Atmosphere Ocean Science Student Seminar
Upscale Impact of Mesoscale Convective Systems on the MJO and Its Parameterization in Coarse-Resolution GCMs
Speaker: Qiu Yang
Location: Warren Weaver Hall 1314
Date: Friday, February 21, 2020, 4 p.m.
A comprehensive and predictive understanding of the multi-scale
organization of tropical convection should not only advance our
understanding of water cycle processes and their
subseasonal-to-multidecadal variations but also provide useful insight to
further improve cumulus parameterization in coarse-resolution GCMs. For
example, Madden-Julian oscillation (MJO), the holy grail of tropical
atmospheric dynamics, is organized in a hierarchical structure that the
eastward-moving planetary-scale envelope usually contains multiple
synoptic-scale superclusters with numerous embedded mesoscale convective
systems (MCSs). Present-day GCMs fail to explicitly resolve small-scale
MCSs due to their coarse resolutions. We hypothesized that such inadequate
treatment of MCSs and their upscale impact leads to the poorly simulated
MJOs in GCMs.
Here we tackled this challenging problem from three different
perspectives based on models in a hierarchy of complexity. We first
simulated the multi-scale organization of tropical convection in a 2D
global cloud-resolving model and demonstrated the crucial upscale impact of
MCSs on the MJO through energy budget analysis. Then we used a multi-scale
theoretical model to describe the typical observation that a convectively
coupled Kelvin wave contains numerous embedded MCSs. The eddy transfer of
momentum and temperature that stands out from the model is interpreted as
the upscale impact of MCSs on large-scale circulation. Finally, we
developed a basic parameterization for the upscale impact of MCSs based on
the multi-scale theoretical model. We tested the effect of this
parameterization in both an idealized testbed and a coarse-resolution GCM.
The results show that this parameterization promotes persistent eastward
propagation of the MJO and recovers its realistic features in the GCM.