In the Earth, the dynamo action is strongly linked to core freezing. There is a solid inner core, the growth of which provides a buoyancy flux that drives the dynamo. The buoyancy in this case derives from a difference in composition between the solid inner core and the fluid outer core. In planetary bodies smaller than the Earth, however, this core differentiation process may differ - Fe may precipitate at the core-mantle boundary (CMB) rather than in the center and may fall as iron snow and initially remelt with greater depth. A chemical stable sedimentation zone develops that comprises with time the entire core - at that time a solid inner core starts to grow. The dynamics of this system is not well understood and also whether it can generate a magnetic field or not. The Jovian moon Ganymede, which shows a present-day magnetic dipole field, is a candidate for which such a scenario has been suggested. We plan to study this Fe-snow regime with both a numerical and experimental approach. In the numerical study, we use a 2D/3D thermo-chemical convection model that considers crystallization and sinking of iron crystals together with the dynamics of the liquid core phase (for the 3D case the influence of the rotation of the Fe snow process is further studied).The numerical calculations will be complemented by two series of experiments: (1) investigations in metal alloys by means of X-ray radioscopy, and (2) measurements in transparent analogues by optical techniques. The experiments will examine typical features of the iron snow regime. On the one hand they will serve as a tool to validate the numerical approach and on the other hand they will yield important insight into sub-processes of the iron snow regime, which cannot be accessed within the numerical approach due to their complexity.
To overcome the limitation in spatial and temporal resolution of methane oceanic measurements, sensors are needed that can autonomously detect CH4-concentrations over longer periods of time. The proposed project is aimed at:- Designing molecular receptors for methane recognition (cryptophane-A and -111) and synthesizing new compounds allowing their introduction in polymeric structure (Task 1; LC, France); - Adapting, calibrating and validating the 2 available optical technologies, one of which serves as the reference sensor, for the in-situ detection and measurements of CH4 in the marine environments (Task 2 and 3; GET, LAAS-OSE, IOW) Boulart et al. (2008) showed that a polymeric filmchanges its bulk refractive index when methane docks on to cryptophane-A supra-molecules that are mixed in to the polymeric film. It is the occurrence of methane in solution, which changes either the refractive index measured with high resolution Surface Plasmon Resonance (SPR; Chinowsky et al., 2003; Boulart et al, 2012b) or the transmitted power measured with differential fiber-optic refractometer (Boulart et al., 2012a; Aouba et al., 2012).- Using the developed sensors for the study of the CH4 cycle in relevant oceanic environment (the GODESS station in the Baltic Sea, Task 4 and 5; IOW, GET); GODESS registers a number of parameters with high temporal and vertical resolution by conducting up to 200 vertical profiles over 3 months deployment with a profiling platform hosting the sensor suite. - Quantifying methane fluxes to the atmosphere (Task 6); clearly, the current project, which aims at developing in-situ aqueous gas sensors, provides the technological tool to achieve the implementation of ocean observatories for CH4. The aim is to bring the fiber-optic methane sensor on the TRL (Technology Readiness Level) from their current Level 3 (Analytical and laboratory studies to validate analytical predictions) - to the Levels 5 and 6 (Component and/or basic sub-system technology validation in relevant sensing environments) and compare it to the SPR methane sensor, taken as the reference sensor (current TRL 5). This would lead to potential patent applications before further tests and commercialization. This will be achieved by the ensemble competences and contributions from the proposed consortium in this project.
Zielsetzung: Angesichts der drängenden Herausforderungen des Klimawandels stehen Museen zunehmend in der Verantwortung, nachhaltige und klimaschonende Praktiken nicht nur im Rahmen ihres Ausstellungsprogramms aufzuzeigen, sondern auch innerhalb der eigenen Organisations- und Arbeitsstrukturen fest zu verankern. Besonders im Fokus steht dabei der Umgang mit Ressourcen und hier vor allem die Ausstellungsproduktion - einem zentralen Kernprozess. Denn gerade da zeigt sich derzeit noch ein überwiegend linearer Ablauf: Neue Möbel, Technik und Baustoffe werden gekauft, (unregelmäßig) genutzt und am Ende entsorgt. Am Ende einer Ausstellung steht daher nicht selten ein Container vor der Tür - Sinnbild dafür, dass Veränderung dringend notwendig ist. Genau hier wollen wir ansetzen und den linearen Produktionsmodus in allen teilnehmenden Institutionen in einen kreislauffähigen Prozess überführen. Das bedeutet, vorhandene Materialien systematisch zu erfassen, zirkulieren zu lassen, die Wieder- und Weiterverwendung planerisch zu berücksichtigen und kreislaufbezogene Praktiken institutionell zu verankern. Nur so kann eine nachhaltige Reduktion von Ressourcenverbrauch und Abfallaufkommen erreicht und zugleich ein zukunftsfähiges Produktionsmodell für Museen etabliert werden. Eine umfassende Datenbank (“Materialpool/Sharingplattform” - unser Arbeitstitel „Museumloop“) ist der Schlüssel zur effizienten Nutzung des bereits vorhandenen Ausstellungsinventars der teilnehmenden Institutionen. Sie soll dabei helfen, das vorhandene Material wie Möbel oder Medientechnik zu erfassen und Leihvorgänge über institutionelle Grenzen hinweg ermöglichen. Ganz im Sinne einer Sharing-Economy können Museen so ihre Bestände besser nutzen, Kosten durch das Vermeiden von Neuanschaffungen senken sowie den eigenen Ressourcenverbrauch und damit ihren ökologischen Fußabdruck reduzieren.
