In hydrology, the relationship between water storage and flow is still fundamental in characterizing and modeling hydrological systems. However, this simplification neglects important aspects of the variability of the hydrological system, such as stable or instable states, tipping points, connectivity, etc. and influences the predictability of hydrological systems, both for extreme events as well as long-term changes. We still lack appropriate data to develop theory linking internal pattern dynamics and integral responses and therefore to identify functionally similar hydrological areas and link this to structural features. We plan to investigate the similarities and differences of the dynamic patterns of state variables and the integral response in replicas of distinct landscape units. A strategic and systematic monitoring network is planned in this project, which contributes the essential dynamic datasets to the research group to characterize EFUs and DFUs and thus significantly improving the usual approach of subdividing the landscape into static entities such as the traditional HRUs. The planned monitoring network is unique and highly innovative in its linkage of surface and subsurface observations and its spatial and temporal resolution and the centerpiece of CAOS.
Although global pesticide use increases steadily, our field-data based knowledge regarding exposure of non-target ecosystems is very restricted. Consequently, this meta-analysis will for the first time evaluate the worldwide available peer-reviewed information on agricultural insecticide concentrations in surface water or sediment and test the following two hypotheses: I) Insecticide concentrations in the field largely exceed regulatory threshold levels and II) Additional factors important for threshold level exceedances can be quantified using retrospective meta-analysis. A feasibility study using a restricted dataset (n = 377) suggested the significance of the expected results, i.e. an threshold level exceedance rate of more than 50Prozent of the detected concentrations. Subsequent to a comprehensive database search in the peer-reviewed literature of the past 60 years, analysis of covariance with the relevant threshold level exceedance as the continuous dependent variable (about 10,000 cases) will be performed and the impact of significant predictor variables will be quantified. Parameters not yet considered in pesticide exposure assessment will be included as independent variables, such as compound class, environmental regulatory quality, and sampling design. The simultaneous presence of several insecticide compounds as a well as their metabolites will also be considered in the evaluation. The present approach may provide an innovative and integrated view on the potential environmental side effects of global high-intensity agriculture and in particular of pesticides use.
The formation of biogeochemical interfaces in soils is controlled, among other factors, by the type of particle surfaces present and the assemblage of organic matter and mineral particles. Therefore, the formation and maturation of interfaces is studied with artificial soils which are produced in long-term biogeochemical laboratory incubation experiments (3, 6, 12, 18 months. Clay minerals, iron oxides and charcoal are used as major model components controlling the formation of interfaces because they exhibit high surface area and microporosity. Soil interface characteristics have been analyzed by several groups involved in the priority program for formation of organo-mineral interfaces, sorptive and thermal interface properties, microbial community structure and function. Already after 6 months of incubation, the artificial soils exhibited different properties in relation to their composition. A unique dataset evolves on the development and the dynamics of interfaces in soil in the different projects contributing to this experiment. An integrated analysis based on a conceptual model and multivariate statistics will help to understand overall processes leading to the biogeochemical properties of interfaces in soil, that are the basis for their functions in ecosystems. Therefore, we propose to establish an integrative project for the evaluation of data obtained and for publication of synergistic work, which will bring the results to a higher level of understanding.
Die Geosuche ist ein Webservice, welcher über die EGovernment-Basiskomponente Geodaten (GeoBAK) bereitgestellt wird. Die Geosuche ermöglicht eine multikriterielle Recherche nach ausgewählten Geobasisdaten und Geofachdaten, Geoinformationen (Metadaten) sowie Portalinhalten (Webseiten, Dokumente). Sie ist zentraler Bestandteil des Geoportals Sachsenatlas und als Freie Suche bzw. Volltextsuche ausgelegt. Die Umsetzung der Suche im Geoportal als singuläres Suchfeld (Omnibox, Einfeldsuche) analog zu bekannten Internetsuchmaschinen, ermöglicht einen schnellen Einstieg der Nutzer. Die Geosuche ermöglicht im Gegensatz zu standardisierten OGC-Geodatendiensten wie z.B. OGC-WFS-Gazetteer eine performanceoptimierte Recherche, welche nicht nur auf Geodaten beschränkt ist. Die Geosuche ermöglicht aufgrund der Filter- und Sortiermöglichkeiten die Umsetzung von über die Einfeldsuche hinausgehenden Recherchemöglichkeiten. Im Geoportal ist dies über die erweiterte Suche mit z.B. räumlicher und zeitlicher Auswahlmöglichkeit umgesetzt. Weiterhin sind einzelne Objekte untereinander verknüpft. Damit ist beispielsweise die Recherche nach allen Hausnummern einer Straße möglich (Drilldown). Die Umsetzung von Formularen mit Auswahllisten für eine Recherche, die die Geosuche aufrufen, ist möglich.
