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The Arctic is the hot spot of the ongoing, global climate change. Over the last decades, near-surface temperatures in the Arctic have been rising almost four times faster than on global average. This amplified warming of the Arctic and the associated rapid changes of its environment are largely influenced by interactions between individual components of the Arctic climate system. On daily to weekly time scales, storms can have major impacts on the Arctic sea-ice cover and are thus an important part of these interactions within the Arctic climate. The sea-ice impacts of storms are related to high wind speeds, which enhance the drift and deformation of sea ice, as well as to changes in the surface energy budget in association with air mass advection, which impact the seasonal sea-ice growth and melt.
The occurrence of storms in the Arctic is typically associated with the passage of transient cyclones. Even though the above described mechanisms how storms/cyclones impact the Arctic sea ice are in principal known, there is a lack of statistical quantification of these effects. In accordance with that, the overarching objective of this thesis is to statistically quantify cyclone impacts on sea-ice concentration (SIC) in the Atlantic Arctic Ocean over the last four decades. In order to further advance the understanding of the related mechanisms, an additional objective is to separate dynamic and thermodynamic cyclone impacts on sea ice and assess their relative importance. Finally, this thesis aims to quantify recent changes in cyclone impacts on SIC. These research objectives are tackled utilizing various data sets, including atmospheric and oceanic reanalysis data as well as a coupled model simulation and a cyclone tracking algorithm.
Results from this thesis demonstrate that cyclones are significantly impacting SIC in the Atlantic Arctic Ocean from autumn to spring, while there are mostly no significant impacts in summer. The strength and the sign (SIC decreasing or SIC increasing) of the cyclone impacts strongly depends on the considered daily time scale and the region of the Atlantic Arctic Ocean. Specifically, an initial decrease in SIC (day -3 to day 0 relative to the cyclone) is found in the Greenland, Barents and Kara Seas, while SIC increases following cyclones (day 0 to day 5 relative to the cyclone) are mostly limited to the Barents and Kara Seas.
For the cold season, this results in a pronounced regional difference between overall (day -3 to day 5 relative to the cyclone) SIC-decreasing cyclone impacts in the Greenland Sea and overall SIC-increasing cyclone impacts in the Barents and Kara Seas. A cyclone case study based on a coupled model simulation indicates that both dynamic and thermodynamic mechanisms contribute to cyclone impacts on sea ice in winter. A typical pattern consisting of an initial dominance of dynamic sea-ice changes followed by enhanced thermodynamic ice growth after the cyclone passage was found. This enhanced ice growth after the cyclone passage most likely also explains the (statistical) overall SIC-increasing effects of cyclones in the Barents and Kara Seas in the cold season.
Significant changes in cyclone impacts on SIC over the last four decades have emerged throughout the year. These recent changes are strongly varying from region to region and month to month. The strongest trends in cyclone impacts on SIC are found in autumn in the Barents and Kara Seas. Here, the magnitude of destructive cyclone impacts on SIC has approximately doubled over the last four decades. The SIC-increasing effects following the cyclone passage have particularly weakened in the Barents Sea in autumn. As a consequence, previously existing overall SIC-increasing cyclone impacts in this region in autumn have recently disappeared. Generally, results from this thesis show that changes in the state of the sea-ice cover (decrease in mean sea-ice concentration and thickness) and near-surface air temperature are most important for changed cyclone impacts on SIC, while changes in cyclone properties (i.e. intensity) do not play a significant role.
