Daily human activity depends largely on increasingly accurate weather predictions. Millions of data captured from satellites, balloons, ships, buoys, airplanes and ground stations feed complex numerical models in real time that are processed on supercomputers and produce the best predictions we have ever had. If it were not for meteorological science that has overcome 200 years of obstacles and misgivings, thousands of activities would be affected or paralyzed.
The graph with the evolution of the percentage of correct predictions from the 80s to the present leaves no room for doubt: a current five-day forecast is as accurate as the 24-hour forecast was in 1980 and useful forecasts (higher than 80% correct) are now projected up to ten days into the future. The accuracy of the predictions in the intervals of three, five, seven and ten days has climbed to almost 90% in both hemispheres and the margin of uncertainty has narrowed in all of them.
Gone are the days when the TVE meteorologist bet his mustache that it would rain the next day and he would lose (as happened to Eugenio Martín Rubio in 1967). But the mockery and reproaches for weather predictions are still installed in the collective unconscious half a century later, as if nothing had changed.
These misunderstandings resurface strongly in extreme situations such as the tragic DANA in Valencia or the Filomena snowfall of 2021, despite the fact that the forecasts were the best with the available technology. One of the causes, experts agree, is that the complexity of the models has led to the incorporation of what is known as probabilistic prediction, which is very useful, but is not intuitive for the general public.
How does this system work? As explained by the State Meteorological Agency (AEMET), the European Center for Medium-Term Forecasting (ECMWF) launches 51 different predictions on its computers, based on 51 initial states, one of them undisturbed and 50 slightly disturbed. . That is, we try to limit the uncertainty of a chaotic system by seeing how 50 simulations evolve in which the values are slightly different, assuming that the initial conditions are never exact.
“From these 51 predictions, the probabilities of precipitation exceeding the indicated thresholds are calculated, as well as the average and maximum precipitation expected at each point,” all with the aim of “capturing the possible evolutions that the atmosphere”, describes the AEMET. To simplify greatly, if in 80% of these simulated scenarios it rains heavily in a region, meteorologists already have confirmation that it will be very likely.
This is the system by which the ECMWF models have warned this Sunday of the possibility that a new DANA hits the Spanish east in the middle of the weekalthough the uncertainty is still very high. The origin of this difficulty is that the equations that describe the behavior of the fluid in the atmosphere, and that are solved by supercomputers, are so complex that the search for exact solutions to the Navier-Stokes equations is one of the mathematical problems of the millennium for which one million euros is offered.
To understand its difficulty, it is said that the German physicist Werner Heisenberg said that if he ever met God he would ask him two questions: why relativity? and why the turbulence? “And I am sure that he will know how to answer me the first time,” he added.
The elusive percentages
The last time the Center for Sociological Research (CIS) asked the population about their trust in AEMET, in 2011, 82.4% of respondents considered that the weather predictions were quite or very accurate. In that CIS survey there were specific questions like the following that allow us to test our understanding of the forecasts:
Suppose tomorrow’s weather forecast says ‘there is a 60% chance of rain’. Which of the following phrases do you think best describes what this means?
- It will rain tomorrow in 60% of the prediction location.
- It will rain tomorrow 60% of the time.
- Of every 100 days with characteristics similar to tomorrow, it will rain on 60.
- 60% of meteorologists believe it will rain tomorrow.
The majority of those surveyed (21.2%) voted option 1 as correct and believed that the percentage referred to the part of the territory in which it would rain. Quite a few believed it was the proportion of meteorologists who agreed with the prediction (13.3%) and a similar percentage (12.4%) believed the key was the number of hours per day in which there would be precipitation.
The correct answer was the third one (“For every 100 days with characteristics similar to tomorrow, it will rain on 60″ and it was the second most voted, with 19.1%. Of course, in an updated version in 2024 it would be more correct to write it in these terms: “Of every 100 predictions that were run in the models, 60 predicted precipitation”.
