Thursday, January 30, 2014

Oh, the weather outside is frightful...

On two occasions I have been asked [by members of Parliament]: 'Pray, Mr. Babbage, if you put into the machine wrong figures, will the right answers come out?' I am not able rightly to apprehend the kind of confusion of ideas that could provoke such a question.- Charles Babbage

As you may have heard, it snowed down here in the South. Birmingham and Atlanta were paralyzed, and most stuff just shut down. That part is normal. Southern cities do not invest heavily in snow removal equipment because it wouldn't be used more than a day or two every couple of years. The normal reaction to snow is to simply close everything down. Everyone stays home, or leaves work or school early, and watches the snow hit the ground from the comfort of their respective living rooms. The next day it melts and things are back to normal.

Well, it didn't work out that way this time. There were two problems. First, the temperature dropped precipitously as the sleet and/or snow fell. Normally, some snow falls, hits the relatively warm ground and promptly melts. In this case though, as the icy stuff hit the warm ground, it melted then got covered by more stuff that didn't melt as the temperatures fell. The ice then got covered by snow, which is about the worst case scenario for winter driving. Yet even that wouldn't have been a huge deal had it not been for the second problem: The weather guessers screwed up big time.

To begin with, winter weather warnings were issued early on (some as early as Sunday evening) that said the bad stuff would arrive around 10 AM and would affect Alabama south of I-85 and US 80. Basically, that's everything south of Montgomery. Birmingham, on the other hand, might get a “dusting” of snow. Now, if I were still doing my ridiculous commute to work in Birmingham, I probably would have considered going into work because both Birmingham and my area (slightly north of Montgomery) were outside the nasty stuff. Fortunately, I am retired now, so I didn't have to make a decision. Thank goodness.

When I got up Tuesday morning, it obvious something had gone very wrong with the predictions. First of all, it was sleeting, almost four hours before the precipitation was supposed to start. Second, looking at the radar, it was obvious that it was snowing like the dickens up in North Alabama, including Birmingham, where it wasn't supposed to. Because people up there believed that this was the “dusting” they were supposed to get, they went to work and school. By the time they realized just how wrong the weather services had been, the roads were a slick mess. But, the schools and businesses decided to tell everyone to make a break for it, which of course ended up with a major traffic catastrophe.

So what happened? Well, it seems that weather models were wrong. To begin with, the storm was farther north than the models had predicted. Then there was this from a National Weather Service person: “ 'The models we use generally show storms coming in slower than they do, so we backed up the predicted time that storms are expected to hit.' ” According to [Mark] Linhares, the NWS forecast backed up Tuesday's storm arrival by several hours, but was still off by a couple of hours.”

Now chew on that for a moment. What he's saying is that the computer models the National Weather Service uses are wrong and haven't been corrected. That is a frightening statement. Yet we see evidence of this all through hurricane season, when the models predict storm paths that are radically different from one another, and which change from one hour to the next. If you ever want to see why the path predictions are so weird, go to a weather site that shows all the models. A couple of years ago, at least one model showed a hurricane making it all the way to Wisconsin. One would think they would have dumped that model, but my suspicion is that on some other occasion it had been accurate, or at least had been more reasonable.

Computer modeling is notoriously difficult, especially when it's about real-world systems. It's one thing to predict collision interactions in a particle accelerator or how galaxies interact gravitational. It's quite another when people's lives are affected by predictions of where a hurricane will strike or how much snow is going to fall. Businesses and governments make decisions based on these predictions, and the consequences of being off by a “couple of hours” can be very costly in terms of money and in terms of lives.

So, when the Weather Service admits the model is wrong and admits that they didn't fudge it right by “a couple of hours” (in some areas it was more like 3 or 4 hours), it's time for someone to evaluate the modeling that's being done. Maybe it's time to dump the models all together and go back to actually having people read the surface maps. I suspect that forcing these people to actually analyze the weather patterns with their heads rather than almost solely with computers and fudge factors might give us better forecasts.

