Search results

(1 - 1 of 1)
GLOBAL ESTIMATION AND ANALYSIS OF IONOSPHERIC DRIVERS WITH A DATA ASSIMILATION ALGORITHM
Title
GLOBAL ESTIMATION AND ANALYSIS OF IONOSPHERIC DRIVERS WITH A DATA ASSIMILATION ALGORITHM
Creator
López Rubio, Aurora
Date
2022
Description
This dissertation studies a data assimilation algorithm that estimates the drivers of the ionosphere-thermosphere (IT) region of the Earth....
Show moreThis dissertation studies a data assimilation algorithm that estimates the drivers of the ionosphere-thermosphere (IT) region of the Earth. The algorithm, EMPIRE (Estimating Model Parameters from Ionospheric Reverse Engineering) can estimate 2 main drivers of the ionospheric behavior: neutral winds and electric potential by ingesting mainly ionospheric densities obtained through Global Satellite System (GNSS) measurements. Additionally, the algorithm can ingest FPI (Fabry-Perot interferometer) neutral wind measurements. The contributions include 1) Vector spherical harmonic basis function for neutral wind estimation, 2) Quantification of the representation error of the estimations of the algorithm EMPIRE, 3) Analysis of Nighttime Ionospheric Localized density Enhancement (NILE) events and 4) Ingestion of global ICON (Ionospheric Connection Explorer) neutral winds measurements. The IT region in the atmosphere is characterized by having a large concentration of free ions and electrons, electromagnetic radiation and Earth's magnetic field. The behavior of the region is dominated by the solar activity, that ionizes the free electrons of the region, forming ionospheric plasma and determining its density. Unusual solar activity or any atmospheric disturbance affects the distribution of the ionospheric plasma and the behavior of the IT region. The redistribution of the ionospheric density impacts technology widely used such as telecommunication or satellite navigation, so it is increasingly important to study the IT system response. The IT behavior can be characterized by what drives its changes. Two drivers that play a key role, the ones we focus on this dissertation, are electric potential, that directly affects the charged ions in the system, and neutral winds, that refers to the velocity of the neutral particles that form the thermosphere. To quantify these drivers, measurements and climate models are available. Measurements are limited as the IT region is vast and covers the entire globe. Climate models can provide information in all the region, but they are usually not as reliable during the unusual solar activity conditions or disturbances. In this dissertation we use a data assimilation algorithm, EMPIRE, that combines both sources of data, measurements and models, to estimate the IT drivers, neutral winds and electric potential. EMPIRE ingests measurements of the plasma density rate and models the physics of the region with the ion continuity equation. The drivers are represented with basis functions and their coefficients are estimated by fitting the expansions with a Kalman filter. In previous work and use of the algorithm, the neutral winds were expanded using power series basis function for each of the components of the vector. The first contribution of the dissertation is to use a vector spherical harmonic expansion to describe the winds, allowing a continuous expansion around the globe and self-consistent components of the vector. Before, EMPIRE estimated the correction of the drivers with respect climate model values. In this work, EMPIRE is also modified to directly estimate the drivers. Then, a study of the representation error, which is the discrepancy between the true physics and the discrete model that represents the physics of EMPIRE and its quantification is done. Next, EMPIRE is used to analyze two NILE events, using the global estimation of both winds, from the first contribution, and the electric potential, derived in previous work. Finally, global estimation of winds allows us to implement the ingestion of ICON global winds in EMPIRE, in addition to the plasma density rate measurements.
Show less