WeatherNext 2: Our most advanced weather forecasting model

I find it interesting that they quantify the improvement on speed and number of forecast-ed scenarios but lack details on how it results in improved accuracy of the forecast per:

``` WeatherNext 2 can generate forecasts 8x faster and with resolution up to 1-hour. This breakthrough is enabled by a new model that can provide hundreds of possible scenarios. ```

As an end user, all I care is that there's one accurate forecasted scenario.

This is really important: You're not the end user of this product. These types of models are not built for laypeople to access them. You're an end user of a product that may use and process this data, but the CRPS scorecard, for example, should mean nothing to you. This is specifically addressing an under-dispersion problem in traditional ensemble models, due to a limited number (~50) and limited set of perturbed initial conditions (and the fact that those perturbations do very poorly at capturing true uncertainty).

Again, you, as an end user, don't need to know any of that. The CRPS scorecard is a very specific measure of error. I don't expect them to reveal the technical details of the model, but an industry expert instantly knows what WeatherBench[1] is, the code it runs, the data it uses, and how that CRPS scorecard was generated.

By having better dispersed ensemble forecasts, we can more quickly address observation gaps that may be needed to better solidify certain patterns or outcomes, which will lead to more accurate deterministic forecasts (aka the ones you get on your phone). These are a piece of the puzzle, though, and not one that you will ever actually encounter as a layperson.

[1]: https://sites.research.google/gr/weatherbench/