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Gravity waves in the Southern Hemisphere

The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was the first comprehensive measurement program devoted to quantifying the evolution of GWs arising from sources at lower altitudes as they propagate upward, interact with mean and other wave motions, and ultimately dissipate in the mesosphere and lower thermosphere (MLT) (Fritts et al. 2016). The key objective was to ”observe and understand the end-to-end dynamics of GWs from the ground to the edge of space”, Eckermann et al. (2018). To achieve this goal, coordinated ground-based and airborne observations were conducted in New Zealand. The DLR Institute of Atmospheric Physics deployed the research aircraft Falcon, provided regular radiosonde soundings, and conducted more than 800 h of ground-based Rayleigh lidar observations of stratospheric and mesospheric temperatures. The published papers include an overview of the atmospheric state during the DEEPWAVE period (Gisinger et al. 2017), case studies (Bramberger et al. 2017, Ehard et al. 2017, Heller et al. 2017, Portele et al. 2018), and climatological studies investigating the relation of low-level forcing and middle atmosphere response (Kaifler et al. 2015). Furthermore, there are numerous DLR contributions to papers of the international DEEPWAVE community, e.g., Fritts et al. (2016), Smith et al. (2016), Bossert et al. (2015), Eckermann et al. (2018).

The BMBF-funded research in the project GW-LCYCLE in Northern Europe led to additional insights which are documented in publications of the participating institutions (Matthias et al. 2016, Dörnbrack et al. 2017, Hildebrand et al. 2017, Kaifler et al. 2017b, Krisch et al. 2017, Stober et al. 2017, Wagner et al. 2017, Witschas et al. 2017, Baumgarten et al. 2018, Rapp et al. 2018). There are three major conclusions from these studies which are relevant for motivating the observational and numerical work being planned and conducted for SOUTHTRAC:

1. Long-term ground-based observations of temperature and wind in the stratosphere and the MLT are essential to understand and simulate the deep GW propagation as well as dissipation during GW breaking events as both processes are controlled by diurnal and semi-diurnal tides (Eckermann et al. 2016, Gisinger et al. 2017, Eckermann et al. 2018).
2. Coordinated airborne observations of GW patterns in the upper troposphere/lower stratosphere (UTLS) are key to classify the vertical and horizontal propagating components (Krisch et al. 2017, Wagner et al. 2017, Witschas et al. 2017); in particular, observations below, at and above flight level need to be combined. Additional airborne observations of flow pattern and temperature perturbations in the MLT can lead to spectacular new insights into the horizontal propagation pathways and the dissipative processes responsible for the momentum deposition (Bossert et al. 2015, Pautet et al. 2016, Bossert et al. 2017, Fritts et al. 2018).
3. Numerical modeling across all scales from global to regional is decisive in connecting and interpreting the scattered observations (Ehard et al. 2018, Fritts et al. 2018); furthermore, the extension of our modeling capabilities into the MLT seems to be the prerequisite to expand our knowledge about the momentum deposition by breaking GWs (Heale et al. 2014, Heale and Snively 2015, Bramberger et al. 2017, Heale et al. 2017).

Research about GWs in the region around South America has been conducted by the particiants from FZJ and DLR for a long time, (e.g., Eckermann and Preusse 1999, Preusse et al. 2002). The results of DEEPWAVE and GW-LCYCLE reinforced the interest in the oblique propagation of OGWs (e.g., Ehard et al. 2017, Krisch et al. 2017).

The flow across the Southern Andes and the Antarctic Peninsula excites OGWs propagating downstream, a prominent and persistent phenomenon occurring every winter and spring in the SH. The observed large GWMFs are partly reproduced by high-resolution NWP models such as the ECMWF IFS which resolves a major part of the GW spectrum (e.g. Wu and Eckermann 2008, Preusse et al. 2014). However, for most regions of enhanced GWMFs around 60°S the GW sources are still unspecified. Filtering of GWs from a homogeneous non-orographic source by the background winds mimics the salient patterns seen in the satellite observations except for the South America (Ern et al.2006, Preusse et al. 2009). Searching for actual source processes, however, a puzzle emerges: though the maximum GWMF is around 60°S, the main mountain ridges, but also indicators of convective GW sources and fronts (Holt et al. 2017) are located either further equatorward (around 40°S) or poleward over the Antarctic Continent.

Oblique propagation of mountain waves was reproduced by coupling an orographic source to ray-tracing (e.g. Eckermann and Preusse 1999, Preusse et al. 2002). Wu and Eckermann (2008) suggested that oblique propagation connects the GW sources in the storm tracks with the stratospheric GWMF maximum and find evidence for this in the orientation of the wave fronts in the ECMWF model data. In a more general context, ray-tracing also indicated the focusing of GWs into the PNJ (Preusse et al. 2009, Sato et al. 2009, Kalisch et al. 2014). However, these studies indicated propagation into the jet over the entire stratosphere while super-pressure balloon observations find the 60°S-maximum already at 18 km (Plougonven et al. 2013). Recent observations from the GW-LCYCLE project by GLORIA combined with ray-tracing modeling present evidence that extreme oblique propagation transfers large amounts of GWMF already below 20 km altitude (Krisch et al. 2017).

In a sensitivity study, Cai (2015) showed the effect of varying the strength of NOGWD: while a simulation without NOGW exhibits a clear cold bias in the polar stratosphere, enhancing NOGWs leads to an enhanced warm bias. At the same time, also PWs are affected, and enhancing the NOGWD also leads to stronger PW activity in the winter stratosphere, increasing temperatures further. Thus, a non-linear response to imposed GWD occurs (in agreement with Cohen et al. 2013), complicating the estimation of needed additional sources further. The lack of success of simply tuning existing GW parameterizations to reach a certain climate state in GCMs strongly emphasizes the need for more physical approaches to better represent the modelled and parameterized GW activity in climate models. The first important step is to validate GWMFs and drag toward observations, high-resolution modeling and drag estimates from reanalysis.

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References

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