Interpreting the nature of Northern and Southern Annular Mode variability in CMIP5 Models

Journal article

Characteristic timescales for the Northern Annular Mode (NAM) and Southern Annular Mode (SAM) variability are diagnosed in historical simulations submitted to the Coupled Model Intercomparison Project Phase 5 (CMIP5) and are compared to the European Centre for Medium-Range Weather Forecasts ERA-Interim data. These timescales are calculated from geopotential height anomaly spectra using a recently developed method, where spectra are divided into low-frequency (Lorentzian) and high-frequency (exponential) parts to account for stochastic and chaotic behaviors, respectively. As found for reanalysis data, model spectra at high frequencies are consistent with low-order chaotic behavior, in contrast to an AR1 process at low frequencies. This places the characterization of the annular mode timescales in a more dynamical rather than purely stochastic context. The characteristic high-frequency timescales for the NAM and SAM derived from the model spectra at high frequencies are ∼5 days, independent of season, which is consistent with the timescales of ERA-Interim. In the low-frequency domain, however, models are slightly biased toward too long timescales, but within the error bars, a finding which is consistent with previous studies of CMIP3 models. For the SAM, low-frequency timescales in November, December, January, and February are overestimated in the models compared to ERA-Interim. In some models, the overestimation in the SAM austral summer timescale is partly due to interannual variability, which can inflate these timescales by up to ∼40% in the models but only accounts for about 5% in the ERA-Interim reanalysis.

Authors: Schenzinger, V; Osprey, S

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Journal of Geophysical Research: Atmospheres
• Volume: 120
• Issue: 21
• Pages: 11203-11214
• Publication date: 2015-11-13
• DOI: 10.1002/2014JD022989
• EISSN: 2169-8996
• ISSN: 2169-897X
• Keywords: annular mode; stochastic; power spectra