Comparison of Independent Feature Recognition Method for Time Series Analysis of Irradiance Variations Based on Statistical Feature Recognition

Solar total and UV irradiances have been observed over three decades, and recently spectral irradiance data are available from the Solar Irradiance Monitor (SIM) on the SORCE Mission. Results of these measurements show that irradiance varies on various time scales from minutes to decades. To better understand the origin of irradiance changes, we need to use spatially resolved data rather than full disk indices. For this purpose various automated image processing and analyses techniques have been developed. Using these image processing techniques, we separated quiet-sun, network, faculae and sunspots. On one hand, we compare the area data of these features derived from various images to validate results and discuss future efforts needed to coordinate efforts between various groups working on image analysis. Another goal is to compare the variations of the identified features with total solar and UV irradiances to establish to what degree

the identified images explain short and long-term irradiance variations.