Browsing by Author "Rojas, E."

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    Mapping irregularities in the postsunset equatorial ionosphere with an expanded network of HF beacons
    (American Geophysical Union, 2021-07) Hysell, D. L.; Rojas, E.; Goldberg, H.; Milla, Marco; Kuyeng, K.; Valdez, A.; Morton, Y. T.; Bourne, H.
    Data from a network of high-frequency (HF) beacons deployed in Peru are used to estimate the regional ionospheric electron density in a volume. Pseudorange, accumulated carrier phase, and signal power measurements for each of the 36 ray paths provided by the network at a 1 min cadence are incorporated in the estimates. Additional data from the Jicamarca incoherent scatter radar, the Jicamarca sounder, and GPS receivers can also be incorporated. The electron density model is estimated as the solution to a global optimization problem that uses ray tracing in the forward model. The electron density is parametrized in terms of B-splines in the horizontal direction and generalized Chapman functions or related functions in the vertical. Variational sensitivity analysis has been added to the method to allow for the utilization of the signal power observable which gives additional information about the morphology of the bottomside F region as well as absorption including absorption in the D and E regions. The goal of the effort is to provide contextual information for improving numerical forecasts of plasma interchange instabilities in the postsunset F region ionosphere associated with equatorial spread F (ESF). Data from two ESF campaigns are presented. In one experiment, the HF data revealed the presence of a large-scale bottomside deformation that seems to have led to instability under otherwise inauspicious conditions. In another experiment, gradual variations in HF signal power were found to be related to the varying shape of the bottomside F layer.
    Palabras clave:BeaconElectron densityEquatorial ionosphere
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    Modeling ionograms with deep neural networks: applications to foF2 forecasting
    (Instituto Geofísico del Perú, 2021-06) Aricoché, J.; Rojas, E.; Milla, Marco
    The ionosphere state parameters are of fundamental importance not only for radio communication but also for space weather. As most of the space phenomena, the dynamics are governed by nonlinear processes that make forecasts a challenging endeavor. We now have available enormous datasets and ubiquitous experimental sources that can help us finding the intricate regularities in these phenomena. In this work, we will focus on the forecasting of some parameters of the steady-state low latitude ionosphere. We used ionograms from Jicamarca Radio Observatory digisonde to train two neural networks. We produced forecasts of ionospheric parameters such as virtual heights and foF2 taking into consideration ionogram characteristics. These estimations were compared to the corresponding values obtained from the digisonde, the persistence model, and foF2 values obtained from the International reference ionosphere.
    Palabras clave:IonogramsNeural networksfoF2