Friday, June 9

The cabañuelas do not predict anything about winter. But these medium-term scientific models do

Winter is back, nougat is back, cabañuelas are back. And it is not strange. The little fish give us what we want: predictions, predictions and more predictions. However, all the time we spend on this pseudoscience, we do not spend it looking at what the science actually says about predicting the weather on a seasonal scale. Because yes, science also has a lot to say about this.

Why don’t cabañuelas work? When modern science begins to take shape throughout the 16th and 17th centuries, it makes a clean slate with a bunch of those traditional systems that, almost gropingly, tried to order reality by mixing community experiences and mythology. The scientific wave was slow to reach meteorology because the techniques to model the weather are very recent. However, those early scientists had known for a long time that things like pigeons had no head or tail.

And I’m talking about the cabañuelas because it’s “our” system and, anyway, since the ‘revival’ of Filomena it regularly invades the media. Essentially, the cabañuelas are a “popular calculation based on the observation of atmospheric changes in the first 12, 18 or 24 days of January or August”.

To the information that they are theoretically capable of extracting from those first dozens of the month, the little fishers would add things like the particularities of the wind or the behavior of the animals. It sounds good, but the problem is that, with very few exceptions, the procedures used by pigeons and astrologers are not very useful: they do not have predictive power.

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If there's a time to say

If it is so clear that it is a lie, why do they continue to exist? The answer, as with many other pseudosciences, is the same: it tries to cover certain needs that are not really well covered. It is enough to realize that when we speak of “medium-term forecasting”, we are talking about seven-day forecasts to understand that our current ability to predict the weather does not fit well with our needs.

That’s where the cabañuelos intervene, people who (often with the best intentions) try to give certainty to all those who (such as farmers and ranchers) need them due to their strategic exposure to the whims and inclement weather. The fact that they are more or less precise is almost secondary: the social, economic and community functions of the cabañuelas make up for their lack of precision. Something that, on the other hand, has also taken advantage of the weather forecast.

So, we can’t predict in the long term? It’s not exactly that. Meteorologists are aware of the value of seasonal forecasts and, although they cannot reach the levels of reliability of daily forecasts, they continue to work on models with which to scrutinize the meteorological future. Although there are numerous models, the main ones are those of NOAA, the British Met Office, the German DWD, the Canadian ECCC, Meteofrance and the ECMWF. What meteorological agencies such as AEMET usually do is combine these models to estimate an average to use as a reference.

How do they work? On a seasonal scale, the best predictions we have are probabilistic in nature. In other words, unlike the deterministic models that we normally use to predict the weather, these types of predictions reflect the probability that, during the next three months, the average value of temperatures or precipitation will be above or below the values ​​considered normal (in our case “normal” is the average between 1981-2010).

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Example Maps | AEMET

And what do the models tell us? For the last three months of 2022, the models indicate a high probability that the temperature will be above the average in mainland Spain and the Balearic Islands. In the Canary Islands, on the other hand, a normal temperature is expected. As for rainfall, the worst part is in the west of the peninsula, which, according to these models, has a greater probability that the drought will intensify. In the rest of the country, a regression to the mean is expected (fingers crossed); that is, a normal rainfall level.

Image | GTRES

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