Evaluating the skill of NMME seasonal precipitation ensemble predictions for 17 hydroclimatic regions in continental China

International Journal of Climatology

Volumn 36, Issue 1, 2016, Pages 132-144

  Ma, Feng ^a,b   Ye, Aizhong ^a,b   Deng, Xiaoxue ^a,b   Zhou, Zheng ^a,b   Liu, Xiaojie ^c   Duan, Qingyun ^a,b   Xu, Jing ^a,b   Miao, Chiyuan ^a,b   Di, Zhenhua ^a,b   Gong, Wei ^a,b  

^a BEIJING NORMAL UNIVERSITY   (China)

^b JOINT CENTER FOR GLOBAL CHANGE STUDIES   (China)

^c INSTITUTE OF GEOGRAPHIC SCIENCES AND NATURAL RESOURCES RESEARCH   (China)

Author keywords

BMA; China; NMME; RRMSE R diagram; Seasonal precipitation predictions

Indexed keywords

BAYESIAN NETWORKS; FORECASTING; MEAN SQUARE ERROR; NASA; UNCERTAINTY ANALYSIS; WEATHER FORECASTING;

BMA; CHINA; NMME; RRMSE-R DIAGRAM; SEASONAL PRECIPITATIONS;

CLIMATE MODELS;

BAYESIAN ANALYSIS; CLIMATE MODELING; CLIMATE PREDICTION; CLIMATOLOGY; ENSEMBLE FORECASTING; PRECIPITATION ASSESSMENT;

CHINA;

EID: 84958040263     PISSN: 08998418     EISSN: 10970088     Source Type: Journal    
DOI: 10.1002/joc.4333     Document Type: Article

References (69)

