LAUSR

Abstract. Ground-based remote sensing of atmospheric parameters is often limited to single station observations of vertical profiles at a certain geographic location. This can be a limiting factor to investigating gravity wave dynamics. In this study we present a new retrieval algorithm for multi-static meteor radar networks to obtain tomographic 3D wind fields within a pre-defined domain area. The algorithm is part of the Agile Software for Gravity wAve Regional Dynamics (ASGARD) called 3DVAR, and based on the optimal estimation technique and Bayesian statistics. The performance of the 3DVAR retrieval is demonstrated using two meteor radar networks, the Nordic Meteor Radar Cluster and the Chilean Observation Network De MeteOr Radars (CONDOR). The optimal estimation implementation provides a statistically sound solution and additional diagnostics from the averaging kernels and measurement response. We present initial scientific results such as body forces of breaking gravity waves leading to two counter-rotating vortices and horizontal wavelength spectra indicating a transition between the vortical κ−3 and divergent κ−5/3 mode at scales of 80–120 km. In addition, we have performed a keogram analysis over extended periods to reflect the latitudinal and temporal impact of a minor sudden stratospheric warming in December 2019. Finally, we demonstrate the applicability of the 3DVAR algorithm to perform large-scale retrievals to derive meteorological wind maps covering a latitude region from Svalbard, north of the European Arctic mainland, to mid-Norway.