Eugenio Martín Rubio, TVE’s weatherman, woke up that morning in January 1967 with a face like “Earth, swallow me.” During the whole of the previous day, not a measly drop of water had fallen in any part of the country; but he had made a bet on television (on the only television channel in the country) that if it didn’t rain, he shaved his mustache. And she shaved it off, boy did she shave it off.
Shouldn’t this poor man to have paid some attention to the cabañuelas?
The previous question is somewhat tricky, of course. In 1967, Martín Rubio made his calculations by combining the data from the Atlantic ships, the Moscow weather forecast or the time it took for the plane to travel from New York to Madrid. Normal that he was wrong: he was using the best of the science of the moment, yes; but that was predicting the weather almost blindly.
And it’s not a figure of speech. The 24-hour forecasts made in the 1980s had the same chance of success as our five-day forecasts. 20 years earlier, without the enormous potential of satellites, making predictions was much more complex. And, even so, Martín Rubio was almost right: the deep storm took a little longer to arrive, but it was so enormous that it saved a particularly dry autumn on the Peninsula.
And before that?
Image | NOAA
However, for thousands of years, humans have used practical systems to predict the weather. They had good reason to try: for thousands of years, a bad storm (or planting, pruning, or harvesting at a bad time) was the difference between a good year and starvation.
The question that defenders of this type of practice insistently ask us is whether something cannot really be learned from all that accumulated knowledge. That is to say, Aren’t the scientists being too arrogant, in their approach to these systems and, therefore, are they leaving something aside?
Although it may not seem like it, the question has its substance. Not as much as some claim, but quite a lot. There are indeed cases in which contemporary science has learned from the historical knowledge of the most varied branches of knowledge. A well-known example (perhaps recently) is that of the Chinese pharmacologist Youyou Tu, Nobel Prize in Medicine in 2015.
With the idea of finding some effective treatment for malaria (malaria), Youyou Tu’s team analyzed more than 2,000 samples that traditional Chinese herbalists had linked to the treatment of this disease. This is how they came across Artemisia annua: whose extracts did prove effective in clinical trials.
But things don’t stay that way: searching through historical manuals, they discovered that traditional solutions (dating back 1,200 years) used a very specific method of preparation. When the researchers used this methodology, the extracts of A. annua were much more powerful against parasites.
The atmosphere and the body
The parallelism between medicine and meteorology is complicated. Above all because, as AEMET reminded us a few days ago, we are very clear that “the atmosphere is a chaotic system, which means that small variations in the initial conditions make the expected evolution very different, which is why the equations are not linear “. That, generally speaking, does not happen in the medical field.
We know that Neanderthals used (the rudimentary equivalent) of aspirin and antibiotics 50,000 years ago. It has never been doubted that there is interesting information among medieval recipe books, Egyptian scrolls or Chinese manuals: in fact, on many occasions, our medical-pharmacological knowledge has been a progressive evolution of pre-medical uses and theories. previous scientific
The problem with the atmosphere is that “the only way to study it correctly is through science“What’s more, all that we have advanced in weather forecasting in recent years (and it has been a lot) is due to two things: more sources to obtain data and more capacity to process them; or, said in meteorological language, collect and assimilate .
In fact, meteorologists and climatologists have not wiped the slate clean with all the previous work. Scientists use local records (along with many other techniques) to study past climate and better understand the recurrence of catastrophic events as weather trends. The problem is that we are talking about completely segregated levels of analysis.
Can’t you learn anything from the cabañuelas?
Imagen |
I wouldn’t dare say that much. Contemporary pseudoscience continues to exist (and is popular) because it manages to cover needs that are not really well covered. In a twisted, lying and inaccurate way? It may be, but it covers them. After all, our current ability to reliably predict the weather is not a good fit for our needs.
In a world like today (with very long logistics chains and crop management strategies at a continental level), “seven days” is not “medium term”: it is a sigh. The survival of the cabañuelos reminds us that there are certain social, economic and community functions that go beyond precision. Functions in which, one way or another, we have to improve if we want to be useful. And, at least in that, in what they point out, yes we can learn things from the cabañuelas.
Image | Dronte (Midjourney)
