On two approaches to the building of local models for electron density based on Irkutsk digizond data

TL;DR

This paper presents two approaches—descriptional and predictional—for constructing local electron density models based on Irkutsk digisonde data, highlighting the importance of parameter selection and model accuracy over a multi-year period.

Contribution

It introduces a multiranges modulation principle for model parameter extension and compares two modeling approaches using real data, emphasizing the impact of parameter choice on prediction accuracy.

Findings

Prediction accuracy varies from 9% to 23% depending on height.

Increasing height correlates with more model parameters needed.

Non-optimal parameter selection can increase prediction error.

Abstract

In the paper the step-by-step principles for making local model of electron density are described. They are based on modulation principle - electron density dependence on time is a product of a number of temporal variations caused by solar radiation, magnetic activity, Earth orientation and unknown additional periodical processes (not a sum, as they suppose sometimes when making such models). A multiranges modulation principle is also suggested, that allows automatically extend the set of parameters by using new ones, obtained by filtration (or averaging) of basic set of parameters over the time. In the paper we describe two approaches to the model creation - descriptional and predictional ones. To test the approach three different models were created for daily electron density logarithm using the described principles. We have used the data of Irkutsk digisonde over the period 2003-2007 years for testing. It becomes clear that a non-optimal choice of the number of model parameters could increase prediction error, inspite the error over the set, used for analysis, will decrease. It is shown that one year prediction has accuracy about 9-23% depending on the height, and the highest error corresponds to the height about 200km. From the modelling we could also see that with increasing of the height the number of parameters increases, and this could be caused by inaccuracy of the model or by not taking additional physical mechanisms into consideration.