Thursday, 27 January 2011
Washington State Convention Center
Empirical Orthogonal Function (EOF) analysis is a common approach used to identify the MJO. Recent works have used outgoing longwave radiation (OLR) in a univariate approach to extract the convective signature of the MJO (e.g., Sperber et al. 2005, Matthews 2008), while others have used a multivariate combined EOF analysis using 15°N-15°S averaged OLR and zonal winds at 850hPa and 200hPa to capture the MJO convection in concert with the baroclinic structure of the zonal wind (Wheeler and Hendon 2004). The CLIVAR (Climate Variability and Predictability) Madden-Julian Oscillation Working Group (MJOWG) has adopted the latter technique with the goal of having the model evaluation community use a standard diagnostic approach to evaluate simulations of the MJO (CLIVAR MJOWG 2009, Kim et al. 2009), and for making real-time experimental forecasts of the MJO (e.g., Gottschalck et al. 2010). In these approaches the two leading EOF's and their respective principal component (PC) time series are used to identify the MJO. However, comparing intraseasonal EOF reconstructions of space-time OLR anomalies against validation data reveals that numerous periods of extended and/or sporadic MJO activity are falsely identified using the 2 leading modes of variability. The new method for identifying MJO events incorporates information associated with higher order modes of variability. The results indicate that validation of the space-time variability of the MJO is important over and above the current reliance on validating phase-space plots of the two leading MJO PC's, and suggests a way forward for improving MJO forecasts.
Acknowledgement. This work was supported under the auspices of the US Department of Energy Office of Science, Regional and Global Climate Modeling Program by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.
- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner