Improving the interpretation of line-of-sight data in SuperDARN convection maps

Ionospheric convection maps are an invaluable data product for the study of the magnetosphere-ionosphere-thermosphere system. The Super Dual Auroral Radar Network (SuperDARN) has high spatial and temporal resolution data with near global coverage in the polar ionosphere, making it the ideal candidate for studying ionospheric convection. Since the creation of the map potential technique [Ruohoniemi and Baker, 1998], the SuperDARN network has expanded to more than 30 radars globally. The expansion of the network and the longevity of the project has created an extensive data archive, which has allowed the recent creation of improved convection models. Ruohoniemi and Greenwald [1996] created a model using data from the first SuperDARN radar, this has been followed by later models including those by Pettigrew et al [2010], Cousins and Shepherd [2010], and most recently Thomas and Shepherd [2018]. Later models benefit from the increased SuperDARN coverage, particularly at mid-latitudes. Futhermore, improvements in the understanding of SuperDARN backscatter can improve the quality of the convection maps. The Chisham [et al, 2008] empirical height model, the Ribiero [et al, 2011] method for identifying slow moving ionospheric scatter and the Burrell [et al, 2015] method for determining the incoming direction of scatter will be considered in this paper. Each of the techniques either improves our knowledge of the location of the scatter or the amount of ionospheric scatter that can be included in the mapping process. We present an investigation of the effect of convection models and backscatter processing techniques on the resultant convection map.