Face it. It's unlikely it could be much worse.

Tuesday, January 14, 2014

A distinct lack of respect

I find your lack of faith disturbing... ~ Darth Vader

Huffington Post took a survey (doesn't everyone?) to see how Americans felt about scientists and science journalists. Seems the answer is “not very good at all.”

Why am I not surprised?

First of all, the general public's attitude (worldwide, not just in the US) toward science has had a tendency to go up and down, depending on what was being discovered. No doubt when medical schools were using grave robbers to get human specimens for dissection, people took a dim view of this medical science stuff. Similarly, early electricity experiments, especially those involving making dead things move, had to freak many out, especially given the sensational way they were reported.

Interestingly, though, people love technology. So, when electricity started producing lighting, steam started powering machines, and so on, the average person thought this “science” stuff was pretty cool. Except when it put him out of work, but that's another story.

So people's faith in scientists kind of goes up and down depending on how much benefit they're seeing from their efforts. But a couple of other things in the HuffPo article are disturbing because they reflect justified attitudes.

For instance, there's the issue of how “pure” scientific research is. A large majority of people thought scientific findings are “often” influenced by politics or corporations. Corporate finagling with research has long been a problem, particularly in the drug industry. When people say “political”, I'm sure they thought of global warming research, but the real impact of politics is on what sorts of research will be done. If a researcher wants a grant, he/she is going to gear a proposal to whatever the powers-that-be (them what controls the money) think is hot or essential. Otherwise, the researcher is going to get squat. So, yes, politics (not limited to elected types) affects research.

Science journalists are far less trusted then the scientists. This is easy to understand if one watches any of the mainstream science reporting. I recently fried the PBS program NOVA for its hideous program on Comet ISON, which features, among other things, photographs of a bunch of comets that weren't ISON while implying that at least some of them were (including a lovely pic of Hale-Bopp). It's ironic that the commercial Science Channel did a much better job with the subject.

So, if people can't depend on NOVA, what does that say about NBC, CBS, or FOX? Worse, when the History Channels bury us under “ancient aliens” and a so-called “forensic” archaeologist (or historian, whatever he calls himself) finding the Holy Grail in the Midwest US or Welsh-speaking Native Americans, it's easy to see how people could wonder about scientists. The trouble is these sorts of nonsensical programs make people wonder about the legitimate scientists, not the phonies claiming to have found female god worship to have been rampant in the Founding Fathers.

But the scientists aren't blameless themselves. Consider these recently reported “researches”:

  • Scientists are searching for time travelers on social media. should have left this one for the Onion. However, if they must look on Facebook for time travelers, I suggest they search for “John Titor.”

  • A deformed rubber sheet is not like spacetime. Gasp! You mean the old analogy of how a big ball warps space is not actually mathematically accurate? The real shock here is that any scientist would have believed that the equations for a rubber sheet would work for four-dimensional spacetime.

  • Then there's the business of faking and/or losing data. A recent example of fakery involves AIDS research, but there have been bundles of them in the last few years. As to losing (or just plain chucking out) old data, I covered that in some detail in my last post.

  • Along the same lines of data finagling, there's this piece of information on the second-hand smoke fiasco. When these studies came out years ago, they were criticized for some fast-and-loose combining of data from different populations to get the lowest possible “significant” correlation. These criticisms came from a lot of non-tobacco funded sources, so it is nice to see that some real data has been gathered. The fact that it took so many years, though, does not increase the view of scientists in the eyes of many.

Certainly, the American distrust of scientists and science reporting reflects poorly on science education and science programming in this country. People have a vague idea how science works and what it's purpose is. All that being said, scientists and science reporters obviously aren't doing a very good job of changing anyone's mind. In other words, if scientists don't like the average American's attitude, it's up to the science community (which includes those who report on science) to do something about it.

Stopping the search for time travelers on Facebook might be a good place to start.

