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Climate Dynamics

, Volume 50, Issue 11–12, pp 3931–3948 | Cite as

Predictability of CFSv2 in the tropical Indo-Pacific region, at daily and subseasonal time scales

  • V. Krishnamurthy
Article

Abstract

The predictability of a coupled climate model is evaluated at daily and intraseasonal time scales in the tropical Indo-Pacific region during boreal summer and winter. This study has assessed the daily retrospective forecasts of the Climate Forecast System version 2 from the National Centers of Environmental Prediction for the period 1982–2010. The growth of errors in the forecasts of daily precipitation, monsoon intraseasonal oscillation (MISO) and the Madden–Julian oscillation (MJO) is studied. The seasonal cycle of the daily climatology of precipitation is reasonably well predicted except for the underestimation during the peak of summer. The anomalies follow the typical pattern of error growth in nonlinear systems and show no difference between summer and winter. The initial errors in all the cases are found to be in the nonlinear phase of the error growth. The doubling time of small errors is estimated by applying Lorenz error formula. For summer and winter, the doubling time of the forecast errors is in the range of 4–7 and 5–14 days while the doubling time of the predictability errors is 6–8 and 8–14 days, respectively. The doubling time in MISO during the summer and MJO during the winter is in the range of 12–14 days, indicating higher predictability and providing optimism for long-range prediction. There is no significant difference in the growth of forecasts errors originating from different phases of MISO and MJO, although the prediction of the active phase seems to be slightly better.

Keywords

South Asian monsoon CFSv2 Forecasts Intraseasonal oscillation MJO 

Notes

Acknowledgements

This work is supported by National Science Foundation (Grant 1338427), National Oceanic and Atmospheric Administration (Grant NA140OAR4310160), and National Aeronautics and Space Administration (Grant NNX14AM19G) from USA.

Compliance with ethical standards

Conflict of interest

The author declares no conflict of interest.

