An update on the estimate of predictability of seasonal mean atmospheric variability using North American Multi-Model Ensemble
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In this analysis, an update in the estimate of predictable component in the wintertime seasonal variability of atmosphere documented by Kumar et al. (J Clim 20: 3888–3901, 2007) is provided. The updated estimate of seasonal predictability of 200-hPa height (Z200) was based on North American Multi-Model Ensemble (NMME) forecast system. The seasonal prediction systems participating in the NMME have gone through an evolution over a 10-year period compared to models that were used in the analysis by Kumar et al. (J Clim 20: 3888–3901, 2007). The general features in the estimates of predictable signal conform with previous results—estimates of predictability remain high in the tropical latitudes and decrease towards the extratropical latitudes; and predictability in the initialized coupled seasonal forecast systems is still primarily associated with ENSO variability. As the horizontal and vertical resolution of the models used in the current analysis is generally higher, it did not have a marked influence on the estimate of the relative amplitude of predictable component. Although the analysis indicates an increase in the estimate of predictable component, however, it maybe related to the increase in ENSO related SST variance over 1982–2000 relative to 1950–2000 (over which the analysis of Kumar et al. in J Clim 20: 3888–3901, 2007 was). The focus of the analysis is wintertime variability in Z200 and its comparison with results in Kumar et al. (J Clim 20: 3888–3901, 2007), some analyses for summertime variability in Z200, and further, for sea surface temperature, 2-m temperature and precipitation are also presented.
KeywordsNMME Predictability Ensemble mean 200 hPa height
The NMME project and data dissemination are supported by NOAA, NSF, NASA and DOE. The help of NCEP, IRI and NCAR personnel in creating, updating and maintaining the NMME archive is acknowledged. All the data used in this paper are available at NOAA Climate Prediction Center (CPC) (http://www.cpc.ncep.noaa.gov/products/NMME/). The scientific results and conclusions, as well as any view or opinions expressed herein, are those of the authors and do not necessarily reflect the views of NWS, NOAA, or the Department of Commerce.
- Hoerling MP, Kumar A (2002) Atmospheric response patterns associated with tropical forcing. J Clim 8:474–495Google Scholar
- Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
- Kumar A, Murtugudde R (2013) Predictability and uncertainty: a unified perspective to build a bridge from weather to climate. COSUST 5:327–333Google Scholar
- Kumar A, Perlwitz J, Eischeid J, Quan X, Xue T, Zhang T, Hoerling M, Jha B, Wang W (2010) Contribution of sea ice loss to Artic amplification. Geophys Res Lett 37:1–6Google Scholar
- National Research Council (2010) Assessment of intraseasonal to interannual climate prediction and predictability. the National Academies Press, Washington, 192 pp., ISBN-10: 0-309-15183-XGoogle Scholar