Ensemble forecast post-processing over Belgium: Comparison of deterministic-like and ensemble regression methods

Meteorological Applications

Volumn 18, Issue 1, 2011, Pages 94-104

  Vannitsem, Stéphane ^a   Hagedorn, Renate ^b  

^a ROYAL METEOROLOGICAL INSTITUTE OF BELGIUM   (Belgium)

^b EUROPEAN CENTRE FOR MEDIUM RANGE WEATHER FORECASTS   (United Kingdom)

Author keywords

ECMWF; ERA interim; Model output statistics; Non homogeneous Gaussian regression; Predictability; Probabilistic forecasts

Indexed keywords

REGRESSION ANALYSIS;

ECMWF; ERA INTERIMS; GAUSSIAN REGRESSION; MODEL OUTPUT STATISTICS; PREDICTABILITY; PROBABILISTIC FORECASTS;

FORECASTING;

DATA PROCESSING; DATA SET; ENSEMBLE FORECASTING; ERROR ANALYSIS; GAUSSIAN METHOD; REGRESSION ANALYSIS; UNCERTAINTY ANALYSIS;

BELGIUM;

EID: 79951829554     PISSN: 13504827     EISSN: 14698080     Source Type: Journal    
DOI: 10.1002/met.217     Document Type: Article

References (29)

1. Bechtold P, Köhler M, Jung Th, Doblas-Reyes F, Leutbecher M, Rodwell MJ, Vitart F, Balsamo G. 2008. Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time scales. Quarterly Journal of the Royal Meteorological Society 134: 1337-1351.
2. Bougeault P, Fuentes M, Raoult B, and co-authors. 2009. The THORPEX Interactive Grand Global Ensemble (TIGGE). Bulletin of the American Meteorological Society in press.
3. Bowler NE. 2006. Explicit accounting for observation error in categorical verification of forecasts. Monthly Weather Review 134: 1600-1606.
4. Buizza R, Houtekamer PL, Pellerin G, Toth Z, Zhu Y, Wei M. 2005. A comparison of the ECMWF, MSC, and NCEP global ensemble prediction systems. Monthly Weather Review 133: 1076-1097.
5. Candille G, Talagrand O. 2008. Impact of observational error on the validation of ensemble prediction systems. Quarterly Journal of the Royal Meteorological Society 134: 959-971.
6. Doblas-Reyes FJ, Hagedorn R, Palmer TN. 2005. The rationale behind the success of multi-model ensembles in seasonal forecasting-II Calibration and combination. Tellus 57A: 234-252.
7. Efron B, Tibshirani R. 1993. An Introduction to the Bootstrap. Chapman & Hall: New York, NY.
8. Glahn HR, Lowry DA. 1972. The use of Model Output Statistics (MOS) in objective weather forecasting. Journal of Applied Meteorology 11: 1203-1211.
9. Glahn HR, Peroutka M, Wiedenfeld J, Wagner J, Zylstra G, Schuknecht B, Jackson B. 2009. MOS uncertainty estimates in an ensemble framework. Monthly Weather Review 137: 246-267.
10. Gneiting T, Raftery AE, Westveld AH III, Goldman T. 2005. Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation. Monthly Weather Review 133: 1098-1118.
11. Hagedorn R. 2008. Using the ECMWF reforecast dataset to calibrate EPS forecasts. ECMWF Newsletter 117: 8-13.
12. Hagedorn R, Hamill TM, Whitaker JS. 2008. Probabilistic forecast calibration using the ECMWF and GFS ensemble reforecasts. Part I: Two-Meter temperatures. Monthly Weather Review 136: 2608-2619.
13. Hamill TM. 2001. Interpretation of Rank Histograms for verifying ensemble forecasts. Monthly Weather Review 129: 550-560.
14. Hamill TM, Whitaker JS, Mullen SL. 2006. Reforecasts: an important dataset for improving weather predictions. Bulletin of the American Meteorological Society 87: 33-46.
15. Hamill TM, Wilks DS. 2007. Comparison of Ensemble-MOS methods using GFS reforecasts. Monthly Weather Review 135: 2379-2390.
16. Mahfouf JF, Bergaoui K, Draper C, Bouyssel F, Taillefer F, Taseva L. 2009. A comparison of two off-line soil analysis schemes for assimilation of screen level observations. Journal of Geophysical Research 114: D08105.
17. Molteni F, Buizza R, Palmer TN, Petroliagis T. 1996. The ECMWF Ensemble Prediction System: Methodology and validation. Quarterly Journal of the Royal Meteorological Society 122: 73-119.
18. Parrish DF, Derber JC. 1992. The National Meteorological Center's spectral statistical-interpolation analysis system. Monthly Weather Review 120: 1747-1763.
19. Press WH, Teukolsky SA, Vetterling WT, Flannery BP. 1996. Numerical Recipes in Fortran 77. Cambridge University Press: Cambridge.
20. Saetra O, Hersbach H, Bidlot J-R, Richardson D. 2004. Effects of observation errors on the statistics for ensemble spread and reliability. Monthly Weather Review 132: 1487-1501.
21. Simmons A, Uppala S, Dee D, Kobayashi S. 2007. ERA-Interim: new ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter 110: 25-35.
22. Toth Z, Kalnay E. 1997. Ensemble forecasting at NCEP and the breeding method. Monthly Weather Review 125: 3297-3319.
23. Unger DA, van den Dool H, O'Lenic E, Collins D. 2009. Ensemble regression. Monthly Weather Review 137: 2365-2379.
24. Uppala SM and co-authors. 2005. The ERA-40 re-analysis. Quarterly Journal of the Royal Meteorological Society 131: 2961-3012.
25. Vannitsem S. 2008. Dynamical properties of MOS forecasts: Analysis of the ECMWF operational forecasting system. Weather and Forecasting 23: 1032-1043.
26. Vannitsem S. 2009. A unified linear model output statistics scheme for both deterministic and ensemble forecasts. Quarterly Journal of the Royal Meteorological Society 135: 1801-1815.
27. Vannitsem S, Nicolis C. 2008. Dynamical properties of model output statistics forecasts. Monthly Weather Review 136: 405-419.
28. Wilks DS. 2006a. Comparison of ensemble-MOS methods in the Lorenz'96 setting. Meteorological Applications 13: 243-256.
29. Wilks DS. 2006b. Statistical Methods in the Atmospheric Sciences. Academic Press: New York, NY.