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ECMWF Ensemble Prediction System (ecmwf + ensemble_prediction_system)

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Earth and Environmental Science100%

Selected Abstracts

Reanalysis and reforecast of three major European storms of the twentieth century using the ECMWF forecasting system.

METEOROLOGICAL APPLICATIONS, Issue 2 2005
Part II: Ensemble forecasts
In Part II of this study the ECMWF Ensemble Prediction System (EPS) is used to study the probabilistic predictability of three major European storms of the twentieth century. The storms considered are the Dutch storm of 1 February 1953, the Hamburg storm of 17 February 1962, and the British/French storm of October 1987 (Great October storm). Common to all these storms is their severity that caused large loss of life and widespread damage. In Part I of this study it has been found that deterministic predictability of the Dutch and Hamburg storms amount to 48 and 84 hours, respectively. Here, it is shown that the ensemble forecasts supplement the deterministic forecasts. The large number of members in the 48 and 84 hour ensemble forecasts of the Dutch and Hamburg storms, respectively, suggest that at this forecast range and for these storms the sensitivity of the forecasts to analysis and model uncertainties is rather small. From these results, therefore, it is argued that reliable warnings (i.e. low probability for the occurrence of a forecast failure) for the Dutch and Hamburg storms could have been issued 48 and 84 hours, respectively, in advance, had the current ECMWF EPS been available. For the Great October storm it has been found in Part I of this study that short-range and medium-range forecasts of the intensity and track of the storm were very skilful with a high-resolution model of the ECWMF model. The actual timing of the storm, however, was difficult to predict. Here, it is shown that the EPS is capable of predicting large forecast uncertainties associated with the timing of the Great October storm up to 4 days in advance. It is argued that reliable warnings could have been issued at least 96 hours in advance had the ECMWF EPS been available. From the results presented in this study it is concluded that an Ensemble Prediction System is an important component of every early warning system for it allows an a priori quantification of the probability of the occurrence of severe wind storms. Copyright © 2005 Royal Meteorological Society [source]

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

METEOROLOGICAL APPLICATIONS, Issue 3 2002
M V Young
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. Copyright © 2002 Royal Meteorological Society. [source]

Storm prediction over Europe using the ECMWF Ensemble Prediction System

METEOROLOGICAL APPLICATIONS, Issue 3 2002
Roberto Buizza
Three severe storms caused great damage in Europe in December 1999. The first storm hit Denmark and Germany on 3 and 4 December, and the other two storms crossed France and Germany on 26 and 28 December. In this study, the performance of the Ensemble Prediction System (EPS) at the European Centre for Medium-Range Weather Forecast (ECMWF) in predicting these intense storms is investigated. Results indicate that the EPS gave early indications of possible severe storm occurrence, and was especially useful when the deterministic TL319L60 forecasts issued on successive days were highly inconsistent. These results indicate that the EPS is a valuable tool for assessing quantitatively the risk of severe weather and issuing early warnings of possible disruptions. The impact of an increase of the ensemble system horizontal resolution (TL255 integration from a TL511 analysis instead of the operational TL159 integration from a TL319 analysis) on the system performance is also investigated. Results show that the resolution increase enhances the ensemble performance in predicting the position and the intensity of intense storms. Copyright © 2002 Royal Meteorological Society. [source]

Probabilistic temperature forecast by using ground station measurements and ECMWF ensemble prediction system

METEOROLOGICAL APPLICATIONS, Issue 4 2004
P. Boi
The ECMWF Ensemble Prediction System 2-metre temperature forecasts are affected by systematic errors due mainly to resolution inadequacies. Moreover, other errors sources are present: differences in height above sea level between the station and the corresponding grid point, boundary layer parameterisation, and description of the land surface. These errors are more marked in regions of complex orography. A recursive statistical procedure to adapt ECMWF EPS-2metre temperature fields to 58 meteorological stations on the Mediterranean island of Sardinia is presented. The correction has been made in three steps: (1) bias correction of systematic errors; (2) calibration to adapt the EPS temperature distribution to the station temperature distribution; and (3) doubling the ensemble size with the aim of taking into account the analysis errors. Two years of probabilistic forecasts of freezing are tested by Brier Score, reliability diagram, rank histogram and Brier Skill Score with respect to the climatological forecast. The score analysis shows much better performance in comparison with the climatological forecast and direct model output, for all forecast timse, even after the first step (bias correction). Further gains in skill are obtained by calibration and by doubling the ensemble size. Copyright © 2004 Royal Meteorological Society. [source]

Scale-dependent verification of ensemble forecasts

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 633 2008
Thomas Jung
Abstract A scale-dependent verification of the ECMWF ensemble prediction system (EPS) in the Northern Hemisphere is presented. The relationship between spread and skill is investigated alongside probabilistic forecast skill for planetary, synoptic and subsynoptic spectral bands. Since the ECMWF model is a spectral model, the three spectral bands have been isolated using total and zonal wavenumber filters. Diagnosed overdispersiveness of ECMWF EPS in the short range is primarily due to excessive amounts of spread on synoptic scales. Diagnosed underdispersiveness of the ensemble beyond day 5 of the forecast can be explained by too little spread on both synoptic and planetary scales. Copyright © 2008 Royal Meteorological Society [source]