Why do weather forecasts sometimes fail to predict accurately?
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Weather is a [chaotic system](https://en.wikipedia.org/wiki/Chaos_theory), where a small change in conditions can easily snowball into a huge change later (go from just rain to a tornado, for example). Predictions are generally accurate 6-24 hours in advance, because it’s easy enough to watch the cloud movements on satellite, but further ahead than that, like I said a small change in wind or temperature can drastically alter the weather later on.
The atmosphere is hilariously complicated to model, mainly due to just how obscenely large it is, meaning you need an insane amount of computing power to model it accurately.
Weather forecasts only function because forecasters make assumptions and simplifications to the model, based on prior experience and general best practices for their field. Those simplifications reduce the computational complexity, but inevitably introduce error.
Sometimes the error is significant.
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I took an atmospheric science class in college as an elective. Calculus was a prerequisite because that’s how complicated the weather is. You have to account for everything including the landscape (hills, mountains, buildings, trees, etc), the geographical location (effects of trade winds, the ocean, how far north or south), the spin of the earth, time of year, and then how all the other weather from everywhere else could mix in. It’s very complex. There are formulas and templates, but I strongly believe they haven’t been updated enough to account for climate change as it is today. There is ice melting into the ocean, creating cold fronts, etc. After taking that class, I’m impressed we can predict it at all.
Remember that weather prediction has continued to get better as years have gone on. When I was a kid (in the dark ages of the 1970s), the weather prediction was:
Tomorrow would right more than half the time. And prediction would be RAIN/SUN/FOG YES/NO and that was it.
The day after that would be right one in ten.
All days past that would be “Partly cloudy” – Not kidding.
And then in the later 1990s, suddenly everyone had very accurate 3 day forecasts – that were accurate. And the one week look ahead was right more than half the time.
Now a days, the weather prediction has gotten very good.
One reason is that predictions about what will happen to the system as a whole can be pretty accurate but predictions about what will happen in a given spot on the earth’s surface (which is what we generally want) are harder. Consider a big storm system with a sharp edge: we might say that it’s moving westward at XX km/h so we expect that it will be in this area in 24 hours. But there is a margin of error in exactly what its path will be. If the spot you are in is A, in the middle of the path, it’s almost certain that the storm will hit you. But if the spot is B, just on the edge of the area it will hit, a 1-degree difference in the path will make the difference between a sunny or rainy day. When meteorologists say that for A there’s a 90% chance of rain, for B there’s a 50% chance of rain, it’s a simplified expression of these different levels of confidence. But they might be very confident that the storm will move in a certain way, just not know exactly where its edges will be. Of course that confidence decreases sharply over time.
There are thousands of variables in the atmosphere, and meteorologists can only really guess and use models to help predict. They know what ingredients are present, what airmasses will collide etc, but they have no idea exactly what shape the weather will take until it forms.
When you see “80% chance of rain,” take that to mean that there’s an 80% chance that it will rain *somewhere near you.*
Weather forecasts aren’t for your backyard specifically, they’re for your area in general.
My area had an 80% chance of 2-3″ of rain yesterday. We had a flood watch, a tornado watch and a hazardous weather outlook all issued. All the models and all of the predictions pointed towards a big rain event, followed by possibly severe storms…
…well, all of that happened, but about 20 miles north of me. All of my neighbors were saying how wrong and stupid the weather people are, when, in reality they were *dead on with their forecast,* but the weather formed 20 miles north of us instead…and all of those folks 20 miles north of me had the *exact same forecast that I did.*
They are not accurate because people don’t understand statistics and what the numbers mean.
The full forecast is quite comprehensive with hundreds of numbers for each forecast cell, and each cell can be as small as 5 km square. Globally, people like airline pilots have access to millions of numbers showing global forecasts with details of every kilometer of their journey at every altitude in the sky. The numbers are quite accurate, but are given with ranges and probability.
The weather forecast models use words many people often misunderstand, and many details of the forecast are omitted in the simple forecaats.
Consider [a chart like this](https://charts.ecmwf.int/products/opencharts_meteogram?epsgram=classical_10d&lat=30.2672&lon=-97.7431&station_name=Austin) which gives a lot of information about the weather that is likely, and the weather that is less likely but still possible, with bands at 10%, 25%, 50%, 75%, and 90%. The detailed models have far more detailed information in smaller time bands, but it is overwhelming for most people. Very useful for people who want the details, though.
Most people want *”we’re getting a bunch of rain, but a few people will miss out”,* rather than *”models forecast 50% at 7/8 cloud cover but 25% chance of 5/8 cloud cover, and 50% of 1.5 cm of rain, 25% of no rain, but a 10% chance of 4 cm.”*
They are all probabilistic, but it could be simplified this way: in a century of observation we know what this pattern looks like. When we see the pattern, 60% of the time we get scattered showers, 30% of the time we are dry, but one in ten we get drenched with flooding.
Aside from what others have said (and with the grain of salt that I’m in the U.S. and if you’re not the situation may different where you are), there are different models that produce different predictions. Some sources will use the prediction of the model they deem mostly likely to be accurate (I get my forecasts from NOAA for this reason -they’re wonderfully accurate [tho of course not perfect]). TV/radio stations, certain websites, basically anyone who’s making weather predictions as part of a money-making operation, are likely to use the predictions of the model that’s going to drive the most engagement. For example, I’m in Minnesota. We get a lot of snow in the winter (usually) and strong thunderstorms/tornadoes in the summer. Local TV forecasts are often much more dramatic – higher snow totals, stronger storms, more tornadoes – than I what I see on NOAA. Most oftern, the NOAA prediction is closer to what happens.
All things considered, we do a damn good job of predicting the weather considering how chaotic of a system it is, and we get better at it every day as we add more and more data into models. The fact that we can have a pretty good idea of where a hurricane is going to hit several days out is nothing short of a modern miracle.
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