The increasing number of known exoplanets raises questions about their demographics and the mechanisms that shape planets into how we observe them today. Young planets in close-in orbits are exposed to harsh environments due to the host star being magnetically highly active, which results in high X-ray and extreme UV fluxes impinging on the planet. Prolonged exposure to this intense photoionizing radiation can cause planetary atmospheres to heat up, expand and escape into space via a hydrodynamic escape process known as photoevaporation. For super-Earth and sub-Neptune-type planets, this can even lead to the complete erosion of their primordial gaseous atmospheres. A factor of interest for this particular mass-loss process is the activity evolution of the host star. Stellar rotation, which drives the dynamo and with it the magnetic activity of a star, changes significantly over the stellar lifetime. This strongly affects the amount of high-energy radiation received by a planet as stars age. At a young age, planets still host warm and extended envelopes, making them particularly susceptible to atmospheric evaporation. Especially in the first gigayear, when X-ray and UV levels can be 100 - 10,000 times higher than for the present-day sun, the characteristics of the host star and the detailed evolution of its high-energy emission are of importance.
In this thesis, I study the impact of stellar activity evolution on the high-energy-induced atmospheric mass loss of young exoplanets. The PLATYPOS code was developed as part of this thesis to calculate photoevaporative mass-loss rates over time. The code, which couples parameterized planetary mass-radius relations with an analytical hydrodynamic escape model, was used, together with Chandra and eROSITA X-ray observations, to investigate the future mass loss of the two young multiplanet systems V1298 Tau and K2-198. Further, in a numerical ensemble study, the effect of a realistic spread of activity tracks on the small-planet radius gap was investigated for the first time. The works in this thesis show that for individual systems, in particular if planetary masses are unconstrained, the difference between a young host star following a low-activity track vs. a high-activity one can have major implications: the exact shape of the activity evolution can determine whether a planet can hold on to some of its atmosphere, or completely loses its envelope, leaving only the bare rocky core behind. For an ensemble of simulated planets, an observationally-motivated distribution of activity tracks does not substantially change the final radius distribution at ages of several gigayears. My simulations indicate that the overall shape and slope of the resulting small-planet radius gap is not significantly affected by the spread in stellar activity tracks. However, it can account for a certain scattering or fuzziness observed in and around the radius gap of the observed exoplanet population.
The icosahedral non-hydrostatic large eddy model (ICON-LEM) was applied around the drift track of the Multidisciplinary Observatory Study of the Arctic (MOSAiC) in 2019 and 2020. The model was set up with horizontal grid-scales between 100m and 800m on areas with radii of 17.5km and 140 km. At its lateral boundaries, the model was driven by analysis data from the German Weather Service (DWD), downscaled by ICON in limited area mode (ICON-LAM) with horizontal grid-scale of 3 km.
The aim of this thesis was the investigation of the atmospheric boundary layer near the surface in the central Arctic during polar winter with a high-resolution mesoscale model. The default settings in ICON-LEM prevent the model from representing the exchange processes in the Arctic boundary layer in accordance to the MOSAiC observations. The implemented sea-ice scheme in ICON does not include a snow layer on sea-ice, which causes a too slow response of the sea-ice surface temperature to atmospheric changes. To allow the sea-ice surface to respond faster to changes in the atmosphere, the implemented sea-ice parameterization in ICON was extended with an adapted heat capacity term.
The adapted sea-ice parameterization resulted in better agreement with the MOSAiC observations. However, the sea-ice surface temperature in the model is generally lower than observed due to biases in the downwelling long-wave radiation and the lack of complex surface structures, like leads. The large eddy resolving turbulence closure yielded a better representation of the lower boundary layer under strongly stable stratification than the non-eddy-resolving turbulence closure. Furthermore, the integration of leads into the sea-ice surface reduced the overestimation of the sensible heat flux for different weather conditions.
The results of this work help to better understand boundary layer processes in the central Arctic during the polar night. High-resolving mesoscale simulations are able to represent temporally and spatially small interactions and help to further develop parameterizations also for the application in regional and global models.
