Why Does the Solar Corona Abnormally Rotate Faster Than the Photosphere?
arXiv:1904.07465 · doi:10.3847/1538-4357/ab0f3a
Abstract
Coronal heating is a big question for modern astronomy. Daily measurement of 985 solar spectral irradiances (SSIs) at the spectral intervals 1-39 nm and 116-2416 nm during March 1 2003 to October 28 2017 is utilized to investigate characteristics of solar rotation in the solar atmosphere by means of the Lomb \,-\, Scargle periodogram method to calculate their power spectra. The rotation period of coronal plasma is obtained to be 26.3 days, and that of the solar atmosphere at the bottom of the photosphere modulated by magnetic structures is 27.5 days. Here we report for the first time that unexpectedly the coronal atmosphere is found to rotate faster than the underlying photosphere. When time series of SSIs are divided into different cycles, and the ascending and descending periods of a solar cycle, rotation rate in the corona is also found to be larger than that in the photosphere, and this actually gives hidden evidence: it is small-scale magnetic activity that heats the corona.
References in corpus (6)
- Key Aspects of Coronal Heating
- A Contemporary View of Coronal Heating
- Multiwavelength studies of MHD waves in the solar chromosphere: An overview of recent results
- A global view of velocity fluctuations in the corona below 1.3 with CoMP
- Observations and numerical models of solar coronal heating associated with spicules
- Variations in the Solar Coronal Rotation with Altitude - Revisited
Cited by in corpus (5)
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- Differential rotation of the chromosphere in the He I absorption line
- The role and contribution of magnetic fields, characterized via their magnetic flux, to the statistical structuring of the solar atmosphere
- Study on the Temporal Evolution of the Radial Differential Rotation of Solar Corona Using Radio Emissions
- Enhancing Image Resolution of Solar Magnetograms: A Latent Diffusion Model Approach