As summarised in the 4th IPCC report, the indirect effect of aerosols on cloud properties constitutes the single largest remaining uncertainty in the climate system. In this project, we propose to make use of a uniquely comprehensive set of observations, in combination with detailed microphysical modelling, to develop accurate ice nucleation parameterisations for different types of aerosol in mixed-phase clouds. Further, we will use the combination of a detailed microphysical box model and a highly resolved three-dimensional model (the weather research and forecasting model, WRF) with spectral bin microphysics, to determine which dynamical processes need to be accounted for, in order to accurately represent the cloud microphysical properties. One of our main objectives in this work, which makes this project novel and original, is to contribute to the resolution of the recent controversy surrounding the efficiency of black carbon aerosol as an ice nucleus. The development of model parameterisations of ice nucleation in clouds is often hampered by the necessity to base the parameterisations on idealised laboratory experiments, and by the paucity of cloud microphysical measurements suitable for model validation. However, this project is in a unique position to benefit from several observational data sets gathered during recent measurement campaigns. The observations on which we will base the modelling work are performed at the high altitude Swiss research station on the Jungfraujoch and provide a highly detailed description of the physical and chemical properties of the ice nucleating aerosol particles in ambient clouds. In addition, they describe the microphysical properties of the observed clouds. The measured aerosol properties give us the benefit of being able to initialise the models with the actual aerosol found in the clouds, rather than an idealised background aerosol derived from emission inventories or large scale models. The observed cloud microphysical properties will allow us to constrain and validate the model simulations in exceptional detail. The models will be tested in their original form, with their existing microphysical parameterisations, and these will then be further developed until the models can represent the observed cloud properties. Special attention will be given to the roles of black carbon (BC) aerosol, because of its anthropogenic source, and the uncertainty surrounding its activity as an ice nucleus (IN) and to mineral dust, because of its high IN activity. We will further use the combination of models and observations to try to identify other important IN components in the observed aerosol, such as biogenic particles or organic species. (...)
Objective: Integrated assessment and energy-economy models have become central tools for informing long-term global and regional climate mitigation strategies. There is a large demand for improved representations of complex system interactions and thorough validation of model behaviour in order to increase user confidence in climate policy assessments. ADVANCE aims to respond to this demand by facilitating the development of a new generation of integrated assessment models. This will be achieved by substantial progress in key areas where model improvements are greatly needed: end use and energy service demand; representation of heterogeneity, behaviour, innovation and consumer choices; technical change and uncertainty; system integration, path dependencies and resource constraints; and economic impacts of mitigation policies. In the past, methodological innovations and improvements were hindered by the unavailability of suitable input data. The ADVANCE project will make a large and coordinated effort to generate relevant datasets. These datasets, along with newly developed methodologies, will be made available to the broader scientific community as open-access resources. ADVANCE will also put a focus on improved model transparency, model validation, and data handling. A central objective of ADVANCE is to evaluate and to improve the suitability of models for climate policy impact assessments. The improved models will be applied to an assessment of long-term EU climate policy in a global context, and disseminated to the wider community. The ADVANCE consortium brings together long-standing expertise in integrated assessment and energy-economy modelling with a strong expertise in material flows, energy system integration, and energy service demand.
Quantitative Precipitation Forecast (QPF) is one of the major challenges in numerical weather prediction (NWP). This is true for QPF ranging from synoptic-scale to small-scale convection. The main goal of this proposal is to improve the short-range QPF on scales of a few hundred km and a few hours. To achieve a significant improvement of QPF on these scales the atmospheric variables, which are representing the pre-convective conditions, need to be determined. Hence an innovative combination of data assimilation techniques and observations is proposed. Within this project, 4D water vapour, as well as wind and cloud data are considered. The focus is on advanced observing systems with high future potential such as GPS, lidar, passive remote sensing from geostationary satellites as well as novel in-situ sensors. Different state-of-the-art assimilation techniques will be compared to find the optimal approach to improve QPF. After the development of suitable observation operators, the optimal use of advanced remote sensing systems will be investigated using various Observing System Experiments (OSE's) and Observing System Simulation Experiments (OSSE's). To quantify the success, model independent data sets inferred from MSG/radar, GPS, and an innovative sounding system will be used for validation.