Properties of Arctic aerosol in the transition between Arctic haze to summer season derived by lidar
(2023)
During the Arctic haze period, the Arctic troposphere consists of larger, yet fewer, aerosol particles than during the summer (Tunved et al., 2013; Quinn et al., 2007). Interannual variability (Graßl and Ritter, 2019; Rinke et al., 2004), as well as unknown origins (Stock et al., 2014) and properties of aerosol complicate modeling these annual aerosol cycles. This thesis investigates the modification of the microphysical properties of Arctic aerosols in the transition from Arctic haze to the summer season. Therefore, lidar measurements of Ny-Ålesund from April 2021 to the end of July 2021 are evaluated based on the aerosols’ optical properties. An overview of those properties will be provided. Furthermore, parallel radiosonde data is considered for indication of hygroscopic growth.
The annual aerosol cycle in 2021 differs from expectations based on previous studies from Tunved et al. (2013) and Quinn et al. (2007). Developments of backscatter, extinction, aerosol depolarisation, lidar ratio and color ratio show a return of the Arctic haze in May. The haze had already reduced in April, but regrew afterwards.
The average Arctic aerosol displays hygroscopic behaviour, meaning growth due to water uptake. To determine such a behaviour is generally laborious because various meteorological circumstances need to be considered. Two case studies provide further information on these possible events. In particular, a day with a rare ice cloud and with highly variable water cloud layers is observed.
Late-type stars are by far the most frequent stars in the universe and of fundamental interest to various fields of astronomy – most notably to Galactic archaeology and exoplanet research. However, such stars barely change during their main sequence lifetime; their temperature, luminosity, or chemical composition evolve only very slowly over the course of billions of years. As such, it is difficult to obtain the age of such a star, especially when it is isolated and no other indications (like cluster association) can be used. Gyrochronology offers a way to overcome this problem.
Stars, just like all other objects in the universe, rotate and the rate at which stars rotate impacts many aspects of their appearance and evolution. Gyrochronology leverages the observed rotation rate of a late-type main sequence star and its systematic evolution to estimate their ages. Unlike the above-mentioned parameters, the rotation rate of a main sequence star changes drastically throughout its main sequence lifetime; stars spin down. The youngest stars rotate every few hours, whereas much older stars rotate only about once a month, or – in the case of some late M-stars – once in a hundred days. Given that this spindown is systematic (with an additional mass dependence), it gave rise to the idea of using the observed rotation rate of a star (and its mass or a suitable proxy thereof) to estimate a star’s age. This has been explored widely in young stellar open clusters but remains essentially unconstrained for stars older than the sun, and K and M stars older than 1 Gyr.
This thesis focuses on the continued exploration of the spindown behavior to assess, whether gyrochronology remains applicable for stars of old ages, whether it is universal for late-type main sequence stars (including field stars), and to provide calibration mileposts for spindown models. To accomplish this, I have analyzed data from Kepler space telescope for the open clusters Ruprecht 147 (2.7 Gyr old) and M 67 (4 Gyr). Time series photometry data (light curves)
were obtained for both clusters during Kepler’s K2 mission. However, due to technical limitations and telescope malfunctions, extracting usable data from the K2 mission to identify (especially long) rotation periods requires extensive data preparation.
For Ruprecht 147, I have compiled a list of about 300 cluster members from the literature and adopted preprocessed light curves from the Kepler archive where available. They have been cleaned of the gravest of data artifacts but still contained systematics. After correcting them for said artifacts, I was able to identify rotation periods in 31 of them.
For M 67 more effort was taken. My work on Ruprecht 147 has shown the limitations imposed by the preselection of Kepler targets. Therefore, I adopted the time series full frame image directly and performed photometry on a much higher spatial resolution to be able to obtain data for as many stars as possible. This also means that I had to deal with the ubiquitous artifacts in Kepler data. For that, I devised a method that correlates the artificial flux variations with the ongoing drift of the telescope pointing in order to remove it. This process was a large success and I was able to create light curves whose quality match and even exceede those that were created by the Kepler mission – all while operating on higher spatial resolution and processing fainter stars. Ultimately, I was able to identify signs of periodic variability in the (created) light curves for 31 and 47 stars in Ruprecht 147 and M 67, respectively. My data connect well to bluer stars of cluster of the same age and extend for the first time to stars redder than early-K and older than 1 Gyr. The cluster data show a clear flattening in the distribution of Ruprecht 147 and even a downturn for M 67, resulting in a somewhat sinusoidal shape. With that, I have shown that the systematic spindown of stars continues at least until 4 Gyr and stars continue to live on a single surface in age-rotation periods-mass space which allows gyrochronology to be used at least up to that age. However, the shape of the spindown – as exemplified by the newly discovered sinusoidal shape of the cluster sequence – deviates strongly from the expectations.
