This graphic, by Boggis Makes Videos and put on YouTube just a few days ago, breaks all the rules of how to make effective, understandable graphs for the general public. However, if you follow all those rules, it is difficult or impossible to get certain message across. Therefore, this graphic is necessary if a bit difficult. I would like you to watch the graphic several times with a prompt before each watching so that you fully appreciate it. This will only take you six or seven minutes, I’m sure you weren’t doing anything else important. Continue reading An Interesting New Graphic Showing Climate Change
The White House calls the disaster in Puerto Rico a “good news story,” implying that the federal government is doing a great job there.
Meanwhile, Donald Trump put out a tweet today that seems to imply that the US needs to consider whether or not it wants to help Puerto Rico, which, by the way, is actually part of the United States.
Here is the mayor of San Juan, Puerto Rico, responding to some of this:
Hat tip: Media Matters for America
This graphic, by Boggis Makes Videos and put on YouTube just a few days ago, breaks all the rules of how to make effective, understandable graphs for the general public. However, if you follow all those rules, it is difficult or impossible to get certain message across. Therefore, this graphic is necessary if a bit difficult. I would like you to watch the graphic several times with a prompt before each watching so that you fully appreciate it. This will only take you six or seven minutes, I’m sure you weren’t doing anything else important.
Pass 1: How to read the graph
This graph’s basic data are temperature anomaly, not temperature, but difference in observed temperature averaged out over a month, using a baseline of 1961-1990. Global warming was already underway for this period, but it still works as a baseline. Anyway notice the scale shown at the beginning of the presentation.
The Graph shows the temperature anomaly across latitude, using a circle meant to represent the earth, so the north pole is on top, the south pole on the bottom, the equator half way between, etc.
The height of the graph’s bars, as well as their color, show the anomaly, but the beginning of the graphic shows you how far out, in standard deviations, the values are.
The Graphic display starts at 1900. The values are shown for each month, but they are 12 month moving average values, otherwise this graphic would give you a seizure.
So watch the first 20 seconds or so as many times as you need to, to fully understand these details.
Pass 2: It is getting warmer and weirder
On the first pass, just note that as the earth gets warmer, at sea and on land (see the two graphics at the bottom). Notice that the variation from year to year as well as the increase in temperature really takes off in the 1980s. Notice that the surface warmth values increase dramtically starting in the 1990s. Notice that things get really wild over just the last ten years or less.
Pass 3: Ends and middles
On your third pass, and this may take a few passes, notice the difference between the equatorial, temperate, and polar regions, as well as the difference between the two poles.
Consider that the increased warming in arctic regions compared to other regions affects many aspects of our weather.
Consider that the increases in temperate and tropical regions means that over some periods of time an increasingly lager area of the earth becomes uninhabitable without air conditioning.
Notice that the northern and southern hemisphere don’t have the same exact pattern.
What else did you see?
I had mentioned before that we are enjoying our Amazon Echo, one of those robots that listens and then responds with a certain degree of intelligence.
We don’t use the Echo for very many things, but that is partly because we are not in the habit. For example, if I’m sitting in a certain chair in the library, reading, I have to stand up and turn around and kind of bend over in a certain direction to see the clock on the wall. Or, I can say, “Alexa, what time is it?” and the Echo Dot tells me. But, I almost never think of asking Alexa. But over time I’m sure I’ll get in the habit, and after that, stop moving around as much. Which will ultimately lead to atrophy about the time the robots take over, which I assume is their plan.
I use Alexa’s shopping list, we ask it questions one might as Google Assistant (but Google Assistant is much more likely so far to come up with the answer). Alexa has a large number of useful information and entertainment services, which we are using more and more, such as getting a news update, the weather, and so on.
In any event, I recommend giving Alexa a try, and if you happen to have an Internet Of Things devices, then you simply have to pepper your home with dots and stop moving entirely.
But, the reason you don’t want to just go out and buy an Echo or related device at this moment is because Amazon just came out with a new line of them. Here is some basic information to help you get oriented. Then, if you pick the second generation Echo as your first Alexa device, go for it, otherwise, I might wait until the other devices are out for a few weeks to see how people like them.
If you want to cut to the chase, CLICK HERE to see a page at Amazon.com with the details, including a product grid to help you pick out which robot you want to have as your new overlord.
The Echo Dot (2nd Generation) is your basic entry level device. It has an adequate speaker but not really good enough for music, but it also has an output you can hook to your own speakers. Your first device should be this inexpensive dot. Then, later, if you want to upgrade to a fancier device, you can still use this one as a second device say, in your garage or bathroom or somewhere.
The Second Generation Echo is essentially the Echo Dot sitting on top of a high quality speaker, and runs about twice the cost of the Echo dot.
The new Echo Plus includes a hub from which to run your smart home devices, has a somewhat better sound system than the Echo 2nd gen, and is slightly larger. This will cost you fifty another fifty bucks, so now we are up to $150, but since it includes the hub it is probably worth it.
The new Echo Spot is Echo Dot size but with a screen, small at 2.5″, but possibly useful. This is not cheaap ($129). The sound quality sis probably better than the traditional Dot. It does not have the hub.
The top of the line is the Echo Show. This has top speakers, a 7 inchs screen, and blue-tooth only audio output (all the others have plug in audio output).
All these devices can control smart home items, and allow free audio calls between people with Echos across North America. They all stream music, etc. using the services that you may or may not have such as Spotify, Pandora, Amazon Music, etc.
I’m not sure that I personally grok the combination of devices. Maybe I want a hub that is separate and inexpensive. Maybe I want a screen that is 7 inches or so to wall mount but it is only an output screen, but it can sit near my front door and tell me the weather, something about traffic, and if the garage door is open. I’ll have to think about it.