Uncertainty levels
“Many people mistakenly think that when we talk about a 50% chance of rain we are avoiding the issue and it is like saying nothing,” explains Arnaitz Fernández, ETB meteorologist. “And others confuse the probability of rain with the intensity with which it will rain.” The debate is open in the scientific community itself, and many meteorologists avoid talking about percentages for fear of being misunderstood (in addition to resorting to deterministic models, which continue to have a high degree of reliability, although not as much in situations such as large storms or situations like DANA).
Many confuse the probability of rain with the intensity with which it will rain.
Arnaitz Fernandez
— ETB Meteorologist
For Fernández, the first thing to keep in mind is that meteorology cannot give us 100% certainty in any event, despite the improvement of satellites, observation systems and predictions using supercomputers. “Because when something happens that the forecasts did not say, some people who do not believe in science already have an argument to attack, without knowing that behind it is the atmosphere, which is a chaotic system.”
“A small variation greatly changes the area where it will rain, and a small error in observing the initial conditions can alter the forecast,” he emphasizes. Ruben del Campospokesperson for AEMET.
What we say is what is most likely to happen, not what will happen for sure.
Jose Miguel Viñas
— Meteored Meteorologist
“We must convey the idea that prediction models are already very good and very reliable, but that there is a limitation and uncertainty in any prediction,” he adds. Jose Miguel ViñasMeteored meteorologist. “But we must banish or gradually banish the idea of success and the mistake”. Among other things because, in the longer term, there is a physical impossibility of being able to accurately predict the meteorological situation in a specific location, because the uncertainty is greater the smaller the forecast area, remember. “What we say is what is most likely to happen, not what is certain to happen.”
Neither prophecies nor divinations
In a paper published in 2018 on “probability and uncertainty in society and the media,” meteorologists attributed public resistance to presentations of probability to “the human tendency to cognitive savings” and to present the truths in the simplest way possible. “A deterministic prediction (it will rain today) will be much more digestible than a probabilistic prediction (there is a 5% chance that it will rain today) and therefore, it seems to give it a divinatory nature, almost outside the scientific range,” they wrote. “Who has not ever said or heard: ‘those of time have not right today’?”
Angel Riveraa state meteorologist who worked for 38 years at AEMET, remembers the times when the means to make predictions were infinitely more precarious. “In 1982, for a situation like the DANA in Valencia, what we knew was that it could rain a lot in a large area of the Mediterranean, from the mouth of the Ebro to Cabo de Gata, but you couldn’t specify more,” he explains. “I saw the start of numerical models, which started with resolutions of 50 km, and now we can go down to a resolution of up to one and two km.” That is why he believes that debates about the reliability of the forecast should be over.
I experienced the start of numerical models, which began with resolutions of 50 km, and now we can go down to a resolution of up to 1 and 2 km
Angel Rivera
— State Meteorologist who worked for 38 years at AEMET
“The distrust and joke about meteorologists goes back to the times when forecasts began to be published in the mainstream media, from the beginnings of radio and television,” he explains. Manuel Palomaresexpert in the history of meteorology. But doubts about the reliability of the forecast are at the beginning of the discipline, he recalls, when the scientists themselves believed that it was an incomprehensible task, due to the complexity of the atmosphere.
“Whatever the progress of science, no sincere observer who cares about his reputation will dare to predict the state of the weather,” declared the prominent French physicist and mathematician François Arago in 1846, with little success. The British Robert FitzRoy, the first to dare to publish predictions in newspapers, put his finger on the problem by coining the word forecast (in English) in 1861. “They are neither prophecies nor predictions: the term forecast [forecast] “It is strictly applicable to an opinion that is the result of a combination of science and calculation,” he stated. In other words, time is not guessedbut rather it was predicted from the data.
FitzRoy was reviled by his contemporaries because his predictions were not made “with precise rules” nor sufficiently supported by “observed facts.” And that harassment led him to suicide. It took almost two centuries to develop the observation tools and machines that make it possible to predict what the atmosphere is going to do hour by hour around the world and with a level of detail that seemed impossible to the pioneers. And yet, many still want lynch to meteorologists as if that scientific and technological revolution had not happened.
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