I then compiled an extensive sample of rotation data in open clusters – very much including my own work – and used the resulting cluster skeleton (with each cluster forming a rip in color-rotation period-mass space) to investigate if field stars follow the same spindown as cluster stars. For the field stars, I used wide binaries, which – with their shared origin and coevality – are in a sense the smallest possible open clusters. I devised an empirical method to evaluate the consistency between the rotation rates of the wide binary components and found that the vast majority of them are in fact consistent with what is observed in open clusters. This leads me to conclude that gyrochronology – calibrated on open clusters – can be applied to determine the ages of field stars.
The Lyman-𝛼 (Ly𝛼) line commonly assists in the detection of high-redshift galaxies, the so-called Lyman-alpha emitters (LAEs). LAEs are useful tools to study the baryonic matter distribution of the high-redshift universe. Exploring their spatial distribution not only reveals the large-scale structure of the universe at early epochs, but it also provides an insight into the early formation and evolution of the galaxies we observe today. Because dark matter halos (DMHs) serve as sites of galaxy formation, the LAE distribution also traces that of the underlying dark matter. However, the details of this relation and their co-evolution over time remain unclear. Moreover, theoretical studies predict that the spatial distribution of LAEs also impacts their own circumgalactic medium (CGM) by influencing their extended Ly𝛼 gaseous halos (LAHs), whose origin is still under investigation. In this thesis, I make several contributions to improve the knowledge on these fields using samples of LAEs observed with the Multi Unit Spectroscopic Explorer (MUSE) at redshifts of 3 < 𝑧 < 6.
In recent decades, astronomy has seen a boom in large-scale stellar surveys of the Galaxy. The detailed information obtained about millions of individual stars in the Milky Way is bringing us a step closer to answering one of the most outstanding questions in astrophysics: how do galaxies form and evolve? The Milky Way is the only galaxy where we can dissect many stars into their high-dimensional chemical composition and complete phase space, which analogously as fossil records can unveil the past history of the genesis of the Galaxy. The processes that lead to large structure formation, such as the Milky Way, are critical for constraining cosmological models; we call this line of study Galactic archaeology or near-field cosmology.
At the core of this work, we present a collection of efforts to chemically and dynamically characterise the disks and bulge of our Galaxy. The results we present in this thesis have only been possible thanks to the advent of the Gaia astrometric satellite, which has revolutionised the field of Galactic archaeology by precisely measuring the positions, parallax distances and motions of more than a billion stars. Another, though not less important, breakthrough is the APOGEE survey, which has observed spectra in the near-infrared peering into the dusty regions of the Galaxy, allowing us to determine detailed chemical abundance patterns in hundreds of thousands of stars. To accurately depict the Milky Way structure, we use and develop the Bayesian isochrone fitting tool/code called StarHorse; this software can predict stellar distances, extinctions and ages by combining astrometry, photometry and spectroscopy based on stellar evolutionary models. The StarHorse code is pivotal to calculating distances where Gaia parallaxes alone cannot allow accurate estimates.
