The Canary Island Long-Baseline Observatory (CILBO) is a double-station meteor camera setup located on the Canary Islands operated by ESA's Meteor Research Group since 2010. Observations of meteors are obtained in the visual wavelength band by intensified video cameras from both stations, supplemented by an intensified video camera mounted with a spectral grating at one of the locations. The cameras observe during cloudless and precipitation-free nights, and data are transferred to a main computer located at ESA/ESTEC once a day. The image frames that contain spectral information are calibrated, corrected, and finally processed into line intensity profiles. An ablation simulation, based on Bayesian statistics using a Markov chain Monte Carlo method, allows determining a parameter space, including the ablation temperatures, chemical elements, and their corresponding line intensities, to fit against the line intensity profiles of the observed meteor spectra. The algorithm is presented in this paper and one example is discussed. Several hundred spectra have been processed and made available through the Guest Archive Facility of the Planetary Science Archive of ESA. The data format and metadata are explained.

The study of solar irradiance variability is of great importance in heliophysics, Earth’s climate, and space weather applications. These studies require careful identifying, tracking and monitoring of features in the solar photosphere, chromosphere, and corona. Do coronal bright points contribute to the solar irradiance or its variability as input to the Earth atmosphere? We studied the variability of solar irradiance for a period of 10 years (May 2010 – June 2020) using the Large Yield Radiometer (LYRA), the Sun Watcher using APS and image Processing (SWAP) on board PROBA2, and the Atmospheric Imaging Assembly (AIA), and applied a linear model between the segmented features identified in the EUV images and the solar irradiance measured by LYRA. Based on EUV images from AIA, a spatial possibilistic clustering algorithm (SPoCA) is applied to identify coronal holes (CHs), and a morphological feature detection algorithm is applied to identify active regions (ARs), coronal bright points (BPs), and the quiet Sun (QS). The resulting segmentation maps were then applied on SWAP images, images of all AIA wavelengths, and parameters such as the intensity, fractional area, and contribution of ARs/CHs/BPs/QS features were computed and compared with LYRA irradiance measurements as a proxy for ultraviolet irradiation incident to the Earth atmosphere. We modeled the relation between the solar disk features (ARs, CHs, BPs, and QS) applied to EUV images against the solar irradiance as measured by LYRA and the F10.7 radio flux. A straightforward linear model was used and corresponding coefficients computed using a Bayesian method, indicating a strong influence of active regions to the EUV irradiance as measured at Earth’s atmosphere. It is concluded that the long- and short-term fluctuations of the active regions drive the EUV signal as measured at Earth’s atmosphere. A significant contribution from the bright points to the LYRA irradiance could not be found.