Stratospheric gravity waves at Southern Hemisphere orographic
hotspots: 2003–2014 AIRS/Aqua observations

Hoffmann, Lars; Grimsdell, Alison W.; Alexander, M. Joan

doi:https://doi.org/10.5194/acp-16-9381-2016

Articles | Volume 16, issue 14

https://doi.org/10.5194/acp-16-9381-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-16-9381-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 16, issue 14

Research article

|

28 Jul 2016

Research article |

| 28 Jul 2016

Stratospheric gravity waves at Southern Hemisphere orographic hotspots: 2003–2014 AIRS/Aqua observations

Lars Hoffmann, Alison W. Grimsdell, and M. Joan Alexander

Data sets

AIRS/Aqua L1B Infrared (IR) geolocated and calibrated radiances V005 AIRS Science Team/Moustafa Chahine http://disc.gsfc.nasa.gov/datacollection/AIRIBRAD_005.html

2-minute Gridded Global Relief Data (ETOPO2) v2 National Geophysical Data Center https://doi.org/10.7289/V5J1012Q

The ERA-Interim reanalysis: configuration and performance of the data assimilation system D. P. Dee, S. M. Uppala, A. J. Simmons, P. Berrisford, P. Poli, S. Kobayashi, U. Andrae, M. A. Balmaseda, G. Balsamo, P. Bauer, P. Bechtold, A. C. M. Beljaars, L. van de Berg, J.Bidlot, N. Bormann, C. Delsol, R. Dragani, M. Fuentes, A. J.Geer, L. Haimberger, S. B. Healy, H. Hersbach, E. V. Hólm, L. Isaksen, P. Kållberg, M. Köhler, M. Matricardi, A. P. McNally, B. M. Monge-Sanz, J.-J. Morcrette, B.-K. Park, C.Peubey, P. de Rosnay, C. Tavolato, J.-N. Thépaut, and F. Vitart https://doi.org/10.1002/qj.828

Short summary

We present a 12-year record (2003-2014) of stratospheric gravity wave activity at Southern Hemisphere orographic hotspots as observed by the AIRS/Aqua satellite instrument. We introduce a method to discriminate between gravity waves from orographic or other sources and propose a simple model to predict the occurrence of mountain waves using zonal wind thresholds. The prediction model can help to disentangle upper level wind effects from low level source and other influences.