The forecast skill horizon

Quarterly Journal of the Royal Meteorological Society

Volumn 141, Issue 693, 2015, Pages 3366-3382

  Buizza, Roberto ^a   Leutbecher, Martin ^a  

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

Author keywords

Butterfly effect; Ensemble prediction; Extended range prediction; Forecast skill horizon; Predictability

Indexed keywords

DISTRIBUTION FUNCTIONS; PROBABILITY; PROBABILITY DISTRIBUTIONS; WATER WAVES; WEATHER FORECASTING;

BUTTERFLY EFFECTS; CLIMATOLOGICAL DISTRIBUTIONS; CONTINUOUS RANKED PROBABILITY SCORES; ENSEMBLE PREDICTION; EXTENDED RANGE; NUMERICAL WEATHER PREDICTION; PREDICTABILITY; SPATIAL AND TEMPORAL SCALE;

FORECASTING;

ACCURACY ASSESSMENT; CLIMATE PREDICTION; CLIMATOLOGY; DATA ASSIMILATION; ENSEMBLE FORECASTING; NUMERICAL MODEL; PROBABILITY; WEATHER FORECASTING;

EID: 84952298672     PISSN: 00359009     EISSN: 1477870X     Source Type: Journal    
DOI: 10.1002/qj.2619     Document Type: Article

References (73)