For now I’ll stick with my dot, and keep playing around with home made devices and robots until I see how it goes.
The big question for YOU is which device to get if this is your first one. I would recommend the Echo Dot then see how it goes, just to be conservative.
However, make sure you get a second generation Echo Dot, or Echo.
Also, Amazon is currently running a promotion where you can get the Echo Dot plus a Fire TV stick (which is roughly like a Roku, I believe) for about 90 bucks, which is cheap.. And, you can browse around for certified refurbished devices which will save you typically ten or twenty percent. Not a huge savings but they are certified.
When the big tsunami hit Japan in 2011, many objects were washed out to sea. This flotsam provided for a giant “rafting event.” A rafting event is when animals, plants, etc. float across an otherwise uncrossable body of water and end up alive on the other side. With this particular event, I don’t think very many terrestrial life forms crossed the Pacific, but a lot of littoral — shore dwelling and near shore — animals and plants did.
Even though the Pacific ocean is one big puddle and you would think that any organism anywhere in it could just go to any other part of the ocean, like in the movie Finding Nemo, that simply isn’t true, and many organisms, most, don’t migrate at all and don’t disperse that far.
This video gives an overview of the dispersal of Japanese marine life forms across the pacific.
One might assume that this sort of rafting event happens all the time, or at least, every century or so when there is a tsunami. Partly true. But the flotsam that flotsamized the Pacific this time around included a lot of stuff that did not, could not, rot, and had generally more chance of making it all the way before floating.
And, of course, this is all being studied by scientists because it is an amazing opportunity. From the abstract of a paper just out:
The 2011 East Japan earthquake generated a massive tsunami that launched an extraordinary transoceanic biological rafting event with no known historical precedent. We document 289 living Japanese coastal marine species from 16 phyla transported over 6 years on objects that traveled thousands of kilometers across the Pacific Ocean to the shores of North America and Hawai‘i. Most of this dispersal occurred on nonbiodegradable objects, resulting in the longest documented transoceanic survival and dispersal of coastal species by rafting. Expanding shoreline infrastructure has increased global sources of plastic materials available for biotic colonization and also interacts with climate change–induced storms of increasing severity to eject debris into the oceans. In turn, increased ocean rafting may intensify species invasions.
Carlton, James, et. al 2017. Tsunami-driven rafting: Transoceanic species dispersal and implications for marine biogeography. Science 357:6358(1402-2406)
Or so it seems.
Donald Trump won the 2016 election with 306 votes to Hillary Clinton’s 232 votes. That is a spread of 74 votes.
Clinton was likely to win in several states in which she lost, including Wisconsin, Michigan, Pennsylvania, maybe Ohio, etc. In three states that could have gone either way, Jill Stein’s vote count was larger than the difference between Clinton and Trump. In Michigan, Trump won by 10,704 votes, Stein got 51,463 votes. In Pennsylvania, Trump won by 46,765 votes, Stein got 49,678 votes. In Wisconsin, Trump won by 22,177 votes, Stein got 31,006 votes.
If every Jill Stein vote would have been a Clinton Vote, it is likely that Clinton would have had 49 electoral votes more than she did have.
That alone would have put Clinton in the white house.
We now know that Russian hackers worked hard on getting people to vote for Stein. They spread around the idea that it was “safe” to vote for a third party candidate in states where the outcome was obvious anyway.
I told people this many times. I said, again and again, the logic that you can vote “safely” in a general election for a third party candidate in certain states is flawed for several reasons. One of those reasons, I said, is that you might only think the state is safe, and perhaps it is not.
Using Stein, who is known to have hobnobbed with Putin (which may or may not be relevant here), and I’m sure a few other trick here and there, the Russians may have given their guy Trump the three electoral college wins that put him in the White House.
We’ve learned this as part of the recent expose of Facebook’s blind cooperation with the Russians in the 2016 election. (Or maybe not all blind? We just don’t know yet. How hard might it have been for the Russians to play Zuckerberg?) We are about to find out if Twitter played a similar role.
It is valid, as well as lazy, to argue that, “but but it was other things too you can’t say this etc.” but the truth is that Stein hardly even ran in most states, got overall less than 1% of the vote.
So yes, it is possible to erase the Stein votes in three key states, and manage for Clinton to still lose in those states, but highly unlikely. It is very likely that the Stein vote was a significant contributor to what ultimately happened.
Putin would not be able to control US elections if two things were true. 1) Americans actually showed up to vote and 2) The percentage of gullible special snowflake ignorant voters was about half of what it apparently is.
Two or three thoughts about the current crisis.
When there is a major climate disaster in the US, people move. Since the US is big and has large gaps in population, it looks different than when a disaster happens in some other places. Five million (or more) Syrians leaving the Levant left a major mark across the globe. A half million leaving the Katrina hit zone was barely noticed on a global, or even national, scale, not just because it was one tenth the amount, but because of our size and space as well.
Something close to half the 400K or so displaced by Katrina (over half of them from NOLA) have returned to the vicinity they formerly lived in, and only a third to the same original location. The others are all over the place, distributed with a rapidly decreasing distance decay function. So these displacements, in the US, tend to be very long term and can thus affect demography and politics far afield.
An exodus from Puerto Rico will likely have a different decay function than seen for Katrina because it is, and apparently few people know this, an Island! But anyway, it is likely that there will be an exodus from Puerto Rico and it is starting to look like it will be sufficient to make Florida less Purple and more Blue, and specifically, more anti-Trump.
