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Modes of variability of Southern Hemisphere atmospheric circulation estimated by AGCMs |
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| Authors: | Simon Grainger Carsten S Frederiksen Xiaogu Zheng David Fereday Chris K Folland Emilia K Jin James L Kinter Jeff R Knight Siegfried Schubert Jozef Syktus |
| Institution: | 1. Centre for Australian Weather and Climate Research, Bureau of Meteorology, Melbourne, Australia 2. National Institute of Water and Atmospheric Research, Wellington, New Zealand 3. College of Global Change and Earth System, Beijing Normal University, Beijing, China 4. Met Office Hadley Centre for Climate Change, Exeter, UK 5. Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA, USA 6. Center for Ocean-Land-Atmosphere Studies, Calverton, MD, USA 7. NASA Goddard Space Flight Center, Greenbelt, MD, USA 8. Queensland Climate Change Centre of Excellence, Brisbane, Australia |
| Abstract: | The seasonal mean variability of the atmospheric circulation is affected by processes with time scales from less than seasonal to interannual or longer. Using monthly mean data from an ensemble of Atmospheric General Circulation Model (AGCM) realisations, the interannual variability of the seasonal mean is separated into intraseasonal, and slowly varying components. For the first time, using a recently developed method, the slowly varying component in multiple AGCM ensembles is further separated into internal and externally forced components. This is done for Southern Hemisphere 500?hPa geopotential height from five AGCMs in the CLIVAR International Climate of the Twentieth Century project for the summer and winter seasons. In both seasons, the intraseasonal and slow modes of variability are qualitatively well reproduced by the models when compared with reanalysis data, with a relative metric finding little overall difference between the models. The Southern Annular Mode (SAM) is by far the dominant mode of slowly varying internal atmospheric variability. Two slow-external modes of variability are related to El Ni?o-Southern Oscillation (ENSO) variability, and a third is the atmospheric response to trends in external forcing. An ENSO-SAM relationship is found in the model slow modes of variability, similar to that found by earlier studies using reanalysis data. There is a greater spread in the representation of model slow-external modes in winter than summer, particularly in the atmospheric response to external forcing trends. This may be attributable to weaker external forcing constraints on SH atmospheric circulation in winter. |
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