1. Balsamo G, Agustì-Panareda A, Albergel C, Beljaars A, Boussetta S, Dutra E, Komori T, Lang S, Muñoz-Sabater J, Pappenberger F, de Rosnay P, Sandu I, Wedi N, Weisheimer A, Wetterhall F, Zsoter E. 2014. Representing the Earth Surfaces in the Integrated Forecasting System: Recent Advances and Future Challenges, ECMWF Research Department Technical Memorandum 729. ECMWF: Reading, UK. www.ecmwf.int (accessed 10 January 2014).
2. Bechtold P, Köhler M, Jung T, Doblas-Reyes F, Leutbecher M, Rodwell M, Vitart F, Balsamo G. 2008. Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales. Q. J. R. Meteorol. Soc. 134: 1337-1351.
3. Bechtold P, Semane N, Lopez P, Chaboureau J-P, Beljaars A, Bormann N. 2013. Representing Equilibrium and Non-Equilibrium Convection in Large-Scale Models, ECMWF Research Department Technical Memorandum 705. ECMWF: Reading UK. www.ecmwf.int (accessed 9 January 2013).
4. Berner J, Shutts G, Leutbecher M, Palmer TN. 2008. A spectral stochastic kinetic energy backscatter scheme and its impact on flow-dependent predictability in the ECMWF Ensemble Prediction System. J. Atmos. Sci. 66: 603-626.
5. Branković C, Palmer TN, Molteni F, Tibaldi S, Cubasch U. 1990. Extended-range predictions with ECMWF models: Time-lagged ensemble forecasting. Q. J. R. Meteorol. Soc. 116: 867-912.
6. Brown TA. 1974. Admissible Scoring Systems for Continuous Distributions. Manuscript P-5235. The Rand Corporation: Santa Monica, CA.
7. Buizza R. 2008. The value of probabilistic prediction. Atmos. Sci. Lett. 9: 36-42.
8. Buizza R. 2014. The TIGGE Ensembles, ECMWF Research Department Technical Memorandum 739. ECMWF: Reading, UK. www.ecmwf.int (accessed 11 January 2014).
9. Buizza R, Palmer TN. 1995. The singular vector structure of the atmospheric general circulation. J. Atmos. Sci. 52: 1434-1456.
10. Buizza R, Miller M, Palmer TN. 1999. Stochastic representation of model uncertainties in the ECMWF EPS. Q. J. R. Meteorol. Soc. 125: 2887-2908.
11. Buizza R, Bidlot J-R, Wedi N, Fuentes M, Hamrud M, Holt G, Vitart F. 2007. The new ECMWF VAREPS (Variable Resolution Ensemble Prediction System). Q. J. R. Meteorol. Soc. 133: 681-695.
12. Buizza R, Leutbecher M, Isaksen L. 2008. Potential use of an ensemble of analyses in the ECMWF Ensemble Prediction System. Q. J. R. Meteorol. Soc. 134: 2051-2066.
13. Charney JG, Fleagle RG, Riehl H, Lally VE, Wark DQ. 1966. The feasibility of a global observation and analysis experiment. Bull. Am. Meteorol. Soc. 47: 200-220.
14. Collins M. 2002. Climate predictability on interannual to decadal time scales: The initial value problem. Clim. Dyn. 19: 671-692.
15. Dalcher A, Kalnay E. 1987. Error growth and predictability in operational ECMWF forecasts. Tellus 39A: 474-491.
16. Dee DP, Uppala SM, Simmons AJ, Berrisford P, Poli P, Kobayashi S, Andrae U, Balmaseda MA, Balsamo G, Bauer P, Bechtold P, Beljaars ACM, van de Berg L, Bidlot J, Bormann N, Delsol C, Dragani R, Fuentes M, Geer AJ, Haimberger L, Healy SB, Hersbach H, Hólm EV, Isaksen L, Kållberg P, Köhler M, Matricardi M, McNally AP, Monge-Sanz BM, Morcrette J-J, Park B-K, Peubey C, de Rosnay P, Tavolato C, Thépaut J-N, Vitart F. 2011. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137: 553-597.
17. DelSole T. 2005. Predictability and information theory. Part II: Imperfect forecasts. J. Atmos. Sci. 62: 3368-3381.
18. DelSole T, Tippet MK. 2007. Predictability: recent insights from information theory. Rev. Geophys. 45: RG4002, doi:10.1029/2006RG000202.
19. Durran DR, Gingrich M. 2014. Atmospheric predictability: Why butterflies are not of practical importance. J. Atmos. Sci. 71: 2476-2488.
20. Epstein ES. 1969. A scoring system for probability forecasts of ranked categories. J. Appl. Meteorol. 8: 985-987.
21. Ferro CAT, Richardson DS, Weigel AP. 2008. On the effect of ensemble size on the discrete and continuous ranked probability scores. Meteorol. Appl. 15: 19-24.
22. Gneiting T, Raftery AE. 2007. Strictly proper scoring rules, prediction and estimation. J. Am. Stat. Assoc. 102: 359-378.
23. Goswami BN, Shukla J. 1991. Predictability of a coupled ocean-atmosphere model. J. Clim. 4: 3-22.
24. Guo Z, Dirmeyer PA, DelSole T, Koster RD. 2012. Rebound in atmospheric predictability and the role of the land surface. J. Clim. 25: 4744-4749.
