How are meteorologists able to predict weather conditions more than a week out? Are these predictions even reliable?
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They have models that perform a lot of math to simulate future weather and they slightly modify parameters which aren’t precisely known as well as to account for the chaos that is weather which can be affected by just about anything. Once they run enough simulations to get the probabilities of things happening they can then base the guess on the highest probability event.
7 days out? They get 80% correct so still pretty good. 10 days out? It goes down to about half. Past that? Don’t even bother.
In short: they cannot, at least not reliably. Source: my mother is a meteorologist, she has studied in Russia and worked for years in a weather station in Kasakstan or however you write it in English, before we moved to Germany and she had to redo her masters because of accreditation issues.
Here’s the thing: Meteorologists measure lots of different kinds of data. They then use different models to predict weather conditions. However, none of them can be entirely accurate, since to achieve that you would have to know all the different states of all the atoms in the air, and even then it would be very sensitive to initial conditions, even small changes would influence the outcome drastically. So they measure lots, calculate different models and combine that data for a rough prediction.
They have lots of models that are built on how things worked in the past. We have a hundred years of detailed weather data, and we can (and do) use that data to build models that are predictive withing certain ranges. We can test them by (for example) picking a date in the past in a given location, input the recorded weather conditions in the model and see how close it came to predicting what actually happened (we check it against the recorded data). Do this enough, and we learn how to tweak the models to increase their ability to predict conditions. And models do get better as a result.
That said, even the best models struggle to predict anything reliable more than a few days out (other than “it’s gonna be hot in the summer” or “it’s gonna be cold in the winter”). There’s just too many variables and too much uncertainty more than 72 hours down the road. Weather modeling is a classic case of applied chaos theory because huge differences in “outcomes” (what the weather actually does a week from now) happen with very small differences in initial conditions (what’s going on right now).
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