Why do weather forecasts sometimes fail to predict accurately?
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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.
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