Climate Dynamics

, Volume 41, Issue 7–8, pp 2231–2249 | Cite as

CFSv2 prediction skill of stratospheric temperature anomalies

  • Qin Zhang
  • Chul-Su Shin
  • Huug van den Dool
  • Ming CaiEmail author
Part of the following topical collections:
  1. Topical Collection on Climate Forecast System Version 2 (CFSv2)


This study evaluates the prediction skill of stratospheric temperature anomalies by the Climate Forecast System version 2 (CFSv2) reforecasts for the 12-year period from January 1, 1999 to December 2010. The goal is to explore if the CFSv2 forecasts for the stratosphere would remain skillful beyond the inherent tropospheric predictability time scale of at most 2 weeks. The anomaly correlation between observations and forecasts for temperature field at 50 hPa (T50) in winter seasons remains above 0.3 over the polar stratosphere out to a lead time of 28 days whereas its counterpart in the troposphere at 500 hPa drops more quickly and falls below the 0.3 level after 12 days. We further show that the CFSv2 has a high prediction skill in the stratosphere both in an absolute sense and in terms of gain over persistence except in the equatorial region where the skill would mainly come from persistence of the quasi-biennial oscillation signal. We present evidence showing that the CFSv2 forecasts can capture both timing and amplitude of wave activities in the extratropical stratosphere at a lead time longer than 30 days. Based on the mass circulation theory, we conjecture that as long as the westward tilting of planetary waves in the stratosphere and their overall amplitude can be captured, the CFSv2 forecasts is still very skillful in predicting zonal mean anomalies even though it cannot predict the exact locations of planetary waves and their spatial scales. This explains why the CFSv2 has a high skill for the first EOF mode of T50, the intraseasonal variability of the annular mode while its skill degrades rapidly for higher EOF modes associated with stationary waves. This also explains why the CFSv2’s skill closely follows the seasonality and its interannual variability of the meridional mass circulation and stratosphere polar vortex. In particular, the CFSv2 is capable of predicting mid-winter polar stratosphere warming events in the Northern Hemisphere and the timing of the final polar stratosphere warming in spring in both hemispheres 3–4 weeks in advance.


Seasonal prediction CFSv2 model Stratosphere dynamics Wave-mean flow interaction 



Ming Cai and Chul-Su Shin are supported in part by research grants from the NOAA CPO/CPPA program (NA10OAR4310168) and National Science Foundation (ATM-0833001). The authors are grateful for the informative and constructive comments from Shuntai Zhou and two anonymous reviewers on the early version of this paper.


