A reassessment of SuperDARN meteor echoes from the upper mesosphere and lower thermosphere

Abstract

The Super Dual Auroral Radar Network (SuperDARN) is a network of HF radars used to study phenomena in the Earth's magnetosphere, ionosphere, and upper atmosphere. Phenomena in the upper mesosphere and lower thermosphere (MLT) can be studied as the SuperDARN radars act effectively as meteor radars at near ranges. However, SuperDARN meteor echo measurements from all heights have typically been combined together to give a height-averaged picture of large-scale characteristics and dynamics of the MLT. This is in part due to the uncertainty in the measurement of individual meteor echo heights, which is in turn partly due to the lack of reliable (and for some radars, the lack of any) interferometric information. Here, we present a method for calibrating SuperDARN interferometer data which reduces the systematic offsets in meteor echo height estimations. Using 9 years of SuperDARN data we then determine occurrence distributions of SuperDARN meteor echo heights. The distributions are approximately Gaussian with height, extending from ∼75 to ∼125km and peaking around ∼102–103km. In addition, we investigate whether the Doppler spectral width measured by the SuperDARN radars, which is related to the ambipolar diffusion coefficient for meteor echoes, can be used as a proxy measurement for meteor echo height. Due to the large spread of spectral width measurements at any one height we conclude that this proxy measurement is not practical and that the height of individual SuperDARN meteor echoes cannot be estimated without interferometric information. We also discuss how more accurate height information could be used to study the height variation of neutral wind velocities and the ambipolar diffusion coefficient across the MLT altitude range, and conclude that SuperDARN meteor echo observations have the potential to complement, and significantly extend the altitude range of, meteor echo observations from standard VHF meteor radars.