Open AccessHow much does simplification of probability forecasts reduce forecast quality?
Author(s) -
DoblasReyes F. J.,
Coelho C. A. S.,
Stephenson D. B.
Publication year - 2008
Publication title -
meteorological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 59
eISSN - 1469-8080
pISSN - 1350-4827
DOI - 10.1002/met.50
Subject(s) - brier score , forecast skill , probabilistic logic , probabilistic forecasting , forecast verification , ensemble forecasting , computer science , set (abstract data type) , consensus forecast , quantitative precipitation forecast , range (aeronautics) , global forecast system , quality (philosophy) , statistics , meteorology , econometrics , numerical weather prediction , mathematics , artificial intelligence , geography , philosophy , materials science , epistemology , composite material , programming language , precipitation
Probability forecasts from an ensemble are often discretized into a small set of categories before being distributed to the users. This study investigates how such simplification can affect the forecast quality of probabilistic predictions as measured by the Brier score (BS). An example from the European Centre for Medium‐Range Weather Forecasts (ECMWF) operational seasonal ensemble forecast system is used to show that the simplification of the forecast probabilities reduces the Brier skill score (BSS) by as much as 57% with respect to the skill score obtained with the full set of probabilities issued from the ensemble. This is more obvious for a small number of probability categories and is mainly due to a decrease in forecast resolution of up to 36%. The impact of the simplification as a function of the ensemble size is also discussed. The results suggest that forecast quality should be made available for the set of probabilities that the forecast user has access to as well as for the complete set of probabilities issued by the ensemble forecasting system. Copyright © 2008 Royal Meteorological Society