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Journal of the Meteorological Society of Japan. Ser. II
Vol. 94 (2016) No. 3 p. 237-256




 Recent studies suggest that the horizontal propagation of gravity waves (GWs) is important in the spatial distribution of gravity wave forcing (GWF), especially during winter in the high latitudes of the Southern Hemisphere (SH). However, most standard gravity wave parameterizations (GWPs) treat GW propagation simply in the vertical. In this study, a new orographic GWP that includes three-dimensional (3D) GW propagation is developed and its impact on large-scale dynamical fields is examined. Our GWP calculates the horizontal locations and changes in the 3D wavenumbers of GWs explicitly through vertical integration of the ray tracing equations. The GWF due to wave refraction, which occurs in inhomogeneous background fields even without wave dissipation, is also calculated. In addition, the computational cost of parallelization is greatly reduced by adopting a Taylor’s series approximation for the horizontal gradient of the background fields needed for the ray tracing calculation. Two numerical experiments are performed using the Model for Interdisciplinary Research of Climate (MIROC)-AGCM: one uses the new orographic GWP and the other uses a conventional GWP. In the experiment with the new GWP, the westward GWF is enhanced in the SH winter mesosphere above the core of the polar night jet. This enhancement results from the significant latitudinal propagation of the parameterized GWs toward the jet axis. The zonal wind is slightly stronger in the SH winter polar upper stratosphere, which is consistent with the differences in GWF caused mainly by refraction. However, the strength and seasonal evolution of the polar night jet is less affected by the different GWPs. This result may be because of the compensation by Eliassen-Palm flux divergence due to the resolved waves. These results suggest that 3D propagation in GWPs is potentially important for better representation of the momentum budget of the middle atmosphere in climate models.

Copyright © 2016 by Meteorological Society of Japan

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