Satellite measurements strongly contribute to the understanding of the processes related to stratospheric ozone loss, e.g. by global and long term monitoring of ozone and its depleting substances. For instance, measurements performed in limb geometry by SCIAMACHY on ENVISAT largely improved the knowledge about the vertical distribution of species like BrO and OClO only recently. However, there are still important open questions, like e.g. the chlorine activation processes on different kinds of aerosols and polar stratospheric clouds. Also, the role of very short lived species in the stratospheric bromine budget or the effects of a possible enhancement of the Brewer-Dobson circulation are not fully understood.Globally, the vertical distribution of ozone depleting species varies significantly in space and time due to solar illumination, atmospheric chemistry and transport. Especially strong gradients occur near the twilight zone or across stratospheric transport barriers (polar vortex boundary, subtropical transport barriers). These regions are of particular importance for chemistry and transport of the lower stratosphere and upper troposphere, since they separate air masses on large scales but also enable exchange between them.Standard 1-D profile retrievals, which assume horizontal homogeneity, result in large systematic biases due to neglecting the effect of horizontal gradients on the measurement. We propose to develop, improve and apply a tomographic profile retrieval algorithm, which optimally combines the information provided by the SCIAMACHY limb and nadir measurements. An improved global dataset of 3D stratospheric profiles for NO2, BrO and OClO for the 10 years of the SCIAMACHY mission (2002-2012) will be developed, compared to atmospheric chemistry simulations and applied to selected questions of atmospheric science. The dataset developed in this project will be very useful for investigating the complex interplay of stratospheric chemistry and transport processes, and will help to reduce the uncertainties in the distribution of ozone depleting species, in particular for regions with large horizontal inhomogeneity.
The HGF Alliance 'Remote Sensing and Earth System Dynamics' aims at the development and evaluation of novel bio/geo-physical information products derived from data acquired by a new generation of remote sensing satellites; and their integration in Earth system models for improving understanding and modelling ability of global environmental processes and ecosystem change. The Earth system comprises a multitude of processes that are intimately meshed through complex interactions. In times of accelerated global change, the understanding and quantification of these processes is of primary importance. Spaceborne remote sensing sensors are predestined to produce bio-geo-information products on a global scale. The upcoming generation of spaceborne remote sensing configurations will be able to provide global data sets and products with unprecedented spatial and temporal resolution in the context of a consistent and systematic observation strategy. The integration of these data sets in existing environmental and climate science components will allow a new global view of the Earth system and its dynamics, initiating a performance leap in ecosystem and climate change modelling.
The investigation of high-silica rhyolitic rocks collected in the recent ICDP drilling from the Snake River Plain (SRP) volcanic province (western United States) as well as rocks from the adjacent rhyolitic complexes offers a unique opportunity to track the evolution of magma storage conditions in time and space in the 'Yellowstone hotspot' intracontinental volcanic province. The application of various geothermometers which can be used to determine pre-eruptive temperatures show a general trend indicating a general decrease of temperature over the last 16 Ma. However, the depth (or pressure) of the magma chambers is difficult to constrain and remains mainly unknown because the mineral assemblage in the rhyolitic systems is not suitable for geobarometry. As an alternative to mineral compositions, the silica content of rhyolitic melts can be used to constrain pressure, provided that the silicate melts have cotectic compositions (melts coexisting with quartz and feldspar), which is the case for most SRP rhyolites. From studies in synthetic systems, it is well known that the silica content of cotectic melts decreases with increasing pressure and that it may be used as barometer in pressure ranges of ca 1000 - 50 MPa. However, the evolution of silica content with pressure is not calibrated for natural systems containing up to 2 wtProzent Cao and 4 wtProzent FeO. In this study, we plan to determine the role of pressure on the silica content of cotectic melts compositions relevant for SRP compositions. The experimental data are crucial to interpret the natural glass compositions (matrix glass and glass inclusions) analyzed in the ICDP core samples and will be used to extract quantitative information on the depth of magma storage prior to eruption. The dataset obtained from various eruptive events (samples from ICDP drillings and other SRP rhyolites) will be used to check if there is an evolution of the depth of magma storage over the lifetime of the 'Yellowstone hotspot' in the last 16 Ma and if there is a correlation between the pre-eruptive pressure, the volume of erupted material, the temperature (or differentiation level) and the water activity of magmas. This study will be conducted in close cooperation with other U.S. groups who are in charge of the analysis of ICDP rhyolitic samples. It is emphasized that the experimental database obtained in this project can also be applied to other case studies (high silica rhyolites, A-type granites).
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