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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%.

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.

Artificial periodic inhomogeneity or API experiments were conducted at the HAARP facility in Gakona, Alaska, in October 2022. The experiments concentrated on measuring ionospheric irregularities induced in theE‐region. The irregularities exhibited characteristics regarding their occurrence altitudes, rise and fall times, and Doppler shifts comparable to results from experiments conducted previously at HAARP and elsewhere. The irregularities also occurred in discrete altitude bands. Seeking to quantify these results, we constructed a simple, one‐dimensional fluid model which includes the effects of HF wave heating (direct and indirect) together with electron and ion cooling and thermal conduction, ion production, loss, and diffusion. Critically, the model includes a potential solver and can represent the ambipolar electric field. The model produced API irregularities in three distinct altitude bands which decayed according to the ambipolar diffusion rate.

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.

Measurements from the Ionospheric Connections Explorer satellite (ICON) form the basis of direct numerical forecast simulations of plasma convective instability in the postsunset equatorialFregion ionosphere. ICON data are selected and used to initialize and force the simulations and then to test the results one orbit later when the satellite revisits the same longitude. Data from the IVM plasma density and drifts instrument and the MIGHTI red‐line thermospheric winds instrument are used to force the simulation. Data from IVM are also used to test for irregularities (electrically polarized plasma depletions). Fourteen datasets from late March 2022, were examined. The simulations correctly predicted the occurrence or non‐occurrence of irregularities 12 times while producing one false positive and one false negative. This demonstrates that the important telltales of instability are present in the ICON state variables and that the important mechanisms for irregularity formation are captured by the simulation code. Possible refinements to the forecast strategy are discussed.

This paper uses a regional simulation of plasma convective instability in the postsunset equatorial ionosphere together with a global atmosphere/ionosphere/plasmasphere GCM (WAM‐IPE) to forecast irregularities associated with equatorial spreadF(ESF) for 1–2 hr after sunset. First, the regional simulation is initialized and forced using ionosphere state parameters derived from campaign data from the Jicamarca Radio Observatory and from empirical models. The irregularities produced by these simulations are found to be quantitatively similar to those observed. Next, the aforementioned state parameters are replaced with parameters from WAM‐IPE, and the resulting departures between the simulated and observed irregularities are noted. In one of five cases, the forecast failed to accurately predict ESF irregularities due to the late reversal of the zonal thermospheric winds. In four of five cases, significant differences between the observed and predicted prereversal enhancement (PRE) of the background vertical drifts resulted in degraded forecast accuracy. This highlights the need for improved PRE forecasting in the global‐scale model.

We present measurements of the equatorial topside ionosphere above Jicamarca made during extremely low solar flux conditions during the deep solar minimum of 2019–2020. Measurements were made in October, 2019, February, 2020, and September, 2020. The main features observed are a large and extended decrease in noontime temperatures unlike that seen in studies at moderate solar flux levels, predawn ionospheric heating as early as 0300 LT, large day‐to‐day variability in the O⁺/H⁺transition height, and negligible helium ion concentration at all altitudes. Data from the Ion Velocity Meter (IVM) instrument onboard the Ionospheric Connection Explorer (ICON) and the Topside Ionospheric Plasma Monitor (SSIES) onboard the Defense Meteorological Satellite Program (DMSP) satellites are used to assess agreement with ISR data and assist with the analysis of the predawn heating phenomena. We also analyze the data in light of the SAMI2‐PE model which shows less agreement with the data than at higher solar flux. The main areas of discrepancy with the data are outlined, such as the absence of significant predawn heating, less pronounced decreases in noontime temperatures, and much higher O⁺fractions at high altitudes, particularly in September. Finally, a sensitivity analysis of the model to various forcing agents such as neutral winds, plasma drifts, solar flux, and heat flow is performed. A discussion is presented on bridging the discrepancies in future model runs. Novel techniques of clutter removal and noise power bias correction are introduced and described in the appendices.