Quarterly Journal of the Royal Meteorological Society Q. J. R. Meteorol. Soc. (2011) Observational probability method to assess ensemble precipitation forecasts Carlos Santos a and Anna Ghelli b * a Spanish Meteorological Agency (AEMET), Madrid, Spain b European Centre for Medium-Range Weather Forecasts (ECMWF), Reading, UK *Correspondence to: C. Santos, AEMET, C/Leonardo Prieto Castro, 8 Ciudad Universitaria, 28071 Madrid E-mail: csantosb@aemet.es It is common practice when assessing the skill of either deterministic or ensemble forecasts to consider the observations with no uncertainty. Observation uncertainty may be associated with different causes and the present paper discusses the uncer- tainty that derives from the mismatch between model-generated grid point precip- itation and locally measured precipitation values. There have been many attempts to add uncertainty to the verification process; in the present paper the uncertainty is derived from the observed precipitation distribution within grid boxes of assigned resolution. The Brier skill score (BSS) and the area under relative operating charac- teristic curve skill score calculated utilizing the verification method which includes observational uncertainty (O-OP), are compared to analogous scores obtained from standard verification methods. The scores are calculated for two different forecast- ing systems: the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System and the Spanish Meteorological Agency Short-Range Ensemble Prediction System. The results show that the resolution component of the BSS improves when using the O-OP method, i.e. forecast probabilities are distinguished from climatological probabilities and therefore the system has better skill. The reliability component, on the contrary, greatly degrades and this degradation is worse for lower precipi- tation thresholds. The results also show that the more asymmetric the precipitation distribution is within the grid box, the larger is the degradation of the reliability com- ponent. The overall BSS improves except for low thresholds. These results encourage further research into observation uncertainty and how it can be effectively accounted for in the verification of weather parameters such as precipitation. Copyright c  2011 Royal Meteorological Society Key Words: observational uncertainty; ensemble forecast verification; Brier skill score; gridded observed precipitation estimation Received 3 November 2010; Revised 5 April 2011; 28 June 2011; Accepted 5 July 2011; Published online in Wiley Online Library Citation: Santos C, Ghelli A. 2011. Observational probability method to assess ensemble precipitation forecasts. Q. J. R. Meteorol. Soc. DOI:10.1002/qj.895 1. Introduction Verification of numerical weather prediction (NWP) models plays a central role in the improvement of both short and medium range forecasts. Deterministic and ensemble forecasts are assessed to ascertain their skill against observations and the latter are assumed to be exact. Even though this assumption is not in general true, it is widely accepted in the context of verification. In the last few years, many papers have discussed the validity of this assumption Copyright c  2011 Royal Meteorological Society