Chang Xu

Chang Xu is a PhD student at CCRC supervised by Steven Sherwood, Martin Jucker, and Clemente Lopez Bravo. Her research uses convection-permitting models (CPMs) to understand key moisture processes that drive the propagation of convectively coupled waves (CCWs), especially the Madden–Julian Oscillation and Kelvin waves, and to improve the simulation of CCWs in general circulation models (GCMs) by improving the representation of convection coupling.

Supervised by: Steven Sherwood, Martin Jucker, Clemente Lopez Bravo

Project Title: The Role of Moisture Fluxes During the Propagation of the Convectively Coupled Waves (CCWs)

Project Description: This thesis aims to enhance the understanding and simulation of Convectively Coupled Waves (CCWs) in general circulation models (GCMs) by quantifying the moisture sources along with their propagation. By allowing for explicit convection simulation, convection-permitting models (CPMs) facilitate learning the physics of tropical convection and perform better in simulating tropical precipitation. This research could improve the simulation skill of tropical variability in GCMs. To assess the robustness of CCWs detection in short-term outputs from CPMs, the first project focused on updating a wavelet-based method that performs better in short-term data and determining the optimal length of a time series required for robust CCWs detection. By employing the recommended method and data length, the second project aims to quantify the key processes of moisture in relation to the MJO propagation phase. This enables us to diagnose the phase-dependent interactions between moisture, waves, and the large-scale environment. These diagnostics will be used in the third project to identify missing physics and misrepresented responses in GCM simulations of the MJO. By forcing a single-column model (SCM) with the same large-scale conditions, we can assess whether the GCM’s physics correctly reproduces the observed moisture tendencies. Simple SCM experiments, such as changing convective schemes, can further reveal how different parameterizations affect the moisture evolution throughout the MJO cycle.