| 1. |
- Lehtinen, J. J., et al.
(författare)
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Topological changes in the magnetic field of LQ Hya during an activity minimum
- 2022
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Ingår i: Astronomy and Astrophysics. - : EDP Sciences. - 0004-6361 .- 1432-0746. ; 660
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Tidskriftsartikel (refereegranskat)abstract
- Aims. Previous studies have related surface temperature maps, obtained with the Doppler imaging (DI) technique, of LQ Hya with long-term photometry. Here, we compare surface magnetic field maps, obtained with the Zeeman Doppler imaging (ZDI) technique, with contemporaneous photometry, with the aim of quantifying the star's magnetic cycle characteristics. Methods. We inverted Stokes IV spectropolarimetry, obtained with the HARPSpol and ESPaDOnS instruments, into magnetic field and surface brightness maps using a tomographic inversion code that models high signal-to-noise ratio mean line profiles produced by the least squares deconvolution (LSD) technique. The maps were compared against long-term ground-based photometry acquired with the T3 0.40 m Automatic Photoelectric Telescope (APT) at Fairborn Observatory, which offers a proxy for the spot cycle of the star, as well as with chromospheric Ca II H&K activity derived from the observed spectra. Results. The magnetic field and surface brightness maps reveal similar patterns relative to previous DI and ZDI studies: nonaxisymmetric polar magnetic field structure, void of fields at mid-latitudes, and a complex structure in the equatorial regions. There is a weak but clear tendency of the polar structures to be linked with a strong radial field and the equatorial ones with the azimuthal field. We find a polarity reversal in the radial field between 2016 and 2017 that is coincident with a spot minimum seen in the long-term photometry, although the precise relation of chromospheric activity to the spot activity remains complex and unclear. The inverted field strengths cannot be easily related with the observed spottedness, but we find that they are partially connected to the retrieved field complexity. Conclusions. This field topology and the dominance of the poloidal field component, when compared to global magnetoconvection models for rapidly rotating young suns, could be explained by a turbulent dynamo, where differential rotation does not play a major role (so-called alpha(2)Omega(2) or alpha(2) dynamos) and axi- and non-axisymmetric modes are excited simultaneously. The complex equatorial magnetic field structure could arise from the twisted (helical) wreaths often seen in these simulations, while the polar feature would be connected to the mostly poloidal non-axisymmetric component that has a smooth spatial structure.
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| 2. |
- Rixen, C., et al.
(författare)
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Winters are changing: snow effects on Arctic and alpine tundra ecosystems
- 2022
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Ingår i: Arctic Science. - : Canadian Science Publishing. - 2368-7460. ; 8:3, s. 572-608
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Tidskriftsartikel (refereegranskat)abstract
- Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season's start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover's role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.
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