Technical Reports

s/n	Title	Authors	Description	Date \| DOI
1	Spectral analysis methodology and data requirements	W. Jarmolowski, P. Wielgosz, A. Krypiak-Gregorczyk (UWM)	This document outlines data requirements and methodology of spectral analysis applicable to station-based, model-based and satellite-based ionospheric data. The DISPEC analysis will provide new high-level data applicable in correlation analyses, modeling and other Scientific Data Applications (SDA) tasks. The report includes a very preliminary round of processing with example data, demonstrating spectral analysis workflow. The parameters applied in this demonstration are unadjusted, and the figures have a preview character.	June 2024 \| 10.5281/zenodo.12658002
2	DISPEC filters and quality control development methodology	A. Belehaki (NOA), K. Koutroumbas (NOA), M. Hernandez Pajares (UPC), I. Galkin (BGD)	This document is a report for the methodology proposed to adopt for the development of the DISPEC data filters and quality control procedures. Data filters are specific to each type of data collection. For ionograms, the proposed filters include an improved method for scaling. For the scaled characteristics, the proposed filters include an outlier detection system and data imputation. Regarding the data collected from GNSS receivers, the preprocessing of carrier phase measurements, will be considered in detail, by comparing the different implementations of the main dual-frequency cycle slip detection technique (the Blewitt technique), and also the new Doppler-based cycle-slip detection and correction technique, suitable for mid-cost single-frequency GNSS receivers and reducing the navigation error.	October 2024 \| https://doi.org/10.5281/zenodo.13899613
3	Ionospheric Data Filters: A new method for ionograms scaling	K. Koutroumbas, A. Belehaki, G. Stamatakis (NOA)	The presentation titled "Ionospheric Data Filters: A new method for Ionogram Scaling" (Presented in the DISPEC WP2 Review Meeting, held in July 2025) summarizes the design, development, and validation of an advanced method for automatic ionogram scaling using AI/ML techniques. The core goal is to improve the accuracy and confidence in determining key ionospheric parameters (especially foF2 and hmF2) from Digisonde data. Key points include: Identifying the need to correct ARTIST outputs using hybrid time series and confidence levels. Developing a new DISPEC autoscaling algorithm based on clustering, curve fitting, and feedforward neural networks. Applying this method to detect E, Es, and F layers, and accurately estimate foF2 and hmF2. Evaluating performance on diverse ionospheric conditions, including MSTIDs, multi-reflections, and disturbed periods (e.g., Hunga volcano eruption). Validation showed a deviation from manual scaling of the size of the instrument resolution. Planned improvements include broader station testing, confidence scoring, hybrid time series filtering, and HLDP (High-Level Data Product) derivation.	July 2025 \| https://zenodo.org/records/16595537

s/n

Title

Authors

Description

Date | DOI

Spectral analysis methodology and data requirements

W. Jarmolowski, P. Wielgosz, A. Krypiak-Gregorczyk (UWM)

This document outlines data requirements and methodology of spectral analysis applicable to station-based, model-based and satellite-based ionospheric data. The DISPEC analysis will provide new high-level data applicable in correlation analyses, modeling and other Scientific Data Applications (SDA) tasks. The report includes a very preliminary round of processing with example data, demonstrating spectral analysis workflow. The parameters applied in this demonstration are unadjusted, and the figures have a preview character.

June 2024 | 10.5281/zenodo.12658002

DISPEC filters and quality control development methodology

A. Belehaki (NOA), K. Koutroumbas (NOA), M. Hernandez Pajares (UPC), I. Galkin (BGD)

This document is a report for the methodology proposed to adopt for the development of the DISPEC data filters and quality control procedures. Data filters are specific to each type of data collection. For ionograms, the proposed filters include an improved method for scaling. For the scaled characteristics, the proposed filters include an outlier detection system and data imputation. Regarding the data collected from GNSS receivers, the preprocessing of carrier phase measurements, will be considered in detail, by comparing the different implementations of the main dual-frequency cycle slip detection technique (the Blewitt technique), and also the new Doppler-based cycle-slip detection and correction technique, suitable for mid-cost single-frequency GNSS receivers and reducing the navigation error.

October 2024 | https://doi.org/10.5281/zenodo.13899613

Ionospheric Data Filters: A new method for ionograms scaling

K. Koutroumbas, A. Belehaki, G. Stamatakis (NOA)

The presentation titled "Ionospheric Data Filters: A new method for Ionogram Scaling" (Presented in the DISPEC WP2 Review Meeting, held in July 2025) summarizes the design, development, and validation of an advanced method for automatic ionogram scaling using AI/ML techniques. The core goal is to improve the accuracy and confidence in determining key ionospheric parameters (especially foF2 and hmF2) from Digisonde data. Key points include:

Identifying the need to correct ARTIST outputs using hybrid time series and confidence levels.
Developing a new DISPEC autoscaling algorithm based on clustering, curve fitting, and feedforward neural networks.
Applying this method to detect E, Es, and F layers, and accurately estimate foF2 and hmF2.
Evaluating performance on diverse ionospheric conditions, including MSTIDs, multi-reflections, and disturbed periods (e.g., Hunga volcano eruption).
Validation showed a deviation from manual scaling of the size of the instrument resolution.

Planned improvements include broader station testing, confidence scoring, hybrid time series filtering, and HLDP (High-Level Data Product) derivation.

July 2025 | https://zenodo.org/records/16595537