Display Abstract

Title Multi-scale properties of idealized Walker Cell

Name Joanna M Slawinska
Country United Arab Emirates
Email js6206@nyu.edu
Co-Author(s) Olivier Pauluis, Andrew Majda, Wojciech Grabowski
Submit Time 2014-02-28 16:27:58
Session
Special Session 81: Improving climate and weather prediction through data-driven statistical modeling
Contents
Two-dimensional Walker circulation over a planetary scale domain is simulated with cloud resolving model for an extended period of time. The simulated flow is characterized by complex multi-scale interactions that are difficult to disentangle. In particular, impact of convection on the dynamics of other scales, although established to be crucial, lacks detailed understanding. Thus, novel approaches have to be applied. Here, we test these approaches in an idealized setting of planetary scale circulation, with tens of convective systems sampled over several hundred days. The circulation exhibits intra-seasonal variability on a time-scale of about 20 days with quasi-periodic intensification of the circulation and broadening of the convective regime. The low frequency oscillation has four main stages: a suppressed stage with strengthened mid-level circulation intensification phase, active phase with strong upper level circulation and a weakening phase. Various physical processes driving low-frequency variability are discussed, with the particular emphasis on the moisture impact. Low-frequency variability and the associated expansion and contraction of the Walker circulation are closely tied to various kinds of organized convective systems that propagate throughout the domain. Associated flow properties across scales, convective, to mesoscale, to synoptic and global, are diagnosed. For that, individual scales are decomposed by wavelet decomposition applied to recently introduced isentropic stream function. Also, prevailing regimes of convection and convective organization are revealed and characterized by clustering of isentropic streamfunction and by applying spatio-temporal analysis.