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Register a new userUsing U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona
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Added by
Valentina Maria Salvatelli
Publication date
2019
fields
Physics
and research's language is
English
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Understanding and monitoring the complex and dynamic processes of the Sun is important for a number of human activities on Earth and in space. For this reason, NASAs Solar Dynamics Observatory (SDO) has been continuously monitoring the multi-layered Suns atmosphere in high-resolution since its launch in 2010, generating terabytes of observational data every day. The synergy between machine learning and this enormous amount of data has the potential, still largely unexploited, to advance our understanding of the Sun and extend the capabilities of heliophysics missions. In the present work, we show that deep learning applied to SDO data can be successfully used to create a high-fidelity virtual telescope that generates synthetic observations of the solar corona by image translation. Towards this end we developed a deep neural network, structured as an encoder-decoder with skip connections (U-Net), that reconstructs the Suns image of one instrument channel given temporally aligned images in three other channels. The approach we present has the potential to reduce the telemetry needs of SDO, enhance the capabilities of missions that have less observing channels, and transform the concept development of future missions.
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The quiet solar corona emits meter-wave thermal bremsstrahlung. Coronal radio emission can only propagate above that radius, $R_omega$, where the local plasma frequency eqals the observing frequency. The radio interferometer LOw Frequency ARray (LOFAR) observes in its low band (10 -- 90 MHz) solar radio emission originating from the middle and upper corona. We present the first solar aperture synthesis imaging observations in the low band of LOFAR in 12 frequencies each separated by 5 MHz. From each of these radio maps we infer $R_omega$, and a scale height temperature, $T$. These results can be combined into coronal density and temperature profiles. We derived radial intensity profiles from the radio images. We focus on polar directions with simpler, radial magnetic field structure. Intensity profiles were modeled by ray-tracing simulations, following wave paths through the refractive solar corona, and including free-free emission and absorption. We fitted model profiles to observations with $R_omega$ and $T$ as fitting parameters. In the low corona, $R_omega < 1.5$ solar radii, we find high scale height temperatures up to 2.2e6 K, much more than the brightness temperatures usually found there. But if all $R_omega$ values are combined into a density profile, this profile can be fitted by a hydrostatic model with the same temperature, thereby confirming this with two independent methods. The density profile deviates from the hydrostatic model above 1.5 solar radii, indicating the transition into the solar wind. These results demonstrate what information can be gleaned from solar low-frequency radio images. The scale height temperatures we find are not only higher than brightness temperatures, but also than temperatures derived from coronograph or EUV data. Future observations will provide continuous frequency coverage, eliminating the need for local hydrostatic density models.
One of the most important features in the solar atmosphere is magnetic network and its rela- tionship with the transition region (TR), and coronal brightness. It is important to understand how energy is transported into the corona and how it travels along the magnetic-field lines be- tween deep photosphere and chromosphere through the TR and corona. An excellent proxy for transportation is the Interface Region Imaging Spectrograph (IRIS) raster scans and imaging observations in near-ultraviolet (NUV) and far-ultraviolet (FUV) emission channels with high time-spatial resolutions. In this study, we focus on the quiet Sun as observed with IRIS. The data with high signal to noise ratio in Si IV, C II and Mg II k lines and with strong emission intensities show a high correlation in TR bright network points. The results of the IRIS intensity maps and dopplergrams are compared with those of Atmo- spheric Imaging Assembly (AIA) and Helioseismic and Magnetic Imager (HMI) instruments onboard the Solar Dynamical Observatory (SDO). The average network intensity profiles show a strong correlation with AIA coronal channels. Furthermore, we applied simultaneous observations of magnetic network from HMI and found a strong relationship between the network bright points in all levels of the solar atmosphere. These features in network elements exhibited high doppler velocity regions and large mag- netic signatures. A dominative fraction of corona bright points emission, accompanied by the magnetic origins in photosphere, suggest that magnetic-field concentrations in the network rosettes could help couple between inner and outer solar atmosphere.
Many observational records critically rely on our ability to merge different (and not necessarily overlapping) observations into a single composite. We provide a novel and fully-traceable approach for doing so, which relies on a multi-scale maximum likelihood estimator. This approach overcomes the problem of data gaps in a natural way and uses data-driven estimates of the uncertainties. We apply it to the total solar irradiance (TSI) composite, which is currently being revised and is critical to our understanding of solar radiative forcing. While the final composite is pending decisions on what corrections to apply to the original observations, we find that the new composite is in closest agreement with the PMOD composite and the NRLTSI2 model. In addition, we evaluate long-term uncertainties in the TSI, which reveal a 1/f scaling
In this work, we focus in the magnetic evolution of a small region as seen by Hinode-SP during the time interval of about one hour. High-cadence LOS magnetograms and velocity maps were derived, allowing the study of different small-scale processes such as the formation/disappearance of bright points accompanying the evolution of an observed convective vortical motion.
We present observations of a powerful solar eruption, accompanied by an X8.2 solar flare, from NOAA Active Region 12673 on 2017 September 10 by the Solar Ultraviolet Imager (SUVI) on the GOES-16 spacecraft. SUVI is noteworthy for its relatively large field of view, which allows it to image solar phenomena to heights approaching 2 solar radii. These observations include the detection of an apparent current sheet associated with magnetic reconnection in the wake of the eruption and evidence of an extreme-ultraviolet wave at some of the largest heights ever reported. We discuss the acceleration of the nascent coronal mass ejection to approximately 2000 km/s at about 1.5 solar radii. We compare these observations with models of eruptions and eruption-related phenomena. We also describe the SUVI data and discuss how the scientific community can access SUVI observations of the event.
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