one of them. Changes of money supply and a new President with a growth agenda likely did as much, or more, to shift direction of the economy.

So right now we’ve got folks stressing over interest rates being “historically low” with Greenspan on CNBC saying that they can only go up from here (so implying a crash of the Bond Market on the cards, while denying any possible urgency in the timing or prediction of a pending event… typical Greenspan doublespeak.) Yet we are at historically low interest rates.

This has folks with access to major credit (i.e. only the very rich) borrowing like crazy and building all sorts of things in Silicon Valley. Whole neighborhoods being bulldozed and replaced with “Agenda 21” style blocks of 4ish story or more apartments over retail centers – so you don’t need a car… which everyone has anyway… since we can’t all work in retail at home. Yet the economy isn’t going gangbusters. It has an effect, but not the intended one. What the interest rates giveth, the tax rates taketh away…

Greenspan: ‘Abnormally Low’ Rates Will Pop Bond-Market Bubble

By F McGuire | Friday, 04 Aug 2017 09:04 AM

Former Federal Reserve Chief Alan Greenspan warned that “abnormally low” interest rates will pop a bubble in the bond markets.

“The current level of interest rates is abnormally low and there’s only one direction in which they can go, and when they start they will be rather rapid,” Greenspan told CNBC.

Since December 2015, the Fed has approved four rate hikes, but government bond yields remained mired near record lows, CNBC explained.

“I have no time frame on the forecast,” he said. “I have a chart which goes back to the 1800s and I can tell you that this particular period sticks out. But you have no way of knowing in advance when it will actually trigger,” he said.

“It looks stronger just before it isn’t stronger,” he said. Anyone who thinks they can forecast when the bubble will break is “in for a disastrous” experience.”

So while admitting that he can’t predict it either, he’s predicting. OK, got it…

But that ties back to the whole non-ergodic issue. The past is NOT prologue!

WHY are interest rates so low, despite The Fed?

Could it be that we’ve trained an entire generation NOT to trust the stock market and the Financial Sector?

Perhaps it is the $TRILLIONS shipped to Japan and China and Oil States all looking for a place to stash their cash that is not subject to their own economies, voters, and rulers? (Special Mention for the EU putting up a big “DO NOT PUT MONEY IN EU BANKS!!!!” sign in how they handled Cyprus… )

Maybe it’s just that a large demographic bubble of “boomers” is heading into retirement and the “rules” say to reduce risky stocks and buy bonds then.

Does The Fed control the demographics, the foreign investors, or the emotional state of the population? Eh?

Will any of those things “suddenly change”?

Or maybe it is just that any increase in money income is going entirely to the top few percent, and they can’t spend it all and have run out of reasonable investment opportunities as the other 95%+ have already spent all their money and just can’t spend more. Have to put all the chips somewhere…

Could it be that any physical investment in real plant, equipment, and jobs is happening in CHINA? Hard to make our economy move (and thus interest rates rise) when competition is getting all the investments, jobs, income, etc. etc. etc. Make interest rates near zero and watch the factories being built in China…

Then again, perhaps driving regulations through the roof, making energy so expensive you can’t cool your home nor drive to work, and making illegal many occupations isn’t all that good for economic growth, so not much demand for loans. Then again, it could be the draconian swing to near ZLP (Zero Loans Policy) driven by Dodd Frank legislation as they drove the laws way too far into ‘strangulation’ as they realized their prior policy of “free money and houses for everyone” was daft and lead directly to the Financial Meltdown.

The point here is pretty simple. Greenspan is making a non-prediction prediction based on a quasi-ergodic belief system. Many external things can cause an economic stagnation, forcing rates to stay low, The Fed be damned. Prime among them being the Progressive Socialist Stagnation from way too many laws, regulations, Social Justice (an oxymoron…) Programs, fuel and electricity price skyrockets, taxes, and more that all act to strangle the Real Economy of actual investment in physical plant, equipment, and labor. First it stagnates. Eventually they go for massive money printing and ‘wealth distribution’ and then you get hyperinflation… followed by extreme economic collapse.