Note that in the past, New York was the most likely destination for a person from Puerto Rico to move, which is funny given Trump’s statements about all his Puerto Rican friends. For those not from that region, Puerto Ricans have long been hated by white supremacists in the greater NY metro area. But I digress. Anyway, over recent years, Florida has become a growing center of the US Mainland Puerto Rican community.
For context: There are about 3.5 million people living in Puerto Rico who identify as Puerto Rican, and about 5.3 million self identified Puerto Ricans in the lower 48. Currently there is somewhat under one million in Florida, somewhat over in NY, but Puerto Ricans are everywhere in the US, with the fewest in the upper plains and the most in the greater NY area (as far out as Penn) and Florida.
We are concerned that cholera will spread in Puerto Rico. You may remember the ca 2011 epidemic that mainly struck Haiti (see chart above). There was another ten years earlier. There is some interesting research out there linking cholera to climate change. The pathogen, Vibrio cholerae, lives in coastal waters where it has a keystone commensal relationship with copepods and other microinvertebrates. We think of cholera as a highly contagious pathogen among humans, but it starts from its natural reservoirs in water. In some areas of South Asia, cholera was significantly attenuated by the discovery that simply passing well water through common cotton cloth filtered out the disease enough to make a difference, at least in some contexts.
For historical context, there was a huge cholera epidemic in the Caribbean in the 19th century, and I understand this event, which killed something like 30,000 in Puerto Rico alone, is still a traumatic memory in the region. From a 2011 summary of the historic epidemic, written I suspect in response to the re-emergence of the problem about six years ago:
The Caribbean region experienced cholera in 3 major waves… The 3 periods of cholera in the Caribbean that we have identified are 1833–1834 (with, according to Kiple , possible lingering cholera in outlying areas until late 1837 or early 1838) in Cuba; 1850–1856 in Jamaica, Cuba, Puerto Rico, St. Thomas, St. Lucia, St. Kitts, Nevis, Trinidad, the Bahamas, St. Vincent, Granada, Anguilla, St. John, Tortola, the Turks and Caicos, the Grenadines (Carriacou and Petite Martinique), and possibly Antigua; and 1865–1872 in Guadeloupe, Cuba, St. Thomas, the Dominican Republic, Dominica, Martinique, and Marie Galante.
It is thought that Cholera is more likely to be abundant and to spread into human populations with warmer waters, and possibly the range over which cholera is a lingering constant threat in coastal waters is likely increasing. Also, increased air temperatures and rainfall can increase growth or spread of cholera in the wild. This is a relationship first identified in the 1990s, and that has been demonstrated through several studies. The next few weeks and months in Puerto Rico are an accidental and potentially horrific experimental laboratory to test the science that has been percolating along over the last 20 years.
True that. In the US, energy policy and regulation happens much more at the state level than the federal level, and our federal government went belly up last January anyway. Some states will not lead, they will go backwards, but others will lead, and show the way.
So, here I want to highlight this new item in Scientific American by Rebecca Otto.
States Can Lead the Way on Climate Change
The Trump administration’s threats to abandon Obama’s Clean Power Plan and exit the Paris accords don’t necessarily mean all is lost
The word “corporation” does not appear in our Constitution or Bill of Rights. But as Rhode Island Sen. Sheldon Whitehouse notes in his book Captured, corporations had already grown so powerful by 1816 that Thomas Jefferson urged Americans to “crush in its birth the aristocracy of our moneyed corporations, which dare already to challenge our government to a trial of strength, and bid defiance to the laws of our country.”
Today the conflict between the unfettered greed of unregulated capitalism and the right of the people to regulate industry with self-governance has reached extreme proportions. Corporations now have more power than many nations and feel justified in manipulating democracy to improve their bottom lines instead of the common good.
Nowhere is this problem more pronounced than…
Then where? THEN WHERE??? Go read the original piece!
There are special elections all the time, mostly at the state level. The news is full of the Moore vs. Strange race, which isn’t just strange because Strange is in it. You all know about that. But what you may not know about is the interesting victory, also yesterday, of Kari Lerner in New Hampshire.
New Hampshire politics are above-average complex at the state level, so I won’t dwell on context. But this is a New Hampshire state house race in a district normally held by Republicans. Lerner is a centrist Democrat. She won 39 votes, and a third party candidate, a Libertarian, won by 41. So, one could say that the right wing won by one vote but split the ticket. Nonetheless, a Republican house seat flipped Democratic.
The pattern has been similar in races at the state and national level across the country. There is some number, which I suspect is predicted by some other number, by which Democrats do better, even if they don’t win. So, for example, in a district where Republicans usually win 66-34, and where Trump got 65% of the vote, the special election will still have the Republican winning but in a close race, like 52-48. In the case of this New Hampshire district, Trump did get 65% of the vote, so it is pretty deep red, and the race came out virtually even (with the Democrat happening to win).
At some point we will have to start to dissect this dynamic and predict the color of states and federal districts over the next two years. Yess, my precious spreadsheet, we wills do thisss…..
But first I think we need more data.
It wasn’t a mammoth, it was a mastodon. But it was still a big hairy elephant featured at the climax-end of the main exhibit hall in the New York State museum. And it was an exhibit to end all exhibits. The New York State Museum, during its heyday, was world class, and the hall of evolution, which seemed old enough to have involved Darwin himself as a consultant, featured the reconstructed skeleton as well as a fur-covered version, of the creature discovered in a kettle only a few miles away. That exhibit, along with a dozen other spectacular exhibits that to my knowledge have not been equaled elsewhere or since, are the reason I became a scientist, and probably helped direct me towards the study of prehistory and archaeology.