1. Atger F. 1999. The skill of ensemble prediction systems. Mon. Weather Rev. 127: 1941-1953.
2. Becker E, van den Dool H, Zhang Q. 2014. Predictability and forecast skill in NMME. J. Clim. 27: 5891-5906.
3. Bei N, Zhang F. 2007. Impacts of initial condition errors on mesoscale predictability of heavy precipitation along the Mei-Yu front of China. Q. J. R. Meteorol. Soc. 133: 83-99.
4. Collins WD, Bitz CM, Blackmon ML, Bonan GB, Bretherton CS, Carton JA, Chang P, Doney SC, Hack JJ, Henderson TB, Kiehl JT, Large WG, McKenna DS, Santer BD, Smith RD. 2006. The community climate system model version 3 (CCSM3). J. Clim. 19: 2122-2143.
5. Dempster A, Laird N, Rubin D. 1977. Maximum likelihood from incomplete data via the EM algorithm. J. R. Stat. Soc. 39: 1-38.
6. DeWitt DG. 2005. Retrospective forecasts of interannual sea surface temperature anomalies from 1982 to present using a directly Coupled Atmosphere-Ocean General Circulation Model. Mon. Weather Rev. 133: 2972, doi: 10.1175/MWR3016.1.
7. 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 A 57: 234-252.
8. Duan Q, Phillips TJ. 2010. Bayesian estimation of local signal and noise in multimodel simulations of climate change. J. Geophys. Res. 115: D18, doi: 10.1029/2009JD013654.
9. Duan Q, Ajami NK, Gao X, Sorooshian S. 2007. Multi-model ensemble hydrologic prediction using Bayesian model averaging. Adv. Water Resour. 30: 1371-1386.
10. Fraley C, Rafery AE, Gneiting T. 2010. Calibrating multimodel forecast ensembles with exchangeable and missing members using Bayesian model averaging. Mon. Weather Rev. 138: 190-202.
11. Hagedorn R, Doblas-Reyes FJ, Palmer TN. 2005. The rationale behind the success of multi-model ensembles in seasonal forecasting - I. Basic concept. Tellus A 57: 219-233.
12. Hamill TM. 2001. Interpretation of rank histograms for verifying ensemble forecasts. Mon. Weather Rev. 129: 550-560.
13. He Y, Wetterhall F, Bao H, Cloke H, Li Z, Pappenberger F, Hu Y, Manful D, Huang Y. 2010. Ensemble forecasting using TIGGE for the July-September 2008 floods in the Upper Huai catchment: a case study. Atmos. Sci. Lett. 11: 132-138.
14. Hersbach H. 2000. Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather Forecast. 15: 559-570.
15. Holdaway D, Errico R, Gelaro R, Kim JG. 2014. Inclusion of linearized moist physics in NASA's Goddard Earth Observing System Data Assimilation Tools. Mon. Weather Rev. 142: 414-433.
16. Infanti JM, Kirtman BP. 2014. Southeastern U.S. rainfall prediction in the North American Multi-Model Ensemble. J. Hydrometeor. 15: 529-550.
17. Kang IS, Lee JY, Park CK. 2003. Potential predictability of summer mean precipitation in a dynamical seasonal prediction system with systematic error correction. J. Clim. 17: 834-844.
18. Katz R, Ehrendorfer M. 2006. Bayesian approach to decision making using ensemble weather forecasts. Weather Forecast. 21: 220-231.
19. Kirtman BP, Min D. 2009. Multimodel ensemble ENSO prediction with CCSM and CFS. Mon. Weather Rev. 137: 2908-2930.
20. Kirtman B, Power SB, Adedoyin JA, Boer GJ, Bojariu R, Camilloni I, Doblas-Reyes FJ, Fiore AM, Kimoto M, Meehl GA, Prather M, Sarr A, Schär C, Sutton R, van Oldenborgh GJ, Vecchi G, Wang HJ. 2013. Climate change 2013: the physical science basis. In Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds). Cambridge University Press: Cambridge, UK and New York, NY, 953-1028.
21. Kirtman BP, Min D, Infanti JM, Kinter JL, Paolino DA, Zhang Q, van den Dool H, Saha S, Mendez MP, Becker E, Peng P, Tripp P, Huang J, DeWitt DG, Tippett MK, Barnston AG, Li S, Rosati A, Schubert SD, Rienecker M, Suarez M, Li ZE, Marshak J, Lim YK, Tribbia J, Pegion K, Merryfield WJ, Denis B, Wood EF. 2014. The North American multimodel ensemble: phase-1 seasonal-to-interannual prediction; phase-2 toward developing intra-seasonal prediction. Bull. Am. Meteorol. Soc. 95: 585-601.
22. Korecha D, Barnston AG. 2007. Predictability of June-September rainfall in Ethiopia. Mon. Weather Rev. 135: 628-650.
23. Lang Y, Ye A, Gong W, Miao C, Di Z, Xu J, Liu Y, Luo L, Duan Q. 2014. Evaluating skill of seasonal precipitation and temperature predictions of NCEP CFSv2 forecasts over 17 hydroclimatic regions in China. J. Hydrometeor. 15: 1546-1559.