So just what In The Real World says that is all being changed or reversed? I’m just not seeing it. Trump is trying, and making some progress, but the counter force is huge. IMHO, it all comes down to a bet on Trump winning or not. If he can’t get the crap out of the economy, and large numbers of the rich and powerful do NOT want to give up their slice of mandates and subsidies, it isn’t going to change.

So what do I see in chart data?

TLT bond fund vs SPY, GLD, and The Euro, August 2017

TLT bond fund vs SPY, GLD, and The Euro, August 2017

Nothing changing.

Now Greenspan is correct, nothing changes until it does. But this could be days, or decades.

SPY The S&P 500 continues a slow slog upward, along with bonds. All those rich folks have to stick their money somewhere and The Fed is giving them lots of it to stick. That hasn’t changed.

Gold is down from the peak, had a Dead Cat Bounce, and is now in the relaxation / stability run out.

News of “Dollar Weakness!” mostly looks just like the slide of the Euro et. al. has stopped and a bit of bounce at their bottom. More 3 months of stability than anything else.

TLT has roughly constant volume. Most notable being that it is higher than 8 or 9 years ago. More folks looking for security than yield. MACD and DMI both saying an OK time to be in, but not particularly going to make a bundle. It is down from the just prior wobble, so maybe a bit of bounce on a trade, but the ideal entry was at the end of last month, so way late in the trade.

So what’s my point?

Pretty simple, really:

There is a huge Uncertainty at the moment in making any prediction about interest rates. Assuming that this being out of line with ‘the past’ so prologue to a rise is assuming ergodic behavior that is not in evidence.

I see nothing significant in the news flow to say any of the ‘maybe’ issues above has changed enough to matter.

All that, to me, says “Nothing much changing” is far more likely than any other Uncertain outcome. Until something changes, nothing has changed…

BUT: Markets “crash” when the last sucker is in, and everyone wants to exit at the same time. IMHO, this is often “stimulated” by a Fat Wallet shorting their market. This lets them “sell first” and then buy back to cover their position later, after they have herded the cattle off the cliff. So here’s the question:

Is this the time that Fat Wallets, like Soros and Friends, would choose to start shorting the Bond Market? Do they even have enough money to make it happen? The Bond Market is way way larger than the stock market. $Trillions, not $Billions needed to play big shot. So is it the time, and is it even possible? Is Greenspan being trotted out to “startle the herd” off the cliff?

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Posted in AGW Science and Background, Economics - Trading - and Money, Global Warming General | Tagged , , , , , , | 15 Comments

NOT PC – La Esquina del Diablo

So back from my week in Chicago and thinking maybe my Spanish needs some polish, I’ve been watching more Spanish TV. Usually I watch a bit every so often, typically news. This time I decided to go for a series, and not just Sabado Gigante or … OMG, we need a sidebar!

Sabado Gigante, iconic Univision program, is ending
by Mariano Castillo @CNNMoney April 19, 2015: 9:16 AM ET

After 53 years, Spanish language television channel Univision says it is ending Sabado Gigante’s run.
The longest-running variety show in television history — Sabado Gigante — will end its 53-year run in September, Univision Communications announced Friday.

The show is near and dear to many Spanish speakers, but even those who don’t know the language are likely to recognize the program.

OMG! I’ve watched this thing, on and off, for half a Century, they just CAN’T end it!!!
But it seems they have…

A variety show with buxom babes, sappy comedy, music, and more. It has been part of my life since near the beginning at my Best Friends Casa …

Well, OK, so I’ve not watched much in the last decade… still, that’s not enoogh to can it….

But, as I was sayng… Watching La Equina del Diablo (The Devil’s Corner), a police show about an undercover lady cop infiltrating drug gangs, there’s an interesting non-PC moment. It comes at about 38 minutes into Season 1 Episode 5 (yes, I’ve been binge watching it… swapping languages is a bit of a pain and I’m kind of prone to staying in Spanish once I’ve swapped, so several hours now…) there’s a very non-PC thing happens that gives me hope.