It is because of that background to my own thinking that I paid a lot of attention over the years to elephants and elephant evolution. I got to help excavate an African four-tusker one year even though I had to push off my other responsibilities to do so. I’ve studied the pseudo archaeological traces left behind by wild forest elephants in the Congo, and now and then, ate one, which may seem strange but I was living among the Pygmy elephant hunters at the time so it seemed like the thing to do.
Several years ago, I came across John McKay. First, his blog, then I met him in person. He had been writing about Pleistocene megafauna but focusing on mammoths. Over our many years of friendship, I watched as he steadily worked on a book putting together his findings, and finally, Discovering the Mammoth: A Tale of Giants, Unicorns, Ivory, and the Birth of a New Science has been completed and is out and in print now!
I liken the discovery of the Mammoth by western science to the mostly lost to history but critical coral reef debate involving Darwin. Both events shaped how we do science today and at the same time revealed mind-changing features of the natural world. I didn’t know until interviewing John on Ikonokast (check out the podcast!) that he had originally become interested in Mammoth by a somewhat indirect route because of the extinct animal’s role in, let us say, alt-theories about the Earth and its history. But regardless of how John became interested, he discovered a complex and almost inexplicable relationship between what people were thinking, the way they arrived at those thoughts, and reality which led to a centuries-long struggle to understand something that to us, today, is fairly simple but to 19th century scholars was outrageous.
Religion and cultural belief prohibited thinking about extinctions or the evolution of one species into another, while at the same time, these bodies of thought and knowledge provided explanations for ancient mammal remains that were, to our minds today, seemingly unbelievable. It was the process of going from being totally wrong and basing conclusions on a combination of bad information and unsupportable logic, to the state of understanding that mammoths are a different species of elephant that once existed where we find their remains, but that went extinct because of major changes in their habitats and possibly other causes.
And that is only part of the central story John brings to the reader in the engagingly written and carefully researched Discovering the Mammoth.
I tend to divide science books into two categories: those written by writers about science, and those written by scientists. Both categories have their duds and their great books, though the former category almost always lacks a certain depth and breath but often in a way the typical interested reader can’t see. Meanwhile, books in the latter category can easily go off the rails or assume too much, and be a burden to read. John McKay’s book is written by an expert on the field (this book is in lieu of his PhD thesis) who had previously spent years developing his craft of explaining scientific things, so it is well done in that regard. But there is another reason the typical reader of this blog will grok McKay’s Mammoths. John’s passion other than dead woolly elephants is falsehoods. This is an interest we share. John McKay is a Snope of science, especially in certain areas, but better. Unlike Snopes, which is content to find enough chinks in the armor of some myth or another to snarkily discard it, McKay often recognizes the ways in which a falsehood informs, and contains non-trivial truth, while various truths can misinform while at the same time containing insidious or at least interesting falsehoods. It is his thinking about the way people get things wrong, combined with scholarly training in various areas of literature and history, that uniquely allow him to tell this particular important story about the the evolution of modern scientific thought.
I highly recommend Discovering the Mammoth: A Tale of Giants, Unicorns, Ivory, and the Birth of a New Science. Also, consider it as a holiday gift for your favorite smart person, so they can get even smarter.
In Tooth and Claw, Season 2 Episode 2 of Doctor Who 2.0, we see the formation of The Torchwood Institute and the banishing of The Doctor (and Rose) from the United Kingdom. Fat lot that does. Anyway, we also see Queen Victoria make mention of the multiple attempts at her assassination. I suppose it is understandable that some eight or nine (nine if you count the werewolf) attempts were made on her life. She was a women in charge of men in the most patriarchal culture ever (the White West generally, not just UK). They also said “Lock her up!” All the time, and there was a never ending investigation of her use of postage stamps, which by the way she freakin’ invented.
Anyway, I’ve been rewatching the new series, and saw that episode just today. I did not know about all those attempts on Her Majesty’s person, but by the way the fact was written into the script in DWS2E2, I suspected it was for real. So I looked it up. And, I cam across a book on it that was marked down to two bucks in Kindle form!
During Queen Victoria’s sixty-four years on the British throne, no fewer than eight attempts were made on her life. Seven teenage boys and one man attempted to kill her. Far from letting it inhibit her reign over the empire, Victoria used the notoriety of the attacks to her advantage. Regardless of the traitorous motives—delusions of grandeur, revenge, paranoia, petty grievances, or a preference of prison to the streets—they were a golden opportunity for the queen to revitalize the British crown, strengthen the monarchy, push through favored acts of legislation, and prove her pluck in the face of newfound public support. “It is worth being shot at,” she said, “to see how much one is loved.”
Recounting what Elizabeth Barrett marveled at as “this strange mania of queen-shooting,” and the punishments, unprecedented trials, and fate of these malcontents who were more pitiable than dangerous, Paul Thomas Murphy explores the realities of life in nineteenth-century England—for both the privileged and the impoverished. From these cloak-and-dagger plots of “regicide” to Victoria’s steadfast courage, Shooting Victoria is thrilling, insightful, and, at times, completely mad historical narrative.
For two bucks, we also have Thinking Machines: The Quest for Artificial Intelligence–and Where It’s Taking Us Next by Luke Dormehl.
When most of us think about Artificial Intelligence, our minds go straight to cyborgs, robots, and sci-fi thrillers where machines take over the world. But the truth is that Artificial Intelligence is already among us. It exists in our smartphones, fitness trackers, and refrigerators that tell us when the milk will expire. In some ways, the future people dreamed of at the World’s Fair in the 1960s is already here. We’re teaching our machines how to think like humans, and they’re learning at an incredible rate.