24. Lavers D, Luo L, Wood EF. 2009. A multiple model assessment of seasonal climate forecast skill for applications. Geophys. Res. Lett. 36: L23711, doi: 10.1029/2009GL041365.
25. Lewis JM. 2005. Roots of ensemble forecasting. Mon. Weather Rev. 133: 1865-1885.
26. Liu Y, Ma K, Lin Z. 2000. Potential predictability of monthly precipitation over China. J. Meteor. Res. 14: 316-329.
27. Liu Y, Duan Q, Zhao L, Ye A, Tao Y, Miao C, Mu X, Schaake JC. 2013. Evaluating the predictive skill of post-processed NCEP GFS ensemble precipitation forecasts in China's Huai river basin. Hydrol. Processes 27: 57-74.
28. Lorenzo MN, Taboada JJ, Iglesias I, Gómez-Gesteira M. 2011. Predictability of the spring rainfall in Northwestern Iberian Peninsula from sea surfaces temperature of ENSO areas. Clim. Change 107: 329-341.
29. Luo L, Wood EF. 2008. Use of Bayesian merging techniques in a multi model seasonal hydrologic ensemble prediction system for the eastern United States. J. Hydrometeor. 9: 866-884.
30. Madden RA, Shea DJ. 1978. Estimates of the natural variability of time-averaged temperatures over the United States. Mon. Weather Rev. 106: 1695-1703.
31. McLachlan G, Krishnan T. 1997. The EM Algorithm and Extensions. New York, NY: John Wiley.
32. Merryfield WJ, Lee WS, Boer GJ, Kharin VV, Scinocca JF, Flato GM, Ajayamohan RS, Fyfe JC, Tang Y, Polavarapu S. 2013. The Canadian seasonal to interannual prediction system. Part I: models and initialization. Mon. Weather Rev. 141: 2910-2945.
33. Miao C, Duan Q, Sun Q, Li J. 2013. Evaluation and application of Bayesian multi-model estimation in temperature simulations. Prog. Phys. Geogr. 37: 727-744.
34. Misra V, Li H. 2014. The seasonal climate predictability of the Atlantic Warm Pool and its teleconnections. Geophys. Res. Lett. 41: 661-666.
35. Nicholson SK. 2014. The predictability of rainfall over the Greater Horn of Africa. Part I. Prediction of seasonal rainfall. J. Hdrometeor. 15: 1011-1027.
36. Palmer TN, Doblas-Reyes FJ, Hagedorn R, Alessandri A, Gualdi S, Andersen U, Feddersen H, Cantelaube P, Terres JM, Davey M, Graham R, Délécluse P, Lazar A, Déqué M, Guérémy JF, Díez E, Orfila B, Hoshen M, Morse AP, Keenlyside N, Latif M, Maisonnave E, Rogel P, Marletto V, Thomson MC. 2004. Development of a European multimodel ensemble system for seasonal-to-interannual prediction (Demeter). Bull. Am. Meteorol. Soc. 85: 853-872.
37. Palmer TN, Doblas-Reyes FJ, Weisheimer A, Rodwell MJ. 2008. Toward seamless prediction: calibration of climate change projections using seasonal forecast. Bull. Am. Meteorol. Soc. 89: 459-470.
38. Pappenberger F, Thielen J, Medico MD. 2011. The impact of weather forecast improvements on large scale hydrology: analysing a decade of forecasts of the European flood alert system. Hydrol. Processes 25: 1091-1113.
39. Park YY, Buizza R, Leutbecher M. 2008. Tigge: preliminary results on comparing and combining ensembles. Q. J. R. Meteorol. Soc. 134: 2029-2050.
40. Peel MC, Finlayson BL, McMahon TA. 2007. Updated world map of the Köppen-Geiger climate classification. Hydrol. Earth Syst. Sci. Discuss. 11: 1633-1644.
41. Peng P, Kumar A, van den Dool H, Barnston AG. 2002. An analysis of multimodel ensemble predictions for seasonal climate anomalies. J. Geophys. Res. 107: 18-1-18-2, doi: 10.1029/2002JD002712.
42. Phillips TJ, Gleckler PJ. 2006. Evaluation of continental precipitation in 20th century climate simulations: the utility of multimodel statistics. Water Resour. Res. 42: W03202, doi: 10.1029/2005WR004313.
43. Saha S, Nadiga S, Thiaw C, Wang J, Wang W, Zhang Q, Van den Dool HM, Pan HL, Moorthi S, Behringer D, Stokes D, Peña M, Lord S, White G, Ebisuzaki W, Peng P, Xie P. 2006. The NCEP climate forecast system. J. Clim. 19: 3483-3517.
44. Saha S, Moorthi S, Wu X, Wang J, Nadiga S, Tripp P, Behringer D, Hou Y-T, H-Y C, Iredell M, Ek M, Meng J, Yang R, Mendez MP, van den Dool H, Zhang Q, Wang W, Chen M, Becker E. 2014. The NCEP climate forecast system version 2. J. Clim. 27: 2185-2208.
45. Schaake J, Demargne J, Hartman R, Mullusky M, Welles E, Wu L, Herr H, Fan X, Seo DJ. 2007. Precipitation and temperature ensemble forecasts from single-value forecasts. Hydrol. Earth Syst. Sci. Discuss. 4: 655-717.
46. Shao Y, Zhang H. 1998. Climate characteristics in the source regions of the Yangtze River and Yellow River. J. Qinghai Environ. 2: 68-72 (in Chinese).