The plot has an Arab guy, somewhere in a Hispanic country, and the Drug Cartel; and the Drug Lord is trying to swap Meth for “T4” (which I assume is Spanish for C4) explosives. The cops are onto the swap, and skipping a bunch of detail, the cops Boss says to the cops direct supervisor, per the Arabs, “And look out for me because those Arabs are messed up” (in translation).

Well, I have to say, it is rather refreshing to see such non-PC commentary in the middle of a “Crime Show”. Never mind that it stars a “babe with guns”, OK? That’s just a personal fetish… Here there is a simple recognition that even with crime lords dealing with Arabs, “those Arabs are messed up”.

There’s hope for the world yet!

IF an Hispanic show can have “babes with guns” and recognize that Arabs are “messed up”, I’m all for open borders with Mexico and South America!

FWIW, in general, paert of why I like watching Spanish Language TV is that they are NOT infested with PC Crap. Babes are babes, lots of cleavage and all, Men are Men, muscles and pants bulges and liking women and all. Guess what, I’m OK with that. So (of all things) I watch Spanish TV for a dose of normality. The only problem is that my audio error correction isn’t as good as with English so I have to run the sound louder.

That they “have clue” about the risks of an Arab Invasion (or Islamic Cultural Genocide) is just gravy on the pie.

FWIW, the cultural rot, PC crap, and cultural collapse seems much less in Hispanic Cultures and Russia, far higher in German Speaking and English derived countries. If only Russian and Hispanic places were less enamored of Socialism….

Well, with that, back to binge watching Devil’s Corner….

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Home Again, Home Again, Clickty Klack!

I’ve been “on the road” most of the last week. Quick trip to Chicago to see the kids and grandkid.

Just a couple of points out of it all:

The influence of New York influenced Puerto Rican cooking was evident in what the daughter-in-law was doing in the kitchen. I clearly have a lot to learn about Caribbean seasonings! Every meal was a joy. One interesting dish was a pizza, but unlike any other I’d had. I think the bread had some olive oil on it, but not any sauce per se, then a layer of goat cheese, slices of green and yellow zucchini slices, some basil, and then a drizzle of lemon juice. (Not sure if some other spices might have been hiding in it somewhere, but didn’t see any). Just tasty and given me a load of ideas for other variations on “pizza”. Another dish was a pot roasted chicken surrounded by vegetables. A mix of onions, carrots, what I think were yams or sweet potatoes, and orange sections (peel left on). A beautiful riot of red/orange colors in the bowl at the table! Chicken covered in a lot of oregano and some lesser spices (TBD…) then slow cooked to very very tender. OMG!

I’m surprised the son has not added a set of “love handles” (then again, his spouse is a nurse so likely keeps the calorie count under control… one doesn’t argue with an E.R. Nurse…)

So on my “to do” list is to study spices and islands cooking.

We had a couple of ‘ersatz parties’. I’ve had a general preconception of Chicago as dreary and not particular a place I’d want to be. This was softened some when I attended the climate conference there a few years back. While exposure to locals was limited, I found them a bit ‘gruff at a distance’ but as soon as you needed help or said hello they were quick and easy friends. One guy at a train platform control booth, when I asked how to use the ticket machine, even told me to just come on through the gate and get on the train with whatever I had… That is something of a Chicago trait I’ve learned more about — folks “do what needs doing” with only passing nods to rules if the rules are in the way. Traffic, for example, has a ‘make it work first, signs or stripes not so much’ style. Rules are followed when helpful, ‘bent’ when necessary. But over all, I’d mostly been there in winter and folks are huddling inside, streets a mess. This trip was different. It was early summer and folks were glorying in it.

