12:00 〜 12:15
[PEM14-09] Statistical study of small solar flares observed with Nobeyama radioheliograph
The temperature of the solar corona is higher than one million K while that of the solar surface (photosphere) is about 6000 K. It’s still unclarified how the solar corona is heated to such high temperature. This is called “coronal heating problem”. The microflare/nanoflare heating model is proposed as one of the heating mechanisms. It is the hypothesis that the corona’s magnetic field gets tangled by convection on the solar surface, and the corona is heated by occurrence of a large number of very small flares, so-called “microflare/nanoflare”. To contribute to solve this problem, we statistically analyze small solar flares observed with Nobeyama radioheliograph, which is a radio telescope dedicated to observe the Sun. The advantages of this instrument are high sensitivity, high temporal resolution (one second), wide field of view (full sun), long-term (~28 years) stable observation and so forth.
We analyzed solar radio images at 17GHz to automatically detect small flares with the following procedure. First, we cut the full sun image in grid pattern and made macropixels. Second, we calculated a mean (μ) and a standard deviation (σ) of one hour data for each macropixel, and detected small flares from the data that exceeded a threshold (μ+3σ). In the case of this method, however, the threshold became higher for the macropixels including relatively intense spikes than expected and some small spikes that seemed real flares were not successfully detected. Thus, we revised the analysis method and the new method intends to detect small flares based on the information of all the local minima/maxima in an intensity time profile. As a result, small flares have been detected precisely. Actually, for the same macropixel, out of the events that the duration exceeded 10 seconds, the new method detected 29 events while the previous one detected only 1 event. Also, the new method succeeded to detect smaller event compare with the previous one. Thus, we confirmed this method can be applied to detect small flares from radio images.
Based on this method, we optimized the size of macropixel and then derived some preliminary results such as the number of events, the mean duration, and the mean peak intensity about small flares in each macropixel. The characteristics of small solar flares at different regions such as active region, coronal hole and quiet region will be discussed.
We analyzed solar radio images at 17GHz to automatically detect small flares with the following procedure. First, we cut the full sun image in grid pattern and made macropixels. Second, we calculated a mean (μ) and a standard deviation (σ) of one hour data for each macropixel, and detected small flares from the data that exceeded a threshold (μ+3σ). In the case of this method, however, the threshold became higher for the macropixels including relatively intense spikes than expected and some small spikes that seemed real flares were not successfully detected. Thus, we revised the analysis method and the new method intends to detect small flares based on the information of all the local minima/maxima in an intensity time profile. As a result, small flares have been detected precisely. Actually, for the same macropixel, out of the events that the duration exceeded 10 seconds, the new method detected 29 events while the previous one detected only 1 event. Also, the new method succeeded to detect smaller event compare with the previous one. Thus, we confirmed this method can be applied to detect small flares from radio images.
Based on this method, we optimized the size of macropixel and then derived some preliminary results such as the number of events, the mean duration, and the mean peak intensity about small flares in each macropixel. The characteristics of small solar flares at different regions such as active region, coronal hole and quiet region will be discussed.