Tuesday, January 07, 2014

Some of our data is missing ...

But there is nothing, no data, no documentation, not a single wire chamber photograph, not a single collision publicly available of which you could make sense. And this is a scandal. ~ Alexander Unzicker, The Higgs Fake: How Particle Physicists Fooled the Nobel Committee

I read Unzicker's book not too long ago and was amazed at just how ticked off he is with particle physics. In general, I tend to agree with him, especially in the matter of the Nobel Committee falling all over itself to give the prize out to Higgs for the possible discovery of what is maybe the Higgs boson.

For perspective, Einstein received a Nobel 10 years after expounding the General Theory of Relativity, and even then he got it for the photoelectric effect, despite the fact that solar eclipse data had verified the warping of space as predicted by Einstein and the fact that perturbations in Mercury's orbit were also explained by his theory of gravity.

But, it was the section where Unzicker started ranting about how much raw data was gone. I thought he might be indulging in hyperbole. After all, the raw data, especially for published research, can be valuable for detailed assessment of experimental accuracy and methodology. It was partly the lack of raw data that brought down Jan Hendrik Schön, which I've discussed before. Eugenie Reich brings out the point in her book Plastic Fantastic: How the Biggest Fraud in Physics Shook the Scientific World that suspicions began to arise when it was noticed that some graphs and tables in different papers from the genius looked exactly alike.  The suspicions began to turn into certainties when Schön couldn't produce his raw data.

Then along came this article, which is downright scary. Seems that a survey by Current Biology found that over 75% of biological study data between 1991 and 2011 seems to have gone away. Well, you say, what the heck, they got what they needed out of the numbers, so who needs them?

Well, how's this for a reason to keep the raw information? Seems that even 40-year old data can provide insights, in this case, into the deposition of moon dust. Amazingly, NASA had lost all the data. Fortunately, one of the researchers kept a backup copy of the tapes.

You want another reason? I'll give you a practical example. This involves mundane consumer products, yet it could have cost a lot of time and money trying to figure out what had changed in the product—when nothing had.

Back when I worked in the razor blade business, a large customer started complaining that one of our products was nowhere near as good as it appeared to be years ago. So we ran tests, meaning we had people shave with the product, and, lo and behold, the result was not as good as it had been a few years before. I'll spare you the gory details of how we went in circles for some time and how my boss ended up leaving the company, in part because of this problem, in part because of some other things. Once he was gone, I was free to take a close look at that old data that he had kept back. These were shaving tests he had run and summarized, and he had insisted there was nothing in that data that was important. Unfortunately, it turned out he had played a little fast and loose with the results, combining some rating levels to make it look like the product was on a par with competitors. Turned out the old data looked just like our new data. In other words, the product hadn't gotten any worse; it had always been kind of crappy.

So why did the customer perceived that the product had declined? The reality was that he wanted a price cut and figured this was a good way to get one. The happy part of the story is that we were able to figure out how to make the product better. The sad part is that the customer still went with someone cheaper (who wasn't as good as our new product). The bottom line is had we known nothing had changed, we wouldn't have wasted a ton of people-hours on a niche product and either would have immediately given him the cut or told him (politely) to go suck rocks.

The reality is that old data can be very revealing when revisited. In addition, there is probably terabytes of data that have never seen the light of day. Astronomers periodically find fascinating things in old Hubble pictures that have never been properly analyzed because of the glut of information available. If they don't see what they were looking for, they don't look at the data any further. In a couple of cases, that means they missed actual images of planets orbiting distant stars. Who knows what else is hidden in the old pictures, assuming they haven't all been tossed?

Now, the Large Hadron Collider, in fact any collider, turns out huge masses of collisions. Today, these are analyzed by computers looking for a particular event that fits a model. Well, if the model is wrong, the event might mean something totally different. We don't know that for certain, but, because data is just being chucked, it will be very difficult to go back and evaluate the possibility.

And that ain't science.