25. Hagedorn R, Buizza R, Hamill TM, Leutbecher M, Palmer TN. 2012. Comparing TIGGE multimodel forecasts with reforecast-calibrated ECMWF ensemble forecasts. Q. J. R. Meteorol. Soc. 139: 1814-1827.
26. Hersbach H. 2000. Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather and Forecasting 15: 559-570.
27. Houtekamer PL, Lefaivre L, Derome J, Ritchie H, Mitchell HL. 1996. A system simulation approach to ensemble prediction. Mon. Weather Rev. 124: 1225-1242.
28. Hoskins BJ. 2013. Review article. The potential for skill across the range of the seamless weather-climate prediction problem: A stimulus for our science. Q. J. R. Meteorol. Soc. 139: 573-584.
29. Hurrell JW, Kushnir Y, Ottersen G, Visbeck M. 2003. An Overview of the North Atlantic Oscillation, Geophysical Monograph 134. American Geophysical Union: Washington, DC.
30. Isaksen L, Bonavita M, Buizza R, Fisher M, Haseler J, Leutbecher Raynaud L. 2010. Ensemble Data Assimilations at ECMWF. ECMWF Research Department Technical Memorandum n. 636. ECMWF: Reading, UK, pp. 45.
31. Janssen PAEM, Bidlot J-R, Abdalla S, Hersbach H. 2005. Progress in Ocean Wave Forecasting at ECMWF, ECMWF Research Department Technical Memorandum 478. ECMWF: Reading, UK. http://old.ecmwf.int/publications/ (accessed 9 January 2005).
32. Janssen PAEM, Breivik O, Mogensen K, Vitart F, Balmaseda M, Bidlot J-R, Keeley S, Leutbecher M, Magnusson L, Molteni F. 2013. Air-Sea Interaction and Surface Waves, ECMWF Research Department Technical Memorandum 712. ECMWF: Reading, UK. http://old.ecmwf.int/publications/ (accessed 11 January 2013).
33. Jung T, Leutbecher M. 2008. Scale-dependent verification of ensemble forecasts. Q. J. R. Meteorol. Soc. 134: 973-984.
34. Kleeman R. 2008. Limits, variability, and general behaviour of statistical predictability of the midlatitude atmosphere. J. Atmos. Sci. 65: 263-275.
35. Kleeman R, Power SB. 1994. Limits to predictability in a coupled ocean-atmosphere model due to atmospheric noise. Tellus 46A: 529-540.
36. Lalaurette F. 2003. Early detection of abnormal weather conditions using a probabilistic extreme forecast index. Q. J. R. Meteorol. Soc. 129: 3037-3057.
37. Leutbecher M, Palmer TN. 2008. Ensemble forecasting. J. Comput. Phys. 227: 3515-3539.
38. Lorenz EN. 1969a. The predictability of a flow which possess many scales of motion. Tellus XXI: 289-307.
39. Lorenz EN. 1969b. Atmospheric predictability as revealed by naturally occurring analogues. J. Atmos. Sci. 26: 636-646.
40. Lorenz EN. 1969c. How much better can weather prediction become?. Technol. Rev. 71: 39-49. Accessible from the MIT library http://eaps4.mit.edu/research/Lorenz/publications.htm (accessed 1 December 1969).
41. Lorenz EN. 1982. Atmospheric predictability experiments with a large numerical model. Tellus 34: 505-513.
42. Madden RA, Julian PR. 1971. Detection of a 40-50 day oscillation in the zonal wind in the tropical Pacific. J. Atmos. Sci. 5: 702-708.
43. Mogensen K, Balmaseda MA, Weaver A. 2012a. The NEMOVAR Ocean Data Assimilation System as Implemented in the ECMWF Ocean Analysis for System 4, ECMWF Research Department Technical Memorandum 668. ECMWF: Reading, UK. http://old.ecmwf.int/publications/ (accessed 2 January 2012).
44. Mogensen K, Keeley S, Towers P. 2012b. Coupling of the NEMO and IFS Models in a Single Executable, ECMWF Research Department Technical Memorandum 673. ECMWF: Reading, UK. http://old.ecmwf.int/publications/ (accessed 4 January 2012).
45. Molteni F, Cubasch U, Tibaldi S. 1987. 30 and 60-day forecast experiments with the ECMWF spectral models. Proceedings of the First ECMWF Workshop on Predictability in the Medium and Extended Range, 17-19 March 1986. 51-108. ECMWF: Reading, UK.
46. Molteni F, Buizza R, Palmer TN, Petroliagis T. 1996. The new ECMWF ensemble prediction system: methodology and validation. Q. J. R. Meteorol. Soc. 122: 73-119.
47. Molteni F, Stockdale T, Balmaseda M, Balsamo G, Buizza R, Ferranti L, Magnusson L, Mogensen K, Palmer T, Vitart F. 2011. The New ECMWF Seasonal Forecast System (System 4), ECMWF Research Department Technical Memorandum 656. ECMWF: Reading, UK. http://old.ecmwf.int/publications/ (accessed 11 January 2011).
