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5. Concluding remarks In this study, the biases of three reanalysis datasets (e.g., NCEP_R1, _R2, and ERA_Interim) in describing MJO were revealed and the impacts of these biases as initial conditions on MJO prediction skills were assessed. A prototype signal-recovery method is proposed to improve the representation of the MJO in initial conditions. Although all three reanalyses underestimate the intensity of the equatorial eastwardpropagating MJO, the overall quality of the ERA_Interim is much better than the NCEP_R1 and R2. When the NCEP_R1 and_R2 are directly used to initialize the forecasts, MJO prediction skill is only about one week (Fig.3). The MJO prediction skill initialized with the ERA_Inerim, however, reaches two weeks. Using the signal-recovered reanalyses as initial conditions, MJO prediction skills are consistently better than that directly initialized with the original reanalyses (Fig. 3). It is well-known that the MJO modulates global weather and climate systems from tropical cyclones, midlatitude extreme weather, wet and dry spells of monsoon systems to ENSO evolutions. Knowing the phase of the MJO 2-4 weeks ahead offers a reliable source for probabilistic assessments on the occurrences of tropical extreme events (e.g., Gottschalk et al. 2010). This information has great socio-economic value particularly for those weather sensitive sectors, e.g., water management, agriculture, disaster prevention, and so on (Brunet et al. 2010). This study is a step towards this direction. In order to ensure steady progress in the advancement of MJO prediction, synergetic efforts between weather and climate communities are needed at least in three fronts: (i) To acquire better initial conditions, through deploying new observations (e.g., DYNAMO) and developing new data assimilation techniques, for the atmosphere-ocean-land coupled forecast systems; (ii) To improve the representations of multi-scale convective systems and their interactions with large-scale circulations in atmospheric models, which are key processes of the observed MJO; (iii) To advance the coupling processes among atmosphere, ocean, and land that are crucial to the realistic simulations of the MJO. Recently, a great effort has been made at NOAA/NCEP to produce a new generation reanalysis (CFSR) (Saha et al. 2010). The CFSR developed at NCEP has very high horizontal and vertical resolution (T382L64) of the atmosphere and includes atmosphere-ocean coupling, which reproduces the observed lead-lag phase relationships between precipitation and sea surface temperature (Saha et al. 2010). Preliminary results show that the CFSR has better quality than the NCEP_R1 and _R2 in describing the MJO. Future study is needed to comprehensively evaluate the MJO in the CFSR and to assess the MJO prediction skill when the CFSR is used as initial condition. References Brunet, G., M. Hoskins, M. Moncrieff, R. Dole, G. N. Kiladis, B. Kirtman, A. Lorenc, B. Mills, R. Morss, S. Polavarapu, and D. Rogers, 2010: Collaboration of the weather and climate communities to advance subseasonal to seasonal prediction. Bull. Amer. Meteor. Soc., 91, 1397-1406. Fu, X., and B. Wang, 2004: The boreal-summer intraseasonal oscillations simulated in a hybrid coupled atmosphere-ocean model. Mon. Wea. Rev., 132, 2628-2649. Fu, X., B. Wang, D. E. Waliser, and L. Tao, 2007: Impact of atmosphere-ocean coupling on the predictability of monsoon intraseasonal oscillations. J. Atmos. Sci., 64, 157-174. Fu, X., B. Wang, Q. Bao, P. Liu, and B. Yang, 2008: Experimental dynamical forecast of an MJO event observed during TOGA-COARE period. Atmos. Oceanic Sci. Lett., 1, 24-28. Fu, X., B. Wang, Q. Bao, P. Liu, and J.-Y. Lee, 2009: Impacts of initial conditions on monsoon intraseasonal forecasting. Geophys. Res. Lett., 36, L08801, doi:10.1029/ 2009GL 037166. Gottschalck, J., and Co-authors, 2010: A framework for assessing operational model MJO forecasts: A project of the CLIVAR Madden-Julian Oscillation working group. Bull. Amer. Meteor. Soc., 91, 1247-1258. Higgins, R. W., J. K. E. Schemm, W. Shi, and A. Leetmaa, 2000: Extreme precipitation events in the western United States related to tropical forcing. J. Climate, 13, 793-820. Jones, C., and J.-K. E. Schemm, 2000: The influence of intraseasonal variations on medium-range weather forecasts over South America. Mon. Wea. Rev., 128, 486-494.