Open AccessUse of medium‐range ensembles at the Met Office I: PREVIN –a system for the production of probabilistic forecast information from the ECMWF EPS
Author(s) -
Legg T P,
Mylne K R,
Woolcock C
Publication year - 2002
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 - 10.1017/s1350482702003018
Subject(s) - probabilistic logic , range (aeronautics) , probabilistic forecasting , computer science , production (economics) , meteorology , consensus forecast , ensemble forecasting , set (abstract data type) , data set , forecast verification , environmental science , forecast skill , econometrics , artificial intelligence , mathematics , geography , materials science , economics , composite material , macroeconomics , programming language
Abstract This is the first of a pair of papers covering the production and use of probability forecasts at ranges of 3 to 10 days at the Met Office using the ECMWF Ensemble Prediction System (EPS). The use of ensembles is intended to provide a set of forecasts which cover the range of possible uncertainty, recognising that it is impossible to obtain a single deterministic forecast which is always correct. We present a brief review of ensemble forecasting techniques and their use for the generation of probability forecasts. A wide range of probability forecasting products and tools are now available to forecasters at the Met Office, generated from the EPS. These will be described, and their use and interpretation discussed, both for site‐specific forecast data and for fields of data covering a wider area. An important part of any forecasting system is verification: this is covered in some detail using several different methods, for the site‐specific forecasts of surface weather parameters. Comparisons are made between the probabilistic forecasts and equivalent deterministic forecasts generated from the high‐resolution ECMWF model, and it is evident that the former are more skilful according to most assessment methods for forecasts more than three days ahead. The companion paper shows how forecasters use the vast amounts of information available in forecast production (Young and Carroll 2002). Copyright © 2002 Royal Meteorological Society.