A diagnostic and modeling study of the monthly mean wintertime anomalies appearing in a 100-year GCM experiment. [GCM (general circulation model)]
Journal Article
·
· Journal of the Atmospheric Sciences; (United States)
- Univ. of Colorado, Boulder, CO (United States)
- Princeton Univ., Princeton, NJ (United States)
The nature of simulated atmospheric variability on monthly time scales has been investigated by analyzing the output from a 100-year integration of a spectral GCM with rhomboidal wavenumber 15 truncation. The principal modes of variability in the model experiment were identified by applying a rotated empirical orthogonal function (EOF) analysis to the Northern Hemisphere monthly averaged 515-mb geopotential height for the winter season. Quasigeostrophic geopotential tendencies forced by synoptic-scale (2.5-6 day) eddy vorticity and heat fluxes were computed for those months when the individual EOF modes are particularly active. The composite patterns of the eddy-induced tendencies were compared with the corresponding monthly mean anomaly patterns. It was seen that the forcing due to eddy vorticity transports exhibited a distinctive barotropic character, and reinforced the monthly averaged geopotential height anomalies throughout the tropospheric column. A linear stationary wave model was used to mimic the individual EOF modes appearing in the GCM experiment, and to diagnose the relative importance of different types of forcing in the generation of such modes. Both tendency calculations and the stationary wave model results indicate the crucial role of vorticity transports by transient eddies. The linear model solutions also illustrate the importance of incorporating the climatological stationary waves in the basic state. 45 refs., 13 figs.
- OSTI ID:
- 5639396
- Journal Information:
- Journal of the Atmospheric Sciences; (United States), Journal Name: Journal of the Atmospheric Sciences; (United States) Vol. 50:17; ISSN 0022-4928; ISSN JAHSAK
- Country of Publication:
- United States
- Language:
- English
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