Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-24T12:04:20.159Z Has data issue: false hasContentIssue false

Use of medium-range ensembles at the Met Office 2: Applications for medium-range forecasting

Published online by Cambridge University Press:  20 August 2002

M V Young
Affiliation:
National Meteorological Centre, Met Office, London Road, Bracknell, RG12 2SZ, United [email protected]
E B Carroll
Affiliation:
National Meteorological Centre, Met Office, London Road, Bracknell, RG12 2SZ, United [email protected]
Get access

Abstract

The term ‘medium range’ is taken to refer to forecasts for lead times ranging from about 2 or 3 days ahead up to about 10 days ahead. A wide variety of numerical model products are available to the forecaster nowadays, and one of the most important of these is the ECMWF Ensemble Prediction System (EPS). This paper shows how forecasters at the Met Office use these products, in particular the EPS, in an operational environment in the production of medium-range forecasts for a variety of customers, and illustrates some of the techniques involved. Particular reference is made to the PREVIN post-processing system for the EPS which is described in the companion paper by Legg et al. (2002). Forecast products illustrated take the form of synoptic charts (produced primarily via Field Modification software), text guidance and other graphical formats. The probabilistic approach to forecasting is discussed with reference to various examples, in particular the application of the EPS in providing early warnings of severe weather for which risk assessment is increasingly important. A central theme of this paper is the vital role played by forecasters in interpreting the output from the models in terms of the likely weather elements, and using the EPS to help assess confidence levels for a particular forecast as well as possible alternative synoptic evolutions. Verification statistics are presented which demonstrate how the EPS helps the forecaster to add value to the wide range of individual deterministic model products and that furthermore, the forecaster can improve upon many probabilistic products derived directly from the ensemble.

Type
Research Article
Copyright
© 2002 Royal Meteorological Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)