The aim of this project is to co-estimate models of the core and ionosphere magnetic fields, with the longer-term view of building a 'comprehensive' model of the Earths magnetic field. In this first step we would like to take advantage of the progresses made in the understanding of the ionosphere by global M-I-T modelling to better separate the core and ionospheric signals in satellite data. The magnetic signal generated in the ionosphere is particularly difficult to handle because satellite data provide only information on a very narrow local time window at a time. To get around this difficulty, we would like to apply a technique derived from assimilation methods and that has been already successfully applied in outer-core flow studies. The technique relies on a theoretical model of the ionosphere such as the Upper Atmosphere Model (UAM), where statistics on the deviations from a simple background model are estimated. The derived statistics provided in a covariance matrix format can then be use directly in the magnetic data inversion process to obtain the expected core and ionospheric models. We plan to apply the technique on the German CHAMP satellite data selected for magnetically quiet times. As an output we should obtain a model of the ionospheric magnetic variation field tailored for the selected data and a core-lithosphere field model where possible leakage from ionospheric signals are avoided or at least reduced. The technique can in theory be easily extended to handle the large-scale field generated in the magnetosphere.
Electrical conductivity is a key parameter in models of magnetic field generation in planetary interiors through magneto-hydrodynamic convection. Measurements of this key material parameter of liquid metals is not possible to date by experiments at relevant conditions, and dynamo models rely on extrapolations from low pressure/temperature experiments, or more recently on ab-initio calculations combining molecular dynamics and linear response calculations, using the Kubo-Greenwood formulation of transport coefficients. Such calculations have been performed for Fe, Fe-alloys, H, He and H-He mixtures to cover the interior of terrestrial and giant gas planets. These simulations are computationally expensive, and an efficient accurate scheme to determine electrical conductivities is desirable. Here we propose a model that can, at much lower computational costs, provide this information. It is based on Ziman theory of electrical conductivity that uses information on the liquid structure, combined with an internally consistent model of potentials for the electron-electron, electron-atom, and atom-atom interactions. In the proposal we formulate the theory and expand it to multi-component systems. We point out that fitting the liquid structure factor is the critical component in the process, and devise strategies on how this can be done efficiently. Fitting the structure factor in a thermodynamically consistent way and having a transferable electron-atom potential we can then relatively cheaply predict the electrical conductivity for a wide range of conditions. Only limited molecular dynamics simulations to obtain the structure factors are required.In the proposed project we will test and advance this model for liquid aluminum, a free-electron like metal, that we have studied with the Kubo-Greenwood method previously. We will then be able to predict the conductivities of Fe, Fe-light elements and H, He, as well as the H-He system that are relevant to the planetary interiors of terrestrial and giant gas planets, respectively.
Es werden die spektralen Emissionsgrade (bis 5 Mikro m) brennender Kokspartikel in Oxyfuel-Atmosphären bestimmt. Dazu wird ein neuartiges Spektrometer aufgebaut. Die Messungen werden in einem laminaren Flugstromreaktor durchgeführt, in dem Kohlepartikel unter typischen Oxyfuel-Feuerraumbedingungen abbrennen. Mittels des Spektrometers wird der Emissionsgrad einzelner Kohlenstaubpartikel 'in-flight' gemessen. Hierzu sind kurze Belichtungszeiten erforderlich, die zu geringen Signalstärken führen. Dabei werden Einflussgrößen wie Kohletyp, abnehmende Kohlenstoffkonzentration mit fortschreitendem Ausbrand sowie der Einfluss der Oxyfuel-Reaktionsatmosphäre auf die Kohlepartikeloberfläche und daraus resultierenden Änderungen des Emissionsgrads untersucht.
The magnetosphere of a planet is controlled by a number of factors such as the intrinsic magnetic field, the atmosphere and ionosphere, and the solar wind. Different combinations of these control factors are at work at the terrestrial planets Mercury, Venus, Earth, and Mars, hence they form a very suitable set for quantitative comparative studies. A significant intrinsic dipolar magnetic field is present only on Earth and on Mercury. However, the configuration at Mercury differs considerably from that at Earth because Mercury does not support an atmosphere and ionosphere, the dipolar field is much weaker, the solar wind denser, and the interplanetary magnetic field stronger. Both Mars and Venus have atmospheres but lack a global planetary magnetic field, with regional crustal magnetization being present on Mars. This proposal aims at investigating and comparing electrical current systems in the space environments of terrestrial planets using magnetic vector data collected by orbiting spacecraft such as Venus Express, Mars Global Surveyor, CHAMP (Earth), and MESSENGER (Mercury). We propose to construct data-driven and physically meaningful representations that reveal and quantify the influence of various control factors. To achieve this, we will tailor Empirical Orthogonal Function (EOF) analysis and other multivariate methods to the specifics of planetary magnetic field observations. In contrast to representations that build on predefined functions like spherical harmonics, basis functions in the EOF approach are derived directly from the data. EOFs are designed to extract dominant coherent variations for further interpretation in terms of known physical phenomena, and then, in a regression step, for modeling using suitable control variables. The EOF methodology thus allows quantifying the relative importance of control factors for each planet individually, and thus contributes to the solution of topical science questions. The resulting empirical models will facilitate comparative studies of current systems at the terrestrial planets.
