Solar seeing monitor MISOLFA: A new method for estimating atmospheric turbulence parameters

摘要

Aims. Daily observation conditions are needed when observing the Sun at high angular resolution. MISOLFA is a daytime seeing monitor developed for this purpose that allows the estimation of the spatial and temporal parameters of atmospheric turbulence. This information is necessary, for instance, for astrometric measurements of the solar radius performed at Calern Observatory (France) with SODISM II, the ground-based version of the SODISM instrument of the PICARD mission. Methods. We present a new way to estimate the spatial parameters of atmospheric turbulence for daily observations. This method is less sensitive to vibrations and guiding defaults of the telescope since it uses short-exposure images. It is based on the comparison of the optical transfer function obtained from solar data and the theoretical values deduced from the Kolmogorov and Von Kàrmàn models. This method, previously tested on simulated solar images, is applied to real data recorded at Calern Observatory in July 2013 with the MISOLFA monitor. Results. First, we use data recorded in the pupil plane mode of MISOLFA and evaluate the turbulence characteristic times of angle-of-arrival fluctuations: between 5 and 16 ms. Second, we use the focal plane mode of MISOLFA to simultaneously record solar images to obtain isoplanatic angles: ranging from 1 to 5 arcsec (in agreement with previously published values). These images and our new method allow Fried’s parameter to be measured; it ranges from 0.5 cm to 4.7 cm with a mean value of 1.5 cm when Kolmogorov’s model is considered, and from less than 0.5 to 2.6 cm with a mean value of 1.3 cm for the Von Kàrmàn model. Measurements of the spatial coherence outer scale parameter are also obtained when using the Von Kàrmàn model; it ranges from 0.25 to 13 m with a mean value of 3.4 m for the four days of observation that we analyzed. We found that its value can undergo large variations in only a few hours and that more data analysis is needed to better define its statistics.