Signatures of Steady Heating in Time Lag Analysis of Coronal Emission

Among the many ways of investigating coronal heating, the time lag method of Viall & Klimchuk (2012) is becoming increasingly prevalent as an analysis technique complementary to those traditionally used. The time lag method cross correlates light curves at a given spatial location obtained in spectral bands that sample different temperature plasmas. It has been used most extensively with data from the Atmospheric Imaging Assembly on the Solar Dynamics Observatory. We have previously applied the time lag method to entire active regions and surrounding quiet Sun and create maps of the results (Viall & Klimchuk 2012; Viall & Klimchuk 2015). We find that the majority of time lags are consistent with the cooling of coronal plasma that has been impulsively heated. Additionally, a significant fraction of the map area has a time lag of zero. This does not indicate a lack of variability. Rather, strong variability must be present, and it must occur in phase in the different channels. We have shown previously that these zero time lags are consistent with the transition region response to coronal nanoflares (Viall & Klimchuk 2015; Bradshaw & Viall 2016), but other explanations are possible. A common misconception is that the zero time lag indicates steady emission resulting from steady heating. Using simulated and observed light curves, we demonstrate here that highly correlated light curves at zero time lag are not compatible with equilibrium solutions. Such light curves can only be created by evolution.Comment: 10 pages, 3 figures. Accepted to ApJ July 5 201

A nanoflare based cellular automaton model and the observed properties of the coronal plasma

We use the cellular automaton model described in L\'opez Fuentes \& Klimchuk (2015, ApJ, 799, 128) to study the evolution of coronal loop plasmas. The model, based on the idea of a critical misalignment angle in tangled magnetic fields, produces nanoflares of varying frequency with respect to the plasma cooling time. We compare the results of the model with active region (AR) observations obtained with the Hinode/XRT and SDO/AIA instruments. The comparison is based on the statistical properties of synthetic and observed loop lightcurves. Our results show that the model reproduces the main observational characteristics of the evolution of the plasma in AR coronal loops. The typical intensity fluctuations have an amplitude of 10 to 15\% both for the model and the observations. The sign of the skewness of the intensity distributions indicates the presence of cooling plasma in the loops. We also study the emission measure (EM) distribution predicted by the model and obtain slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with published observational values.Comment: Paper 2 of 2: Model comparison with observations. Accepted for publication in Ap

Active Region Moss: Doppler Shifts from Hinode/EIS Observations

Studying the Doppler shifts and the temperature dependence of Doppler shifts in moss regions can help us understand the heating processes in the core of the active regions. In this paper we have used an active region observation recorded by the Extreme-ultraviolet Imaging Spectrometer (EIS) onboard Hinode on 12-Dec-2007 to measure the Doppler shifts in the moss regions. We have distinguished the moss regions from the rest of the active region by defining a low density cut-off as derived by Tripathi et al. (2010). We have carried out a very careful analysis of the EIS wavelength calibration based on the method described in Young et al. (2012). For spectral lines having maximum sensitivity between log T = 5.85 and log T = 6.25 K, we find that the velocity distribution peaks at around 0 km/s with an estimated error of 4-5 km/s. The width of the distribution decreases with temperature. The mean of the distribution shows a blue shift which increases with increasing temperature and the distribution also shows asymmetries towards blue-shift. Comparing these results with observables predicted from different coronal heating models, we find that these results are consistent with both steady and impulsive heating scenarios. However, the fact that there are a significant number of pixels showing velocity amplitudes that exceed the uncertainty of 5 km s$^{-1}$ is suggestive of impulsive heating. Clearly, further observational constraints are needed to distinguish between these two heating scenarios.Comment: 21 pages (single column), 7 figures, Accepted for Publication in The Astrophysical Journa