We use more than 4,500 microflares from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) microflare data set (Christe et al., 2008, Ap. J., 677, 1385) to estimate electron densities and volumetric filling factors of microflare loops
using a cooling time analysis. We show that if the filling factor is assumed to be unity, the calculated conductive cooling times are much shorter than the observed flare decay times, which in turn are much shorter than the calculated radiative cooling times. This is likely unphysical, but the contradic- tion can be resolved by assuming the radiative and conductive cooling times are comparable, which is valid when the flare loop temperature is a maximum and when external heating can be ignored. We find that resultant radiative and con- ductive cooling times are comparable to observed decay times, which has been used as an assumption in some previous studies. The inferred electron densities have a mean value of 10^11.6 cm^-3 and filling factors have a mean of 10^-3.7. The filling factors are lower and densities are higher than previous estimates for large flares, but are similar to those found for two microflares by Moore et al. (Ap. J., 526, 505, 1999).
Sequences of line-of-sight (LOS) magnetograms recorded by the Michelson-Doppler Imager are used to quantitatively characterize photospheric magnetic structure and evolution in three active regions that rotated across the Suns disk during the Whole He
liosphere Interval (WHI), in an attempt to relate the photospheric magnetic properties of these active regions to flares and coronal mass ejections (CMEs). Several approaches are used in our analysis, on scales ranging from whole active regions, to magnetic features, to supergranular scales, and, finally, to individual pixels. We calculated several parameterizations of magnetic structure and evolution that have previously been associated with flare and CME activity, including total unsigned magnetic flux, magnetic flux near polarity inversion lines, amount of cancelled flux, the proxy Poynting flux, and helicity flux. To catalog flare events, we used flare lists derived from both GOES and RHESSI observations. By most such measures, AR 10988 should have been the most flare- and CME-productive active region, and AR 10989 the least. Observations, however, were not consistent with this expectation: ARs 10988 and 10989 produced similar numbers of flares, and AR 10989 also produced a few CMEs. These results highlight present limitations of statistics-based flare and CME forecasting tools that rely upon line-of-sight photospheric magnetic data alone.
We present X-ray imaging and spectral analysis of all microflares the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) observed between March 2002 and March 2007, a total of 25,705 events. These microflares are small flares, from low GOE
S C Class to below A Class (background subtracted) and are associated with active regions. They were found by searching the 6-12 keV energy range during periods when the full sensitivity of RHESSIs detectors was available (see paper I). Each microflare is automatically analyzed at the peak time of the 6-12 keV emission: the thermal source size is found by forward-fitting the complex visibilities for 4-8 keV, and the spectral parameters (temperature, emission measure, power-law index) are found by forward fitting a thermal plus non-thermal model. The combination of these parameters allows us to present the first statistical analysis of the thermal and non-thermal energy at the peak times of microflares.
