Comment by deanputney
1 day ago
I've found this to be more related to poor representation of the data than inaccurate data.
For example on Apple's Weather app, a "rainy" day means a high chance of rain at any point during the day. If it's 80% chance of rain at 5am and sunny the rest of the day– that counts as rainy. You can see an hourly report for more info, and generally this is pretty accurate. You have to learn how to find the right data, know your local area, and interpret it yourself.
Then you have to consider what effects this has on your plans and it gets more complicated. Finding a window to walk the dog, choosing a day to go sailing, or determining conditions for backcountry skiing all have different requirements and resources. What I'd like AI to do is know my own interests and highlight what the forecast means for me.
In Norway people are extremely weather-focused, and the national weather service delivers quite advanced graphics for people to understand what is going on.
The standard graph that most people look at to get an idea about today and tomorrow: https://www.yr.no/en/forecast/graph/1-72837/Norway/Oslo/Oslo...
The live weather radar which shows where it is raining right now and prediction/history for rain +/- 90 minutes. This is accurate enough that you can use it to time your walk from the office to the subway and avoid getting wet: https://www.yr.no/en/map/radar/1-72837/Norway/Oslo/Oslo/Oslo
Then you have more specialised forecasts of course. Dew point, feels like temperature, UV, pollution, avalanche risks, statistics, sea conditions, tides, ... People tend to geek out quite heavily on these.
The United States (National Weather Service) has these too: https://www.weather.gov/forecastmaps/
I use these and Windy: https://www.windy.com/
In my experience, these forecasts are really good 5-7 days out, and then degrade in reliability (as you would expect from predictions of chaotic systems). The apps that show you a rain cloud and a percentage number are always terrible in my experience for some reason, even if the origin of the data is the same. I'm not sure why that might be.