Imaging ionospheric inhomogeneities using spaceborne synthetic aperture radar

We present a technique and results of 2-D imaging of Faraday rotation and total electron content using spaceborne L band polarimetric synthetic aperture radar (PolSAR). The results are obtained by processing PolSAR data collected using the Phased Array type L-band Synthetic Aperture Radar (PALSAR) on board the Advanced Land Observation Satellite. Distinguished ionospheric inhomogeneities are captured in 2-D images from space with relatively high resolutions of hundreds of meters to a couple of kilometers in auroral-, middle-, and low-latitude regions. The observed phenomena include aurora-associated ionospheric enhancement arcs, the middle-latitude trough, traveling ionospheric disturbances, and plasma bubbles, as well as ionospheric irregularities. These demonstrate a new capability of spaceborne synthetic aperture radar that will not only provide measurements to correction of ionospheric effects in Earth science imagery but also significantly benefit ionospheric studies

Statistical Analysis of Medium-Scale Traveling Ionospheric Disturbances Over Japan Based on Deep Learning Instance Segmentation

Medium-scale traveling ionospheric disturbances (MSTIDs) are observed as parallelly arrayed wavelike perturbations of Total Electron Content (TEC) in ionospheric F region leading to satellite navigation error and communication signal scintillation. The observation method for MSTIDs, detrended TEC (dTEC) map, summarizes the perturbation component of TEC having the merits of full-time and two-dimensional. However, previous automatic processing methods for dTEC map cannot discriminate MSTIDs from other irregular ionospheric perturbations intelligently. With the development of artificial intelligence in recent years, deep learning approach is expecting to clarify the controversy of MSTID external dependence (season and solar/geomagnetic activity) under debating for decades. Therefore, this research proposes a real-time processing algorithm for dTEC maps based on Mask Region-Convolutional Neural Network (R-CNN) model of deep learning instance segmentation to detect wavelike perturbations intelligently with an accuracy of about 80% and a processing speed of about 8 fps. Then isolated perturbations are eliminated and only MSTID waveforms are chosen to obtain statistical characteristics of MSTIDs. With this algorithm, we analyzed up to 1, 209, 600 dTEC maps from 1997 to 2019 over Japan automatically and established a database of hourly averaged MSTID characteristics. This research introduces the partial correlation coefficient for the first time to clarify the solar/geomagnetic activity dependence of MSTID characteristics which is independent with each other

Assessment of the capabilities and applicability of ionospheric perturbation indices provided in Europe

© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/Perturbations in the ionosphere are of great interest not only for scientific research, but also for applications using transionospheric radiosignals (e.g. GNSS applications and HF communication), because the transmission of radiosignals is sensitive to the electron density in the ionosphere. However, ionospheric perturbations have manifold character. Their spatial range can vary between global and very local effects (a few hundreds of km range) and their temporal range varies between seconds and days. All these perturbations have different physical background and different impact on applications. Many ionosphere perturbation indices that characterize the state of ionospheric perturbations have been introduced in the past (e.g. ROTI, S4, , AATR, Reff, W-index, SISTED, SOLERA, DIXSG, IBI, Dfu/Dfl, etc.). This manuscript is an assessment of a subset of diverse ionospheric indices developed and/or applied in Europe. It describes the objectives of the indices, demonstrates their character in a case study for September 2017, indicates their applicability for different use cases in science and industry and guides users to find the appropriate index for their purposes.Peer ReviewedPostprint (published version

Identification of potential precursors for the occurrence of Large-Scale Traveling Ionospheric Disturbances in a case study during September 2017

Traveling Ionospheric Disturbances (TIDs) reflect changes in the ionospheric electron density which are caused by atmospheric gravity waves. These changes in the electron density impact the functionality of different applications such as precise navigation and high-frequency geolocation. The Horizon 2020 project TechTIDE establishes a warning system for the occurrence of TIDs with the motivation to mitigate their impact on communication and navigation applications. This requires the identification of appropriate indicators for the generation of TIDs and for this purpose we investigate potential precursors for the TID occurrence. This paper presents a case study of the double main phase geomagnetic storm, starting from the night of 7th September and lasting until the end of 8th September 2017. Detrended Total Electron Content (TEC) derived from Global Navigation Satellite System (GNSS) measurements from more than 880 ground stations in Europe was used to identify the occurrence of different types of large scale traveling ionospheric disturbances (LSTIDs) propagating over the European sector. In this case study, LSTIDs were observed more frequently and with higher amplitude during periods of enhanced auroral activity, as indicated by increased electrojet index (IE) from the International Monitor for Auroral Geomagnetic Effects (IMAGE). Our investigation suggests that Joule heating due to the dissipation of Pedersen currents is the main contributor to the excitation of the observed LSTIDs. We observe that the LSTIDs are excited predominantly after strong ionospheric perturbations at high-latitudes. Ionospheric parameters including TEC gradients, the Along Arc TEC Rate (AATR) index and the Rate Of change of TEC index (ROTI) have been analysed for their suitability to serve as a precursor for LSTID occurrence in mid-latitude Europe, aiming for near real-time indication and warning of LSTID activity. The results of the presented case study suggest that the AATR index and TEC gradients are promising candidates for near real-time indication and warning of the LSTIDs occurrence in mid-latitude Europe since they have a close relation to the source mechanisms of LSTIDs during periods of increased auroral activity