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Comparison between Singular Vectors and Breeding Vectors as Initial Perturbations for the ECMWF Ensemble Prediction System
Stockholm University, Faculty of Science, Department of Meteorology.
Stockholm University, Faculty of Science, Department of Meteorology.
2008 (English)In: Monthly Weather Review, ISSN 0027-0644, Vol. 136, no 11, 4092-4104 p.Article in journal (Refereed) Published
Abstract [en]

In this paper a study aimed at comparing the perturbation methodologies based on the singular vector ensemble prediction system (SV-EPS) and the breeding vector ensemble prediction system (BV-EPS) in the same model environment is presented. A simple breeding system (simple BV-EPS) as well as one with regional rescaling dependent on an estimate of the analysis error variance (masked BV-EPS) were used. The ECMWF Integrated Forecast System has been used and the three experiments are compared for 46 forecast cases between 1 December 2005 and 15 January 2006. By studying the distribution of the perturbation energy it was possible to see large differences between the experiments initially, but after 48 h the distributions have converged. Using probabilistic scores, these results show that SV-EPS has a somewhat better performance for the Northern Hemisphere compared to BV-EPS. For the Southern Hemisphere masked BV-EPS and SV-EPS yield almost equal results. For the tropics the masked breeding ensemble shows the best performance during the first 6 days. One reason for this is the current setup of the singular vector ensemble at ECMWF yielding in general very low initial perturbation amplitudes in the tropics.

Place, publisher, year, edition, pages
2008. Vol. 136, no 11, 4092-4104 p.
National Category
Meteorology and Atmospheric Sciences
Identifiers
URN: urn:nbn:se:su:diva-14998DOI: 10.1175/2008MWR2498.1ISI: 000260861900005OAI: oai:DiVA.org:su-14998DiVA: diva2:181518
Available from: 2009-01-13 Created: 2009-01-13 Last updated: 2009-04-22Bibliographically approved
In thesis
1. Sampling uncertainties in ensemble weather forecasting
Open this publication in new window or tab >>Sampling uncertainties in ensemble weather forecasting
2009 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The aim of ensemble weather forecasting is to provide probability forecasts for the occurrence of meteorological events. The ensembles are constructed by assembling several forecast realisations, each member of the ensemble being constructed to sample the uncertainties in the forecast. These originate from uncertainties in the initial conditions (the analysis) and imperfections of the numerical model. 

 In order to sample the initial uncertainties several techniques have been proposed. The singular-vector technique yields perturbations optimised to maximize the perturbation growth over a finite time interval, whereas the breeding method recycles the perturbations from the previous ensemble in order to sample growing modes.  The ensemble-transform method represents a further development of the breeding method. Here, to create initial perturbations independent of the current flow situation of the atmosphere, random perturbations are introduced by using the difference between two randomly chosen atmospheric states (i.e. analyses). The method produces dynamically balanced perturbations denoted Random Field perturbations (RF). 

 Our results show that the RF perturbations initially have the same dynamical properties as the variability of the atmosphere. After integration over a day the perturbations from all three methods (RF, singular vectors and ensemble transform perturbations) converge. The skill scores indicate a statistically significant advantage for the RF method during the first 2-3 days for most of the evaluated parameters. Over the medium range (3-8 days) the differences are very small. We also discuss the influence of the asymptotic variability of the forecasting model on the ensemble properties.

 

Place, publisher, year, edition, pages
Stockholm: Department of Meteorology, Stockholm University, 2009. 52 p.
Keyword
Ensemble forecasting, Initial perturbation techniques
National Category
Meteorology and Atmospheric Sciences
Research subject
Meteorology
Identifiers
urn:nbn:se:su:diva-27021 (URN)978-91-7155-865-7 (ISBN)
Public defence
2009-06-05, William-Olssonsalen, Geovetenskapens hus, Svante Arrhenius väg 8 A, Stockholm, 10:00 (English)
Opponent
Supervisors
Available from: 2009-05-14 Created: 2009-04-22 Last updated: 2009-04-22Bibliographically approved

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