Abstract
Using multi‐decadal simulations, we investigate the relationship between the quasi‐biennial oscillation (QBO) and the Madden–Julian oscillation (MJO) in the Global Ocean Mixed Layer configuration of the Met Office Unified Model (MetUM‐GOML1) at two horizontal resolutions (approximately 200 and 90 km at the equator). MetUM‐GOML1 produces a weak and insignificant correlation between QBO winds and mean MJO amplitude in boreal winter, in contrast to the significant anti‐correlation in reanalysis. While reanalysis shows the easterly QBO favors stronger Maritime Continent MJO activity, MetUM‐GOML1 displays stronger West Pacific MJO activity. The biased QBO–MJO relationship in MetUM‐GOML1 may be due to weak QBO‐induced temperature anomalies in the tropical tropopause layer, or to errors in MJO vertical structure.
Highlights
The Madden–Julian oscillation (MJO) (Madden & Julian, 1971) is a major component of tropical tropospheric intraseasonal variability (≈30–70-day period), characterized by coherent regions of deep convection, enhanced rainfall and associated zonally overturning circulations
We have investigated the quasi-biennial oscillation (QBO)–MJO relationship in Met Office Unified Model (MetUM)-GOML, a relatively simple coupled model comprising a state-of-the-art atmospheric general circulation models (GCMs) coupled to a mixed-layer ocean
Our choice of MetUM-GOML was motivated by its ability to simulate the MJO, in the configuration with increased convective mixing employed here (Klingaman & Woolnough, 2014a); MetUM coupled configurations with dynamic oceans struggle to represent the MJO in climate simulations (e.g., Jiang et al, 2015; Klingaman & Woolnough, 2014b)
Summary
The Madden–Julian oscillation (MJO) (Madden & Julian, 1971) is a major component of tropical tropospheric intraseasonal variability (≈30–70-day period), characterized by coherent regions of deep convection, enhanced rainfall and associated zonally overturning circulations. Marshall et al (2017) found higher MJO skill during EQBO winters, using subseasonal re-forecasts with the Predictive Ocean Atmosphere Model for Australia In this emerging area of research, no study has investigated whether a climate model can reproduce this relationship, possibly because many GCMs struggle to internally generate the QBO or the MJO, or both. MJO strength and phase are determined by daily 1979–2014 real-time multivariate MJO (RMM) indices, RMM1 and RMM2 (Wheeler & Hendon, 2004), computed from National Oceanic and Atmospheric Administration satellite-derived outgoing long-wave radiation (OLR) and National Centers for Environmental Prediction reanalysis zonal winds at 850 and 200 hPa. RMM1 represents MJO variability in the Maritime Continent; RMM2 represents the anti-correlation of convective activity between the Indian. No ENSO filtering is performed as GOML1 never produces a Niño3.4 anomaly larger than Æ1.0C
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