> 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.

Sorry - not sure this is a reasonable take-away. The models here are all still initialized from analysis performed by ECMWF; Google is not running an in-house data assimilation product for this. So there's no feedback mechanism between ensemble spread/uncertainty and the observation itself in this stack. The output of this system could be interrogated using something like Ensemble Sensitivity Analysis, but there's nothing novel about that and we can do that with existing ensemble forecast systems.