So there was a ‘block party’ scheduled. Folks parked cars to block off the ends of the block, set up a bounce house. Two guys who worked at competing local brewpubs set up a beer tent (and shared the ‘taps box’ between their two brands!) with just a donations bucket. “Metropolitan” and “Surly” IIRC (accuracy not guaranteed as it was good and I made a big donation ;-) One house had a slow cooker full of hotdogs, big bag of buns and condiments on the table. All the hotdogs you could eat donated to the party. There was pulled pork, big trays of fresh fruit slices and berries, a strawberry upside down cake, some spiced fruit that I think was mango? and some salsa like thing (no tomatoes in it, but onions and green stuff and some spices and some ??? and…) and more.

Somewhere along the way, I found myself being friends with a dozen folks I’d never met before. A ’30 something’ black lady who was touring the street with a 60 something Polish extraction native of Chicago guy and his wife from Ireland, the hotdog folks doing the ‘steps sitting’ thing, some Hispanic kids playing ball in the street, even the “Alderman” came by. (Chicago has their own political names and I’m not sure what an Alderman is, but folks were busy passing on their concerns and desires – the “alderman” being nothing like what I expected was a ’30 something’ young lady). Even had two police stroll up, start being all “Who’s truck is this?” demanding about a pickup inside the barrier parked in the non-parking temporary sign zone. Folks talked with them, said “Hey, we’re fine, parked cars are folks who live here, so no tickets please” and the cops went away. Sure, it was a “rule” on no-parking in block parties, but this is Chicago…

Another day another party… the flat below the Son’s had a kid with a 2nd birthday, so had set up a BBQ in the common backyard. I took the dogs down for a ‘walk’ and was invited to have a beer and stay. Eventually we ended up with our whole extended family joining their extended group in the back yard. Our 18 month kid being the same size as their 2 year old, and them playing well together.

The grandson is busy learning words at a surprising rate. He makes an interesting distinction between “no” and “nope”. When unhappy (like getting his nose wiped) he will say “Nooo!” as a protest. But when asked something like “Want more cereal?” or “Pick up your toy.” when he is no so disposed says “Nope!” with emphasis on the P plosive sound. Just cute. At the party we worked on “Hola!” and “Mira” as his first Spanish… (And “Maya” as the birthday girl’s name… where he got to practice his flirting skills ;-)

So we added that pizza to the table and I had some barbacoa and more beer along with some great Spanish rice (whole green olives in it… that’s an interesting idea…) Got to practice my Spanish, too, as about 1/2 the folks present spoke little English and the same percentage of our group having little or no Spanish – or very rusty Spanish… But everyone got by fine with a constantly rotating mix of Spanish, English, and Spanglish. As dusk arrived, lightning bugs started streaking in the vines and bushes around the yard adding their bit of magic to the party.

It is summer, and in Chicago, after a long indoors winter, folks are ready to get out and enjoy the good weather. Not wasting a bit of it.

We also went to a park on Lake Michigan and again, folks were busy enjoying life. Birds galore, kids chasing geese, boats all over, swimming and more. Another day went to the zoo. The zoo is free. Yes, zero cost. Parking was $30, but if you want to go by other transport, not a problem for a free day at the zoo. (Parking is by the hour, $40 max, and is what funds the zoo, so we were happy to pay it). Again, full of people much more interested in enjoying the place than being bothered about anything.

Folks in Chicago know how to just enjoy life and make it good in the good times. After putting up with winter, slushy streets, days of cold and dark, it is a celebration of life and good times. Seems like the whole city gets into it. We drove by several other ‘block parties’ in other neighborhoods while there.

So my attitude about Chicago has shifted. Winters they enjoy lots of indoor museums and shows and such. So you can find things of interest in winter, but expect it all to be indoors. The real kick, IMHO, comes in Spring and Summer. Outdoor concerts (some free), block parties, zoos, beach time, boats, BBQ in the yard, family, neighbors and even stray visitors, y’all come!

