Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere (SIGMA) II: Inverse modeling with high‐latitude observations to deduce irregularity physics. Issue 9 (28th September 2016) - Deshpande, K. B.; Bust, G. S.; Clauer, C. R.; Scales, W. A.; Frissell, N. A.; Ruohoniemi, J. M.; Spogli, L.; Mitchell, C.; Weatherwax, A. T.
Abstract: Ionospheric scintillation is caused by irregularities in the ionospheric electron density. The characterization of ionospheric irregularities is important to further our understanding of the underlying physics. Our goal is to characterize the intermediate (0.1–10 km) to medium (10–100 km) scale high‐latitude irregularities which are likely to produce these scintillations. In this paper, we characterize irregularities observed by Global Navigation Satellite System (GNSS) during a geomagnetically active period on 9 March 2012. For this purpose, along with the measurements, we are using the recently developed model: "Satellite‐beacon Ionospheric‐scintillation Global Model of the upper Atmosphere" (SIGMA). The model is particularly applicable at high latitudes as it accounts for the complicated geometry of the magnetic field lines in these regions and is presented in an earlier paper. We use an inverse modeling technique to derive irregularity parameters by comparing the high rate (50 Hz) GNSS observations to the modeled outputs. In this investigation, we consider experimental observations from both the northern and southern high latitudes. The results include predominance of phase scintillations compared to amplitude scintillations that imply the presence of larger‐scale irregularities of sizes above the Fresnel scale at GPS frequencies, and the spectral index ranges from 2.4 to 4.2 and the RMS number density ranges from 3e11 to 2.3e12 el/m 3 . The best fits we obtained from our inverse method that considers only weak scattering mostly agree with the observations. Finally, we suggest some improvements in order to facilitate the possibility of accomplishing a unique solution to such inverse problems. Key Points: We characterize high‐latitude irregularities using GPS data, SIGMA model, and an inverse method Phase scintillations as high rate GPS data at multiple polar locations across the Arctic and Antarctic are both measured and modeled Spectral indices we found for F region irregularities are as expected for 3‐D spectra indicated that inverse modeling approach is valid