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Abstract The prereversal enhancement (PRE) is a brief surge in upward plasma velocity in the evening equatorial ionosphere and a driver of equatorial spread‐F. This study reports the first PRE climatology from Ionospheric Connection Explorer (ICON) data, exhibiting seasonal and longitudinal variability that is qualitatively consistent with results from two previous satellite missions. Previous missions, however, lacked the neutral wind observations to characterize their impact on the PRE. To quantitatively assess wind impacts, numerical experiments are performed with a standalone dynamo solver using winds from the TIEGCM‐ICON, which is driven from below by observed tides. To quantify the impact of solar/magnetic geometry, such as the alignment between the solar terminator and the magnetic meridian, the model was first driven with seasonally and longitudinally averaged winds (which includes seasonally averaged zonal‐mean winds and migrating tides). This reproduces the observed PRE variability with a correlation of 0.44. Incorporating longitudinally and seasonally varying wind patterns improves the correlation to 0.68. This suggests that climatological wind variability is an important driver of PRE variability, but future work is needed to account for the missing variability. Potential missing drivers include conductivity variability near the terminator and mesoscale wind features such as the solar terminator wave.
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Quantifying Uncertainties in the Quiet‐Time Ionosphere‐Thermosphere Using WAM‐IPE
Abstract This study presents a data‐driven approach to quantify uncertainties in the ionosphere‐thermosphere (IT) system due to varying solar wind parameters (drivers) during quiet conditions (Kp < 4) and fixed solar radiation and lower atmospheric conditions representative of 16 March 2013. Ensemble simulations of the coupled Whole Atmosphere Model with Ionosphere Plasmasphere Electrodynamics (WAM‐IPE) driven by synthetic solar wind drivers generated through a multi‐channel variational autoencoder (MCVAE) model are obtained. Applying the polynomial chaos expansion (PCE) technique, it is possible to estimate the means and variances of the QoIs as well as the sensitivities of the QoIs with regard to the drivers. Our results highlight unique features of the IT system's uncertainty: (a) the uncertainty of the IT system is larger during nighttime; (b) the spatial distributions of the uncertainty for electron density and zonal drift at fixed local times present 4 peaks in the evening sector, which are associated with the low‐density regions of longitude structure of electron density; (c) the uncertainty of the equatorial electron density is highly correlated with the uncertainty of the zonal drift, especially in the evening sector, while it is weakly correlated with the vertical drift. A variance‐based global sensitivity analysis suggests that the IMF Bz plays a dominant role in the uncertainty of electron density. A further discussion shows that the uncertainty of the IT system is determined by the magnitudes and universal time variations of solar wind drivers. Its temporal and spatial distribution can be modulated by the average state of the IT system.
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- Award ID(s):
- 2028032
- PAR ID:
- 10541647
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- Space Weather
- Volume:
- 22
- Issue:
- 2
- ISSN:
- 1542-7390
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1029/2023SW003665
