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Abstract Continuous wave signals from a network of high frequency (HF) beacons in Peru and other instruments are used to reconstruct the regional ionospheric electron number density in the volume surrounding the network. The continuous wave (CW) HF signals employ binary phase codes with pseudorandom noise (PRN) encoding, and the observables include propagation time or pseudorange, Doppler shift or beat carrier phase, and amplitude. A forward model based on geometric optics in an inhomogeneous, anisotropic, lossy plasma is used to relate plasma number density to the observables. Plasma number density is parametrized in terms of a modified Chapman profile in the vertical and biquintic B‐splines in the horizontal. Sensitivity analysis is required both to model the ray amplitudes and to solve the two‐point boundary problem for each ray. Sensitivity analysis is performed here using reverse‐mode automatic differentiation. In particular, we use an LLVM compiler (Clang), the corresponding OpenMP library, and the Enzyme Automatic Differentiation Framework plugin to compute the sensitivity (gradients) of ray endpoints with respect to their initial bearings. The resulting algorithm exhibits no performance penalty compared to variational sensitivity analysis and is far simpler to implement. 

Abstract The numerical forecast methods used to predict ionospheric convective plasma instabilities associated with Equatorial Spread‐F(ESF) have limited accuracy and are often computationally expensive. We test whether it is possible to bypass first‐principle numeric simulations and forecast irregularities using machine learning models. The data are obtained from the incoherent scatter radar at the Jicamarca Radio Observatory located in Lima, Peru. Our models map vertical plasma drifts, time, and solar activity to the occurrence and location of clusters of echoes telltale of ionospheric irregularities. Our results show that these models are capable of identifying the predictive power of the tested inputs, obtaining accuracies around 75%. 

Abstract Aperture‐synthesis images of ionospheric irregularities in the equatorial electrojet are computed using multiple‐input multiple‐output (MIMO) radar methods at the Jicamarca Radio Observatory. MIMO methods increase the number of distinct interferometry baselines available for imaging (by a factor of essentially three in these experiments) as well as the overall size of the synthetic aperture. The particular method employed here involves time‐division multiplexing or time diversity to distinguish pulses transmitted from different quarters of the Jicamarca array. The method comes at the cost of a large increase in computation time and complexity and a reduced signal‐to‐noise ratio. We discuss the details involved in the signal processing and the trade space involved in image optimization. 

Abstract We investigate the mechanism underlying lower hybrid waves associated with high altitude echoes recently detected in the post‐sunset equatorial topside ionosphere and inner plasmasphere by the Jicamarca VHF radar. These waves are visible as prominent sidebands in the echo Doppler spectra. New experimental results and newly processed incoherent scatter radar (ISR) datasets are presented that provide clues as to the conditions in which the echoes and associated waves occur. Numerical simulations are presented which demonstrate the feasibility of an inverse energy cascade coupled with a short wavelength instability, that is, the lower hybrid drift instability, in explaining the waves. An inverse cascade is required for short wavelength lower hybrid waves to extend to the 3 m wavelengths measured by the Jicamarca radar. The simulations were able to reproduce some features of the measurements including the lower hybrid sidebands at 3 m wavelengths, asymmetry in the sidebands, and the damping effect of higher densities and lower altitudes. 

A three-dimensional, regional simulation is used to investigate ionospheric plasma density irregularities associated with Equatorial Spread F. This simulation is first driven with background electric fields derived from ISR observations. Next, the simulation is driven with electric fields taken from the WAM-IPE global model. The discrepancies between the two electric fields, particularly in the evening prereversal enhancement, produce disagreeing simulation results. The WAM-IPE electric fields are then studied through a simple sensitivity analysis of a field-line integrated electrodynamics model similar to the one used in WAM-IPE. This analysis suggests there is no simple tuning of ion composition or neutral winds that accurately reproduce ISR-observed electric fields on a day-to-day basis. Additionally, the persistency of the prereversal enhancement structure over time is studied and compared to measurements from the ICON satellite. These results suggest that WAM-IPE electric fields generally have a shorter and more variable correlation time than those measured by ICON.