Idealized Quasi-Biennial Oscillations in an Ensemble of Dry GCM Dynamical Cores

Abstract

The paper demonstrates that quasi-biennial oscillation (QBO)-like oscillations can be simulated in an ensemble of dry GCM dynamical cores that are driven by a simple Held-Suarez temperature relaxation and lowlevel Rayleigh friction. The tropical stratospheric circulations of four dynamical cores, which are options in NCAR's Community Atmosphere Model, version 5 (CAM5), are intercompared. These are the semi-Lagrangian (SLD) and Eulerian (EUL) spectral transform, finite-volume (FV), and spectral element (SE) dynamical cores. The paper investigates how the model design choices impact the wave generation, propagation, and dissipation mechanisms in the equatorial region. SLD, EUL, and SE develop spontaneous QBO-like oscillations in the upper equatorial stratosphere, whereas FV does not sustain the oscillation. Transformed Eulerian-mean (TEM) analyses reveal that resolved waves are the dominant drivers of the QBOs. However, the Eliassen-Palm flux divergence is strongly counteracted by the TEM momentum budget residual, which represents the forcing by diffusion and thermal damping. Interestingly, a reversed Brewer-Dobson circulation accelerates the downward propagation of the SLD's QBO, whereas the EUL's and SE's QBOs are slowed by a mean ascent. Waves are abundant in the SLD's, EUL's, and SE's tropical atmosphere despite the absence of moist convection as a typical wave trigger. Dynamic instabilities are suggested as a wave-triggering mechanism in the troposphere and wave-dissipation process in the stratosphere. In particular, there are indications that the increased occurrences of strongly negative instability indicators in SLD, EUL, and SE are related to more vigorous wave activities and higher magnitudes of the resolved wave forcing in comparison to FV.

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)

“…Sensitivity to vertical resolution has been reported by numerous studies, for example by Giorgetta et al (2006) for the middle atmosphere version of the ECHAM5 (MAECHAM5) model and by Geller et al (2016) for the NASA Goddard Institute for Space Studies (GISS) climate model. In addition Yao and Jablonowski (2015) identified a sensitivity to the choice of dynamical core. Other key questions concerning simulation of the QBO regard its possible synchronization with other modes of variability, such as the annual cycle (e.g.…”

“…In a set of idealized experiments Yao and Jablonowski (2015) demonstrated that spontaneous generation of QBO-like behaviour in general circulation models was sensitive to the dynamical core chosen. This involved both the choice of numerical advection scheme (including any associated numerical diffusion) and the dissipation mechanisms.…”

“…This involved both the choice of numerical advection scheme (including any associated numerical diffusion) and the dissipation mechanisms. As well as impacting wave generation, propagation, and dissipation mechanisms, the choices can impact (Yao and Jablonowski, 2015) the simulation of the Brewer-Dobson circulation (Butchart, 2014), in particular its tropical upwelling component which opposes the descending QBO cycles in the standard paradigm (Baldwin et al, 2001). The different advection schemes used by the QBOi models are given in column 2 of Table 7.…”

“…Yao and Jablonowski, 2015) or perhaps simulations in which the QBO is artificially removed (e.g. by turning off the non-orographic GWD parameterization in the tropics).…”

Overview of experiment design and comparison of models participating in phase 1 of the SPARC Quasi-Biennial Oscillation initiative (QBOi)

“…Sensitivity to vertical resolution has been reported by numerous studies, for example by Giorgetta et al (2006) for the Middle Atmosphere version of the ECHAM5 (MAECHAM5) model and by Geller et al (2016) for the NASA Goddard Institute for Space Studies (GISS) climate model. In addition Yao and Jablonowski (2015) identified a sensitivity to the choice of dynamical core. Other key questions concerning 5 simulation of the QBO lie with its possible synchronisation with other modes of variability such as the annual cycle (e.g., Rajendran et al, 2016) and El Niño-Southern Oscillation (e.g., Christiansen et al, 2016), with the QBO's predictability (e.g., Pohlmann et al, 2013;Scaife et al, 2014) and finally with the robustness of the QBO response to climate change (e.g.…”