TY - JOUR

T1 - A Model of High Latitude Ionospheric Convection Derived From SuperDARN EOF Model Data

AU - Lam, M. M.

AU - Shore, R. M.

AU - Chisham, G.

AU - Freeman, M. P.

AU - Grocott, A.

AU - Walach, M.‐T.

AU - Orr, L.

PY - 2023/7/31

Y1 - 2023/7/31

N2 - Forecasting of the effects of thermospheric drag on satellites will be improved significantly with better modeling of space weather effects on the high-latitude ionosphere, in particular the Joule heating arising from electric field variability. We use a regression analysis to build a model of the ionospheric convection drift velocity which is driven by relatively few solar and solar wind variables. The model is developed using a solar cycle's worth (1997–2008 inclusive) of 5-min resolution Empirical Orthogonal Function (EOF) patterns derived from Super Dual Auroral Radar Network (SuperDARN) line-of-sight observations of the convection velocity across the high-latitude northern hemisphere ionosphere. At key stages of development of the model, we use the percentage of explained variance P to see how well the model reproduces the EOF data. The final model is driven by four variables: (a) the interplanetary magnetic field component B y, (b) the solar wind coupling parameter epsilon ε, (c) a trigonometric function of day-of-year, and (d) the monthly F 10.7 index. The model can reproduce the EOF velocities with a characteristic P = 0.7. The model and EOF data compare best around the solar maximum of 2001. (Figure presented.) is lower around solar minimum, due to occasional limitations in the geographical and temporal coverage of the SuperDARN measurements. This may indicate the need to modify our model around the minimum of the solar cycle. Our model has the potential to be used to forecast the ionospheric electric field using the real-time solar wind data available from spacecraft located upstream of the Earth.

AB - Forecasting of the effects of thermospheric drag on satellites will be improved significantly with better modeling of space weather effects on the high-latitude ionosphere, in particular the Joule heating arising from electric field variability. We use a regression analysis to build a model of the ionospheric convection drift velocity which is driven by relatively few solar and solar wind variables. The model is developed using a solar cycle's worth (1997–2008 inclusive) of 5-min resolution Empirical Orthogonal Function (EOF) patterns derived from Super Dual Auroral Radar Network (SuperDARN) line-of-sight observations of the convection velocity across the high-latitude northern hemisphere ionosphere. At key stages of development of the model, we use the percentage of explained variance P to see how well the model reproduces the EOF data. The final model is driven by four variables: (a) the interplanetary magnetic field component B y, (b) the solar wind coupling parameter epsilon ε, (c) a trigonometric function of day-of-year, and (d) the monthly F 10.7 index. The model can reproduce the EOF velocities with a characteristic P = 0.7. The model and EOF data compare best around the solar maximum of 2001. (Figure presented.) is lower around solar minimum, due to occasional limitations in the geographical and temporal coverage of the SuperDARN measurements. This may indicate the need to modify our model around the minimum of the solar cycle. Our model has the potential to be used to forecast the ionospheric electric field using the real-time solar wind data available from spacecraft located upstream of the Earth.

KW - ionospheric convection

KW - solar wind‐magnetosphere coupling

KW - operational nowcasting

KW - solar cycle variations

KW - high‐latitude ionosphere

KW - BAS SuperDARN EOF analysis

U2 - 10.1029/2023SW003428

DO - 10.1029/2023SW003428

M3 - Journal article

VL - 21

JO - Space Weather

JF - Space Weather

SN - 1542-7390

IS - 7

M1 - e2023SW003428

ER -