48. Morcrette JJ, Bechtold P, Beljaars A, Benedetti A, Bonet A, Doublas-Reyes F, Hague J, Hamrud M, Haseler J, Kaiser JW, Leutbecher M, Mozdzynsky G, Razinger M, Salmond D, Serrar S, Suttie M, Tomkins A, Untch A, Weisheimer A. 2007. Recent Advances in Radiation Transfer Parameterizations, ECMWF Research Department Technical Memorandum 539. ECMWF: Reading, UK. http://old.ecmwf.int/publications/ (accessed 10 January 2007).
49. Murphy AH. 1971. A note on the ranked probability score. J. Appl. Meteorol. 10: 155-156.
50. Palmer TN, Anderson DLT. 1994. The prospects for seasonal forecasting-A review paper. Q. J. R. Meteorol. Soc. 120: 755-793.
51. Palmer TN, Molteni F, Mureau R, Buizza R, Chapelet P, Tribbia J. 1993. Ensemble prediction. In Proceedings of the ECMWF Seminar on Validation of Models over Europe, 7-11 September 1992. Vol. 1: 21-66. ECMWF: Reading, UK.
52. Palmer TN, Buizza R, Leutbecher M, Hagedorn R, Jung T, Rodwell M, Vitart F, Berner J, Hagel E, Lawrence A, Pappenberger F, Park Y-Y, van Bremen L, Gilmour I, Smith L. 2007. The ECMWF Ensemble Prediction System: Recent and On-Going Developments, ECMWF Research Department Technical Memorandum 540. ECMWF: Reading, UK.
53. Palmer TN, Buizza R, Doblas-Reyes F, Jung T, Leutbecher M, Shutts GJ, Steinheimer M, Weisheimer A. 2009. Stochastic Parametrization and Model Uncertainty, ECMWF Research Department Technical Memorandum 598. ECMWF: Reading, UK.
54. Pelly JL, Hoskins BJ. 2003. How well does the ECMWF Ensemble Prediction System predict blocking?. Q. J. R. Meteorol. Soc. 129: 1683-1702.
55. Rotunno R, Snyder C. 2008. A generalization of Lorenz's model for the predictability of flows with many scales of motion. J. Atmos. Sci. 65: 1063-1076.
56. Shukla J. 1981. Dynamical predictability of monthly means. J. Atmos. Sci. 38: 2547-2572.
57. Shukla J. 1998. Predictability in the midst of chaos: a scientific basis for climate forecasting. Science 282: 728-731.
58. Shutts G. 2005. A kinetic energy backscatter algorithm for use in ensemble prediction systems. Q. J. R. Meteorol. Soc. 131: 3079-3100.
59. Shutts G, Leutbecher M, Weisheimer A, Stockdale T, Isaksen L, Bonavita M. 2011. Representing model uncertainty: Stochastic parametrizations at ECMWF. ECMWF Newsl. 129: 19-24.
60. Simmons AJ, Hollingsworth A. 2002. Some aspects of the improvement in skill of numerical weather prediction. Q. J. R. Meteorol. Soc. 128: 647-677.
61. Smagorinsky J. 1969. Problems and promises of deterministic extended-range forecasting. Bull. Am. Meteorol. Soc. 50: 286-311.
62. Stockdale TN, Anderson DLT, Alves JO, Balmaseda MA. 1998. Global seasonal rainfall forecasts with a coupled ocean atmosphere model. Nature 392: 370-373.
63. Tietsche S, Day JJ, Guemas V, Hurlin WJ, Keeley SPE, Matei D, Msadek R, Collins M, Hawkins E. 2014. Seasonal to interannual Arctic sea ice predictability in current global climate models. Geophys. Res. Lett. 41: 1035-1043.
64. Toth Z, Kalnay E. 1993. Ensemble forecasting at NMC: The generation of perturbations. Bull. Am. Meteorol. Soc. 74: 2317-2330.
65. Toth Z, Kalnay E. 1997. Ensemble forecasting at NCEP and the breeding method. Mon. Weather Rev. 125: 3297-3319.
66. Tracton MS, Kalnay E. 1993. Operational ensemble prediction at the National Meteorological Center: Practical aspects. Weather and Forecasting 8: 379-398.
67. Vannitsem S. 2014. Dynamics and predictability of a low-order wind-driven ocean-atmosphere coupled model. Clim. Dyn. 42: 1981-1998.
68. Vitart F. 2004. Monthly forecasting at ECMWF. Mon. Weather Rev. 132: 2761-2779.
69. Vitart F, Woolnough S, Balmaseda MA, Tompkins A. 2007. Monthly forecast of the Madden-Julian Oscillation using a coupled GCM. Mon. Weather Rev. 135: 2700-2715.
70. Vitart F, Buizza R, Balmaseda MA, Balsamo G, Bidlot J-R, Bonet A, Fuentes M, Hofstadler A, Molteni F, Palmer TN. 2008. The new VarEPS-monthly forecasting system: A first step towards seamless prediction. Q. J. R. Meteorol. Soc. 134: 1789-1799.
71. Vitart F, Balsamo G, Buizza R, Ferranti L, Keeley S, Magnusson L, Molteni F, Weisheimer A. 2014. Sub-Seasonal Predictions, ECMWF Research Department Technical Memorandum 734. ECMWF: Reading, UK.
72. Weigel A, Baggenstos D, Liniger MA, Vitart F, Appenzeller C. 2008. Probabilistic verification of monthly temperature forecasts. Mon. Weather Rev. 136: 5162-5182.
73. Zsoter E. 2006. Recent developments in extreme weather forecasting. ECMWF Newsl. 107: 8-17.