Authors response to reviewers and community comment

Abstract

The mesosphere and lower thermosphere (MLT), at heights of 80–100 km, is critical in the coupling of the middle and upper atmosphere and controls the momentum and energy transfer between these two regions. However, despite its importance, many General Circulation Models (GCMs) do not extend upwards into the MLT and those that do remain poorly constrained. In this study, we use a long-term meteor radar wind dataset from Rothera (67° S, 68° W) on the Antarctic Peninsula to test the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X). This radar has an interferometer to determine meteor heights and has been running since 2005. This unique combination yields a dataset ideally suited to investigate interannual variability. We find that although some characteristic features in monthly median winds are represented well in WACCM-X, the model exhibits significant biases. In particular, the observations reveal a ∼10 ms-1 eastward wind at heights of 85–100 km in Antarctic winter, whereas the model predicts winds of the same magnitude but of opposite direction. We propose that this bias exists because WACCM-X is missing eastward momentum forcing in the MLT from the breaking of secondary gravity waves. Both the model and observations reveal significant interannual variability in monthly median winds. We investigate the role of particular key external phenomena in driving the winds in this region. These phenomena are; i) variations in Solar activity, ii) the El Nino Southern Oscillation (ENSO), iii) the Quasi-Biennial Oscillation (QBO) and iv) the Southern Annular Mode (SAM). We use a linear regression method to investigate how the observed and modelled winds, and modelled gravity wave tendencies in the Antarctic MLT vary in relation to the indices that quantify these phenomena. We find that there are some times of year and some height ranges at which there are significant correlations between the indices and the observed/modelled winds. In particular, in summer, there is a strong positive correlation in the modelled and observed zonal winds with the 11-year Solar cycle of magnitude up to 9 ms-1 per 70 Solar flux units. However, there appears to be little significant influence of the ENSO on the winds observed by the radar although WACCM-X zonal winds display a negative correlation throughout January–February and a positive correlation during March–May. Results from the QBO indices are varied and we find differing correlations in the model and observations. Finally, we find a positive correlation between observed summertime zonal winds and the SAM which has a magnitude of 9 ms-1 per 2.5 hPa change in the SAM index. However, in WACCM-X zonal winds the summertime response is negative and around 10 ms-1 per 2.5 hPa. The significance of this work lies in our quantifying the biases in a leading GCM and demonstrating there is significant interannual variability in both modelled and observed winds, some of which are consistent with the proposal of external forcing.