A Precipitation-Based Index for Tropical Intraseasonal Oscillations

Characteristic patterns of precipitation-associated tropical intraseasonal oscillations, including the Madden–Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO), are identified using local empirical orthogonal function (EOF) analysis of the Tropical Rainfall Measuring Mission (TRMM) precipitation data as a function of the day of the year. The explained variances of the EOF analysis show two peaks across the year: one in the middle of the boreal winter corresponding to the MJO and the other in the middle of summer corresponding to the BSISO. Comparing the fractional variance indicates that the BSISO is more coherent than the MJO during the TRMM period. Similar EOF analyses with the outgoing longwave radiation (OLR) confirm this result and indicate that the BSISO is less coherent before the TRMM era (1979–98). In contrast, the MJO exhibits much less decadal variability. A precipitation-based index for tropical intraseasonal oscillation (PII) is derived by projecting bandpass-filtered precipitation anomalies to the two leading EOFs as a function of day of the year. A real-time version that approximates the PII is further developed using precipitation anomalies without any bandpass filtering. It is further shown that this real-time PII index may be used to diagnose precipitation in the subseasonal forecasts.

Kernel Analog Forecasting of Tropical Intraseasonal Oscillations

This paper presents the results of forecasting the Madden–Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO) through the use of satellite-obtained global brightness temperature data with a recently developed nonparametric empirical method. This new method, referred to as kernel analog forecasting, adopts specific indices extracted using the technique of nonlinear Laplacian spectral analysis as baseline definitions of the intraseasonal oscillations of interest, which are then extended into forecasts through an iterated weighted averaging scheme that exploits the predictability inherent to those indices. The pattern correlation of the forecasts produced in this manner remains above 0.6 for 50 days for both the MJO and BSISO when 23 yr of training data are used and 37 days for the MJO when 9 yr of data are used.