Multiscale Interaction in MJO Initiation over the Tropical Indian Ocean: DYNAMO and Beyond

One of the most challenging problems in prediction of Madden-Julian Oscillation (MJO) is the initiation of large-scale convection over the equatorial Indian Ocean. The Dynamics of MJO (DYNAMO) field campaign in 2011-12 has provided unprecedented in situ observations to advance our understanding of MJO initiation. It is evident that the complex multiscale interaction among convective cloud systems and their large-scale environment on time scales from hours to months is a key contributing factor. Two new science hypotheses on MJO initiation have emerged based on DYNAMO observations. First, dry air intrusions associated with synoptic-scale wave-like disturbances from subtropical Indian Ocean play an important role in 1) alternating deep convection from ITCZ to equatorial convection during the onset of MJO initiation and 2) favoring eastward propagation of MJO convection by entraining dry air into the equatorial region to the west by the Rossby-wave like gyres. Second, convective cloud systems and convective cold pools are sensitive to the large-scale water vapor distribution and air-sea fluxes. The boundary layer recovery time from the cold pools can affect the re-development of convection. The cold pool recovery time vary from a few hours during the convective active phases of MJO to more than 30 hrs during the suppressed phase, which indicating the upscaling effects of convective systems on MJO may be important for the evolution of MJO.

This study investigates the generality of these hypotheses by analyzing MJO initiation events from 1999-2013 using satellite data including TRMM rainfall, total perceptible water (TPW), AIRS water vapor profiles, and surface wind data from QuikSCAT, ASCAT and OSCAT. The results will be compared with the MJO events observed during DYNAMO. To further address the question of convective upscaling and dry air intrusions on MJO initiation, numerical experiments using a coupled atmosphere-ocean model are used to better understand the physical processes and multiscale interaction.