Professor Adrian Matthews School of Environmental Sciences and School of Mathematics, University of East Anglia, Norwich, UK

Research group
PhD projects

MJO introduction
Current MJO forecast
MJO forecast method
MJO forecast validation
MJO forecast archive
MJO EMD archive
Other MJO forecasts

Centre for Ocean and Atmospheric Sciences

MJO forecast method

A statistical technique is used to forecast the MJO. A brief technical description is given here. Full details can be found in Love BS, Matthews AJ, Janacek GJ, 2008: Real-time extraction of the Madden-Julian Oscillation using empirical mode decomposition and statistical forecasting with a VARMA model. J. Climate, 21, 5318-5335.

The data set used is the NOAA AVHRR gridded outgoing longwave radiation (OLR). Pentad (5-day) mean maps of OLR anomalies are calculated by subtracting the annual cycle at each grid point. Then, the MJO signal at each grid point is isolated using empirical mode decomposition (EMD). This acts as a time filter that can be applied in real time with minimal end effects.

The EMD-filtered OLR maps up to the current pentad are then projected onto the leading two empirical orthogonal functions (EOFs) of tropical OLR. The resulting two principal component (PC) time series, PC1 and PC2, describe the state of the MJO at each time.

Future values of PC1 and PC2 are then predicted using a vector autoregressive moving average (VARMA) model. The parameters of the VARMA model were determined by a maximum likelihood technique using a training data set, from 1979 to 1996.

The forecast OLR anomaly maps are produced by multiplying seasonally varying regression maps of OLR by the predicted values of PC1 and PC2.

Created: Mon Apr 24 02:02:20 2017