It is of great interest and importance to study the variabilities of solar EUV, UV and X-ray irradiance in heliophysics, in Earth's climate, and space weather applications. A careful study is required to identify, track, monitor and segment the different coronal features such as active regions (ARs), coronal holes (CHs), the background regions (BGs) and the X-ray bright points (XBPs) from spatially resolved full-disk images of the Sun. Variability of solar soft X-ray irradiance is studied for a period of 13 years (February 2007-March 2020, covers Solar Cycle 24), using the X-Ray Telescope on board the Hinode (Hinode/XRT) and GOES (1 -8 Å). The full-disk X-ray images observed in Al_mesh filter from XRT are used, for the first time, to understand the solar X-ray irradiance variability measured, Sun as a star, by GOES instrument. An algorithm in Python has been developed and applied to identify and segment coronal X-ray features (ARs, CHs, BGs, and XBPs) from the full-disk soft X-ray observations of Hinode/XRT. The segmentation process has been carried out automatically based on the intensity level, morphology and sizes of the X-ray features. The total intensity, area, and contribution of ARs/CHs/BGs/XBPs features were estimated and compared with the full-disk integrated intensity (FDI) and GOES (1 -8 Å) X-ray irradiance measurements. The XBPs have been identified and counted automatically over the full disk to investigate their relation to solar magnetic cycle. The total R. Kariyappa
Corona is the outermost layer of the Sun, which extends to several thousand kilometers from the visible photosphere. It is made up of very tenuous plasma but is very hot. The sudden increase of temperature in the coronal layer from the underlying chromosphere and photosphere makes it very interesting. The average temperature of a corona is measured about 2 MK, and it may show a large variation in temperature with respect to different surface features. Studying the variation of the temperature of the full-disk corona and of individual feature’s temperature along with the solar cycle will be interesting and important to understand the Physics of the Sun. Although an attempt has been made earlier to measure the temperature of coronal XBPs for a short period with high cadence of observations in localized regions, but the variation in temperature of the full-disk image and of individual features over the solar cycle is not measured yet. Since Hinode/XRT allows capturing images of the Sun in 8 different filters, it has got a unique feature that, using 2 different filters, the temperature map of the Sun can be generated. In order to study the temperature variations, we have used Al mesh and Ti poly filters of full-disk composite, level-2, X-ray images of the Sun obtained from Hin- ode/XRT. We developed a sophisticated python algorithm to segment different coronal features (ARs, CHs, BGs, & XBPs), derived the integrated intensity of all the features in both the filters, and generated the temperature maps of the corona using the filter ratio method. Because of the XRT straylight issue and unavailability of a good pair of images we have restricted our analysis for the period of 4 years (February 01, 2008 - May 08, 2012, covering the starting part of the solar cycle 24). In this paper, the first analysis in using direct energy values of the coronal features from segmented solar disk and its relation to solar activity is presented. We have discussed the variations of the temperature of a full-disk corona, and of all the features (ARs, CHs, BGs & XBPs).We found from the time series plots of the average temperature of the full-disk and of all the features show temperature fluctuations and they vary in phase with the sunspot numbers (solar activity). Although the temperature of all the features varies but the mean temperature estimated for the whole observed period of the full-disk is around 1.39 ± 0.28 MK and active regions (ARs) will be around 1.98 ± 0.44 MK, whereas BGs, CHs & XBPs are 1.37 ± 0.26 MK, 1.34 ± 0.33 MK, and 1.52± 0.34 MK respectively. In addition, we found that the mean temperature contribution estimated of the background regions (BG) will be around 91 %, whereas ARs, CHs, & XBPs are 5 %, 2 % and 2 % respectively to the average coronal temperature of the full-disk for the period: 2008-2012. The temperature values and their variations of all the features suggest that the features show a high variability in their temperature and that the heating rate of the emission features may be highly variable on solar cycle timescales. It is clear from the analysis that the filter ratio method can be directly used for temperature analysis of coronal features and to study their surface temperature variability as a function of solar magnetic activity.
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