Die ständige Weiterentwicklung und Verbesserung der Wetter- und Klimamodelle stellt die Fernerkundung der Atmosphäre vor große Herausforderungen. Für die Evaluierung der Modelle werden immer besser aufgelöste Messungen und Methoden benötigt. Herkömmliche Ansätze scheitern hier vor allem an fehlenden kontinuierlichen Beobachtungen der Temperatur und Feuchte bei allen Wetterbedingungen und insbesondere bei Regen. Ein Windprofiler ist allerdings auch bei solchen Bedingungen in der Lage Vertikalinformationen der Temperatur- und Feuchtegradienten zu messen. Der hier vorgeschlagene neuartige Ansatz aus einer Synergie aus Windprofiler (inklusive Radio Acoustic Sounding System), Ramanlidar, Mikrowellenradiometer und Wolkenradar ermöglicht eine automatisierte und kontinuierliche Erstellung von Temperatur- und Feuchteprofilen sogar bei Niederschlägen. Die zu verwendende variationelle Methode (optimale Schätzung, in engl. â€Ìoptimal estimationâ€Ì) bietet dabei ein robustes Hilfsmittel für die Kombination mehrerer Messgeräte unter Einbeziehung der Unsicherheiten der einzelnen Systeme. Bei der optimalen Schätzung wird ein vorgegebener Anfangszustand (z.B. die Klimatologie des Standorts oder der letzte bekannte Zustand) so lange iterativ variiert, bis er mit den Beobachtungen der verschiedenen Messgeräte innerhalb der Unsicherheiten übereinstimmt. Die Methode ermöglicht auch eine ausführliche Analyse der Unsicherheiten der Resultate und eine Einschätzung der Beiträge der einzelnen Geräte.Die langen Zeitreihen an Daten und die Kombination an sich ergänzenden Messinstrumenten, insbesondere mit dem 482 MHz Windprofiler am Meteorologischen Observatorium Lindenberg â€Ì Richard Aßmann Observatorium (MOL-RAO), sind einzigartig. Der Antragsteller kann hier seine umfangreichen Erfahrungen mit Instrumentensynergie und der Entwicklung von Algorithmen zur Ableitung atmosphärischer Variablen einbringen, um eine kontinuierliche Zeitreihe von Temperatur- und Feuchteprofilen mit bisher nicht erreichter Genauigkeit innerhalb und oberhalb von Wolken und insbesondere bei Niederschlag zu erstellen. Die thermodynamischen Profile bieten die ideale Möglichkeit, die Verdunstungsraten und die daraus resultierende Abkühlung mit einer verbesserten Genauigkeit zu quantifizieren. Die Unsicherheiten, die durch ungenaue Profile der relativen Feuchte und Temperatur entstehen, werden mit Hilfe von Simulationen abgeschätzt. Langzeitbeobachtungen an MOL-RAO werden genutzt, um aussagekräfige Statistiken über die Verdunstungs- und Abkühlungsraten zu erstellen. Die Ergebnisse werden für verschiedene Bedingungen wie stratiformen und konvektiven Niederschlag und für verschiedenen Jahreszeiten evaluiert. Dies wird den Modellieren helfen, die Parametrisierungen der Verdunstungsraten in kleinskaligen Modellen zu evaluieren.
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.
