Climate Dynamics

, Volume 37, Issue 5–6, pp 1119–1131 | Cite as

An analysis of prediction skill of monthly mean climate variability

Article

Abstract

In this paper, lead-time and spatial dependence in skill for prediction of monthly mean climate variability is analyzed. The analysis is based on a set of extensive hindcasts from the Climate Forecast System at the National Centers for Environmental Prediction. The skill characteristics of initialized predictions is also compared with the AMIP simulations forced with the observed sea surface temperature (SST) to quantify the role of initial versus boundary conditions in the prediction of monthly means. The analysis is for prediction of monthly mean SST, precipitation, and 200-hPa height. The results show a rapid decay in skill with lead time for the atmospheric variables in the extratropical latitudes. Further, after a lead-time of approximately 30–40 days, the skill of monthly mean prediction is essentially a boundary forced problem, with SST anomalies in the tropical central/eastern Pacific playing a dominant role. Because of the larger contribution from the atmospheric internal variability to monthly time-averages (compared to seasonal averages), skill for monthly mean prediction associated with boundary forcing is also lower. The analysis indicates that the prospects of skillful prediction of monthly means may remain a challenging problem, and may be limited by inherent limits in predictability.

Keywords

Climate variability Monthly means Prediction skill Boundary forcing Atmospheric initial condition 

