Ionospheric modelling and Data Assimilation

  • Federico Da Dalt

Student thesis: Doctoral ThesisPhD


A New Ionospheric Model (ANIMo) based upon the physics of production, loss, and vertical transport has been developed. The model is driven by estimates of neutral composition, temperature and solar flux and is applicable to the mid-latitude regions of the Earth under quiet and moderate geomagnetic conditions. This model was designed to exhibit specific features that were not easy to find all together in other existing ionospheric models. ANIMo needed to be simple to use and interact with, relatively accurate, reliable, robust and computationally efficient. The definition of these characteristics was mostly driven by the intention to use ANIMo in a Data Assimilation (DA) scheme. DA or data ingestion can be described as a technique where observations and model realizations, called background information, are combined together to achieve a level of accuracy that is higher than the accuracy of the two elements taken separately. In this project ANIMo was developed to provide a robust and reliable background contribution. The observations are given by the Global Positioning System (GPS) ionospheric measurements, collected from several networks of GPS ground-station receivers and are available on on-line repositories. The research benefits from the Multi-Instrument Data Analysis System (MIDAS) [Mitchell and Spencer, 2003; Spencer and Mitchell, 2007], which is an established ionospheric tomography software package that produces three dimensional reconstructions of the ionosphere starting from GPS measurements. Utilizing ANIMo in support of MIDAS has therefore the potential to generate a very stable set-up for monitoring and study the ionosphere. In particular, the model is expected to compensate some of the typical limitations of ionospheric tomography techniques described by Yeh and Raymund [1991] and Raymund et al. [1994]. These are associated with the lack of data due to the uneven distribution of ground-based receivers and limitations to viewing angles. Even in regions of good receiver coverage there is a need to compensate for information on the vertical profile of ionisation. MIDAS and other tomography techniques introduce regularization factors that can assure the achievement of a unique solution in the inversion operation. These issues could be solved by aiding the operation with external information provided by a physical model, like ANIMo, through a data ingestion scheme; this ensures that the contribution is completely independent and there is an effective accuracy improvement. Previously, the limitation in vertical resolution has been solved by applying vertical orthonormal functions based upon empirical models in different ways [Fougere, 1995; Fremouw et al., 1992; Sutton and Na, 1994]. The potential for the application of a physical model, such ANIMo is that it can provide this information according to the current ionospheric conditions. During the project period ANIMo has been developed and incorporated with MIDAS. The result is A New Ionospheric Data Assimilation System (ANIDAS); its name suggests that the system is the implementation of ANIMo in MIDAS. Because ANIDAS is a data ingestion scheme, it has the potential to be used to perform not only more accurate now-casting but also forecasting. The outcomes of ANIDAS at the current time can be used to initialise ANIMo for the next time step and therefore trigger another assimilation turn. In future, it is intended that ANIMo will form the basis to a new system to predict the electron density of the ionosphere – ionospheric forecasting.
Date of Award24 Jun 2015
Original languageEnglish
Awarding Institution
  • University of Bath
SponsorsCEC - Marie Curie
SupervisorCathryn Mitchell (Supervisor) & Nathan Smith (Supervisor)


  • ionosphere
  • ionospheric modelling
  • data assimilation
  • ANIMo

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