Boron (B) is an essential microelement for plants. Despite the use of modern fertilization methods, B deficiency still causes losses in agricultural plant production. Even though many positive effects of B on plant growth and physiology have been reported, a large majority of B functions and the regulatory mechanisms controlling the B nutritional status remain unknown. The main objective of this project is to elucidate how the greatly B deficiency-sensitive Brassica crop plants process and regulate their B status during vegetative and reproductive growth. In this context, the project aims at identifying the mode of action of B in mechanisms regulating the B status itself and uncovering those mechanisms contributing to B efficiency in different genotypes. Plant species subjected to investigation will be the agronomically important oilseed and vegetable plant Brassica napus (rapeseed) and its close relative the genetic and molecular model plant Arabidopsis thaliana. Questions addressed within the scope of this project should lead to a detailed understanding of mechanisms controlling B uptake and allocation from the level of the whole plant down to the cellular level. B transport routes and rates will be determined in sink- and source tissues and in developmental periods with a particularly high B demand. A special focus will be on the identification of B transport bottlenecks and the analysis of B deficiency-sensitive transport processes to and within the highly B-demanding reproductive organs. Recent studies in Arabidopsis suggest that Nodulin26-like Intrinsic Proteins (NIPs), which belong to the aquaporin channel protein family, are essential for plant B uptake and distribution. The systematic focus on the molecular and physiological characterization of B. napus NIPs will clarify their role in B transport and will identify novel NIP-associated mechanisms playing key roles in the B response network.To further resolve the mostly unknown impact of the B nutritional status on gene regulation and metabolism, a transcript and metabolite profile of B-sufficient and B-deficient rapeseed plants will be generated. Additionally, an Arabidopsis transcription factor knockout collection (greater 300 lines) will be screened for abnormalities in responses to the B nutritional status. This will identify yet unknown B-responsive genes (transcription factors and their targets) and gene products (enzymes or metabolite variations) playing key roles in signalling pathways and mechanisms regulating the B homeostasis. Boron (in form of boric acid) and arsenite (As) share in all likelihood the same NIP-mediated transport pathways. To assess the consequences of this dual transport pathway the so far unstudied impact of the plants B nutritional status on the accumulation and distribution of As will be investigated in B. napus. Moreover, the current dimension of the As contamination of Brassica-based food products, to which consumers are exposed to, will be analyzed. usw.
We study the effects of plants and root-associated fungi on wind erosion within the alpine environment of Tibet. China is one of the countries most affected by desertification processes and Tibet, in particular, a key region in desertification combat. The presented project focuses on the Barkha Plain surrounded by Mount Kailash and the Lake of Manasarovar (Ngari Prefecture). This Western Tibet region experienced little scientific attention but, nowadays, faces rapidly increasing touristic activities and expanding local settlements associated with socio-economic changes that are serious threats to the delicate ecological balance and potential triggers of desertification. It exists almost unanimous agreement that revegetation is the most efficient and promising strategy to combat wind erosion and desertification in the long term. However, re-colonising success is often poor, mainly under extreme environmental conditions. Compared to conventional practices, the approach of the presented project attains better accordance with natural succession processes and promises acceleration of both plant and soil development and, conclusively, more efficient desertification control. The project assesses the potential of native plants and symbiotic fungi to control wind erosion and desertification processes. It aims to identify key plants and fungi that increase soil aggregate stability and efficiently drive succession into a natural and self-maintaining cycle of the ecosystem. Furthermore, it provides crucial information for implementing environmentally compatible and cost-effective measures to protect high-elevation ecosystems against desertification. Within three successional stages (early, intermediate, late), field investigations are performed on the basis of Modified-Whittaker plots. Classic methods of vegetation analysis and myco-sociology are combined with analysis of distribution patterns at different scales (patchiness, connectivity). Comprehensive soil analysis is performed comprising grain size distribution, aggregate stability, pH as well as water and nutrient contents. Additionally, important parameters of wind erosion are measured concurrently and continuously to assess their magnitude and variability with respect to vegetation and soil at different levels of development. The parameters addressed, include sediment transport, air temperature, radiation, precipitation, relative humidity as well as speed and direction of wind. Surface moisture is recorded periodically and roughness described. Species and environmental parameters are checked for spatial correlation. Cutting edge technologies are applied in laboratory work, comprising molecular methods for fungal species identification and micro-tomography to analyse soil structure. Furthermore, successfully cultivated fungi and plants are subject of synthesis experiments and industrial propagation in view of practical implementation in restoration measures.
Das Hauptziel des Projekts ist die Untersuchung und die Entwicklung von Methoden nicht nur zur punktuellen, sondern auch zur flächenhaften Bestimmung der Bodenfeuchte. Zur Anwendung sollen Geländetechniken wie Time-Domain Reflectrometry (TDR), Georadar (GPR), Elektrische Widerstand (ER), Elektromagnetische Induktion (EMI) sowie GNSS Scatterometry kommen. Eine der methodischen Hauptfragen ist die Nutzung der GNSS Scatterometry zur Ermittlung der Bodenfeuchte im Feldmaßstab. Eine weitere grundlegende Forschungsfrage wird die weitere Entwicklung der elektrischen und elektromagnetischen geophysikalischen Techniken für bodenkundliche Anwendungen sein.
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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