References

  1. Alexander MA, Bladé I, Newman M, Lanzante JR, Lau NC, Scott JD (2002) The atmospheric bridge: the influence of ENSO teleconnections on air–sea interaction over the global oceans. J Clim 15:2205–2231CrossRefGoogle Scholar
  2. Barsugli JJ, Battisti DS (1998) The basic effects of atmosphere–ocean thermal coupling on midlatitude variability. J Atmos Sci 55:477–493CrossRefGoogle Scholar
  3. Bladé I (1997) The influence of midlatitude ocean–atmosphere coupling on the low-frequency variability of a GCM. Part I: no tropical SST forcing. J Clim 10:2087–2106CrossRefGoogle Scholar
  4. Chen M, Wang W, Kumar A (2010) Prediction of monthly-mean temperature: the role of atmospheric and land initial conditions and sea surface temperature. J Clim 23:717–725CrossRefGoogle Scholar
  5. de Boyer Montégut C, Madec CG, Fischer AS, Lazar A, Iudicone D (2004) Mixed layer depth over the global ocean: an examination of profile data and a profile-based climatology. J Geophys Res 109:C12003. doi:10.1029/2004JC002378 CrossRefGoogle Scholar
  6. DelSole T, Shukla J (2006) Specification of wintertime North American surface temperature. J Clim 19:2691–2716CrossRefGoogle Scholar
  7. Deser C, Alexander MA, Xie SP, Phillips AS (2010) Sea surface temperature variability: patterns and mechanisms. Annu Rev Mar Sci 2:115–143. doi:10.1146/annurev-marine-120408-151453 CrossRefGoogle Scholar
  8. Folland CK, Colman AW, Rowell DP, Davey MK (2001) Predictability of Northeast Brazil rainfall and real-time forecast skill, 1987–98. J Clim 14:1937–1958CrossRefGoogle Scholar
  9. Horel JD, Wallace JM (1981) Planetary-scale atmospheric phenomena associated with the Southern Oscillation. Mon Weather Rev 109:813–829CrossRefGoogle Scholar
  10. Janowiak JE, Xie P (1999) CAMS-OPI: a global satellite-rain gauge merged product for real-time precipitation monitoring applications. J Clim 12:3335–3342CrossRefGoogle Scholar
  11. Jin EK et al (2008) Current status of ENSO prediction skill in coupled ocean-atmosphere models. Clim Dyn 14:647–664CrossRefGoogle Scholar
  12. Kanamitsu M, Ebisuzaki W, Woollen WJ, Yang SK, Hnilo JJ, Fiorino M, Potter GL (2002) NCEP-DEO AMIP-II reanalysis (R-2). Bull Am Meteorol Soc 83:1631–1643CrossRefGoogle Scholar
  13. Krishna Kumar K, Hoerling MP, Rajagopalan B (2005) Advancing dynamical prediction of Indian monsoon rainfall. Geophys Res Lett 32:L08704. doi:10.1029/2004GL021979 CrossRefGoogle Scholar
  14. Kumar A, Hoerling MP (1998) Annual cycle of Pacific–North American seasonal predictability associated with different phases of ENSO. J Clim 11:3295–3308CrossRefGoogle Scholar
  15. Kumar A, Hoerling MP (2000) Analysis of a conceptual model of seasonal climate variability and implications for seasonal predictions. Bull Am Meteor Soc 81:255–264CrossRefGoogle Scholar
  16. Kumar A, Wang W, Hoerling MP, Leetmaa A, Ji M (2001) The sustained North American warming of 1997 and 1998. J Clim 14:345–353CrossRefGoogle Scholar
  17. Kumar A, Schubert SD, Suarez MS (2003) Variability and predictability of 200-mb seasonal mean height during summer and winter. J Geophys Res 108(D5):4169. doi:10.1029/2002JD002728 CrossRefGoogle Scholar
  18. Kumar A, Jha B, Zhang Q, Bounoua L (2007) A new methodology for estimating the unpredictable component of seasonal atmospheric variability. J Clim 20:3888–3901CrossRefGoogle Scholar
  19. Lau NC, Leetmaa A, Nath MJ (2008) Interactions between the responses of north America Climate to El Nino-La Nina and to secular warming trend in the Indian-Western Pacific oceans. J Clim 21:474–494CrossRefGoogle Scholar
  20. Mathieu PP, Sutton RT, Dong B, Collins M (2004) Predictability of winter climate over the North Atlantic European region during. J Clim 17:1953–1974CrossRefGoogle Scholar
  21. Pacanowski RC, Griffies SM (1998) MOM 3.0 manual. NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, 668 ppGoogle Scholar
  22. Peng P, Kumar A (2005) A large ensemble analysis of the influence of tropical SSTs on seasonal atmospheric variability. J Clim 18:1068–1085CrossRefGoogle Scholar
  23. Peng P, Kumar A, Barnston AG, Goddard L (2000) Simulation skills of the SST-forced global climate variability of the NCEP–MRF9 and the Scripps–MPI ECHAM3 models. J Clim 20:3657–3679CrossRefGoogle Scholar
  24. Peng P, Kumar A, Wang W (2009) An analysis of seasonal predictability in coupled model forecasts. Clim Dyn. doi:10.1007/s00382-009-0711-8
  25. Phelps M, Kumar A, O’Brien JJ (2004) Potential predictability in the NCEP CPC dynamical seasonal forecast system. J Clim 17:3773–3785CrossRefGoogle Scholar
  26. Quan X, Hoerling MP, Whitaker J, Xu T (2006) Diagnosing sources of U.S. seasonal forecast skill. J Clim 19:3279–3293CrossRefGoogle Scholar
  27. Reichler T, Roads JO (2005a) Long-range predictability in tropics. Part I: monthly averages. J Clim 18:619–633CrossRefGoogle Scholar
  28. Reichler T, Roads JO (2005b) Long-range predictability in tropics. Part II: 30–60-day variability. J Clim 18:634–650CrossRefGoogle Scholar
  29. Reynolds WR, Rayner NA, Smoth TM, Stokes DC, Wang W (2002) An improved in situ and satellite SST analysis for climate. J Clim 15:1609–1625CrossRefGoogle Scholar
  30. Rodwell MJ, Boblas-Reyes FJ (2006) Medium-range, monthly, and seasonal prediction for Europe and the use of forecast information. J Clim 19:6025–6046CrossRefGoogle Scholar
  31. Rowell DP (1998) Assessing potential seasonal predictability with an ensemble of multi-decadal GCM simulations. J Clim 11:109–120CrossRefGoogle Scholar
  32. Saha S, Nadiga S, Thiaw C, Wang J, Wang W, Zhang Q, van den Dool HM, Pan HL, Moorthi S, Behringer D, Stokes D, Pena M, Lord S, White G, Ebisuzaki W, Peng P, Xie P (2006) The NCEP climate forecast system. J Clim 19:3483–3517CrossRefGoogle Scholar
  33. Schubert SD, Suarez MJ, Pegion PJ, Koster RD, Bacmeister JT (2008) Potential predictability of long-term drought and pluvial conditions in the U.S. Great Plains. J Clim 21:802–816CrossRefGoogle Scholar
  34. Trenberth KE, Branstator GW, Karoly D, Kumar A, Lau NC, Ropelewski C (1998) Progress during TOGA in understanding and modeling global teleconnections associated with tropical sea surface temperatures. J Geophys Res 103:14 291–14 324CrossRefGoogle Scholar
  35. Vitart F (2004) Monthly forecasting at ECMWF. Mon Weather Rev 132:2761–2779CrossRefGoogle Scholar
  36. Walsh JE, Ross B (1988) Sensitivity of 30-day dynamical forecasts to continental snow cover. J Clim 1:739–754CrossRefGoogle Scholar
  37. Wang B, Ding Q, Fu X, Kang IS, Jin K, Shukla J, Doblas-Reyes F (2005a) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys Res Lett 32:L15711. doi:10.1029/2005GL022734 CrossRefGoogle Scholar
  38. Wang W, Saha S, Pan HL, Nadiga S, White G (2005b) Simulation of ENSO in the new NCEP coupled forecast system model (CFS). Mon Weather Rev 133:1574–1593CrossRefGoogle Scholar
  39. Wu R, Kirtman BP (2005) Roles of Indian and Pacific Ocean air–sea coupling in tropical atmospheric variability. Clim Dyn 25:155–170CrossRefGoogle Scholar

Copyright information

© US Government 2010

Authors and Affiliations

  1. 1.Climate Prediction Center, National Centers for Environmental Prediction (CPC/NCEP)Camp SpringsUSA

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