In Thinking Machines, technology journalist Luke Dormehl takes you through the history of AI and how it makes up the foundations of the machines that think for us today. Furthermore, Dormehl speculates on the incredible–and possibly terrifying–future that’s much closer than many would imagine. This remarkable book will invite you to marvel at what now seems commonplace and to dream about a future in which the scope of humanity may need to broaden itself to include intelligent machines.
I have a love-hate relationship with farmers. I have a great deal of respect for the enterprise and for those who dedicate their lives to it. But, I also become annoyed at the culture in which modern American farming embeds itself. And, I don’t feel a lot of reticence talking openly about that.
Having done plenty of farming myself, I don’t feel the need that so many others do to be extra nice to farmers out of lack of understanding. I know when the farmers complain about too little or too much rain, they are studiously ignoring the fact that if it is harder to plant or harvest, they make out like bandits with the price of their product. Farmers talk about how hard that life is, and yes, it is indeed very hard, but they seem to not mention that a typical large scale farm these days (as most farms are) is a multi tens of millions of dollars business sitting on enormously valuable land. Whenever things go really wrong with farms in the US, they get help. As it is now, we have some of the most bone-headed agricultural policies ever invented mainly to keep farmers happy, because so many US Congressional districts span vast farmland and little else.
And what does America get back for giving farmers so much help in producing a product that we have no choice but to buy? We get a lot of crap. Red counties are farm counties. Red districts give us a Republican House. Farmers mainly backed trump, even though Trump policies are almost all bad for almost all farmers.
As a brief aside, and to illustrate the disconnect between farmer culture and actual farmer self interest, I can give you this example.
Have you ever heard of Mexican cheese? Or, more to the point, have you ever been to Mexico, and then, while there, had some cheese? That cheese might have been made in Mexico, but they don’t really make cheese in Mexico. Most of the cheese eaten there is imported. From where? From Wisconsin. Nowhere else. Why? Because of Clinton’s trade policies. Clinton made a bunch of sweet deals for American farmers and that was one of them. Rural farmers in Wisconsin voted for Trump, and Trump was the guy who was going to end NAFTA (and still might, who knows?). NAFTA keeps Wisconsin dairy and cheese in business. Get rid of NAFTA, Wisconsin becomes the West Virginia of cheese. Why? Because Mexico would rather buy its cheese from South America because it is cheaper, and the moment the Wisconsin dairy industry is not propped up by NAFTA, the free market takes over and California ends Wisconsin agriculture.
Look around the world. Farmers are taking it in the neck in many other countries, often because of the very climate change so many farmers pretend to believe is a hoax. But not in countries that take care of their farmers. America takes care of its farmers. And at every opportunity, the farmers screw over America.
Therefore, perhaps it will be with great pleasure that Modern Civilization advances to the next level. Robot farmers.
Hands Free Hectare is a project run by Harper Adams University and Precision Decisions Inc. The idea is to develop robots that will plant, tend, and harvest crops.
Now, of course, there will still be farmers, but fewer. So few, perhaps, that most people who are all “oh, I’m a poor farmer, living out in the farmlands, help me help me,” can stop whinging and move to the city. A small number of technologists, mostly the children of former Mexican migrant workers because immigrants or the children of recent immigrants or migrants are the only people in America who still have ambition, will learn the technology and run the farms and, we hope, keep the robots happy and busy.
Anyway, HFHa, as it calls itself, has been at this a while, and the latest iteration involved a major harvest of barley without humans touching anything but buttons and software. HFHa robot expert Martin Abell working for Precision Decisions, noted “This project aimed to prove that there’s no technological reason why a field can’t be farmed without humans working the land directly now and we’ve done that. We achieved this on an impressively low budget [and] we used machinery that was readily available for farmers to buy; open source technology; and an autopilot from a drone for the navigation system.”
Notably, much of the large equipment used was decades old, with the new technology added to it.
Here is the site for Hands Free Hectare, which is a British enterprise.
I for one welcome our new farmer-robot overlords.
Just heard Foreign Minister of North Korea speak at U.N. If he echoes thoughts of Little Rocket Man, they won't be around much longer!
— Donald J. Trump (@realDonaldTrump) September 24, 2017
A pair of American B-1 Lancer bombers is flying north northeast along the border of North Korean air space. Accompanying the bombers is a squadron of F-15C Eagle fighter jets. The crews are aware of the fact that North Korea may have a policy of shoot first and ask questions later, as a response to a tweet by the Russian-installed president of the United States, in which he threatened to kill the psychopathic leader of North Korea.
(I fear for a big drop in Tom Clancy novels, as they are no longer challenging or outlandish. But I digress. Back to the bombers.)
There was never any intent for these bombers to move into North Korean air space. In fact, the bombers are not armed. This is an annoyance mission, mere saber rattling in response to North Korean rhetoric that was, in turn, a response to the tweet by the President.
Suddenly, a nearby RQ-4 Global Hawk Drone detects a pair of MiG-29s moving at high speed on an intercept path with the bombers and their accompanying F-15Cs. The MiGs are armed but they are under orders to harass but not fire on the American planes. However, the American fighters do not know their intentions, but they do know that there will be no opportunity to stop the MiGs from destroying the bombers if they chose to fire missiles over the next minute or so, unless they act now. So, the fighters turn towards the MiGs, lock on, and fire their AMRAAM misles.
The bombers change to a defensive course, and even as the last bits of the MiGs float at various speeds down to the sea after being exploded in mid air, American and North Korean fighter aircraft are scrambling on both sides of the demilitarized zone. More ominously, senior officers in the North Korean People’s Army Air Force, the United States Strategic Air Command, and the US Navy Pacific Command automatically move their missile firing units to ready alert and arm a variety of conventional and nuclear missiles, ready to launch in seconds.
