Seamless precipitation prediction skill comparison between two global models

Quarterly Journal of the Royal Meteorological Society

Volumn 143, Issue 702, 2017, Pages 374-383

  Wheeler, Matthew C ^a   Zhu, Hongyan ^a   Sobel, Adam H ^b   Hudson, Debra ^a   Vitart, Frédéric ^c  

^a BUREAU OF METEOROLOGY   (Australia)

^b International Research Institute for Climate and Society   (United States)

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

Author keywords

ECMWF; GPCP precipitation; POAMA; potential skill; prediction skill; seamless prediction; seamless verification

Indexed keywords

FORECASTING; TIME MEASUREMENT; TROPICS;

BUREAU OF METEOROLOGIES; ECMWF; EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS; OCEAN-ATMOSPHERE MODELS; POAMA; POTENTIAL SKILL; PRECIPITATION PREDICTIONS; SOUTHERN HEMISPHERE;

WEATHER FORECASTING;

ACCURACY ASSESSMENT; CLIMATE MODELING; ENSEMBLE FORECASTING; PRECIPITATION (CLIMATOLOGY); PRECIPITATION INTENSITY; SOUTHERN HEMISPHERE; WEATHER FORECASTING;

PACIFIC OCEAN; PACIFIC OCEAN (EQUATORIAL);

EID: 85000894017     PISSN: 00359009     EISSN: 1477870X     Source Type: Journal    
DOI: 10.1002/qj.2928     Document Type: Article

References (38)

