EAPS

Special Weather & Climate Lecture Series - Fuqing Zhang (Penn State)
Date Time Location
September 29th, 2015 3:00pm-4:00pm 54-915
"Predictability and Dynamics of Weather and Climate at the Regional Scales | Spontaneous balance adjustment and gravity waves from moist baroclinic jets and fronts"

Speaker: Fuqing Zhang, Professor of Meteorology, Director, Center for Advanced Data Assimilation and Predictability Techniques, Penn State, University

ABSTRACT: This talk reviews the spontaneous balance adjustment (SBA) hypothesis that is developed over a series of studies over the past decade [e.g., Zhang 2004 JAS; Wu and Zhang 2004 JGR; Wang and Zhang 2007 MWR; Plougonven and Zhang 2007 JAS; Lin and Zhang 2008 JAS; Wang et al. 2009 JAS, 2010 QJ; Wang and Zhang 2010 JAS; Wei and Zhang 2013 JAS] through examining gravity waves initiation from idealized simulations of baroclinic life cycles and vortex-jet dipoles with both high-resolution complex non-hydrostatic mesoscale models and/or linear forcing or ray tracing models. More specifically, it is hypothesized that within the developing baroclinic jet-front system, the large-scale background flow can continuously produce flow imbalance while the gravity waves are continuously generated from flow imbalance through spontaneous balance adjustment [Zhang 2004 JAS]. A framework to describe this emission mechanism was proposed by Plougonven and Zhang [2007 JAS] through scale analysis and analytical derivation of a wave equation linearized on the balanced background flow that is forced by synoptic-scale flow imbalance. This was implemented and expanded to explain gravity waves emitted in dipoles [Wang and Zhang, 2010 JAS], and has recently been used to explain at least some of the jet-exit region gravity waves found in baroclinic life cycles. Ongoing study is also extend this framework to examine the gravity waves in moist baroclinic life cycles [Wei and Zhang 2014 JAS 2015 JAMES]. Also discussed will be the impacts of gravity waves on weather, general circulation, mesoscale energy spectrum and atmospheric predictability.