While all this is happening, American President Donald Trump is in the White House. It is late at night, and he is in the bathroom, sitting on the toilet. At first, he just needed to pee, as is often the case with men of his age, with their increasingly swollen prostrates. But then he decided he wanted to spend a little more time in the privacy of his bathroom. With the door locked, he has had his smart phone out, and has been scrolling through the tweets from the special list he calls “Enemies_of_me,” and he is becoming increasingly agitated at the negativity. Many of the nasty tweets are about his handling of North Korea, since his earlier tweet that the North Koreans took, reasonably, as a declaration of war.
There is a knock at the bathroom door. It is Trump’s personal assistant.
“You have to go to the situation room, sir,” calls John. “They say they need you now.”
“Tell them I’ll come by in the morning,” the President responds.
“Sir, they say they need you now, I need you to buck up and come down the the situation room. They say it is urgent.”
“OK, OK, I’ll be there in the very near future. Did they say what is about?”
“Sir, they didn’t say but I think it is about Korea. North Korea.”
“OK, just one second. I’m coming.”
Time for one tweet, he thinks. But I’m going to make it a good one. How about this ….
Over the next hour, the era of nuclear threat ends and the beginning of the age of nuclear war begins.
Let’s pause for a moment and consider a couple of other stories.
In August, 2017, a Twitter user in Japan was bitten by a mosquito. He tweeted, “Bastard! Where do you get off biting me all over while I’m just trying to relax and watch TV? Die! (Actually you’re already dead).”
He was then banned by twitter.
Milo Yiannopoulos, white supremacist troll, was banned by Twitter for making racist comments.
Back in mid 2016, it was revealed that at least a couple of major companies decided to not buy Twitter (presumably at a high price) because they did not want to own a social networking venue in which bullies and bullying were so common. Perhaps in response to concern about this, Twitter may have increased its tendency to ban bullies, despite the fact that there manages to be an increasing number of certain kinds of accounts, notably those that are racist or white supremacist.
Yesterday, a friend of mine sent Trump a tweet that implied that Hillary Clinton, not Donald Trump, had won the election. She was banned from Twitter.
So, clearly, the banning practices of Twitter have economic meaning. Clearly, Twitter can be very bad at making decisions about banning individuals, and has no clear or reasonable policy. (As I write this Twitter is promising to let everyone know what its policies really are, and how those policies allow Donald Trump to threaten to kill people to keep their accounts, while someone who gets snarky at the President gets banned.)
My point here is that Twitter is at sea, and Twitter is allowing something very dangerous to develop. Twitter is the vehicle by which Donald Trump has isolated America among world powers, it is the vehicle by which Trump has made repeated racist and sexist attacks on our own citizens, and now, it is the vehcile by which Trump is bringing the United States to the brink of war. One highly respected expert on US-North Korea relations puts our chance of conventional war with North Korea at about 50%, and the chance of nuclear war with North Korea at about 10%. Other experts see those numbers as low.
Because of Trump tweeting. And Trump gets to tweet because Twitter lets him.
Let it be said today, and remembered for all time, that every person who dies in any upcoming conflict with North Korea will have died in no small part because Twitter does not ban Donald Trump’s account.
Watch the following overview of US and North Korea conflict provided as context to the situation of this very morning:
Now, go to this tweet. Click on the little down arrow in the upper right, and chose “Report Tweet,” if you understand and agree with why this is a problem.
Note: the above tweet about blowing up Kim Jong-un is a fake tweet. Hard to tell, though, isn’t it?
It isn’t. Well, it is a little, but not totally. OK, it is, but actually, it is complicated.
First, you are probably asking about the Atlantic hurricane season, not the global issue of hurricanes and typhoons and such. If you are asking world-wide, recent prior years were worse if counted by how many humans killed and how much damage done.
With respect to the Atlantic, this was a bad year and there are special features of this year that were bad in a way that is best accounted for by global warming. But looking at the Atlantic hurricanes from a somewhat different but valid perspective, last year was worse (so far) and this year is ordinary, within the context of global warming. So, let’s talk about the global warming question first.
How Global Warming Makes Hurricane Seasons Worse
The effects of global warming on hurricanes in the Atlantic have two interesting features that must be understood to place this discussion in proper context.
First, we are having a bunch of bad decades in a row probably because of global warming. If we compare pre-1980, for a decade, with post 1980, or pre vs. post 1990, or anything similar, the more recent years have had more hurricanes than the earlier years. Comparing to even earlier time periods is tricky because of differences in available data (Satellites make a difference, probably, even with giant weather features like hurricanes). This is mainly due to increasing sea surface temperatures, but there are other factors as well.
Hurricanes are more likely to form when sea surface temperatures are higher. Higher sea surface temperatures can make a hurricane larger or stronger. Hurricanes will last longer if there is more, higher, hurricane-hot sea to travel over. If sea surface temperatures are high enough to cause hurricanes earlier in the year or later in the year, the hurricane season can be longer. Possibly, storms that in a non-warmed world would not have made it to “named storm” status are moved to that level of strength and organization because of the elevated sea surface temperature.
Sea surface temperature increases of small amounts cause large changes in hurricanes, and large changes in hurricanes cause larger changes in potential damage level. The increase in Atlantic sea surface temperatures over recent decades have probably been sufficient, according to my thumb-suck estimate that I strongly suspect is close to correct, to make about half the hurricanes that would have existed anyway jump up one category. Then, when hurricanes get stronger, the amount of damage they can do goes up exponentially. So the sea surface temperature increases we’ve see with global warming easily explain the fact that we’ve had more hurricanes overall, and stronger ones, over the last twenty or thirty years than during the previous years back to when the data are still pretty good.
