Abstract
AbstractThe 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 χ2/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 ∼50° 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.
Highlights
The Super Dual Auroral Radar Network (SuperDARN) consists of high-frequency coherent scatter radars built to study ionospheric convection by means of Doppler-shifted, pulse sequences and has been widely used in space physics and ionospheric research (e.g.Greenwald et al, 1995; Ruohoniemi & Greenwald, 1996; Chisham et al, 2007; Nishitani et al, 2019)
We have investigated how the SuperDARN maps have changed historically by creating 5 different versions of the convection map files for a timespan of 6 years and comparing them statistically
PolarDARN radars add the most data to the dataset, but the StormDARN radars are important for constraining the maps
Summary
The Super Dual Auroral Radar Network (SuperDARN) consists of high-frequency coherent scatter radars built to study ionospheric convection by means of Doppler-shifted, pulse sequences and has been widely used in space physics and ionospheric research Analysis Working Group, Thomas, Ponomarenko, Billett, et al, 2018) This background model was used by most SuperDARN users when generating convection maps and used in many scientific studies. Many more radars have been added to SuperDARN This raises the question of how much of an effect changing the background model has on the convection map dataset, which was investigated by Shepherd and Ruohoniemi (2000). The Pettigrew et al (2010) and Cousins and Shepherd (2010) models were not implemented into RST until version 4.1 (SuperDARN Data Analysis Working Group, Thomas, Ponomarenko, Bland, et al, 2018). The background model by Thomas and Shepherd (2018) was released, which is standard in RST since version 4.2 We probe the effects of the following changes: 1. Inclusion of the backscatter range limits
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