Why are weather forecasts always wrong when modern science is so advanced?

Seeing that the weather forecast said there would be heavy rain the next day, I was forced to cancel my travel plan. I ended up staying at home waiting for a whole day, but the gloomy sky only shed a few pitiful tears, and the promised heavy rain was nowhere to be seen.

Have you ever encountered such a situation? You must have, and more than once. Since the weather forecast was introduced, "inaccurate weather forecast" has been a topic of jokes among people after dinner. The reason why people always make fun of the weather forecast is that they don't understand why the weather forecast is always inaccurate. You know, contemporary science has been so advanced, the total number of various spacecraft orbiting the earth has exceeded 1,000, we have not only landed on the back of the moon, but also sent explorers to Mars. The development speed of human civilization is so fast, why is a small weather forecast always wrong? In fact, it is not the fault of the weather forecast, because it is normal for the forecast to be inaccurate.

In daily life, it is not just the weather forecast that is uncertain. For example, if we grab a handful of beans and throw them forward, the beans will scatter all over the ground. If we grab a handful of beans again and throw them with the same force and at the same angle, will all the beans fall exactly to the place where they were thrown for the first time?

No, no matter how many times you try, you can’t do it. Even if you use machines with extremely precise strength and angles to replace people, you still can’t do it. Similar things also happen in the stock market. No matter how long you stare at the K-line chart, how much analysis you do, or how rich your experience is, it is impossible to accurately predict tomorrow’s trend. It is an unforgivable mistake for an architect to collapse a building, but it is normal for a securities analyst to misjudge tomorrow’s trend.

Why can't we accurately predict the bean-scattering and stock market trends? This has to start with a concept that we are all very familiar with, that is, the butterfly effect.

The butterfly effect theory tells us: "A butterfly in the Amazon rainforest occasionally flaps its wings, and two weeks later it can cause a tornado in Texas, USA." What does this mean? It means that a small change in the initial conditions will drive the entire system to produce a long-term huge chain reaction. Of course, not all changes in the initial conditions of the system will lead to a huge chain reaction. The system that will have such an impact is called a "chaotic system." The chaotic system is a concept proposed by American meteorologist Edward Lorenz in 1963.

When studying atmospheric changes, Lorenz tried to use computers to simulate and calculate various data in the atmosphere. The data used in the first calculation was accurate to 6 decimal places, while the data used in the second calculation was only accurate to 3 decimal places.

In fact, the difference between the data used in the two calculations is very small, but the final calculation results are far apart, so Lorenz proposed the concept of "chaotic system", which is extremely sensitive to changes in initial data. The so-called chaotic system refers to a deterministic system in which there are seemingly random irregular movements. Why do we say it seems random? Because the macroscopic physical world we know is not random, but deterministic, and you will get what you sow. However, since there are too many factors that affect the movement in the chaotic system, a small change in any factor will lead to a huge change in the final result.

Taking bean-scattering as an example, can we really ensure that the force angle and various objective conditions of the two throws are exactly the same?

No, neither humans nor machines can do it. As long as there is a nanometer-level difference in force and angle, the results will be greatly different. Moreover, the air flow in the experimental environment cannot be completely consistent. The same is true for the stock market. If you can know the trading conditions and psychological activities of all trading participants, you can certainly accurately predict the stock trend every day, but in fact this is impossible. You can't know whether a trader ate something unclean in the morning, which caused diarrhea and forced him to cancel or postpone his trading behavior that day.

A chaotic system is not truly random, but it appears to be random. The randomness it exhibits comes from the fact that there are too many factors within the system that affect the movement, so that we cannot figure out all the data and make accurate predictions.

Weather is such a chaotic system. We can obtain more accurate weather data through more advanced weather satellites, but more accurate does not mean absolutely accurate. Slight differences will lead to large differences in the final weather conditions. The more we know about the initial data, the more accurate our prediction of the final result will be. However, we cannot accurately know all the initial data, so it is impossible to make the prediction absolutely accurate. Therefore, it is normal for weather forecasts to be inaccurate. Even in the future, we can only make weather forecasts more and more accurate, but we cannot make them perfect.

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