Second, the science says this will get worse. There is one 2007 study (by Vecci and Soden, in Geophysical Research Letters) that suggests that maybe in the Atlantic, smaller size hurricanes will be less likely to form because of increased vertical wind shear, but that study does not mean much for larger or stronger hurricanes. This decade old study is constantly cited as evidence that global warming will not increase hurricanes in the Atlantic. Other studies show that the overall amount of hurricane activity, and the potential higher end of hurricane strength, and the size, and the speed at which they form, and the amount of water they can contain, and possibly the likelihood of a hurricane stalling right after landfall, go up. Up. Up. Up. One study says down and that word, “down” it resonates across the land like a sonic boom. The other studies say we can expect, and to varying degrees already see, up, up, up, up, up, and denial makes words like “up” and “more” and “worse” and “exasperated” dangerously quiet. Please don’t fall into that trap. Oh, by the way,the one study that says “down” has not been replicated and though experts feel it has some merit, it is far from proven and there are reasons to suggest it my be problematic.
Comparing the 2017 Atlantic Hurricane Season to Other Years
Funny thing about hurricanes: They exist whether or not they menace you. Every year a certain number of hurricanes (usually) form and wander about in the Atlantic ocean for a while, maybe hitting some boats, but otherwise doing little more than causing some big waves to eventually reach beaches in the Caribbean or the eastern US.
This year, we’ve had four major hurricanes so far. Harvey, which maxed out as a Cat 4, ravaged and flooded Texas and Louisiana. Irma, maxing at Cat 5, ravaged Florida after wiping out islands in the Leewards and doing great damage to Cuba and elsewhere in the Caribbean. Maria, maxing out as a Cat 5, did major damage in the Leewards and notably wiped out Puerto Rico. So, four Major Hurricanes formed in the Atlantic and hit something major.
Meanwhile, Jose, another Major hurricane at Cat 4 status, still spinning about in the North Atlantic, is one of those that hit nothing. And that’s all so far this year.
Last year, there were almost exactly the same number of named storms in total (so far) and just like 2017, 2016 had four major hurricanes.
You remember Matthew, which scraped the Atlantic coast and was rather damaging. But do you remember Gaston (Cat 3)? Nicole (Cat 4)? Otto (Cat 3)?
Gaston and Nicole wandered about in the Atlantic and hit nothing. Otto was for real, it hit Central America, but not the US, so from the US perspective, it counts as a non-hitting hurricane. Also, it was only barely cat 3 and weakened quickly.
From 2000 to 2016, inclusively, we have had an average of 15 named storms per year, with a minimum of 8 and a maximum of 28, with most years being between 10 and 16. So far 2017 has had 13 named storms. We may have a couple more. So, likely, we will be right in the middle.
For the same period, the number of hurricanes has ranged from 2 to 15 with an average of about 7. This year, we have had … wait for it … 7. We may or ma not get another one, not very likely two more. In other words, this is an average year for the number of hurricanes.
For the same period, the number of major hurricanes ranges from 0 (though only one year ad zero, it is more typical to have 2 in a low year) to 7, but again, 7 is extreme. It is usually from 2-5. The average is just over 3. This year, we have four. That’s pretty typical.
So, within the context that the last couple of decades has had a somewhat higher than average frequency of hurricanes, and probably more strong ones than previous decades, this we had a typical year this year.
Why does it feel different? Why is it in fact difference, with respect to the horror of it all? Because we had more landfalls, and more serious landfalls.
Keep in mind that Harvey could have hit Houston differently and done more damage. Keep in mind that Cuba beat up Irma, then Irma failed to strike Florida in just the right way to do maximum damage. Keep in mind that after wiping out Puerto Rico, Maria swerved quickly out to sea. In other words, keep in mind that this year could have been much worse than it was.
This is the point that you must understand: Any year can be like this year, or worse. And, with increasing sea surface temperatures and other global warming related factors, worse still.
To understand the Trump-Russia scandal, I believe it is necessary to step way back and take the very long view. I’m not talking about going back to early 2016, or even the year before. Much farther.
I’m not going to make a claim in this post as to what happened and who did what. Rather, I’d like to present a hypothesis, a single interpretation of events, that may or may not be correct, but that is based on this long view.
Whatever did actually happen, it did involve, or somehow exclude, Donald Trump and a number of individuals with whom he has had long term relationships, and Vladimir Putin and individuals with whom he has had long term relationships, and of course, an overlapping set of individuals who fit in both categories.
The Trump real estate business, centered mainly on Donald Trump itself, involved Roger Stone, Paul Manafort,and others. There are allegations of connections between Trump and the mob, sufficient to get at least one project denied in 1987. Manafort and Stone had long time connections with Russian interests and individuals, going way back in time, and there were numerous Trump-family-Russian deals over a long period of time, not just recently.
Deutche Bank, which apparently has served as a Russian Oligarch money laundering facility, took on Trump’s business as far back as 1998, when Trump started to run out of places to borrow money. Subsequently, the Russian state owned bank, Putin’s personal facility bailed the troubled Trump enterprise out of at least one financial hole.
Carter Page, Jeff Sessions, Michael Flynn, and several others are relative newcomers to the drama, and because their involvement and possible activities is both recent and confused, it is easy to miss the forest for the trees.
The short version is this. According to this entirely hypothetical model, Trump was involved with a wide range of shady characters doing shady deals for decades. Putin and his Oligarch friends were involved with a wide range of shady characters doing shady deals for decades. There was significant overlap between the two groups.
