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AN ELECTRON DENSITY PROFILE MODEL FOR THE SOUTH AFRICAN IONOSPHERE Lee-Anne McKinnell Physics Department, Rhodes University, Grahamstown, South Africa.

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Presentation on theme: "AN ELECTRON DENSITY PROFILE MODEL FOR THE SOUTH AFRICAN IONOSPHERE Lee-Anne McKinnell Physics Department, Rhodes University, Grahamstown, South Africa."— Presentation transcript:

1 AN ELECTRON DENSITY PROFILE MODEL FOR THE SOUTH AFRICAN IONOSPHERE Lee-Anne McKinnell Physics Department, Rhodes University, Grahamstown, South Africa Space Physics Group, Hermanus Magnetic Observatory (HMO), Hermanus, South Africa

2 South African Ionosonde Network

3 Neural Networks Training a computer to learn the relationship between a given set of inputs and a corresponding output highly suitable for non-linear relationships Main requirement -- an archived database describing the history of the relationship South African region Grahamstown, n(h) profile data from 1996, characteristics from 1973 Louisvale & Madimbo, n(h) profile data from 2000

4 SABIM Model South African region Bottomside ionospheric model Electron density profile Several NNs combined Special Features F1 Probability Network Smoothing technique Criterion for optimisation rms error on individual parameters Ability to reproduce realistic profiles

5 Solar Activity

6 SABIM South African Bottomside Ionospheric Model Day Number Solar Activity Hour Magnetic Activity Electron Density Profile Model Geomagnetic position info Neural Network based empirical ionospheric model for the South African region

7 E layer Profile Is E layer predictable? E limits NN Predict E layer foE, hmE, E profile NNs Determining the probability of an F1 layer F1 Probability NN Output determines 1) or 2) or 3) 1) No F1 layer F2NN 2) F1 layer definite F1F2NN 3) F1 layer in L condition L Algorithm Smoothing Technique The Model F layer Profile F2 Layer Network Included Peak parameters – foF2, hmF2 Chebyshev coefficients Profile constructed foF2 – global foF2 network used F1 Layer Network Included Peak parameters – foF1, hmF1 Chebyshev coefficients Profile constructed L-algorithm, weighted avg btn F1 and No F1

8 Diurnal foF2 variations

9 foF1 variations h00 UT foF1

10 h00 UT foE foE variations

11 Predicted profiles

12 foE hmE foF1 hmF1 Summer 10h00 UT Contour Plots

13 foE hmE foF1 hmF1 Winter 10h00 UT Contour Plots

14 foF2 hmF2 Winter Summer

15 F1 Probability

16 Uncertainty

17 Future Plans extend SABIM to include Hermanus data update every 2 years use manually obtained F1 information for F1 probability network expand uncertainty network

18


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