@article{DenkerKuckeinVermaetal.2018,
  author    = {Denker, Carsten and Kuckein, Christoph and Verma, Meetu and Manrique Gonzalez, Sergio Javier Gonzalez and Diercke, Andrea and Enke, Harry and Klar, Jochen and Balthasar, Horst and Louis, Rohan E. and Dineva, Ekaterina Ivanova},
  title     = {High-cadence Imaging and Imaging Spectroscopy at the GREGOR Solar Telescope-A Collaborative Research Environment for High-resolution Solar Physics},
  series = {The astrophysical journal : an international review of spectroscopy and astronomical physics ; Supplement series},
  volume    = {236},
  journal   = {The astrophysical journal : an international review of spectroscopy and astronomical physics ; Supplement series},
  number    = {1},
  publisher = {IOP Publ. Ltd.},
  address   = {Bristol},
  issn      = {0067-0049},
  doi       = {10.3847/1538-4365/aab773},
  pages     = {12},
  year      = {2018},
  abstract  = {In high-resolution solar physics, the volume and complexity of photometric, spectroscopic, and polarimetric ground-based data significantly increased in the last decade, reaching data acquisition rates of terabytes per hour. This is driven by the desire to capture fast processes on the Sun and the necessity for short exposure times "freezing" the atmospheric seeing, thus enabling ex post facto image restoration. Consequently, large-format and high-cadence detectors are nowadays used in solar observations to facilitate image restoration. Based on our experience during the "early science" phase with the 1.5 m GREGOR solar telescope (2014-2015) and the subsequent transition to routine observations in 2016, we describe data collection and data management tailored toward image restoration and imaging spectroscopy. We outline our approaches regarding data processing, analysis, and archiving for two of GREGOR's post-focus instruments (see http://gregor.aip.de), i.e., the GREGOR Fabry-P{\´e}rot Interferometer (GFPI) and the newly installed High-Resolution Fast Imager (HiFI). The heterogeneous and complex nature of multidimensional data arising from high-resolution solar observations provides an intriguing but also a challenging example for "big data" in astronomy. The big data challenge has two aspects: (1) establishing a workflow for publishing the data for the whole community and beyond and (2) creating a collaborative research environment (CRE), where computationally intense data and postprocessing tools are colocated and collaborative work is enabled for scientists of multiple institutes. This requires either collaboration with a data center or frameworks and databases capable of dealing with huge data sets based on virtual observatory (VO) and other community standards and procedures.},
  language  = {en}
}
@article{DierckeKuckeinVermaetal.2018,
  author    = {Diercke, Andrea and Kuckein, Christoph and Verma, Meetu and Denker, Carsten},
  title     = {Counter-streaming flows in a giant quiet-Sun filament observed in the extreme ultraviolet},
  series = {Astronomy and astrophysics : an international weekly journal},
  volume    = {611},
  journal   = {Astronomy and astrophysics : an international weekly journal},
  publisher = {EDP Sciences},
  address   = {Les Ulis},
  issn      = {1432-0746},
  doi       = {10.1051/0004-6361/201730536},
  pages     = {11},
  year      = {2018},
  abstract  = {Aims. The giant solar filament was visible on the solar surface from 2011 November 8-23. Multiwavelength data from the Solar Dynamics Observatory (SDO) were used to examine counter-streaming flows within the spine of the filament. Methods. We use data from two SDO instruments, the Atmospheric Imaging Assembly (AIA) and the Helioseismic and Magnetic Imager (HMI), covering the whole filament, which stretched over more than half a solar diameter. H alpha images from the Kanzelhohe Solar Observatory (KSO) provide context information of where the spine of the filament is defined and the barbs are located. We apply local correlation tracking (LCT) to a two-hour time series on 2011 November 16 of the AIA images to derive horizontal flow velocities of the filament. To enhance the contrast of the AIA images, noise adaptive fuzzy equalization (NAFE) is employed, which allows us to identify and quantify counter-streaming flows in the filament. We observe the same cool filament plasma in absorption in both H alpha and EUV images. Hence, the counter-streaming flows are directly related to this filament material in the spine. In addition, we use directional flow maps to highlight the counter-streaming flows. Results. We detect counter-streaming flows in the filament, which are visible in the time-lapse movies in all four examined AIA wavelength bands (lambda 171 angstrom, lambda 193 angstrom, lambda 304 angstrom, and lambda 211 angstrom). In the time-lapse movies we see that these persistent flows lasted for at least two hours, although they became less prominent towards the end of the time series. Furthermore, by applying LCT to the images we clearly determine counter-streaming flows in time series of lambda 171 angstrom and lambda 193 angstrom images. In the lambda 304 angstrom wavelength band, we only see minor indications for counter-streaming flows with LCT, while in the lambda 211 angstrom wavelength band the counter-streaming flows are not detectable with this method. The diverse morphology of the filament in H alpha and EUV images is caused by different absorption processes, i.e., spectral line absorption and absorption by hydrogen and helium continua, respectively. The horizontal flows reach mean flow speeds of about 0.5 km s(-1) for all wavelength bands. The highest horizontal flow speeds are identified in the lambda 171 angstrom band with flow speeds of up to 2.5 km s(-1). The results are averaged over a time series of 90 minutes. Because the LCT sampling window has finite width, a spatial degradation cannot be avoided leading to lower estimates of the flow velocities as compared to feature tracking or Doppler measurements. The counter-streaming flows cover about 15-20\% of the whole area of the EUV filament channel and are located in the central part of the spine. Conclusions. Compared to the ground-based observations, the absence of seeing effects in AIA observations reveal counter-streaming flows in the filament even with a moderate image scale of 0 '.6 pixel(-1). Using a contrast enhancement technique, these flows can be detected and quantified with LCT in different wavelengths. We confirm the omnipresence of counter-streaming flows also in giant quiet-Sun filaments.},
  language  = {en}
}