We had one day of too hot and muggy, and the rest of the days were basically glorious. 70s to low 80s and modest humidity. (Prior week had torrential downpours, so YMMV and watch the weather reports…)

In Conclusion

So here I am, back in California. It is “just another perfect day like all the others”. ’60s F at night, may reach 80F today, but likely just high 70s. Low humidity. No bugs. And outside you see folks in cars going places…

Nobody glories in the Same Old Same Old. Yeah, someone somewhere is having a party and someone somewhere is at a park. Largely isolated from each other. Strangers in the same street. My neighborhood does have an annual July 4th block party. I meet and talk with mostly the same folks I already know, like everyone else… Just not the same dynamic. When “great weather” means “Just another day going to work”, you treat it differently.

I find myself thinking that a regular Week-In-Chicago-Spring would be a great “attitude adjustment” about just what really is important and just what really is of value… and just how to really enjoy life when the opportunity presents.

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Are Ice Age Glacials Caused By Orbital Inclination?

Is it orbital inclination (or tilt of the Earth’s orbit compared to Jupiter’s orbit), not eccentricity, that give ice age glacials a 100,000 year cycle?

This paper mostly does a spectral anaysis, but it is still very interesting. The proposed mechanism depends on cosmic dust, and with a step change 1 million years ago, so a bit of special pleading, but it does cite other papaers that claim to find that dust variation.

The abstract mostly cites problems with eccentricity, then at the end claims incination fits better.

Spectrum of 100-kyr glacial cycle: Orbital inclination, not eccentricity
Richard A. Muller* and Gordon J. MacDonald†


Spectral analysis of climate data shows a strong narrow peak with period ≈100 kyr, attributed by the Milankovitch theory to changes in the eccentricity of the earth’s orbit. The narrowness of the peak does suggest an astronomical origin; however the shape of the peak is incompatible with both linear and nonlinear models that attribute the cycle to eccentricity or (equivalently) to the envelope of the precession. In contrast, the orbital inclination parameter gives a good match to both the spectrum and bispectrum of the climate data. Extraterrestrial accretion from meteoroids or interplanetary dust is proposed as a mechanism that could link inclination to climate, and experimental tests are described that could prove or disprove this hypothesis.

Using much improved dating techniques, Broecker and van Donk (1) in 1970 conclusively established that the dominant cycle in proxy climate records is 100 kyr. Broecker and van Donk did not commit themselves as to the origin of the 100-kyr cycle. In the years after 1970, it became customary to attribute the 100,000-year cycle to variations in the orbital eccentricity of the earth (2). Calculated variation of eccentricity shows a quasi-periodic behavior, with a period of about 100 kyr. Milankovitch (3, 4) proposed that eccentricity affected the climate through its effect on insolation: the average solar energy reaching the earth. In this paper we note five sets of observations which conflict with the suggestion that insolation variations associated with eccentricity are responsible for the dominant 100,000-year cycle.

First, the eccentricity changes are small, between 0.01 and 0.05. The resulting changes in insolation are far too small to account for the dominant 100,000-year cycle observed in proxy climate records. Second, the orbital calculations which can be carried out with great accuracy back to several million years (5) show that the major cycle in eccentricity is 400,000 (400 kyr), rather than 100 kyr. A 400-kyr fluctuation is absent in most climate records, leading to specific disagreement between eccentricity and glacial data at both 400 ka and the present (the “stage 1” and “stage 11” problems). Many proposed explanations for the discrepancies have been advanced; in a recent review, Imbrie et al. (6) give a short list consisting of seven groups of models. Many of the models involve resonant or nonlinear behavior of the ice–ocean–atmosphere system; some derive the 100-kyr period from the envelope of the variation in the precession parameter.

Well-dated climate proxy records show the 100,000-year cycle only over the last million years (7). Prior to this transition, the 100-kyr period is either absent or very weak. Calculated variation of eccentricity does not show any discontinuity a million years ago. If the eccentricity drove changes in insolation, it would be anticipated that variations in insolation due to changes in eccentricity would affect climate in earlier periods, as well as over the past million years.

