Super Dual Auroral Radar Network Expansion and Its Influence on the Derived Ionospheric Convection Pattern

The Super Dual Auroral Radar Network (SuperDARN) was built to study ionospheric convection and has in recent years been expanded geographically. Alongside software developments, this has resulted in many different versions of the convection maps data set being available. Using data from 2012 to 2018, we produce five different versions of the widely used convection maps, using limited backscatter ranges, background models and the exclusion/inclusion of data from specific radar groups such as the StormDARN radars. This enables us to simulate how much information was missing from older SuperDARN research. We study changes in the Heppner-Maynard boundary (HMB), the cross polar cap potential (CPCP), the number of backscatter echoes (n) and the chi(2)/n statistic which is a measure of the global agreement between the measured and fitted velocities. We find that the CPCP is reduced when the PolarDARN radars are introduced, but then increases again when the StormDARN radars are added. When the background model is changed from the RG96 model, to the most recent TS18 model, the CPCP tends to decrease for lower values, but tends to increase for higher values. When comparing to geomagnetic indices, we find that there is on average a linear relationship between the HMB and the geomagnetic indices, as well as n, which breaks when the HMB is located at latitudes below similar to 50 degrees due to the low observational density. Whilst n is important in constraining the maps (maps with n > 400 data points are unlikely to differ), it is insufficient as the sole measure of quality.