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To explain the high temperature of the corona, much attention has been paidto the distribution of energy in dissipation events. Indeed, if the eventenergy distribution is steep enough, the smallest, unobservable events could bethe largest contributors to the total energy dissipation in the corona.Previous observations have shown a wide distribution of energies but remaininconclusive about the precise slope. Furthermore, these results rely on a verycrude estimate of the energy. On the other hand, more detailed spectroscopicstudies of structures such as coronal bright points do not provide enoughstatistical information to derive their total contribution to heating. We aimat getting a better estimate of the distributions of the energy dissipated incoronal heating events using high-resolution, multi-channel ExtremeUltra-Violet (EUV) data. To estimate the energies corresponding to heatingevents and deduce their distribution, we detect brightenings in five EUVchannels of the Atmospheric Imaging Assembly (AIA) on-board the Solar DynamicsObservatory (SDO). We combine the results of these detections and we use mapsof temperature and emission measure derived from the same observations tocompute the energies. We obtain distributions of areas, durations, intensities,and energies (thermal, radiative, and conductive) of events. Thesedistributions are power-laws, and we find also power-law correlations betweenevent parameters. The energy distributions indicate that the energy from apopulation of events like the ones we detect represents a small contribution tothe total coronal heating, even when extrapolating to smaller scales. The mainexplanations for this are how heating events can be extracted fromobservational data, and the incomplete knowledge of the thermal structure andprocesses in the coronal plasma attainable from available observations.

Energetic characterisation and statistics of solar coronal brightenings