Since methods of dating have improved, a fourth possible problem with the Milankovitch insolation has developed: several recent observations suggest that the abrupt termination of the ice ages preceded warming from insolation (8), an effect we refer to as “causality problem.” The interpretation of these results is still controversial (9–13). Furthermore, Imbrie et al. (9) argue that a true test of the Milankovitch theory must be performed in the frequency domain, not the time domain.

The fifth problem with the Milankovitch insolation theory is found in the frequency domain. In this paper, we present a full resolution spectral analysis of δ18O proxy climate records. The analysis shows that the 100-kyr period is a single, narrow peak, a simple pattern that strongly confirms an astronomical origin, but which cannot be reconciled with any of the models presented in the review by Imbrie et al. (6) In contrast, an alternative model that we have proposed, which attributes the 100-kyr cycle to orbital inclination, passes all the spectral tests that the Milankovitch model fails

They also plead that in avoiding issues in simple Fourier transforms, the usual process hid the nature of the 100 ky peak. As the nature of “math manipulations hiding things” (especially averages) is one of my hot buttons, that caught my attention:

The narrow width of the 100-kyr peak strongly suggests a driven oscillation of astronomical origin. In contrast to dynamical astronomy, where dissipative processes are almost nonexistent, all known resonances within the earth–atmosphere system have energy transfer mechanisms that cause loss of phase stability. Narrowness of the 41-kyr and 23-kyr cycles is not necessarily significant, since the time scale of the data was tuned by adjusting the sedimentation rate to match the expected orbital cycles. The 100-kyr peak is incoherent with these other two cycles, there is no phase relationship. The fact that an unrelated peak is sharp can be considered as an a posteriori evidence that the tuning procedure yielded a basically correct time scale, although it could be incorrect by an overall stretch factor and delay. We did not anticipate the narrowness of the 100-kyr peak, assuming, as others have done, that it was due to forcing by variations in eccentricity. However, it is not easily reconciled with any published theory. The narrowness of the peak was missed in previous spectral analysis of isotopic data because of the common use of the Blackman–Tukey algorithm (20), which, as usually applied (lag parameter = 1/3), artificially broadens narrow peaks by a factor of 3. The Blackman–Tukey algorithm gained wide use in the 1950s because of Tukey’s admonition that analysts could be misled by using classical periodograms in analyzing spectra having a continuous spectrum. For analysis of glacial cycles, these considerations did not arise, because the spectra are mixed spectra with very strong quasi-periodic peaks. Spectra of glacial cycles, as Tukey recognized, lend themselves to the use of conventional Fourier transforms.

It does seem to solve some of the problems (though depends on some magic dust about dust…)

Orbital Inclination: An Alternative 100-kyr Cycle

We recently proposed that a different orbital parameter, the inclination of the earth’s orbit to the invariable plane of the solar system, should be associated with the 100-kyr glacial cycle (14, 24). The invariable plane of the solar system is that plane perpendicular to the angular momentum vector of the solar system, and is approximately equal to the orbital plane of Jupiter. The dominant peak in the spectrum of the inclination is at 0.01 cycles per kyr (100-kyr period) in a remarkably close match to the 100-kyr peak observed in the climate spectra. According to theory, this 100-kyr peak is also split, but only by 10−3 cycles per kyr, and this cannot be resolved with the 600-kyr record length. The variation of inclination i with time is calculated using the long-term integrations of Quinn et al. (5) and projecting the variation of inclination to the invariable plane.

The existence of the 100-kyr cycle of orbital inclination does not seem to have been previously noted by climatologists. It may have been missed for two reasons. Ever since the work of Milankovitch, the implicit assumption has been that insolation is the driving force for climate cycles, and the insolation is not directly affected by orbital inclination. In addition, the 100-kyr cycle is not evident until the orbital elements are transferred to the natural reference plane of the solar system, the invariable plane.