Die Polynya Signature Simulation Method (PSSM) und das Ice Edge Detection (IED)-Verfahren erlauben es, aus Daten des satellitengetragenen Mikrowellenradiometers Special Sensor Microwave/ Imager (SSM/I) Polynjenfläche und Eiskante mit einer Genauigkeit von 100km2 bzw. 10km zu bestimmen. Mit dem PSSM-Verfahren soll die gesamte Polynjenfläche der Antarktis für jeden Tag des Zeitraums 1992-2006 aus SSM/I-Daten mehrerer Satelliten berechnet werden. Dabei ist ab 1995 die Ableitung eines Tageszyklus möglich. Meteorologische Daten sollen in Kombination mit Satellitenmessungen im sichtbaren und infraroten Spektralbereich dazu dienen, für diese Polynjenfläche Eis- und Salzproduktion sowie typische Dicke und Ausdehnung des an die Polynjenfläche angrenzenden dünnen Meereises abzuschätzen. PSSM und IED sollen auf Daten des neuen und feiner auflösenden passiven Mikrowellensensors Advanced Microwave Scanning Radiometer (AMSR/AMSR-E) auf AQUA und ADEOS-2 übertragen werden, um einerseits die minimale Größe detektierbarer Polynjen und Leads herabzusetzen und andererseits die Eiskante mit einer höheren Genauigkeit zu detektieren (4km statt 10km). Die niederfrequenten AMSR(-E)-Kanäle (6.9 und 10.7GHz) sollen hinsichtlich ihrer Nutzung für die Abschätzung der Dicke von dünnem Meereis untersucht werden.
Cherry leaf roll virus (CLRV) is a plant pathogen of economic and ecologic importance. It is globally distributed in a wide range of forest, fruit, and ornamental trees and shrubs. In several areas of cherry and walnut production CLRV causes severe losses in yield and quality. With current reference to the rapid dissemination and strong symptom expression in Finnish birches and the Germany-wide distribution of CLRV in birches and elderberry, we continuously investigate and gradually reveal CLRV transmission pathways as by pollen, seeds or water. However, modes and interactions responsible for the wide intergeneric host transmission as well as for the exceptional CLRV epidemic in Fennoscandia still remain unknown. In this project systematic studies shall investigate biological vectors as a causal agent to finally derive control mechanisms and strategies to avoid new epidemics in different hosts and geographic regions. Detailed monitoring of the invertebrate fauna of birch stands/forests and elderberry plantations in Germany and Finland shall reveal potential vectors to subsequently study them in detail by approved virus detection methods and transmission experiments. Molecular analyses of the CLRV coat protein shall prove its role as a viral determinant for a virus/vector interaction. Consequently, this project essentially will contribute important answers on the CLRV epidemiology, and this will be a key element within the first network of research on plant viral pathogens in forest trees.
