Contributions of Convectively Coupled Equatorial Rossby Waves and Kelvin Waves to the Real-Time Multivariate MJO Indices

Abstract

The real-time multivariate (RMM) Madden–Julian oscillation (MJO) indices have been widely applied to diagnose and track the progression of the MJO. Although it has been well demonstrated that the MJO contributes to the leading signals in these indices, the RMM indices vary erratically from day to day. These variations are associated with noise in the outgoing longwave radiation (OLR) and wind data used to generate the indices. This note demonstrates that some of this “noise” evolves systematically and is associated with other types of propagating modes that project onto the RMM eigenmodes. OLR and zonal wind data are filtered in the wavenumber–frequency domain for the MJO, convectively coupled equatorial Rossby (ER) waves, and convectively coupled Kelvin waves. The filtered data are then projected onto the RMM modes. An example phase space associated with these projections is presented. Linear regression is then applied to isolate the wave signals from random variations in the same bands of the wavenumber–frequency domain, and the regressed data are projected onto the RMM EOFs. Results demonstrate the magnitudes of the contributions of the systematically evolving signals associated with these waves to variations in the RMM principal components, and how these contributions vary with the longitude of the active moist deep convection coupled to the waves.

A Framework for Assessing Operational Madden–Julian Oscillation Forecasts

“…Moreover, the method is straightforward to adopt and has already been applied at several operational centers, albeit in slightly different forms. Disadvantages of the method are i) minor contamination from higher-frequency variability unrelated to the MJO still exists (Roundy et al 2009), ii) minor ambiguities arising from the removal of interannual variability such as that associated with ENSO, and iii) the index is unable to account for interevent variations of MJO structure. Specific details of this method are outlined below, specifically noting one slight modification from WH04 that was adopted for this activity.…”

Regression Analysis of Zonally Narrow Components of the MJO

“…When assessed over a long climatology, the spectra of these signals are not easily distinguished from red noise except that signals characterized by phase speeds between 2 and 8 m s 21 appear to be favored (Roundy 2012a). Following a 40-yr tradition, the Madden-Julian oscillation (MJO; Madden andJulian 1972, 1994;Zhang 2005) is frequently described as a distinct signal projecting most strongly onto planetary scales and the 30-60-or 40-50-day band.…”

“…Hereafter, I label these 30-60-day signals as the traditionally defined MJO. A few authors have extended this band to include periods in the intraseasonal range greater than 20 days (e.g., Sobel and Kim 2012;Kim et al 2009). Those who have extended the range to shorter time scales have frequently done so to accommodate different forms of intraseasonal variability in models [such as Kim et al (2009)], while others might have observed that some disturbances in the 20-30-day band take on characteristics of MJO events [such as during December 2011 during the Dynamics of the MJO (DYNAMO) field campaign (Gottschalck et al 2013;Yoneyama et al 2013)].…”

Tropical Cyclone Mekkhala’s (2008) Formation over the South China Sea: Mesoscale, Synoptic-Scale, and Large-Scale Contributions

“…On 22 September it transitioned to phase 6, which is generally associated with enhanced convection in the western Pacific. While the RMM is a valuable tool for tracking the MJO, it can be sensitive to higherfrequency equatorial wave (Roundy et al 2009). Thus, the 20-100-day bandpass-filtered OLR and 850-hPa winds were examined.…”