Xue, Y, Chen, M., Kumar, A., Hu, Z.-Z. and Wang, W. 2013. Prediction skill and bias of tropical Pacific sea surface temperatures in the NCEP Climate Forecast System version 2. Journal of Climate 26: 5358-5378.
The authors write that "seasonal climate predictions are now routinely made at operational centers using coupled dynamical models (e.g., Ji et al., 1998; Saha et al., 2006; Stockdale et al., 2011; Barnston et al., 2012)," while adding that "in the development of seasonal prediction systems, prediction skill of the tropical Pacific sea surface temperature (SST) anomaly [SSTA] associated with the El Niño-Southern Oscillation (ENSO) is commonly used as a bench mark for evaluating progress."
What was done
Xue et al. documented "the prediction skill of ENSO and the biases in the new coupled dynamical model, which is referred to as Climate Forecast System, version 2 (CFSv2)," and which was" implemented at the National Centers for Environmental Prediction (NCEP) in early 2011," with one of the Center's chief objectives being "to evaluate the variability, prediction skill, and predictability of ENSO in CFSv2 over two periods, 1982-1998 and 1999-2010, separately.
What was learned
The five U.S. researchers report that (1) "there was a systematic cold bias in the central-eastern equatorial Pacific during 1982-1998 that reached -2.5°C during summer/fall," that (2) "at the end of 1998, the cold bias suddenly reduced to about -1°C during summer/fall, and a warm bias of +0.5°C developed during winter/spring," that (3) "this shift of the systematic biases in hindcast SST around 1999 contributed to a spurious warming trend in forecast SSTA based on the 1982-2010 climatology (Kim et al., 2012)," such that (4) "the standard deviation (STD) of forecast SSTA agreed well with that of observations in 1982-1998, but in 1999-2010 it was about 200% too strong in the eastern Pacific and 50% too weak near the date line during winter/spring."
What it means
When model-estimated standard deviations of different portions of a region suddenly differ by something on the order of 200%, the so-called "progress" being made would appear to have a lot to be desired.
Barnston, A.G., Tippett, M.K., L'Heureux, M.L. and De Witt, D.G. 2012. Skill of real-time seasonal ENSO model predictions during 2002-11: Is our capability increasing? Bulletin of the American Meteorological Society 93: 631-651.
Ji, M., Behringer, D.W. and Leetmaa, A. 1998. An improved coupled model for ENSO prediction and implications for ocean initialization. Part II: The coupled model. Monthly Weather Review 126: 1022-1034.
Kim, H.M., Webster, P.J. and Curry, J.A. 2012. Seasonal prediction skill of ECMWF system 4 and NCEP CFSv2 retrospective forecast for the Northern Hemisphere winter. Climate Dynamics 39: 2957-2973.
Saha, S., Nadiga, S., Thiaw, C., Wang, J., Wang, W., Zhang, Q., Van den Dool, H.M., Pan, H.-L., Moorthi, S., Behringer, D., Stokes, D., Pena, M., Lord, S., White, G., Ebisuzaki, W., Peng, P. and Xie, P. 2006. The NCEP Climate Forecast System. Journal of Climate 19: 3483-3517.
Stockdale, T.N., Anderson, D., Balmaseda, M., Doblas-Reyes, F., Ferranti, L., Mogensen, K., Molteni, F. and Vitart, F. 2011. ECMWF Seasonal Forecast system 3 and its prediction of sea surface temperature. Climate Dynamics 37: 455-471.Reviewed 6 November 2013