Aktuelle wissenschaftliche Studien legen nahe, dass die aktuelle Erderwärmung durch Treibhausgasemissionen hervorgerufen wird, die vom Menschen verursacht sind. Um gegen diese Entwicklung geeignete Maßnahmen ergreifen zu können bzw. um zu überprüfen, ob solche Maßnahmen von Erfolg gekrönt sind, ist es notwendig, die Schadstoffkonzentrationen inklusive der zugehörigen Emissionsquellen genau zu kennen. Diese Informationen sind bisher jedoch sehr lückenhaft und beruhen auf sogenannten 'bottom-up' Berechnungen. Da diese Kalkulationen nicht auf direkten Messungen beruhen, weisen sie große Ungenauigkeiten auf und sind außerdem nicht in der Lage, bisher unbekannte Emissionsquellen zu identifizieren. In dem hier vorgestellten Projekt soll ein mesoskaliges Netzwerk für die Überwachung von Luftschadstoffen wie CO2, CH4, CO, NO2 und O3 aufgebaut werden, das auf dem neuartigen Konzept der differentiellen Säulenmessung beruht. Bei diesem Ansatz wird die Differenz zwischen den Luftsäulen luv- und leewärts einer Stadt gebildet. Diese Differenz ist proportional zu den emittierten Schadstoffen und somit eine Maßzahl für die Emissionen, welche in der Stadt generiert werden.Mithilfe dieser Methode wird es in Zukunft möglich sein, städtische Emissionen über lange Zeiträume hinweg zu überwachen. Damit können neue Informationen über die Generierung und Umverteilung von Luftschadstoffen gewonnen werden. Wir werden u.a. folgende zentrale Fragen beantworten: Wie verhält sich der tatsächliche Trend der CO2, CH4 und NO2 Emissionen in München über mehrere Jahre? Wo sind die Emissions-Hotspots? Wie akkurat sind die bisherigen 'bottom-up' Abschätzungen? Wie effektiv sind die Maßnahmen zur Emissionsreduzierung tatsächlich? Sind vor allem für Methan weitere Maßnahmen zur Reduzierung der Emissionen notwendig? Zu diesem Zweck werden wir ein vollautomatisiertes Messnetzwerk aufbauen und passende Methoden zur Modellierung entwickeln, welche u.a. auf STILT (Stochastic Time-Inverted Lagrangian Transport) und CFD (Computational Fluid Dynamics) basieren. Mithilfe der Modellierungsresultate werden wir eine Strategie entwerfen, wie städtische Netzwerke zur Überwachung von Luftschadstoffen aufgebaut werden müssen, um repräsentative Ergebnisse zu erhalten. Außerdem können mit den so gewonnenen städtischen Emissionszahlen z.B. dem Stadtreferat, den Stadtwerken München oder der Bayerischen Staatsregierung Möglichkeiten zur Beurteilung der Effektivität der angewandten Klimaschutzmaßnahmen an die Hand gegeben werden. Das hier vorgestellte Messnetzwerk dient somit als Prototyp, um die grundlegenden Fragen zum Aufbau eines solchen Sensornetzwerks zu klären, damit objektive Aussagen zu städtischen Emissionen möglich werden. Dieses Projekt ist weltweit einmalig und wird zukunftsweisende Ergebnisse liefern.
Bamboos (Poaceae) are widespread in tropical and subtropical forests. Particularly in Asia, bamboos are cultivated by smallholders and increasingly in large plantations. In contrast to trees, reliable assessments of water use characteristics for bamboo are very scarce. Recently we tested a set of methods for assessing bamboo water use and obtained first results. Objectives of the proposed project are (1) to further test and develop the methods, (2) to compare the water use of different bamboo species, (3) to analyze the water use to bamboo size relationship across species, and (4) to assess effects of bamboo culm density on the stand-level transpiration. The study shall be conducted in South China where bamboos are very abundant. It is planned to work in a common garden (method testing), a botanical garden (species comparison, water use to size relationship), and on-farm (effects of culm density). Method testing will include a variety of approaches (thermal dissipation probes, stem heat balance, deuterium tracing and gravimetry), whereas subsequent steps will be based on thermal methods. The results may contribute to an improved understanding of bamboo water use characteristics and a more appropriate management of bamboo with respect to water resources.
Comprehension of belowground competition between plant species is a central part in understanding the complex interactions in intercropped agricultural systems, between crops and weeds as well as in natural ecosystems. So far, no simple and rapid method for species discrimination of roots in the soil exists. We will be developing a method for root discrimination of various species based on Fourier Transform Infrared (FTIR)-Attenuated Total Reflexion (ATR) Spectroscopy and expanding its application to the field. The absorbance patterns of FTIR-ATR spectra represent the chemical sample composition like an individual fingerprint. By means of multivariate methods, spectra will be grouped according to spectral and chemical similarity in order to achieve species discrimination. We will investigate pea and oat roots as well as maize and barnyard grass roots using various cultivars/proveniences grown in the greenhouse. Pea and oat are recommendable species for intercropping to achieve superior grain and protein yields in an environmentally sustainable manner. To evaluate the effects of intercropping on root distribution in the field, root segments will be measured directly at the soil profile wall using a mobile FTIR spectrometer. By extracting the main root compounds (lipids, proteins, carbohydrates) and recording their FTIR-ATR spectra as references, we will elucidate the chemical basis of species-specific differences.
The aim of this project is to develop a methodology to quantify the magnitudes and frequencies of individual surface change processes of a rock glacier over several years. We do this by analyzing three dimensional (3D) surface change based on high-resolution, high-frequency and multisource LiDAR data. The derived information will enable us to develop methods to automatically characterize and disaggregate multiple processes and mechanisms that contribute to surface change signals derived from less frequent monitoring (e.g. yearly). Such methods can enhance our general understanding of the spatial and temporal variability of rock glacier deformation and the interaction of rock glaciers with connected environmental systems.
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