The fit of orbital inclination to the δ18O data from Specmap is shown in Fig. 3. Only two parameters were adjusted in the fit: one to set the relative scale between inclination and δ18O and a lag representing the delayed ice response to inclination. The best fit had a lag of 33 ± 3 kyr, with inclination accounting for 43% of the variation in the δ18O signal (for a record extending back 900 kyr the fit is even better, with inclination accounting for 48% of the variation) (25). Note that the inclination cycle has no 400-kyr component: the 100-kyr cycle remains strong for the last 600 kyr. Thus attribution of the cycle to inclination provides a natural (no-parameter) solution to the stage 1 and stage 11 problems as well as to the causality problems[…]

Linking Mechanisms

Since orbital inclination does not affect insolation, we must search for another mechanism relating changes in orbital inclination to changes in global climate. The only plausible one we have found is accretion of interplanetary material: meteoroids and dust. As the orbit of the earth changes, it passes through different parts of the sun’s zodiacal ring and encounters different regions of density of material. Changes in inclination will be reflected in changes of accretion. The meteoroids and dust will, through orbital processes, tend to concentrate in the invariable plane. As the earth passes through the invariable plane, accretion increases, and we speculate that glaciers grow, while recession of glaciers takes place during high inclinations when the earth’s orbit tips out of the invariable plane. We emphasize that this mechanism is speculative, and that there is no known meteoroid or dust band that satisfies all the properties that we require, although it is possible that such a band could exist. We will offer some indirect evidence that accretion does vary with orbital inclination.

Interplanetary dust accreting on the sun has previously been proposed as a driver of the ice ages (28, 29). Clube (30) discussed the possibility of accretion from a single large and unknown meteor stream affecting earth’s climate, but he did not draw any conclusions with respect to the periodicity of glacial cycles. Hoyle and Wickramasinghe (31) calculated the effect that accreting dust in the atmosphere could have on the greenhouse effect through the seeding of ice crystals, and speculated that such accretion could have been responsible for the Little Ice Age. At a meeting of the Royal Astronomical Society, reported by G. Manley (32), Hoyle discussed the possibility that accretion could remove enough atmospheric water vapor to reduce the greenhouse effect and cause cooling. Stratospheric dust could also be an effective scavenger of other greenhouse gases, including ozone, and possibly could affect the concentration of components such as chlorine that are thought to be responsible for the destruction of ozone.

The climatic effects of high-altitude dust and aerosols are known primarily from volcanic eruptions; global cooling of 0.5–1°C was estimated from the eruption of Krakatoa, and measurable climate changes have been attributed to El Chichon, Pinatubo, and other recent eruptions that injected several megatons of material into the stratosphere. Large explosive volcanic events occur typically once every century, so the average injection of volcanic material is approximately 100 kton/yr (33). Measurements by Kyte and Wasson (34) of iridium in oceanic sediments show that the long-term global average flux from extraterrestrial materials for the period 35–70 Ma is 60–120 kton/yr, about the same as the long-term average from present-day volcanic eruptions.

Accretion could cause cooling (as volcanic eruption suggests) or warming (if cometary particles inject water). Large particles (10 μm) take a few hours to reach the ground: smaller particles (0.5 μm) take a few months. Gases can reside for much longer. Extraterrestrial accretion occurs at the top of the atmosphere, so the climate effects could be significantly different from those resulting from volcanic eruptions. In addition, the global distribution of dust from the two mechanisms is different; for example, stratospheric circulation patterns rarely carry volcanic material to the poles.

Data on noctilucent clouds (mesospheric clouds strongly associated with the effects of high meteors and high altitude dust) supports the hypothesis that accretion increases significantly when the Earth passes through the invariable plane. A strong peak in the number of observed noctilucent clouds occurs on about July 9 in the northern hemisphere (35, 36) within about a day of the date when the Earth passes through the invariable plane. In the southern hemisphere the peak is approximately on January 9, also consistent with the invariable plane passage, but the data are sparse. This coincidence has not been previously noted, and it supports the contention that there is a peak in accretion at these times. On about the same date there is a similarly narrow peak in the number of polar mesospheric clouds (37) and there is a broad peak in total meteoric flux (38). It is therefore possible that it is a trail of meteors in the upper atmosphere, rather than dust, that is responsible for the climate effects.

