So, Windy takes the model data (once for each of ECMWF, GFS, NAM, etc.), runs it through deterministic models, and that spits out windy's 'layers,' generated on a 'high' resolution grid. And the results are not probabilities, they are straight up predictions for what's going to happen at that geo-temporal point. Correct me if that's wrong.
With the ensemble method; because it uses 20-21 forecasts for a larger area (lower resolution grid), with each input perturbed, and some of those numerus forecasts result in rain and some result in less rain, that is how that method generates a probability?
Is the reason you can't do this at a higher resolution just a computational limitation, or are the 20-21 points representative of sub-pixels in different geo-areas of one of the larger main output pixels (and so with more sub-pixels, the result is more accurate but at the same time covers a larger resulting land area)?