This project aims at the improvement and testing of a modeling tool which will allow the simulation of impacts of on-going and projected changes in land use/ management on the dynamic exchange of C and N components between diversifying rice cropping systems and the atmosphere and hydrosphere. Model development is based on the modeling framework MOBILE-DNDC. Improvements of the soil biogeochemical submodule will be based on ICON data as well as on results from published studies. To improve simulation of rice growth the model ORYZA will be integrated and tested with own measurements of crop biomass development and transpiration. Model development will be continuously accompanied by uncertainty assessment of parameters. Due to the importance of soil hydrology and lateral transport of water and nutrients for exchange processes we will couple MOBILE-DNDC with the regional hydrological model CMF (SP7). The new framework will be used at field scale to demonstrate proof of concept and to study the importance of lateral transport for expectable small-scale spatial variability of crop production, soil C/N stocks and GHG fluxes. Further application of the coupled model, including scenarios of land use/ land management and climate at a wider regional scale, are scheduled for Phase II of ICON.
Water, carbon and nitrogen are key elements in all ecosystem turnover processes and they are related to a variety of environmental problems, including eutrophication, greenhouse gas emissions or carbon sequestration. An in-depth knowledge of the interaction of water, carbon and nitrogen on the landscape scale is required to improve land use and management while at the same time mitigating environmental impact. This is even more important under the light of future climate and land use changes.In the frame of the proposal 'Uncertainty of predicted hydro-biogeochemical fluxes and trace gas emissions on the landscape scale under climate and land use change' we advocate the development of fully coupled, process-oriented models that explicitly simulate the dynamic interaction of water, carbon and nitrogen turnover processes on the landscape scale. We will use the Catchment Modelling Framework CMF, a modular toolbox to implement and test hypothesis of hydrologic behaviour and couple this to the biogeochemical LandscapeDNDC model, a process-based dynamic model for the simulation of greenhouse gas emissions from soils and their associated turnover processes.Due to the intrinsic complexity of the models in use, the predictive uncertainty of the coupled models is unknown. This predictive (global) uncertainty is composed of stochastic and structural components. Stochastic uncertainty results from errors in parameter estimation, poorly known initial states of the model, mismatching boundary conditions or inaccuracies in model input and validation data. Structural uncertainty is related to the flawed or simplified description of natural processes in a model.The objective of this proposal is therefore to quantify the global uncertainty of the coupled hydro-biogeochemical models and investigate the uncertainty chain from parameter uncertainty over forcing data uncertainty up the structural model uncertainty be setting up different combinations of CMF and LandscapeDNDC. A comprehensive work program has been developed structured in 4 work packages, that consist of (1) model set up, calibration and uncertainty assessment on site scale followed by (2) an application and uncertainty assessment of the coupled model structures on regional scale, (3) global change scenario analyses and finally (4) evaluating model results in an ensemble fashion.Last but not least, a further motivation of this proposal is to provide project results in a manner that they support planning and decision taking under uncertainty, as this proposal is part of the package proposal on 'Methodologies for dealing with uncertainties in landscape planning and related modelling'.
Rocket launches for space missions are well-defined ground-truth events generating strong infrasonic signatures. This data set covers ground-truth information for 1001 rocket launches from 27 global spaceports between 2009 and mid-2020. Infrasound signatures from up to 73% of the launches were identified at infrasound arrays of the International Monitoring System. The detection parameters were obtained using the Progressive Multi-Channel Correlation (PMCC) algorithm. Propagation and quality parameters supplement the PMCC detection parameters in this dataset. The results are provided for further use as a ground-truth reference in geophysical and atmospheric research. The open-access publication “1001 Rocket Launches for Space Missions and their Infrasonic Signature” (Pilger et al., 2021, Geophys. Res. Letters, doi:10.1029/2020GL092262) provides further details on this data set. Data format: The data are provided both as ASCII files (separate lists of infrasound signatures and rocket launch events, plus README files) and as a comprehensive netCDF file.
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