5.3 Satellite Estimates of Momentum Fluxes from High-Impact Gravity Wave Events in the Stratosphere and Their Effects on Circulation

Wednesday, 9 January 2019: 9:00 AM
West 212A (Phoenix Convention Center - West and North Buildings)
Laura Holt, NorthWest Research Associates, Boulder, CO; and M. J. Alexander, N. Hindley, L. Coy, W. M. Putman, and L. Hoffmann

Recent assessments of chemistry-climate models (CCMs) reveal biases in temperatures and winds in, especially but not limited to, the Southern Hemisphere stratosphere, where winds are generally too strong and temperatures too cold. The reasons for these biases are not completely understood, but it is thought that missing wave drag in models is a major culprit. Observational and modeling studies support this idea by elucidating the role of infrequent but very high-impact gravity wave events in the stratosphere. These highly intermittent gravity wave events with large momentum fluxes are the most important drivers of circulation and transport in the stratosphere, yet they are not treated correctly in most global models. This has implications for the cold pole problem in the Southern Hemisphere and the global Brewer-Dobson circulation in general.

In this presentation we show results combining HIRDLS and AIRS to derive detailed gravity wave properties and obtain new quantitative estimates of the local and intermittent gravity wave drag in the stratosphere. The combination of high-vertical resolution (1 km) and near-global (60°S to 80°N), close horizontal sampling (100 km) makes HIRDLS temperatures the best available dataset for retrieving gravity wave properties needed to diagnose gravity wave effects on circulation. We further exploit the close zonal sampling of HIRDLS near the turnaround latitude in the Southern Hemisphere to obtain estimates of the missing drag. We combine the HIRDLS results with AIRS brightness temperature images, which reveal high-spatial resolution detail of long vertical wavelength waves, to obtain 3-D, day-to-day variability in gravity wave properties and attribute the wave events to wave sources. The AIRS and HIRDLS datasets complement each other well since the two instruments have very different resolutions and horizontal sampling.

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