11:00 AM - 1:00 PM
[PEM10-P11] Magnetospheric-density estimation from automatically identified FLR in ground and ionospheric backscatters of SuperDARN
Where the frequency of waves coming into the magnetosphere matches the eigenfrequency of a geomagnetic field line, which runs through the ground, the ionosphere, and the magnetosphere, the FLR (field-line resonance) can excite eigen-oscillations of the field line and the plasma frozen-in to the field line. The FLR-generated eigen-oscillation can be identified from the combination of the maximum in its power and the steepest change in its phase at its eigen-frequency (called the FLR frequency below). From thus identified FLR frequency one can estimate the density along the magnetic field line, because, in a simplified expression, 'heavier' field line oscillates more slowly.
Since the FLR oscillates the ionospheric plasma, too, there could exist cases in which multiple SuperDARN radars' VLOS (Velocity along the Line of Sight) detect the two-dimensional (2D) distribution of the FLR frequency, from which we can estimate 2D plasma-density distribution on the magnetospheric equatorial plane. However, visual identification of the FLR in the VLOS data is time-consuming, and the visual identification could miss FLR events superposed by non-FLR perturbations. In addition, there are lots of VLOS data to be analyzed.
We have so far developed a set of computer codes to automatically identify the FLR for any beam of any radars, by using the amplitude-ratio method and the cross-phase methods; these methods cancel out the superposed non-FLR perturbations by dividing the data from a Range Gate (RG) by the data from a nearby RG along the same beam, because the FLR frequency tends to depend on the latitude more strongly than the superposed non-FLR perturbations. Another advantage of applying these methods to the SuperDARN VLOS data is that we can choose any pair of RGs (along the same beam) with different distances, and thus can identify what distance is the best to identify the FLR. This distance reflects the resonance width, which is an important quantity reflecting the diffusion and dissipation of the FLR energy.
We are now developing an all-in-one IDL code which unifies the above-stated set of codes and is applied to VLOS data of all the beams of a radar at once. The code needs to automatically distinguish whether the identified FLR was in the ionospheric backscattered signal or in the ground/sea backscattered signal; for the latter, the code needs to find the ionospheric reflection point, which is the actual location of the observed FLR. We have implemented these features and tested them for a few events in which FLR was simultaneously identified at a few ground/sea-backscattered points and at a few ionosphere-backscattered points; we have found that the ionospheric reflection points of the ground/sea backscatters tend to be located at latitudes near the latitudes of the ionosphere-backscattered points. We have also calculated, for each point, the corresponding magnetospheric equatorial density; we will show and discuss the density distribution at the meeting.
Since the FLR oscillates the ionospheric plasma, too, there could exist cases in which multiple SuperDARN radars' VLOS (Velocity along the Line of Sight) detect the two-dimensional (2D) distribution of the FLR frequency, from which we can estimate 2D plasma-density distribution on the magnetospheric equatorial plane. However, visual identification of the FLR in the VLOS data is time-consuming, and the visual identification could miss FLR events superposed by non-FLR perturbations. In addition, there are lots of VLOS data to be analyzed.
We have so far developed a set of computer codes to automatically identify the FLR for any beam of any radars, by using the amplitude-ratio method and the cross-phase methods; these methods cancel out the superposed non-FLR perturbations by dividing the data from a Range Gate (RG) by the data from a nearby RG along the same beam, because the FLR frequency tends to depend on the latitude more strongly than the superposed non-FLR perturbations. Another advantage of applying these methods to the SuperDARN VLOS data is that we can choose any pair of RGs (along the same beam) with different distances, and thus can identify what distance is the best to identify the FLR. This distance reflects the resonance width, which is an important quantity reflecting the diffusion and dissipation of the FLR energy.
We are now developing an all-in-one IDL code which unifies the above-stated set of codes and is applied to VLOS data of all the beams of a radar at once. The code needs to automatically distinguish whether the identified FLR was in the ionospheric backscattered signal or in the ground/sea backscattered signal; for the latter, the code needs to find the ionospheric reflection point, which is the actual location of the observed FLR. We have implemented these features and tested them for a few events in which FLR was simultaneously identified at a few ground/sea-backscattered points and at a few ionosphere-backscattered points; we have found that the ionospheric reflection points of the ground/sea backscatters tend to be located at latitudes near the latitudes of the ionosphere-backscattered points. We have also calculated, for each point, the corresponding magnetospheric equatorial density; we will show and discuss the density distribution at the meeting.