Gravity waves are atmospheric waves that can be generated by winds blowing over mountains, storms, unstable jet streams and strong convection. As the waves ascend from their sources in the lower atmosphere, into the stratosphere and mesosphere, they transport momentum in a "momentum flux". When the waves become unstable they "break", rather like ocean surface waves breaking on a beach. This acts to transfer their momentum into the atmosphere, exerting a "drag force" that dramatically influences the global atmospheric circulation.

Computer General Circulation Models (GCMs) used for numerical weather prediction and climate research must represent these waves realistically if they are to predict the behaviour of the real atmosphere.

However, the GCMs display "biases" in which the behaviour they predict does not match that revealed by observations. The largest biases in nearly all GCMs occur in the winter and springtime Antarctic stratosphere. There, they produce a polar region, the "polar vortex", that when compared to observations, is too cold by 5-10 K, has winds that are too strong by about 10 m/s and that persists some 2-3 weeks too long into spring before it breaks up. These significant biases are known as the "cold pole" problem.

It is now realised that the biases arise because the GCMs are missing large amounts of gravity-wave flux that must occur in the real atmosphere at latitudes near 60 degrees S. These latitudes include the stormy Southern Ocean and the Drake Passage. However, the nature, sources, variability and fluxes of these "missing" waves are currently very uncertain.

In DRAGON-WEX (DRake pAssaGe sOuthern oceaN - Wave EXperiment, supported through NERC grant awards NE/R001391/1 and NE/R001235/1) use was made of satellites, radiosondes and radars to directly measure the waves over the Southern Ocean and Drake Passage near 60 S, determine their properties and investigate their role in coupling together the troposphere, stratosphere and mesosphere. The project's results will thus help resolve the cold pole problem.

The project applied a very powerful novel 3D method the project had developed for analysing satellite data. With their method, they could detect individual gravity waves in the stratosphere in 3D and measure their momentum fluxes. Importantly, because it is a fully 3D method they could do this without needing the assumptions that critically limit earlier 1D and 2D methods. The project used their method to identify an estimated 100,000 individual gravity waves near 60 S.

The project sought to combine the satellite observations with measurements of gravity waves made by radiosondes ("weather balloons") and radars to characterise the "missing" gravity waves, determining their short-term and seasonal variability and investigate their sources - in particular, the contributions made to the waves by the mountains of the Southern Andes and Antarctic Peninsula, storms over the Southern Ocean/Drake Passage, unstable jet streams and by waves propagating into the 60 S region from latitudes to the North or South.

The project also sought to use a unique combination of meteor radars, one in the Antarctic and a new radar on the remote mountainous island of South Georgia to measure the winds, waves and tides of the mesosphere. The project also sought to determine the degree to which fluctuations in the waves they measured in the stratosphere drive the variability of the mesosphere and, in particular, the role of waves in driving anomalous events recently observed at heights near 90 km in the polar mesosphere, when the Northward winds of the general circulation appeared to briefly cease and when the occurrence frequency of polar mesospheric clouds was greatly reduced.

They used meteor radars on the island of South Georgia and at Rothera in the Antarctic to investigate recent suggestions that waves generated by mountains can propagate to heights of 90 km or more - effectively the edge of space.

Finally, in Pathways to Impact the project worked closely with the Met Office to use the project's results to test and improve their Unified Model GCM.