47. Sloughter JML, Raftery AE, Gneiting T, Fraley C. 2007. Probabilistic quantitative precipitation forecasting using Bayesian model averaging. Mon. Weather Rev. 135: 3209-3220.
48. Sloughter JM, Gneiting T, Raftery AE. 2013. Probabilistic wind vector forecasting using ensembles and Bayesian model averaging. Mon. Weather Rev. 141: 2107-2119.
49. Sun Q, Miao C, Duan Q, Kong D, Ye A, Di Z, Gong W. 2014. Would the 'real' observed dataset stand up? A critical examination of eight observed gridded climate datasets for China. Environ. Res. Lett. 9: 015001, doi: 10.1088/1748-9326/9/1/015001.
50. Taylor KE. 2001. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 106: 7183-7192, doi: 10.1029/2000JD900719.
51. Tebaldi C, Knutti R. 2007. The use of the multi-model ensemble in probabilistic climate projections. Philos. Trans. R. Soc. A 365: 2053-2075.
52. Tian X, Xie Z, Wang A, Yang X. 2011. A new method for solving the Bayesian model average. Sci China Press 41: 1679-1687 (in Chinese).
53. Unganai LS, Mason SJ. 2002. Long-range predictability of Zimbabwe summer rainfall. Int. J. Climatol. 22: 1091-1103.
54. Verbist K, Robertson AW, Cornelis WM, Gabriels D. 2010. Seasonal predictability of daily rainfall characteristics in central Northern Chile for dry-land management. J. Appl. Meteorol. Climatol. 49: 1938-1955.
55. Wang B, Lee JY, Kang IS, Shukla SJ, Kug JS, Kumar A, Schemm J, Luo JJ, Yamagata T, Park CK. 2007. How accurately do coupled climate models predict the leading modes of Asian-Australian monsoon interannual variability? Clim. Dyn. 30: 605-619.
56. Weisheimer A, Doblas-Reyes FJ, Palmer TN, Alessandri A, Arribas A, Déqué M, Keenlyside N, Mac Vean M, Navarra A, Rogel P. 2009. ENSEMBLES: a new multi-model ensemble for seasonal-to-annual predictions-skill and progress beyond DEMETER in forecasting tropical Pacific SSTs. Geophys. Res. Lett. 36: L21711, doi: 10.1029/2009GL040896.
57. Wilks DS. 1995. Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press: San Diego, CA, 467 pp.
58. Xie P, Chen M, Yang S, Yatagai A, Hayasaka T, Fukushima Y, Liu C. 2007. A gauge-based analysis of daily precipitation over East Asia. J. Hydrometeor. 8: 607-626.
59. Xu G, Zhao S, Wang Y, Yang Y. 2007. Experiment of ensemble forecast of heavy rainfall in the Huaihe River during rainy season of 2003 (in Chinese). Climatic Environ. Res. 12: 481-488.
60. Yang S, Li C, Lu R. 2014. Predictability of winter rainfall in South China as demonstrated by the coupled models of ensembles. Adv. Atmos. Sci. 31: 779-786.
61. Ying K, Zheng X, Quan X, Frederiksen CS. 2013. Predictable signals of seasonal precipitation in the Yangtze-Huaihe River Valley. Int. J. Climatol. 33: 3002-3015.
62. Yuan X, Wood EF. 2013. Multimodel seasonal forecasting of global drought onset. Geophys. Res. Lett. 40: 4900-4905.
63. Yuan X, Wood EF, Luo L, Pan M. 2011. A first look at Climate Forecast System version 2 (CFSv2) for hydrological seasonal prediction. Geophys. Res. Lett. 38: L13402, doi: 10.1029/2011GL047792.
64. Zhang S, Harrison MJ, Rosati A, Wittenberg A. 2007. System design and evaluation of coupled ensemble data assimilation for global oceanic climate studies. Mon. Weather Rev. 135: 3541-3564.
65. Zhang Q, Dool H, Saha S, Mendez M, Becker E, Peng P, Huang J. 2011. Preliminary evaluation of multi-model ensemble system for monthly and seasonal prediction. In the 36th NOAA Annual Climate Diagnostics and Prediction Workshop. NOAA: Silver Spring, MD, 124-131.
66. Zhao X, Wu H, He L. 2008. Estimate of climatic noise and potential predictability of seasonal precipitation in China. J. Nanjing Inst. Meteor. 31: 819-827.
67. Zhao L, Liang L, Cheng C, Zhang Y, Liu Y. 2011. Bias correction for ensemble predictions of precipitation based on Bayesian model averaging. In 28th Meteorological Conference on S3 Weather Prediction, Meteorological Society China, Xiamen, 14 pp.
68. Zheng X, Nakamura H, Renwick JA. 2000. Potential predictability of seasonal means based on monthly time series of meteorological variables. J. Clim. 13: 2591-2604.
69. Zheng X, Sugi M, Frederiksen CS. 2004. Interannual variability and predictability in an ensemble of climate simulations with the MRI-JMA AGCM. J. Meteor. Soc. Jpn. Ser. II 82: 1-18.