@article{BurattiThomasRoussosetal.2019, author = {Buratti, Bonnie J. and Thomas, P. C. and Roussos, E. and Howett, Carly and Seiss, Martin and Hendrix, A. R. and Helfenstein, Paul and Brown, R. H. and Clark, R. N. and Denk, Tilmann and Filacchione, Gianrico and Hoffmann, Holger and Jones, Geraint H. and Khawaja, N. and Kollmann, Peter and Krupp, Norbert and Lunine, Jonathan and Momary, T. W. and Paranicas, Christopher and Postberg, Frank and Sachse, Manuel and Spahn, Frank and Spencer, John and Srama, Ralf and Albin, T. and Baines, K. H. and Ciarniello, Mauro and Economou, Thanasis and Hsu, Hsiang-Wen and Kempf, Sascha and Krimigis, Stamatios M. and Mitchell, Donald and Moragas-Klostermeyer, Georg and Nicholson, Philip D. and Porco, C. C. and Rosenberg, Heike and Simolka, Jonas and Soderblom, Laurence A.}, title = {Close Cassini flybys of Saturn's ring moons Pan, Daphnis, Atlas, Pandora, and Epimetheus}, series = {Science}, volume = {364}, journal = {Science}, number = {6445}, publisher = {American Assoc. for the Advancement of Science}, address = {Washington}, issn = {0036-8075}, doi = {10.1126/science.aat2349}, pages = {1053}, year = {2019}, abstract = {Saturn's main ring system is associated with a set of small moons that either are embedded within it or interact with the rings to alter their shape and composition. Five close flybys of the moons Pan, Daphnis, Atlas, Pandora, and Epimetheus were performed between December 2016 and April 2017 during the ring-grazing orbits of the Cassini mission. Data on the moons' morphology, structure, particle environment, and composition were returned, along with images in the ultraviolet and thermal infrared. We find that the optical properties of the moons' surfaces are determined by two competing processes: contamination by a red material formed in Saturn's main ring system and accretion of bright icy particles or water vapor from volcanic plumes originating on the moon Enceladus.}, language = {en} } @article{SmirnovShpritsAllisonetal.2022, author = {Smirnov, Artem and Shprits, Yuri Y. and Allison, Hayley and Aseev, Nikita and Drozdov, Alexander and Kollmann, Peter and Wang, Dedong and Saikin, Anthony}, title = {Storm-Time evolution of the Equatorial Electron Pitch Angle Distributions in Earth's Outer Radiation Belt}, series = {Frontiers in astronomy and space sciences}, volume = {9}, journal = {Frontiers in astronomy and space sciences}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-987X}, doi = {10.3389/fspas.2022.836811}, pages = {15}, year = {2022}, abstract = {In this study we analyze the storm-time evolution of equatorial electron pitch angle distributions (PADs) in the outer radiation belt region using observations from the Magnetic Electron Ion Spectrometer (MagEIS) instrument aboard the Van Allen Probes in 2012-2019. The PADs are approximated using a sum of the first, third and fifth sine harmonics. Different combinations of the respective coefficients refer to the main PAD shapes within the outer radiation belt, namely the pancake, flat-top, butterfly and cap PADs. We conduct a superposed epoch analysis of 129 geomagnetic storms and analyze the PAD evolution for day and night MLT sectors. PAD shapes exhibit a strong energy-dependent response. At energies of tens of keV, the PADs exhibit little variation throughout geomagnetic storms. Cap PADs are mainly observed at energies < 300 keV, and their extent in L shrinks with increasing energy. The cap distributions transform into the pancake PADs around the main phase of the storm on the nightside, and then come back to their original shapes during the recovery phase. At higher energies on the dayside, the PADs are mainly pancake during pre-storm conditions and become more anisotropic during the main phase. The quiet-time butterfly PADs can be observed on the nightside at L> 5.6. During the main phase, butterfly PADs have stronger 90 degrees-minima and can be observed at lower L-shells (down to L = 5), then transitioning into flat-top PADs at L similar to 4.5 - 5 and pancake PADs at L < 4.5. The resulting PAD coefficients for different energies, locations and storm epochs can be used to test the wave models and physics-based radiation belt codes in terms of pitch angle distributions.}, language = {en} } @article{SmirnovShpritsAllisonetal.2022, author = {Smirnov, Artem and Shprits, Yuri Y. and Allison, Hayley and Aseev, Nikita and Drozdov, Alexander and Kollmann, Peter and Wang, Dedong and Saikin, Anthony}, title = {An empirical model of the equatorial electron pitch angle distributions in earth's outer radiation belt}, series = {Space Weather: the International Journal of Research and Applications}, volume = {20}, journal = {Space Weather: the International Journal of Research and Applications}, number = {9}, publisher = {American Geophysical Union}, address = {Washington, DC}, issn = {1542-7390}, doi = {10.1029/2022SW003053}, pages = {17}, year = {2022}, abstract = {In this study, we present an empirical model of the equatorial electron pitch angle distributions (PADs) in the outer radiation belt based on the full data set collected by the Magnetic Electron Ion Spectrometer (MagEIS) instrument onboard the Van Allen Probes in 2012-2019. The PADs are fitted with a combination of the first, third and fifth sine harmonics. The resulting equation resolves all PAD types found in the outer radiation belt (pancake, flat-top, butterfly and cap PADs) and can be analytically integrated to derive omnidirectional flux. We introduce a two-step modeling procedure that for the first time ensures a continuous dependence on L, magnetic local time and activity, parametrized by the solar wind dynamic pressure. We propose two methods to reconstruct equatorial electron flux using the model. The first approach requires two uni-directional flux observations and is applicable to low-PA data. The second method can be used to reconstruct the full equatorial PADs from a single uni- or omnidirectional measurement at off-equatorial latitudes. The model can be used for converting the long-term data sets of electron fluxes to phase space density in terms of adiabatic invariants, for physics-based modeling in the form of boundary conditions, and for data assimilation purposes.}, language = {en} }