Refine
Year of publication
Document Type
- Article (32)
- Postprint (8)
- Other (2)
- Conference Proceeding (1)
- Review (1)
Is part of the Bibliography
- yes (44)
Keywords
- Climate change (3)
- ancient DNA (3)
- permafrost (3)
- thermokarst (3)
- Arctic lakes (2)
- drained lake basins (2)
- lake drainage (2)
- permafrost regions (2)
- thermokarst lakes (2)
- Alaska (1)
Institute
- Institut für Geowissenschaften (17)
- Institut für Biochemie und Biologie (13)
- Mathematisch-Naturwissenschaftliche Fakultät (4)
- Extern (3)
- Institut für Physik und Astronomie (2)
- Department Psychologie (1)
- Hasso-Plattner-Institut für Digital Engineering GmbH (1)
- Institut für Chemie (1)
- Institut für Ernährungswissenschaft (1)
- Institut für Informatik und Computational Science (1)
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.
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
Sea level rise and coastal erosion have inundated large areas of Arctic permafrost. Submergence by warm and saline waters increases the rate of inundated permafrost thaw compared to sub-aerial thawing on land. Studying the contact between the unfrozen and frozen sediments below the seabed, also known as the ice-bearing permafrost table (IBPT), provides valuable information to understand the evolution of sub-aquatic permafrost, which is key to improving and understanding coastal erosion prediction models and potential greenhouse gas emissions. In this study, we use data from 2D electrical resistivity tomography (ERT) collected in the nearshore coastal zone of two Arctic regions that differ in their environmental conditions (e.g., seawater depth and resistivity) to image and study the subsea permafrost. The inversion of 2D ERT data sets is commonly performed using deterministic approaches that favor smoothed solutions, which are typically interpreted using a user-specified resistivity threshold to identify the IBPT position. In contrast, to target the IBPT position directly during inversion, we use a layer-based model parameterization and a global optimization approach to invert our ERT data. This approach results in ensembles of layered 2D model solutions, which we use to identify the IBPT and estimate the resistivity of the unfrozen and frozen sediments, including estimates of uncertainties. Additionally, we globally invert 1D synthetic resistivity data and perform sensitivity analyses to study, in a simpler way, the correlations and influences of our model parameters. The set of methods provided in this study may help to further exploit ERT data collected in such permafrost environments as well as for the design of future field experiments.
The global warming potential of nitrous oxide (N2O) and its long atmospheric lifetime mean its presence in the atmosphere is of major concern, and that methods are required to measure and reduce emissions. Large spatial and temporal variations means, however, that simple extrapolation of measured data is inappropriate, and that other methods of quantification are required. Although process-based models have been developed to simulate these emissions, they often require a large amount of input data that is not available at a regional scale, making regional and global emission estimates difficult to achieve. The spatial extent of organic soils means that quantification of emissions from these soil types is also required, but will not be achievable using a process-based model that has not been developed to simulate soil water contents above field capacity or organic soils. The ECOSSE model was developed to overcome these limitations, and with a requirement for only input data that is readily available at a regional scale, it can be used to quantify regional emissions and directly inform land-use change decisions. ECOSSE includes the major processes of nitrogen (N) turnover, with material being exchanged between pools of SOM at rates modified by temperature, soil moisture, soil pH and crop cover. Evaluation of its performance at site-scale is presented to demonstrate its ability to adequately simulate soil N contents and N2O emissions from cropland soils in Europe. Mitigation scenarios and sensitivity analyses are also presented to demonstrate how ECOSSE can be used to estimate the impact of future climate and land-use change on N2O emissions.