References

  1. Achuthavarier D, Krishnamurthy V (2011a) Daily modes of South Asian summer monsoon variability in the NCEP climate forecast system. Clim Dyn 36:1941–1958CrossRefGoogle Scholar
  2. Achuthavarier D, Krishnamurthy V (2011b) Role of Indian and Pacific SST in Indian summer monsoon intraseasonal variability. J Clim 24:2915–2930CrossRefGoogle Scholar
  3. Charney JG, Shukla J (1981) Predictability of monsoons. In: Lighthill J, Pearce RP (eds) Monsoon Dynamics. Cambridge University Press, New York, pp 99–109CrossRefGoogle Scholar
  4. Fu X, Wang B, Waliser DE, Tao L (2007) Impact of atmosphere–ocean coupling on the predictability of monsoon intraseasonal oscillations. J Atmos Sci 64:157–174CrossRefGoogle Scholar
  5. Ghil M, Allen MR, Dettinger MD, Ide K, Kondrashov D, Mann ME, Robertson AW, Saunders A, Tian Y, Varadi F, Yiou P (2002) Advanced spectral methods for climatic time series. Rev Geophys 40(1):1003. doi: 10.1029/2000RG000092 CrossRefGoogle Scholar
  6. Goswami BN, Krishnamurthy V, Annamalai H (1999) A broad-scale circulation index for the interannual variability of the Indian summer monsoon. Q J Roy Meteor Soc 125:611–633CrossRefGoogle Scholar
  7. Huffman GJ, Adler RF, Bolvin DT, Gu G, Nelkin EJ, Bowman KP, Hong Y, Stocker EF, Wolff DB (2007) The TRMM multisatellite precipitation analysis (TMPA): quasi-global, multi-year, combined-sensor precipitation estimates at fine scales. J Hydrometeor 8:38–55CrossRefGoogle Scholar
  8. Hung M-P, Lin J-L, Wang W, Kim D, Shinoda T, Weaver SJ (2013) MJO and convectively coupled equatorial waves simulated by CMIP5 climate models. J Clim 26:6185–6214CrossRefGoogle Scholar
  9. Jiang X, Yang S, Li Y, Kumar A, Liu X, Zuo Z, Jha B (2013) Seasonal-to-interannual prediction of the Asian summer monsoon in the NCEP climate forecast system version 2. J Clim 26:3708–3727CrossRefGoogle Scholar
  10. Krishnamurthy V (1993) A predictability study of Lorenz’s 28-variable model as a dynamical system. J Atmos Sci 50:2215–2229CrossRefGoogle Scholar
  11. Krishnamurthy V (2016) Tropical intraseasonal oscillation in CFSv2 during boreal summer and winter. Int J Climatol. doi: 10.1002/joc.4948 Google Scholar
  12. Krishnamurthy V, Rai S (2011) Predictability of the South Asian monsoon circulation in the NCEP climate forecast system. Adv Geosci 22:65–76Google Scholar
  13. Krishnamurthy V, Shukla J (2007) Intraseasonal and seasonally persisting patterns of Indian monsoon rainfall. J Clim 20:3–20CrossRefGoogle Scholar
  14. Krishnamurthy V, Shukla J (2008) Seasonal persistence and propagation of intraseasonal patterns over the Indian monsoon region. Clim Dyn 30:353–369CrossRefGoogle Scholar
  15. Lin J-L et al (2006) Tropical intraseasonal variability in 14 IPCC AR4 climate models. Part I: convective signals. J Clim 19:2665–2690CrossRefGoogle Scholar
  16. Lorenz EN (1965) A study of the predictability of a 28-variable atmospheric model. Tellus 17:321–333CrossRefGoogle Scholar
  17. Lorenz EN (1969) Atmospheric predictability as revealed by naturally occurring analogues. J Atmos Sci 26:636–646CrossRefGoogle Scholar
  18. Lorenz EN (1982) Atmospheric predictability experiments with a large numerical model. Tellus 34:505–513CrossRefGoogle Scholar
  19. Lorenz EN (1985) The growth of errors in prediction. In: Ghil M, Benzi R (eds) Turbulence and predictability in geophysical fluid dynamics and climate dynamics. LXXXVIII Corso Soc. Itiliana di Fisica, Bologna, pp 243–265Google Scholar
  20. Madden RA, Julian PR (1971) Description of a 40–50 day oscillation in the zonal wind in the tropical Pacific. J Atmos Sci 28:702–708CrossRefGoogle Scholar
  21. Madden RA, Julian PR (1972) Description of global-scale circulation cells in the tropics with a 40–50 day period. J Atmos Sci 29:1109–1123CrossRefGoogle Scholar
  22. Moron V, Vautard R, Ghil M (1998) Trends, interdecadal and interannual oscillations in global sea-surface temperatures. Clim Dyn 14:545–569CrossRefGoogle Scholar
  23. Neena JM, Lee JY, Waliser D, Wang B, Jiang X (2014) Predictability of the Madden–Julian oscillation in the intraseasonal variability hindcast experiment (ISVHE). J Clim 27:4531–4543CrossRefGoogle Scholar
  24. Pai DS, Sridhar L, Rajeevan M, Sreejith OP, Satbhai NS, Mukhopadhyay B (2014) Development of a new high spatial resolution (0.25 × 0.25) long period (1901–2010) daily gridded rainfall data set over India and its comparison with existing data sets over the region. Mausam 65:1–18Google Scholar
  25. Pegion K, Kirtman BP (2008a) The impact of air–sea interactions on the predictability of the tropical intraseasonal oscillation. J Clim 21:5870–5886CrossRefGoogle Scholar
  26. Pegion K, Kirtman BP (2008b) The impact of air–sea interactions on the simulation of tropical intraseasonal variability. J Clim 21:6616–6635CrossRefGoogle Scholar
  27. Plaut G, Vautard R (1994) Spells of low-frequency oscillations and weather regimes in the Northern Hemisphere. J Atmos Sci 51:210–236CrossRefGoogle Scholar
  28. Pokhrel S, Saha SK, Dhakate A, Rahman H, Chaudhari HS, Salunke K, Hazra A, Sujith K, Sikka DR (2016) Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error. Clim Dyn 46:2305–2326CrossRefGoogle Scholar
  29. Press WH, Flannery BP, Teukolsky SA, Vettering WT (1989) Numerical recipes. Cambridge University Press, Cambridge, pp 498–546Google Scholar
  30. Rai S, Krishnamurthy V (2011) Error growth in climate forecast system daily retrospective forecasts of South Asian monsoon. J Geophys Res 116:D03108. doi: 10.1029/2010JD014840 CrossRefGoogle Scholar
  31. Rajeevan M, Bhate J, Kale KD, Lal B (2006) High resolution daily gridded rainfall data for the Indian region: analysis of break and active monsoon spells. Curr Sci 91:296–306Google Scholar
  32. Saha S et al (2006) The NCEP climate forecast system. J Clim 19:3483–3517CrossRefGoogle Scholar
  33. Saha S et al (2014) The NCEP climate forecast system version 2. J Clim 27:2185–2208CrossRefGoogle Scholar
  34. Simmons AJ, Hollingsworth A (2002) Some aspects of the improvement in skill of numerical weather prediction. Q J Roy Meteor Soc 128:647–677CrossRefGoogle Scholar
  35. Sperber KR, Annamalai H (2008) Coupled model simulations of boreal summer intraseasonal (30–50 day) variability, part I: systematic errors and caution on use of metrics. Clim Dyn 31:345–372CrossRefGoogle Scholar
  36. Sperber KR, Annamalai H, Kang I-S, Kitoh A, Moise A, Turner A, Wang B, Zhou T (2013) The Asian summer monsoon: an intercomparison of CMIP5 vs. CMIP3 simulations of the late 20th century. Clim Dyn 41:2711–2744CrossRefGoogle Scholar
  37. Straus DM, Paolino D (2009) Intermediate time error growth and predictability: tropics versus mid-latitudes. Tellus A 61:579–586CrossRefGoogle Scholar
  38. Wang B, Ding Q, Fu X, Kang I-S, Jin K, Shukla J, Doblas-Reyes F (2005) Fundamental challenge in simulation and prediction of summer monsoon rainfall. Geophys Res Lett 32:L15711. doi: 10.1029/2005GL022734 CrossRefGoogle Scholar
  39. Wang W, Hung M-P, Weaver SJ, Kumar A, Fu X (2014) MJO prediction in the NCEP climate forecast system version 2. Clim Dyn 42:2509–2520CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany 2017

Authors and Affiliations

  1. 1.Center for Ocean-Land-Atmosphere StudiesGeorge Mason UniversityFairfaxUSA

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