The skill of atmospheric linear inverse models in hindcasting the Madden-Julian Oscillation

A suite of statistical atmosphere-only linear inverse models of varying complexity are used to hindcast recent MJO events from the Year of Tropical Convection and the Cooperative Indian Ocean Experiment on Intraseasonal Variability/Dynamics of the Madden-Julian Oscillation mission periods, as well as over the 2000-2009 time period. Skill exists for over two weeks, competitive with the skill of some numerical models in both bivariate correlation and root-mean-squared-error scores during both observational mission periods. Skill is higher during mature Madden-Julian Oscillation conditions, as opposed to during growth phases, suggesting that growth dynamics may be more complex or non-linear since they are not as well captured by a linear model. There is little prediction skill gained by including non-leading modes of variability.