Cavanaugh, N. R., T. Allen, A. Subramanian, B. Mapes, H. Seo and A. J.
Miller, 2015:
The skill of atmospheric linear inverse models in hindcasting the Madden-Julian Oscillation.
Climate Dynamics, 44, 897-906.
Abstract.
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.
Reprint (pdf)