PCA-MRM model to forecast TEC at middle latitudes

TL;DR

This paper presents a PCA-MRM model that forecasts TEC over the Iberian Peninsula using principal component analysis and multiple linear regression with space weather parameters, achieving good accuracy during quiet periods.

Contribution

The study introduces a PCA-MRM approach combining PCA and regression with space weather data to improve TEC forecasting at middle latitudes.

Findings

Model performs well during quiet days with MAE around 3 TECu.

Performance deteriorates during geomagnetic storms, with errors up to 13 TECu.

Daytime errors are higher than nighttime during disturbed periods.

Abstract

The total electron content (TEC) over the Iberian Peninsula was modelled using PCA-MRM models based on decomposition of the observed TEC series using the principal component analysis (PCA) and reconstruction of the daily modes amplitudes by a multiple linear regression model (MRM) using space weather parameters as regressors. The following space weather parameters are used: proxies for the solar UV and XR fluxes, number of the solar flares of different classes, parameters of the solar wind and of the interplanetary magnetic field, and geomagnetic indices. Time lags of 1 and 2 days between the TEC and space weather parameters are used. The performance of the PCA-MRM model is tested using data for 2015, both geomagnetically quiet and disturbed periods. The model performs well for quiet days and days with solar flares but without geomagnetic disturbances. The MAE and RMSE metrics are of the order of 3-3.5 TECu for daytime and about 2 TECu for night-time. During geomagnetically disturbed periods the performance of the model deteriorates but only for daytime: MAE and RMSE are of the order of 4.5-5.8 TECu and can rise to about 13 TECu for the strongest geomagnetic storms.