1. Balmaseda M, Vidard A, Anderson D. 2007. The ECMWF System-3 Ocean Analysis System. ECMWF Technical Memorandum 508. ECMWF: Reading, UK.
2. Barnston AG, Tippett MK, L'Heureux ML, Li S, DeWitt DG. 2012. Skill of real-time seasonal ENSO model predictions during 2002–11: Is our capability increasing? Bull. Am. Meteorol. Soc. 93: 631–651.
3. Bechtold P, Koehler M, Jung T, Doblas-Reyes P, Leutbecher M, Rodwell M, Vitart F. 2008. Advances in simulating atmospheric variability with the ECMWF model: From synoptic to decadal time-scales. Q. J. R. Meteorol. Soc. 134: 1337–1351.
4. Becker EJ, van den Dool HM, Pena M. 2013. Short-term climate extremes: Prediction skill and predictability. J. Clim. 26: 512–531.
5. Blanchard-Wrigglesworth E, Armour KC, Bitz CM, DeWeaver E. 2011. Persistence and inherent predictability of Arctic sea ice in a GCM ensemble and observations. J. Clim. 24: 231–250.
6. Boer GJ, Kharin VV, Merryfield WJ. 2013. Decadal predictability and forecast skill. Clim. Dyn. 41: 1817–1833.
7. Bolvin DT, Adler RF, Huffman GJ, Nelkin EJ, Poutiainen JP. 2009. Comparison of GPCP monthly and daily precipitation estimates with high-latitude gauge observations. J. Appl. Meteorol. Climatol. 48: 1843–1857.
8. Buizza R. 1997. Potential forecast skill of ensemble prediction and spread and skill distributions of the ECMWF ensemble prediction system. Mon. Weather Rev. 125: 99–119.
9. Buizza R, Palmer TN. 1995. The singular-vector structure of the atmospheric global circulation. J. Atmos. Sci. 52: 1434–1456.
10. Chen M, Wang W, Kumar A. 2010. Prediction of monthly-mean temperature: The roles of atmospheric and land initial conditions and sea surface temperature. J. Clim. 23: 717–725.
11. 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.
12. Ebert EE, Damrath U, Ergen W, Baldwin ME. 2003. The WGNE assessment of short-term quantitative precipitation forecasts. Bull. Am. Meteorol. Soc. 84: 481–492.
13. Forbes RM, Tompkins AM, Untch A. 2012. ‘A new prognostic bulk microphysics scheme for the ECMWF forecast model’. In EGU General Assembly Conference Abstracts, 22-27 April, 2012. Vienna, Austria. Vol. 14, p. 12155.
14. Holland MM, Blanchard-Wrigglesworth E, Kay J, Vavrus S. 2013. Initial-value predictability of Antarctic sea ice in the Community Climate System Model 3. Geophys. Res. Lett. 40: 2121–2124, doi: 10.1002/grl.50410.
15. Hope P, Lim E-P, Wang G, Hendon HH, Arblaster JM. 2015. Contributors to the record high temperatures across Australia in late spring. In Explaining Extremes of 2014 from a Climate Perspective, Herring SC, Hoerling MP, Peterson TC, Stott PA. (eds.) Bull. Amer. Meteor. Soc. 96(12): S149–S153. American Meteorological Society: Boston, MA.
16. Hudson D, Alves O, Hendon HH, Wang G. 2011. The impact of atmospheric initialisation on seasonal prediction of tropical Pacific SST. Clim. Dyn. 36: 1155–1171.
17. Hudson D, Marshall AG, Yin Y, Alves O, Hendon HH. 2013. Improving intraseasonal prediction with a new ensemble generation strategy. Mon. Weather Rev. 141: 4429–4449.
18. Huffman GJ, Adler RF, Morrissey M, Bolvin DT, Curtis S, Joyce R, McGavock B, Susskind J. 2001. Global precipitation at one-degree daily resolution from multi-satellite observations. J. Hydrometeorol. 2: 36–50.
19. Kirtman B, Anderson D, Brunet G, Kang IS, Scaife AA, Smith DM. 2013. Prediction from weeks to decades. In Climate Science for Serving Society, Asrar GR, Hurrell JW. (eds.): 205–235. Springer: Dordrecht, Netherlands, doi: 10.1007/978-94-007-6692-1_8.
20. Kumar A, Chen M, Wang W. 2011. An analysis of prediction skill of monthly mean climate variability. Clim. Dyn. 37: 1119–1131.
21. Kumar A, Peng P, Chen M. 2014. Is there a relationship between potential and actual skill? Mon. Weather Rev. 142: 2220–2227.
22. Langford S, Hendon HH. 2013. Improving reliability of coupled model forecasts of Australian seasonal rainfall. Mon. Weather Rev. 141: 728–741.
23. Li S, Robertson AW. 2015. Evaluation of submonthly precipitation forecast skill from global ensemble prediction systems. Mon. Weather Rev. 143: 2871–2889.
24. Madden RA, Julian PR. 1972. Description of global-scale circulation cells in the Tropics with a 40–50-day period. J. Atmos. Sci. 29: 1109–1123.
25. Neelin JD, Battisti DS, Hirst AC, Jin F-F, Wakata Y, Yamagata T, Zebiak SE. 1998. ENSO theory. J. Geophys. Res. 103: 14261–14290, doi: 10.1029/97JC03424.
26. Palmer TN. 2001. A nonlinear dynamical perspective on model error: A proposal for nonlocal stochastic dynamic parameterization in weather and climate prediction models. Q. J. R. Meteorol. Soc. 127: 279–304.
27. Rodwell MJ, Doblas-Reyes FJ. 2006. Medium-range, monthly, and seasonal prediction for Europe and the use of forecast information. J. Clim. 19: 6025–6046.
28. Stockdale TN. 1997. Coupled ocean–atmosphere forecasts in the presence of climate drift. Mon. Weather Rev. 125: 809–818.
29. Uppala SM, Kållberg PW, Simmons AJ, Andrae U, Da Costa Bechtold V, Fiorino M, Gibson JK, Haseler J, Hernandez A, Kelly GA, Li X, Onogi K, Saarinen S, Sokka N, Allan RP, Andersson E, Arpe K, Balmaseda MA, Beljaars ACM, Van De Berg L, Bidlot J, Bormann N, Caires S, Chevallier F, Dethof A, Dragosavac M, Fisher M, Fuentes M, Hagemann S, Hólm E, Hoskins BJ, Isaksen L, Janssen PAEM, Jenne R, McNally AP, Mahfouf J-F, Morcrette J-J, Rayner NA, Saunders RW, Simon P, Sterl A, Trenberth KE, Untch A, Vasiljevic D, Viterbo P, Woollen J. 2005. The ERA-40 re-analysis. Q. J. R. Meteorol. Soc. 131: 2961–3012.
30. Vialard J, Vitart F, Balmaseda MA, Stockdale T, Anderson DLT. 2005. An ensemble generation method for seasonal forecasting with an ocean–atmosphere coupled model. Mon. Weather Rev. 133: 441–453.
31. Vitart F. 2004. Monthly forecasting at ECMWF. Mon. Weather Rev. 132: 2761–2779.
32. Vitart F. 2014. Evolution of ECMWF sub-seasonal forecast skill scores. Q. J. R. Meteorol. Soc. 140: 1889–1899.
33. 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.
34. Vitart F, Leroy A, Wheeler MC. 2010. A comparison of dynamical and statistical predictions of weekly tropical cyclone activity in the Southern Hemisphere. Mon. Weather Rev. 138: 3671–3682.
35. Webster PJ, Toma VE, Kim H-M. 2011. Were the 2010 Pakistan floods predictable? Geophys. Res. Lett. 38: L04806, doi: 10.1029/2010GL046346.
36. Wheeler MC, Hendon HH. 2004. An all-season real-time multivariate MJO index: Development of an index for monitoring and prediction. Mon. Weather Rev. 132: 1917–1932.
37. Yin Y, Alves O, Oke PR. 2011. An ensemble ocean data assimilation system for seasonal prediction. Mon. Weather Rev. 139: 786–808.
38. Zhu H, Wheeler MC, Sobel AH, Hudson D. 2014. Seamless precipitation prediction skill in the Tropics and extratropics from a global model. Mon. Weather Rev. 142: 1556–1569.