After a little statistical postprocessing (that can be done operationally and that takes care of the bias in probabilities arising due to model/ensemble problems) probabilistic forecasts from the global ensemble are very reliable. If the ensemble suggests an event will happen with 80% (or 10%) probability, that type of event will verify with roughly 80% (or 10%) of such forecast cases! Please see examples of reliability diagrams for 12-24 hrs and 120 hrs forecasts. We get similarly reliable probabilistic forecasts at all lead times out to 15 days. Note, however, that at longer lead times forecast probability values will generally be further and further restricted toward values near climatological probabilities, reflecting the loss of predictability at longer lead times.

On different days the loss of predictability, however, occurs at various lead times: for example, 10-15% OF THE TIME A 12-DAY FORECAST CAN BE AS GOOD, OR A 1-DAY FORECAST CAN BE AS POOR AS AN AVERAGE 4-DAY FORECAST! And the ensemble can reliably identify these cases in advance.  By using the full probability information from the ensemble (red line), as compared to using categorical forecasts from the control forecasts (green and blue lines), the information content of a 5-day forecast can be more than doubled; or a 7.5 day forecast with the full ensemble-based probablity distribution has as much information as a 5-day categorical forecast guidance based on a single deterministic run.