Alexander V. Kozlov

Exploring Digisonde Ionogram Data with SAO-X and DIDBase

A comprehensive suite of software tools for ionogram data analysis and archiving has been developed at UMLCAR to support the exploration of raw and processed data from the worldwide network of digisondes in a low-latency, user-friendly environment. Paired with the remotely accessible Digital Ionogram Data Base (DIDBase), the SAO Explorer software serves as an example of how an academic institution conscientiously manages its resident data archive while local experts continue to work on design of new and improved data products, all in the name of free public access to the full roster of acquired ionospheric sounding data.

The ARTIST 5

Version 5 of the Automatic Real-Time Ionogram Scaler with True height (ARTIST), an intelligent system developed at UMLCAR for extraction of ionospheric specification data from Digisonde ionograms, entered its operational phase in May 2007. Version 5 implements the classic ARTIST techniques re-vamped for modern computers and programming environments, as well as new approaches developed to strengthen the ARTIST performance. This paper describes progress in the ionogram autoscaling research at UMLCAR that has culminated into release of the ARTIST 5 software.

Advancing Digisonde Technology: the DPS-4D

A new ionosonde, the Digisonde model DPS-4D, replaces the aging DPS-4. Faster computer hardware and operating systems together with digital transmitters/receivers provide unprecedented measurement flexibility, data precision, and signal processing gain. The novel features in this latest Digisonde are discussed and explained.

Digisonde Drift Analysis Software

This paper introduces a newly developed conceptual Java-based software package for the digisonde drift data analysis and visualization. This package replaced the less versatile Fortran-based applications previously developed at UMLCAR. A dedicated database intended for raw and processed drift data storage, access, and exchange has also been established and is described in this paper.

Intelligent Resident Archive for RPI Level 2 Data

A resident archive for Level 2 dataset (derived and expert-annotated products) of the radio plasma imager (RPI) on NASA IMAGE spacecraft has been operated at UMLCAR since 2001. The archive provides a much needed, publicly available annotation service for the voluminous collection of RPI data whose interpretations become available to the wave instrument community. Both human and automatically generated annotations are stored in the database server at UMLCAR, remotely accessible over the Internet for both data retrieval and submission of the annotations. Available annotations can be used for the content-based data retrieval of only relevant measurements by non-expert users. The paper discusses implementation details of the Level 2 interactive data archive.

Pilot Ionosonde Network for Identification of Traveling Ionospheric Disturbances

Travelling Ionospheric Disturbances (TIDs) are the ionospheric signatures of atmospheric gravity waves (AGWs). Their identification and tracking is important because the TIDs affect all services that rely on predictable ionospheric radio wave propagation. Although various techniques have been proposed to measure TID characteristics, their real-time implementation still has several difficulties. In this contribution, we present a new technique, based on the analysis of oblique Digisonde-to-Digisonde (D2D) “skymap” observations, to directly identify TIDs and specify the TID wave parameters based on the measurement of angle-of-arrival, Doppler frequency, and time-of-flight of ionospherically reflected high-frequency (HF) radio pulses. The technique has been implemented for the first time for the Net-TIDE project with data streaming from the network of European Digisonde DPS4D observatories. The performance is demonstrated during a period of moderate auroral activity, assessing its consistency with independent measurements such as data from auroral magnetometers and electron density perturbations from Digisondes and GNSS stations. Given that the different types of measurements used for this assessment were not made at exactly the same time and location, and that there was insufficient coverage in the area between the AGW sources and the measurement locations, we can only consider our interpretation as plausible and indicative for the reliability of the extracted TID characteristics. In the framework of the new TechTIDE project (European Commission H2020), a retrospective analysis of the Net-TIDE results in comparison with those extracted from GNSS TEC-based methodologies is currently being attempted, and the results will be the objective of a follow up paper.

GAMBIT database and explorer

The Global Assimilative Modeling of Bottomside Ionospheric Timelines (GAMBIT) is a recent addition to the Global Ionosphere Radio Observatory (GIRO) Internet-accessible data resources provided for public access by the Lowell GIRO Data Center (LGDC). The GAMBIT Database is an online retrospective repository of records that are computed in real-time every 15 minutes by the IRI-based Real-Time Assimilating Mapping (IRTAM) algorithms. The IRTAM morphs the empirical “climatology” IRI model into agreement with the GIRO measurements, so that the new model representations of the ionosphere closely follow its “weather” variability. These ionospheric weather timelines can be acquired from LGDC-operated GAMBIT in their compact form of expansion coefficients for visualization and applications. New GAMBIT Explorer software is available for further analysis. The GAMBIT Explorer uses NASA WorldWind libraries to build an interactive environment with a variety of representations of 2D global surfaces of the IRTAM-computed characteristics, currently foF2 and hmF2, on the Earths projections. A suite of tools is available for validation of the IRTAM results obtained by using partial or complete input GIRO data sets, and by comparisons with coincident global GNSS TEC maps acquired from the MIT Madrigal repository.

Intelligent Image Prospecting System for Image/RPI Mission

The radio plasma imager (RPI) onboard NASAs IMAGE spacecraft has acquired over 1.2 million plasmagrams, images of remote sensing of the Earths magnetosphere. Plasmagram archive is a classic-example dataset posing unrealistic demands of manual labor in order to analyze each collected image for useful features. We present an intelligent data prospecting system based on a bio-plausible model of the pre-attentive vision whose purpose is to draw attention of human analysts to the most interesting data. Presence of weak signatures in the RPI plasmagrams makes this dataset an excellent testbed for sensitive image prospecting techniques. We discuss our progress to date.