We show that by combining Gaia, APOGEE, photometric surveys and using StarHorse, we can produce a chemical cartography of the Milky way disks from their outermost to innermost parts. Such a map is unprecedented in the inner Galaxy. It reveals a continuity of the bimodal chemical pattern previously detected in the solar neighbourhood, indicating two populations with distinct formation histories. Furthermore, the data reveals a chemical gradient within the thin disk where the content of 𝛼-process elements and metals is higher towards the centre. Focusing on a sample in the inner MW we confirm the extension of the chemical duality to the innermost regions of the Galaxy. We find stars with bar shape orbits to show both high- and low-𝛼 abundances, suggesting the bar formed by secular evolution trapping stars that already existed. By analysing the chemical orbital space of the inner Galactic regions, we disentangle the multiple populations that inhabit this complex region. We reveal the presence of the thin disk, thick disk, bar, and a counter-rotating population, which resembles the outcome of a perturbed proto-Galactic disk. Our study also finds that the inner Galaxy holds a high quantity of super metal-rich stars up to three times solar suggesting it is a possible repository of old super-metal-rich stars found in the solar neighbourhood.
We also enter into the complicated task of deriving individual stellar ages. With StarHorse, we calculate the ages of main-sequence turn-off and sub-giant stars for several public spectroscopic surveys. We validate our results by investigating linear relations between chemical abundances and time since the 𝛼 and neutron capture elements are sensitive to age as a reflection of the different enrichment timescales of these elements. For further study of the disks in the solar neighbourhood, we use an unsupervised machine learning algorithm to delineate a multidimensional separation of chrono-chemical stellar groups revealing the chemical thick disk, the thin disk, and young 𝛼-rich stars. The thick disk is shown to have a small age dispersion indicating its fast formation contrary to the thin disk that spans a wide range of ages.
With groundbreaking data, this thesis encloses a detailed chemo-dynamical view of the disk and bulge of our Galaxy. Our findings on the Milky Way can be linked to the evolution of high redshift disk galaxies, helping to solve the conundrum of galaxy formation.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
Inverted perovskite solar cells still suffer from significant non-radiative recombination losses at the perovskite surface and across the perovskite/C₆₀ interface, limiting the future development of perovskite-based single- and multi-junction photovoltaics. Therefore, more effective inter- or transport layers are urgently required. To tackle these recombination losses, we introduce ortho-carborane as an interlayer material that has a spherical molecular structure and a three-dimensional aromaticity. Based on a variety of experimental techniques, we show that ortho-carborane decorated with phenylamino groups effectively passivates the perovskite surface and essentially eliminates the non-radiative recombination loss across the perovskite/C₆₀ interface with high thermal stability. We further demonstrate the potential of carborane as an electron transport material, facilitating electron extraction while blocking holes from the interface. The resulting inverted perovskite solar cells deliver a power conversion efficiency of over 23% with a low non-radiative voltage loss of 110 mV, and retain >97% of the initial efficiency after 400 h of maximum power point tracking. Overall, the designed carborane based interlayer simultaneously enables passivation, electron-transport and hole-blocking and paves the way toward more efficient and stable perovskite solar cells.
Anomalous-diffusion, the departure of the spreading dynamics of diffusing particles from the traditional law of Brownian-motion, is a signature feature of a large number of complex soft-matter and biological systems. Anomalous-diffusion emerges due to a variety of physical mechanisms, e.g., trapping interactions or the viscoelasticity of the environment. However, sometimes systems dynamics are erroneously claimed to be anomalous, despite the fact that the true motion is Brownian—or vice versa. This ambiguity in establishing whether the dynamics as normal or anomalous can have far-reaching consequences, e.g., in predictions for reaction- or relaxation-laws. Demonstrating that a system exhibits normal- or anomalous-diffusion is highly desirable for a vast host of applications. Here, we present a criterion for anomalous-diffusion based on the method of power-spectral analysis of single trajectories. The robustness of this criterion is studied for trajectories of fractional-Brownian-motion, a ubiquitous stochastic process for the description of anomalous-diffusion, in the presence of two types of measurement errors. In particular, we find that our criterion is very robust for subdiffusion. Various tests on surrogate data in absence or presence of additional positional noise demonstrate the efficacy of this method in practical contexts. Finally, we provide a proof-of-concept based on diverse experiments exhibiting both normal and anomalous-diffusion.