  1. Anderson JL, van den Dool HM (1994) Skill and return of skill in dynamic extended-range forecasts. Mon Weather Rev-USA 122:507–516CrossRefGoogle Scholar
  2. Baldwin MP, Dunkerton TJ (1999) Propagation of the Arctic Oscillation from the stratosphere to the troposphere. J Geophys Res 104:30937–30946CrossRefGoogle Scholar
  3. Baldwin MP, Dunkerton TJ (2001) Stratospheric harbingers of anomalous weather regimes. Science 294:581–584CrossRefGoogle Scholar
  4. Baldwin MP, Thompson DWJ, Shuckburgh EF, Norton WA, Gillett NP (2003a) Weather from the Stratosphere? Science 301:317–319CrossRefGoogle Scholar
  5. Baldwin MP, Stephenson DB, Thompson DWJ, Dunkerton TJ, Charlton AJ, O’Neill A (2003b) Stratospheric memory and extended-range weather forecasts. Science 301:636–640CrossRefGoogle Scholar
  6. Baldwin MP, Stephenson DB, Jolliffe IT (2009) Spatial weighting and iterative projection methods for EOFs. J Clim 22:234–243CrossRefGoogle Scholar
  7. Cai M (2003) Potential vorticity intrusion index and climate variability of surface temperature. Geophys Res Lett 30:1119. doi: 10.1029/2002GL015926 CrossRefGoogle Scholar
  8. Cai M, Ren R-C (2006) 40–70 day meridional propagation of global circulation anomalies. Geophys Res Lett 33:L06818. doi: 10.1029/2005GL025024 CrossRefGoogle Scholar
  9. Cai M, Ren R-C (2007) Meridional and downward propagation of atmospheric circulation anomalies. Part I: Northern Hemisphere cold season variability. J Atmos Sci 64:1880–1901CrossRefGoogle Scholar
  10. Charlton AJ, Polvani LM (2007) A new look at stratospheric sudden warmings. Part I: climatology and modeling benchmarks. J Clim 20:449–469. doi: 10.1175/JCLI3996.1 CrossRefGoogle Scholar
  11. Charney JG, Drazin PG (1961) Propagation of planetary-scale disturbances from the lower into the upper atmosphere. J Geophys Res 66:83–109CrossRefGoogle Scholar
  12. Christiansen B (2005) Downward propagation and statistical forecast of the near-surface weather. J Geophys Res 110:D14104. doi: 10.1029/2004JD005431 CrossRefGoogle Scholar
  13. Hardiman SC, Butchart N, Charlton-Perez AJ, Shaw TA, Akiyoshi H, Baumgaertner A, Bekki S, Braesicke P, Chipperfield M, Dameris M, Garcia RR, Michou M, Pawson S, Rozanov E, Shibata K (2011) Improved predictability of the troposphere using stratospheric final warmings. J Geophys Res 116:D18113. doi: 10.1029/2011JD015914
  14. Hörnqvist E, Körnich H (2012) Tropospheric predictability around stratospheric warming events examined with an idealized forecast ensemble. EGU General Assembly 2012, held 22–27 April, 2012 in Vienna, Austria, p 12093Google Scholar
  15. Johnson DR (1989) The forcing and maintenance of global monsoonal circulations: an isentropic analysis. Adv Geophys 31:43–316CrossRefGoogle Scholar
  16. Kiehl JT, Solomon S (1986) On the radiative balance of the stratosphere. J Atmos Sci 43:1525–1534CrossRefGoogle Scholar
  17. Kurda Y (2010) High initial-time sensitivity of medium-range forecasting observed for a stratospheric sudden warming. Geophys Res Lett 37:L16804. doi: 10.1029/2010GL044119 Google Scholar
  18. Lindzen RS, Holton JR (1968) A theory of the quasi-biennial oscillation. J Atmos Sci 25:1095–1107CrossRefGoogle Scholar
  19. Marshall AG, Scaife AA, Ineson S (2009) Enhanced seasonal prediction of European winter warming following volcanic eruptions. J Clim 22:6168–6180. doi: 10.1175/2009JCLI3145.1 CrossRefGoogle Scholar
  20. Maycock AC, Keeley SPE, Charlton-Perez AJ, Doblas-Reyes FJ (2011) Stratospheric circulation in seasonal forecasting models: implications for seasonal prediction. Clim Dyn 36(1–2):309–321. doi: 10.1007/s00382-009-0665-x CrossRefGoogle Scholar
  21. Newman PA, Rosenfield JE (1997) Stratospheric thermal damping times. Geophys Res Lett 24:433–436CrossRefGoogle Scholar
  22. Ren R-C, Cai M (2006) Polar vortex oscillation viewed in an isentropic potential vorticity coordinate. Adv Atmos Sci 23:884–900CrossRefGoogle Scholar
  23. Ren R-C, Cai M (2007) Meridional and vertical out-of-phase relationships of temperature anomalies associated with the NAM variability. Geophys Res Lett 34:L07704. doi: 10.1029/2006GL028729 CrossRefGoogle Scholar
  24. Ren R-C, Cai M (2008) Meridional and downward propagation of atmospheric circulation anomalies. Part II: Southern Hemisphere cold season variability. J Atmos Sci 65:2343–2359CrossRefGoogle Scholar
  25. Saha S et al (2010) The NCEP climate forecast system reanalysis. Bull Am Meteorol Soc 91:1015–1057. doi: 10.1175/2010BAMS3001.1 CrossRefGoogle Scholar
  26. Saha S, Moorthi S, Wu X, Wang J, Nadiga S, Tripp P, Behringer D, Hou Y-T, Chuang H, Iredell M, Ek M, Meng J, Yang R, van den Dool H, Zhang Q, Wang W, Chen M (2013) The NCEP climate forecast system version 2. Submitted to J ClimGoogle Scholar
  27. Thompson DWJ, Wallace JM (2001) Regional climate impacts of the Northern Hemisphere annular mode. Science 293:85–89CrossRefGoogle Scholar
  28. Thompson DWJ, Baldwin MP, Wallace JM (2002) Stratospheric connection to Northern Hemisphere wintertime weather: implications for prediction. J Clim 15:1421–1428CrossRefGoogle Scholar
  29. Townsend RD, Johnson DR (1985) A diagnostic study of the isentropic zonally averaged mass circulation during the first GARP global experiment. J Atmos Sci 42:1565–1579. doi: 10.1175/1520-0469(1985)042<1565:ADSOTI>2.0.CO;2 CrossRefGoogle Scholar
  30. Van den Dool H (2011) An iterative projection method to calculate EOFs successively without use of the covariance matrix. In: 36th NOAA annual climate diagnostics and prediction workshop fort worth, TX, 3–6 October 2011.
  31. Van den Dool H, Saha S, Johansson A (2000) Empirical orthogonal teleconnections. J Clim 13:1421–1435CrossRefGoogle Scholar
  32. Zhang Q, van den Dool H (2012) Relative merit of model improvement versus availability of retrospective forecasts: the case of Climate Forecast System MJO prediction. Weather Forecast 27:1045–1051CrossRefGoogle Scholar
  33. Zhou S, Miller AJ, Wang J, Angell JK (2002) Downward-propagating temperature anomalies in the preconditioned polar stratosphere. J Clim 15:781–792CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Qin Zhang
    • 1
  • Chul-Su Shin
    • 2
    • 3
  • Huug van den Dool
    • 1
  • Ming Cai
    • 2
    Email author
  1. 1.Climate Prediction CenterNCEP/NWS/NOAACollege ParkUSA
  2. 2.Department of Earth, Ocean, and Atmospheric ScienceFlorida State UniversityTallahasseeUSA
  3. 3.Center for Ocean-Land-Atmosphere StudiesGeorge Mason UniversityFairfaxUSA

Personalised recommendations