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Register a new userGenerate Radioheliograph Image from SDO/AIA Data with Machine Learning Method
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The radioheliograph image is essential for the study of solar short term activities and long term variations, while the continuity and granularity of radioheliograph data is not so ideal, due to the short visible time of the sun and the complex electron-magnetic environment near the ground-based radio telescope. In this work, we develop a multi-channel input single-channel output neural network, which can generate radioheliograph image in microwave band from the Extreme Ultra-violet (EUV) observation of the Atmospheric Imaging Assembly (AIA) on-board the Solar Dynamic Observatory (SDO). The neural network is trained with nearly 8 years of data of Nobeyama Radioheliograph (NoRH) at 17 GHz and SDO/AIA from January 2011 to September 2018. The generated radioheliograph image is in good consistency with the well-calibrated NoRH observation. SDO/AIA provides solar atmosphere images in multiple EUV wavelengths every 12 seconds from space, so the present model can fill the vacancy of limited observation time of microwave radioheliograph, and support further study of the relationship between the microwave and EUV emission.
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We found systematic microwave source motions along a flare-arcade using Nobeyama Radioheliograph (NoRH) 17 GHz images. The motions were associated with a X-class disk flare which occurred on 15th February 2011. For this study, we also used EUV images from Atmospheric Imaging Assembly (AIA) and magnetograms from Helioseismic and Magnetic Imager (HMI) onboard Solar Dynamics Observatory, and multi-channel microwave data from Nobeyama Radiopolarimeters (NoRP) and Korean Solar Radio Burst Locator (KSRBL). We traced centroids of the microwave source observed by NoRH 17 GHz during the flare and found two episodes of the motion with several facts: 1) The microwave source moved systematically along the flare-arcade, which was observed by the AIA 94 A in a direction parallel to the neutral line. 2) The period of each episode was 5 min and 14 min, respectively. 3) Estimated parallel speed was 34 km/s for the first episode and 22 km/s for the second episode. The spectral slope of microwave flux above 10 GHz obtained by NoRP and KSRBL was negative for both episodes, and for the last phase of the second episodes, it was flat with the flux of 150 sfu. The negative spectrum and the flat with high flux indicate that the gyrosynchrotron emission from accelerated electrons was dominant during the source motions. The sequential images from the AIA 304 A and 94 A channels revealed that there were successive plasma eruptions and each eruption was initiated just before the start time of the microwave sources motion. Based on the results, we suggest that the microwave source motion manifests the displacement of the particle acceleration site caused by plasma eruptions.
The Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO) returns high-resolution images of the solar atmosphere in seven extreme ultraviolet wavelength channels. The images are processed on the ground to remove intensity spikes arising from energetic particles hitting the instrument, and the despiked images are provided to the community. In this work a three-hour series of images from the 171 A channel obtained on 2017 February 28 was studied to investigate how often the despiking algorithm gave false positives caused by compact brightenings in the solar atmosphere. The latter were identified through spikes appearing in the same detector pixel for three consecutive frames, and 1096 examples were found from the 900 image frames. These three-spikes were assigned to 126 dynamic solar features, and it is estimated that the three-spike method identifies 25% of the total number of features affected by despiking. For any 10 minute sequence of AIA 171 A images there are therefore around 28 solar features that have their intensity modified by despiking. The features are found in active regions, quiet Sun and coronal holes and, in relation to solar surface area, there is a greater proportion within coronal holes. In 96% of the cases, the despiked structure is a compact brightening of size 2 arcsec or less and the remaining 4% have narrow, elongated structures. In all cases, the events are not rendered invisible by the AIA processing pipeline, but the total intensity over the events lifetimes can be reduced by up to 67%. Scientists are recommended to always restore the original intensities to AIA data when studying short-lived or rapidly-evolving features that exhibit fine-scale structure.
Waves have long been thought to contribute to the heating of the solar corona and the generation of the solar wind. Recent observations have demonstrated evidence of quasi-periodic longitudinal disturbances and ubiquitous transverse wave propagation in many different coronal environments. This paper investigates signatures of different types of oscillatory behaviour, both above the solar limb and on-disk, by comparing findings from the Coronal Multi-channel Polarimeter (CoMP) and the Atmospheric Imaging Assembly (AIA) on board the Solar Dynamics Observatory (SDO) for the same active region. We study both transverse and longitudinal motion by comparing and contrasting time-distance images of parallel and perpendicular cuts along/across active region fan loops. Comparisons between parallel space-time features in CoMP Doppler velocity and transverse oscillations in AIA images are made, together with space-time analysis of propagating quasi-periodic intensity features seen near the base of loops in AIA. Signatures of transverse motions are observed along the same magnetic structure using CoMP Doppler velocity (Vphase=600-750km/s, P=3-6mins) and in AIA/SDO above the limb (P=3-8mins). Quasi-periodic intensity features (Vphase=100-200km/s, P=6-11mins) also travel along the base of the same structure. On the disk, signatures of both transverse and longitudinal intensity features were observed by AIA; both show similar properties to signatures found along structures anchored in the same active region three days earlier above the limb. Correlated features are recovered by space-time analysis of neighbouring tracks over perpendicular distances of <2.6Mm.
In this paper, we carry out multiwavelength observations of three recurring jets on 2014 November 7. The jets originated from the same region at the edge of AR 12205 and propagated along the same coronal loop. The eruptions were generated by magnetic reconnection, which is evidenced by continuous magnetic cancellation at the jet base. The projected initial velocity of the jet2 is 402 km s. The accelerations in the ascending and descending phases of jet2 are not consistent, the former is considerably larger than the value of solar gravitational acceleration at the solar surface, while the latter is lower than solar gravitational acceleration. There are two possible candidates of extra forces acting on jet2 during its propagation. One is the downward gas pressure from jet1 when it falls back and meets with jet2. The other is the viscous drag from the surrounding plasma during the fast propagation of jet2. As a contrast, the accelerations of jet3 in the rising and falling phases are constant, implying that the propagation of jet3 is not significantly influenced byextra forces.
We present an empirical model based on the visible area covered by coronal holes close to the central meridian in order to predict the solar wind speed at 1 AU with a lead time up to four days in advance with a 1hr time resolution. Linear prediction functions are used to relate coronal hole areas to solar wind speed. The function parameters are automatically adapted by using the information from the previous 3 Carrington Rotations. Thus the algorithm automatically reacts on the changes of the solar wind speed during different phases of the solar cycle. The adaptive algorithm has been applied to and tested on SDO/AIA-193A observations and ACE measurements during the years 2011-2013, covering 41 Carrington Rotations. The solar wind speed arrival time is delayed and needs on average 4.02 +/- 0.5 days to reach Earth. The algorithm produces good predictions for the 156 solar wind high speed streams peak amplitudes with correlation coefficients of cc~0.60. For 80% of the peaks, the predicted arrival matches within a time window of 0.5 days of the ACE in situ measurements. The same algorithm, using linear predictions, was also applied to predict the magnetic field strength from coronal hole areas but did not give reliable predictions (cc~0.2).
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