Solar Radio Brightenings and Dimmings from 37 GHz Ra- dio Maps Since 1996

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Journal ISSN

Volume Title

Sähkötekniikan korkeakoulu | Master's thesis

Date

2020-06-15

Department

Major/Subject

Space Science and Technology

Mcode

ELEC3039

Degree programme

Master’s Programme in Electronics and Nanotechnology (TS2013)

Language

en

Pages

117 + 9

Series

Abstract

Solar radio observations have been recorded over the last few decades and it has become crucial to automate the image processing and feature detection pipeline. Metsähovi Radio Observatory has recorded solar radio observations for nearly 40 years. Such a long span of solar radio dataset is quite a rare and will produce unique information on the solar radio disturbances when analysed thoroughly with modern artificial intelligence methods. In this thesis, an end-to-end process has been developed which includes clas- sification, processing and analysis of the solar radio maps observed at 37 GHz from January 1996 to December 2018. We generated solar radio maps out of the raw observations, detected different solar bright or quiet features, com- pared the features with other solar datasets and finally produced long term quantitative and morphology analysis of the detected features. Analysis with different available methods for interpolation, thresholding, clustering gave a better idea about the dataset itself as well as about the effectiveness of the processing techniques. Supervised classification for removal of cloud affected observations helped improving the algorithms. Active regions and coronal mass ejections were found to be easily detectable around the limb in Metsähovi observations. Radio brightenings were observed not only at same locations as active regions, but in addition, at high latitudes. Enhanced brightness in the polar region confirmed the earlier claims about polar cap brightening in mm-wavelength observations. The complex magnetic regions were found to produce the most intense radio brightenings.

Description

Supervisor

Tanskanen, Eija

Thesis advisor

Nikbaksh, Shabnam
Kallunki, Juha

Keywords

radio, sun, feature, detection, classification, analysis

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