Yes / The variation of solar irradiance is one of the natural forcing mechanisms of the terrestrial climate. Hence, the time-dependent
solar irradiance is an important input parameter for climate modelling. The solar surface magnetic field is a powerful proxy for
solar irradiance reconstruction. The analyses of data obtained with the Michelson Doppler Imager (MDI) on board the SOHO
mission are therefore useful for the identification of solar surface magnetic features to be used in solar irradiance reconstruction
models. However, there is still a need for automated technologies that would enable the identification of solar activity features
from large databases. To achieve this we present a series of enhanced segmentation algorithms developed to detect and calculate
the area coverages of specific magnetic features from MDI intensitygrams and magnetograms. These algorithms are part of the
Automated Solar Activity Prediction (ASAP) tool. The segmentation algorithms allow us to identify the areas on the solar disk
covered by magnetic elements inside and outside boundaries of active regions. Depending on their contrast properties, magnetic
features within an active region boundary are classified as sunspot umbra and penumbra, or faculae. Outside an active region
boundary magnetic elements are identified as network. We present the detailed steps involved in the segmentation process and
provide the area coverages of the segmented MDI intensitygrams and magnetograms. The feature segmentation was carried
out on daily intensitygrams and magnetograms from April 21, 1996 to April 11, 2011. This offers an exciting opportunity to
undertake further investigations that benefit from solar features segmentations, such as solar irradiance reconstruction, which
we plan to investigate in the future.
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/7580 |
| Date | 05 May 2015 |
| Creators | Ashamari, Omar, Qahwaji, Rami S.R., Ispon, Stanley S., Schöll, M., Nibouche, O., Haberreiter, M. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Article, published version paper |
| Rights | (c) 2015 Ashmari, O et al. CC-BY. |
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