Editorial Type:
Article
Article Type:
Research Article

The Prediction of Extratropical Storm Tracks by the ECMWF and NCEP Ensemble Prediction Systems

Lizzie S. R. Froude Environmental Systems Science Centre, University of Reading, Reading, United Kingdom

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Lennart Bengtsson Environmental Systems Science Centre, University of Reading, Reading, United Kingdom

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Kevin I. Hodges Environmental Systems Science Centre, University of Reading, Reading, United Kingdom

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Print Publication:
01 Jul 2007
DOI:
https://doi.org/10.1175/MWR3422.1
Page(s):
2545–2567
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Abstract

The prediction of extratropical cyclones by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ensemble prediction systems (EPSs) has been investigated using an objective feature tracking methodology to identify and track the cyclones along the forecast trajectories. Overall the results show that the ECMWF EPS has a slightly higher level of skill than the NCEP EPS in the Northern Hemisphere (NH). However in the Southern Hemisphere (SH), NCEP has higher predictive skill than ECMWF for the intensity of the cyclones. The results from both EPSs indicate a higher level of predictive skill for the position of extratropical cyclones than their intensity and show that there is a larger spread in intensity than position. Further analysis shows that the predicted propagation speed of cyclones is generally too slow for the ECMWF EPS and shows a slight bias for the intensity of the cyclones to be overpredicted. This is also true for the NCEP EPS in the SH. For the NCEP EPS in the NH the intensity of the cyclones is underpredicted. There is small bias in both the EPS for the cyclones to be displaced toward the poles. For each ensemble forecast of each cyclone, the predictive skill of the ensemble member that best predicts the cyclone’s position and intensity was computed. The results are very encouraging showing that the predictive skill of the best ensemble member is significantly higher than that of the control forecast in terms of both the position and intensity of the cyclones. The prediction of cyclones before they are identified as 850-hPa vorticity centers in the analysis cycle was also considered. It is shown that an indication of extratropical cyclones can be given by at least 1 ensemble member 7 days before they are identified in the analysis. Further analysis of the ECMWF EPS shows that the ensemble mean has a higher level of skill than the control forecast, particularly for the intensity of the cyclones, from day 3 of the forecast. There is a higher level of skill in the NH than the SH and the spread in the SH is correspondingly larger. The difference between the ensemble mean error and spread is very small for the position of the cyclones, but the spread of the ensemble is smaller than the ensemble mean error for the intensity of the cyclones in both hemispheres. Results also show that the ECMWF control forecast has ½ to 1 day more skill than the perturbed members, for both the position and intensity of the cyclones, throughout the forecast.

Corresponding author address: Lizzie S. R. Froude, Environmental Systems Science Centre, University of Reading, Harry Pitt Building, Whiteknights, P.O. Box 238, Reading RG6 6AL, United Kingdom. Email: lsrf@mail.nerc-essc.ac.uk

Abstract

The prediction of extratropical cyclones by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction (NCEP) ensemble prediction systems (EPSs) has been investigated using an objective feature tracking methodology to identify and track the cyclones along the forecast trajectories. Overall the results show that the ECMWF EPS has a slightly higher level of skill than the NCEP EPS in the Northern Hemisphere (NH). However in the Southern Hemisphere (SH), NCEP has higher predictive skill than ECMWF for the intensity of the cyclones. The results from both EPSs indicate a higher level of predictive skill for the position of extratropical cyclones than their intensity and show that there is a larger spread in intensity than position. Further analysis shows that the predicted propagation speed of cyclones is generally too slow for the ECMWF EPS and shows a slight bias for the intensity of the cyclones to be overpredicted. This is also true for the NCEP EPS in the SH. For the NCEP EPS in the NH the intensity of the cyclones is underpredicted. There is small bias in both the EPS for the cyclones to be displaced toward the poles. For each ensemble forecast of each cyclone, the predictive skill of the ensemble member that best predicts the cyclone’s position and intensity was computed. The results are very encouraging showing that the predictive skill of the best ensemble member is significantly higher than that of the control forecast in terms of both the position and intensity of the cyclones. The prediction of cyclones before they are identified as 850-hPa vorticity centers in the analysis cycle was also considered. It is shown that an indication of extratropical cyclones can be given by at least 1 ensemble member 7 days before they are identified in the analysis. Further analysis of the ECMWF EPS shows that the ensemble mean has a higher level of skill than the control forecast, particularly for the intensity of the cyclones, from day 3 of the forecast. There is a higher level of skill in the NH than the SH and the spread in the SH is correspondingly larger. The difference between the ensemble mean error and spread is very small for the position of the cyclones, but the spread of the ensemble is smaller than the ensemble mean error for the intensity of the cyclones in both hemispheres. Results also show that the ECMWF control forecast has ½ to 1 day more skill than the perturbed members, for both the position and intensity of the cyclones, throughout the forecast.

Corresponding author address: Lizzie S. R. Froude, Environmental Systems Science Centre, University of Reading, Harry Pitt Building, Whiteknights, P.O. Box 238, Reading RG6 6AL, United Kingdom. Email: lsrf@mail.nerc-essc.ac.uk

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