Why can't the meteorologists predict for sure if the day would be rainy even on the beginning of the day sometimes?

Question

Why do the meteorologists still cannot predict if a day would be rainy or cloudy or blizzardy even on the beginning of the day sometimes?

My life circles around weather and an avid weather watcher.

And I noticed the computers still are not advanced enough to get all the variables to predict the weather accurately. The weathermen and women still read the probabilities. For example, there is a 70% chance of rain. I take the umbrella outside and there is no rain. Then the prediction is the day would be cloudy. But then there is rain. I am not saying it happens most of the time. But it happens sometimes.

Do we need a quantum computer then with qubits? Because it can hold a myriad of variables and consider them in the calculation of the weather.

Answer 1

The probability of precipitation (POP) has to take into account the areal coverage of some region, e.g. the broadcast market of your local TV station, but perhaps the size of your local county or region.

Because of this the POP is calculated as

$\mathrm{POP} = C \times A$

where $C$ is the confidence it will rain somewhere within the forecast region and $A$ how much of the area will experience the precipitation.

So a 100% chance of rain means it is going to rain in the entire forecast region and they are confident that it will rain. That is a high bar, as spatial coverage of storms is often localized.

For example, if one storm is going to track through your city and its path is only going to cover 15% of the area, even if we are 100% sure it is going to happen, that still only yields a "15% chance of rain". This is because people living in that area where the storm goes though will get rained on, but the other people will not. This also helps average out temporal and spatial errors in the forecast.