Somewhere along the way, Putin, with Manafort’s help, started to become increasingly engaged in messing with the politics of other countries, and at some point developed, or came upon, a method of using emerging social media to hack elections. It was probably not difficult for Putin to make the shift from collecting American billionaires to using one of them specifically, Trump, to develop a US presidential campaign, on the off chance that this could disrupt American politics, back around 2015. It was then not too difficult to take the next step, realizing that Trump might actually win, to hack the election and put a man he had worked with, indirectly and possibly directly, and on whom (we hypothesize) he held considerable Kompromat, in the white house.
While these latter moves are perhaps the most important, and most urgent, they are small steps from what seems to have been going on all along, constituting minor adjustments in a larger over-arching program of money making, money laundering, and manipulation oligarch style.
And the engine that drove this process, the methodology by which Putin ultimately came to own several American operatives including, according to this model,Trump, was something out of a movie based on a Tom Clancy novel. In order to understand that engine, I offer a parable.
The Parable of Mark
Imagine an evil drug dealer named Alexey. He has a customer named Mark. Mark doesn’t think he is an addict, but he is, and that gets worse for him over time. Mark likes to buy 10 bags of product, then he marks them up and sells eight to his friends so that he can do two bags and use the profit on the other eight to cover his costs of each buy. Most of the time. Sometimes he parties with friends Nastia and Sasha, and they go through three or four bags. But that’s OK, because his other friend, Dima always loans Mark money when he needs it, so he can get more drugs from Alexey. And Alexey always has product.
Over time, if Mark was more smart and less obsessed with meeting his own desires to party and get stoned, he could have kept himself in drugs and made a steady profit over time. After a few years, Mark did manage to stash away about $500 bucks, but not the few thousand bucks he might have made had he made the right moves.
Meanehile,Mark became deeper and deeper in debt to Dima, and by the way, also to Alexey, who also helped Mark out now and then when he was down on cash. There was also that time when Mark got busted because someone claimed to see him dealing on a street corner, and Alexey provided an alibi for him. That court case was still pending, and Mark was hoping Alexey would remember to show up and give his alibi to the judge next month. Oh, and by the way, Nastia and Sasha also loaned Mark some money now and then. Oh, and the person who dropped the dime on Mark? Mark does not know it, but it was Sasha.
So, after a few years, Mark had that 500 bucks stashed away, had been having plenty of fun, and just barely, stayed out of trouble.
But, he also owes Dima about $42,000, and another 15,000 or so to the others. He is in trouble with the law and reliant on Alexey to help him out, and lately Sasha and Nastia had been snubbing him.
Turns out that Dima, Mark’s banker, was Alexey’s brother. Sasha and Nastia were Alexey’s cousins. The judge in that open court case was Alexey’s father. And, they were all members of the same organized criminal gang with Alexey in charge.
Putting this another way, Mark was in the business of buying and selling a product, and financing the deals, and staying out of trouble, by interacting with the same exact person at every level and in every direction. Over time, with every transaction, instead of Mark having the opportunity to make a little money here, and a little product there, and to develop a reasonable if unsavory business model, at every juncture of events, Alexey turned the screw and brought Mark deeper and deeper into debt and dependency. Everybody was in on it, and Mark was the unwitting mark. As it were.
What is to be learned from this parable?
This is what Vladimir Putin and a handful of his associates, according to this hypothetical model, may have done to Donald Trump. Early on, Paul Manafort developed a relationship with Trump, and not long after, with Putin’s gang. His business with Russia was to develop ways for Putin to influence foreign governments, and eventually, elections. As early as 2000, Trump was being looked at by American conservatives as a potential presidential candidate. Over time Trump engaged in a considerable amount of Obama bashing, which served his white supremacist tendencies. Putin must have seen Trump as a potential asset, with the added bonus that they shared a racist view of life.
During this entire time multiple seemingly independent Russian entities engaged in business with Trump and his family, including a wide range of “Trump Tower” like projects, and other land deals. This also included banking and loaning money. Trump and his family were fully engaged in a money making machine much like the fictional Mark’s, buying and selling and borrowing and having fun, and Putin and his oligarch associates, using Manafort and other Americans as professional manipulators, were behind most of it, possibly all of it. Trump was buying and selling and borrowing, and meeting various prurient needs, all with the same guy, Puppet Master Putin. Or, so the theory goes.
So, when mid 2016 came along, Trump looked like a viable candidate. Republicans started to manage their role in the possible Trump presidency. Putin turned on his machine, manufactured and modeled out by Manafort and others, with the hope of electing Trump as President, and even before the election, manipulated the Republican platform. Members of the Trump Team were generally in contact with Russian agents, and various members of Washington’s Republican political elite, including multiple elected officials, became first transition advisers, then cabinet members or senior white house advisers after the election, and were brought into Club Russia to varying degrees. .
Much of the news that has developed over the last several months has focused on this period, from mid 2016 to the present. It has been difficult to understand what it all means. But if one steps back and starts by examining Trump and his associates in the 1980s, and Putin and his associates, some of which were already long time Trump associates, in the 2000’s, much of that confusion seems to melt away. Putin and Trump have both been playing a sort of long game, but with Putin much more in charge and, I would guess, with the much larger vision.
Trump looks like a chump through much of this, and he probably is. But he has had his own objectives mainly having to do with making money and being a bully, which Putin was able to garner into deep debt and probably blackmail. According to this hypothesis.
So in sum, three elements make up the model:
1) Trump plus American mob plus Russian mob plus Real Estate
2) Putin plus foreign political hacking and eventually election hacking
3) Decades old overlap between these two groups.
And, not entirely by chance but with a little luck for Putin, Trump rides the racist post Obama wave and becomes a viable candidate, then Putin puts him in.
If you want to go into the weeds on this, and you should, aside from watching every edition of the Rachel Maddow show for the last year or so, check out this handy dandy timeline.