WeatherNext 2: Our most advanced weather forecasting model

They "MetNet-3" into Google products and my personal perception was accuracy decreased.

Indeed. The most important benchmark is accuracy and how well it stacks up against existing physics-based models like GFS or ECMWF.

Sure, those big physics-based models are very computationally intensive (national weather bureaus run them on sizeable HPC clusters), but you only need to run them every few hours in a central location and then distribute the outputs online. It's not like every forecaster in a country needs to run a model, they just need online access to the outputs. Even if they could run the models themselves, they would still need the mountains of raw observation data that feeds the models (weather stations, satellite imagery, radars, wind profilers...). And these are usually distributed by... the national weather bureau of that country. So the weather bureau might as well do the number crunching as well and distribute that.

As a end user I also want to see the variance to get a feeling of the uncertainty.

Quite a lot of weather sites offer this data in an easily eatable visual format.

No need for anecdata! We have the data: https://ourworldindata.org/weather-forecasts

tdlr: Weather forecasts have improved a lot

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.

Windy allows you to select your model. For that reason it's my go to for accuracy.

Different models have different strengths, though. Some are shorter range (72h) or longer range (1-3 weeks). Some are higher resolution for where you live (the size of an area which it assigns a forecast to, so your forecast is more local).

Some governments will have their own weather model for your country that is the most accurate for where you live. What I did for a long time was use Windy and use HDRPS (a Canadian short range model with a higher resolution in Canada so I have more accurate forecasts). Now I just use the government of Canada weather app.

I genuinely wonder what the weather Channel, iPhone/Android official weather apps, etc. use under the hood for global models. My gut says ECMWF (a European model with global coverage) mixed with a little magic.

I find that unlikely, my forecasts for much of Europe and East Asia have been consistently accurate.