Is it right? I don’t know…but it is intriguing. I’ve suspected cosmic and meteor drivers for other known climate events, like the Younger Dryas, so it fits my fancy, but that doesn’t mean it is right… or wrong.

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Posted in AGW Climate Perspective, Earth Sciences, Science Bits | Tagged , , , , | 36 Comments

Alzheimer’s as Type 3 Diabetes

There is a hypothesis that Alzheimer’s is a type of diabetes. If so, blood sugar regulation might be a treatment.

Alzheimer’s Disease Is Type 3 Diabetes–Evidence Reviewed

Suzanne M. de la Monte, M.D., M.P.H.1,2,3 and Jack R. Wands, M.D.3

Alzheimer’s disease (AD) has characteristic histopathological, molecular, and biochemical abnormalities, including cell loss; abundant neurofibrillary tangles; dystrophic neurites; amyloid precursor protein, amyloid-β (APP-Aβ) deposits; increased activation of prodeath genes and signaling pathways; impaired energy metabolism; mitochondrial dysfunction; chronic oxidative stress; and DNA damage. Gaining a better understanding of AD pathogenesis will require a framework that mechanistically interlinks all these phenomena.

Currently, there is a rapid growth in the literature pointing toward insulin deficiency and insulin resistance as mediators of AD-type neurodegeneration, but this surge of new information is riddled with conflicting and unresolved concepts regarding the potential contributions of type 2 diabetes mellitus (T2DM), metabolic syndrome, and obesity to AD pathogenesis. Herein, we review the evidence that (1) T2DM causes brain insulin resistance, oxidative stress, and cognitive impairment, but its aggregate effects fall far short of mimicking AD; (2) extensive disturbances in brain insulin and insulin-like growth factor (IGF) signaling mechanisms represent early and progressive abnormalities and could account for the majority of molecular, biochemical, and histopathological lesions in AD; (3) experimental brain diabetes produced by intracerebral administration of streptozotocin shares many features with AD, including cognitive impairment and disturbances in acetylcholine homeostasis; and (4) experimental brain diabetes is treatable with insulin sensitizer agents, i.e., drugs currently used to treat T2DM. We conclude that the term “type 3 diabetes” accurately reflects the fact that AD represents a form of diabetes that selectively involves the brain and has molecular and biochemical features that overlap with both type 1 diabetes mellitus and T2DM.

Ok… so if insulin like growth factor is involved, could that be the mechanism by which excercize helps too?

Then just the idea that good blood glucose control is needed points a fat finger at sugar loaded diets in the “epidemic” of new cases. Perhaps we all just need more periodic fasts…

High-fat diet feeding for 16 weeks doubled mean body weight, caused T2DM, and marginally reduced mean brain weight.80 Those effects were associated with significantly increased levels of tau, IGF-1 receptor, IRS-1, IRS-4, ubiquitin, glial fibrillary acidic protein (GFAP), and 4-hydroxynonenal and decreased expression of β actin. Importantly, HFD feeding also caused brain insulin resistance manifested by reduced top-level (Bmax) insulin receptor binding and modestly increased brain insulin gene expression. However, HFD fed mouse brains did not exhibit AD histopathology or increases in APP-Aβ or phospho-tau, nor were there impairments in IGF signaling, which typically occurs in AD.10 In essence, although the chronic obesity with T2DM model exhibited mild brain atrophy with insulin resistance, oxidative stress, and cytoskeleton degradation, the effects were modest compared with AD5,10 and other more robust experimental models of T3DM,28,29 and most of the molecular, biochemical, and histopathological features that typify AD were not present. Therefore, T2DM and obesity may contribute to, i.e., serve as cofactors of AD but by themselves are probably not sufficient to cause AD.

Yeah, fat rats don’t think as well, got it…. (where did I put that bike in the garage…)

There is much more in the article, well woth reading it. Human studies, drugs that work, and more.

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Posted in Biology Biochem | Tagged , , | 3 Comments