Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMeasurement of the Height of the Chromospheric Network Emission from Solar Dynamics Observatory Images
214
0
0.0
(
0
)
Added by
Costas Alissandrakis
Publication date
2019
fields
Physics
and research's language is
English
Authors
C. E. Alissandrakis
Ask ChatGPT about the research
No Arabic abstract
We measured the height of the chromospheric network in the 1700, 1600, and 304 A wavelength bands of the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) from the shift of features on the disk with respect to corresponding features in SDO/Helioseismic and Magnetic Imager (HMI) images of the absolute value of the longitudinal magnetic field. We found that near the limb the 304 A network emission forms 3.60$pm$0.24 Mm above the 1600 A emission, which, in turn, forms 0.48$pm$0.10 Mm above the HMI (6173 A) level. At the center of the disk the corresponding height differences are 2.99$pm$0.02 Mm and 0.39$pm$0.06 Mm respectively. We also found that the 1600 A network emission forms 0.25$pm$0.02 Mm above the 1700 A emission near the limb and 0.20$pm$0.02 Mm at the disk center. Finally, we examined possible variations with the solar cycle. Our results can help to check and refine atmospheric models.
rate research
Read More
Stellar magnetic activity decays over the main-sequence life of cool stars due to the stellar spin-down driven by magnetic braking. The evolution of chromospheric emission is well-studied for younger stars, but difficulties in determining the ages of older cool stars on the main sequence have complicated such studies for older stars in the past. Here we report on chromospheric Ca II H and K line measurements for 26 main-sequence cool stars with asteroseismic ages older than a gigayear and spectral types F and G. We find that for the G stars and the cooler F-type stars which still have convective envelopes the magnetic activity continues to decrease at stellar ages above one gigayear. Our magnetic activity measurements do not show evidence for a stalling of the magnetic braking mechanism, which has been reported for stellar rotation versus age for G and F type stars. We also find that the measured RHK indicator value for the cool F stars in our sample is lower than predicted by common age-activity relations that are mainly calibrated on data from young stellar clusters. We conclude that, within individual spectral type bins, chromospheric magnetic activity correlates well with stellar age even for old stars.
We need to establish a correspondence between the magnetic structures generated by models and usual stellar activity indexes to simulate radial velocity time series for stars less active than the Sun. This is necessary to compare the outputs of such models with observed radial velocity jitters and is critical to better understand the impact of stellar activity on exoplanet detectability. We propose a coherent picture to describe the relationship between magnetic activity, including the quiet Sun regions, and the chromospheric emission using the Sun as a test-bench and a reference. We analyzed a time series of MDI magnetograms jointly with chromospheric emission time series obtained at Sacramento Peak and Kitt Peak observatories. This has allowed us to study the variability in the quiet Sun over the solar cycle, and then, based on available relations between magnetic fields in active structures and chromospheric emission, to propose an empirical reconstruction of the solar chromospheric emission based on all contributions. We show that the magnetic flux covering the solar surface, including in the quieted regions, varies in phase with the solar cycle, suggesting a long-term relationship between the global dynamo and the contribution of all components of solar activity. We have been able to propose a reconstruction of the solar S-index, including a relationship between the weak field component and its chomospheric emission, which is in good agreement with the literature. This allows us to explain that stars with a low average chromospheric emission level exhibit a low variability. We conclude that weak flux regions significantly contribute to the chromospheric emission; these regions should be critical in explaining the lower variability associated with the lower average activity level in other stars as compared to the Sun and estimated from their chromospheric emission.
In this paper we present a curated dataset from the NASA Solar Dynamics Observatory (SDO) mission in a format suitable for machine learning research. Beginning from level 1 scientific products we have processed various instrumental corrections, downsampled to manageable spatial and temporal resolutions, and synchronized observations spatially and temporally. We illustrate the use of this dataset with two example applications: forecasting future EVE irradiance from present EVE irradiance and translating HMI observations into AIA observations. For each application we provide metrics and baselines for future model comparison. We anticipate this curated dataset will facilitate machine learning research in heliophysics and the physical sciences generally, increasing the scientific return of the SDO mission. This work is a direct result of the 2018 NASA Frontier Development Laboratory Program. Please see the appendix for access to the dataset.
The emission of the upper atmosphere of the Sun is closely related to magnetic field concentrations at the solar surface. It is well established that this relation between chromospheric emission and magnetic field is nonlinear. Here we investigate systematically how this relation, characterised by the exponent of a power-law fit, changes through the atmosphere, from the upper photosphere through the temperature minimum region and chromosphere to the transition region. We used spectral maps from IRIS: MgII and its wings, CII, and SiIV together with magnetograms and UV continuum images from SDO. We performed a power-law fit for the relation between each pair of observables and determine the power-law index (or exponent) for these. While the correlation between emission and magnetic field drops monotonically with temperature, the power-law index shows a hockey-stick-type variation: from the upper photosphere to the temperature-minimum it drops sharply and then increases through the chromosphere into the transition region. This is even seen through the features of the MgII line, this is, from k1 to k2 and k3. It is irrespective of spatial resolution or feature types on the Sun. In accordance with the general picture of flux-flux relations from the chromosphere to the corona, above the temperature minimum the sensitivity of the emission to the plasma heating increases with temperature. Below the temperature minimum a different mechanism has to govern the opposite trend of the power-law index with temperature. We suggest four possibilities, in other words, a geometric effect of expanding flux tubes filling the available chromospheric volume, the height of formation of the emitted radiation, the dependence on wavelength of the intensity-temperature relationship, and the dependence of the heating of flux tubes on the magnetic flux density.
We provide a large image parameter dataset extracted from the Solar Dynamics Observatory (SDO) missions AIA instrument, for the period of January 2011 through the current date, with the cadence of six minutes, for nine wavelength channels. The volume of the dataset for each year is just short of 1 TiB. Towards achieving better results in the region classification of active regions and coronal holes, we improve upon the performance of a set of ten image parameters, through an in depth evaluation of various assumptions that are necessary for calculation of these image parameters. Then, where possible, a method for finding an appropriate settings for the parameter calculations was devised, as well as a validation task to show our improved results. In addition, we include comparisons of JP2 and FITS image formats using supervised classification models, by tuning the parameters specific to the format of the images from which they are extracted, and specific to each wavelength. The results of these comparisons show that utilizing JP2 images, which are significantly smaller files, is not detrimental to the region classification task that these parameters were originally intended for. Finally, we compute the tuned parameters on the AIA images and provide a public API (http://dmlab.cs.gsu.edu/dmlabapi) to access the dataset. This dataset can be used in a range of studies on AIA images, such as content-based image retrieval or tracking of solar events, where dimensionality reduction on the images is necessary for feasibility of the tasks.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
