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Abstract Numerical forecasts of plasma convective instability in the postsunset equatorial ionosphere are made based on data from the Ionospheric Connections Explorer satellite (ICON) following the method outlined in a previous study. Data are selected from pairs of successive orbits. Data from the first orbit in the pair are used to initialize and force a numerical forecast simulation, and data from the second orbit are used to validate the results 104 min later. Data from the IVM plasma density and drifts instrument and the MIGHTI red‐line thermospheric winds instrument are used to force the forecast model. Thirteen (16) data set pairs from August (October), 2022, are considered. Forecasts produced one false negative in August and another false negative in October. Possible causes of forecast discrepancies are evaluated including the failure to initialize the numerical simulations with electron density profiles measured concurrently. Volume emission 135.6‐nm OI profiles from the Far Ultraviolet (FUV) instrument on ICON are considered in the evaluation. 

Abstract 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.