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.
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.
Temperatures in Switzerland increased about 0.57 C over the last three decades and climate models predict that this increase will continue during the 21st century and beyond. Accompanied by changes in the water supply due to the expected increase in the frequency and intensity of heavy precipitation and/or drought events, these effects will strongly force changes in forest productivity, spatial distribution of tree species, and changes in the species composition within forests. Projections of the future dimensions and interactions of these effects require detailed understanding of short and long-term changes in eco-physiological responses to past and present climate variation. Stable isotopes in tree rings have become a significant tool in obtaining retrospective insight into the plant physiological response to climate and other environmental variables. The increasing number of isotope records, however, also highlights important unsolved questions and current limitations of this tree-ring parameter. Obviously, an improved understanding of the mechanisms leading to variations in the tree's internal carbon and water cycle in relation to climate, soil moisture conditions, transpiration and expansion of the root system is urgently needed. ISOPATH aims to decipher the origin and variability of the isotopic signal in the tree rings of two alpine species, frequently used in climate reconstructions, and to understand the environmental and physiological information encoded. We will develop weekly resolved records of carbon and oxygen isotopes in xylem and needle water, needle sugars, phloem sugars and stem wood/cellulose of two physiologically differing species (larch and spruce) growing under varying temperature, soil moisture and relative humidity conditions. Those data will be related to a large suite of external variables including precipitation and soil water, temperature, and vapour pressure deficit. We act (i) on a spatial scale by following the complete pathway of stable isotopes from the atmosphere into the tree ring under varying environmental conditions and (ii) on a temporal scale by studying seasonal cycles of the isotope signals in all these different components, covering four growth seasons (2008-2011). This unique dataset in terms of length, resolution and number of measured variables will be used to test and improve advanced models for isotope fractionation at the leaf level and in the tree ring, in relation to species-specific traits, temperature and soil moisture conditions. The measured and modelled isotope signatures will allow to predict plant physiological adaptation in the alpine environment to climate change of the 21st century.
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.
Current and future global warming will cause the degradation of mountain permafrost, which may strongly influence the stability of permafrost slopes or rock walls with potentially hazardous consequences. Due to the strong heterogeneity of both the thermal regime and the ground composition of mountain permafrost, its response to atmospheric forcing can however be highly variable for different landforms and within short distances. The spatial distribution of ice and liquid water is important for determining the sensitivity of a specific permafrost occurrence to climate change because of their large influence on the pace of temperature changes (by effects of latent heat) and their importance for geotechnical properties of the ground. Detailed knowledge of the material properties and internal structures of frozen ground is therefore an important prerequisite to determine the sensitivity of permafrost to climate change. Except for the active layer ice and water contents and their temporal and spatial variability usually cannot be measured directly. Geophysical methods are sensitive for the ice and liquid water content in the ground. With the proposed collaboration, two similar but complementary approaches to quantify the composition of the ground based on 2D sections of geophysical data will be combined for an improved determination of ice and water contents in permafrost regions. The so-called 4-phase model (4PM) is based on two simple petrophysical relationships for electrical resistivity and seismic velocity and estimates volumetric fractions of ice, water, and air within the pore volume of a rock matrix by jointly using complementary data sets from electric and seismic measurements. Due to inherent ambiguities in the model it is still restricted to specific cases and often allows only a rough estimation of the phase fractions. Major drawbacks of the current 4PM comprise the unsatisfactory discrimination between rock and ice and its under-determinedness, requiring the prescription of the porosity and further parameters. The so-called RSANN model (developed and used by the host institution) uses the technique of simulated annealing (a Monte-Carlo-type stochastic simulation approach) as an optimization tool for the integration of electrical resistivity and P-wave velocity to derive 2D sections of porosity, water saturation and volumetric water content. The simulated annealing technique allows - due to its iterative procedure - more parameters to be predicted instead of being prescribed as in the 4PM. The objective of the proposed collaboration is to combine the advantages of the two algorithms (4PM and RSANN) to overcome the shortcomings of the 4PM in order to improve the reliability of the determined ice and liquid water contents. (...)
In contrast to their advances in other areas, weather forecast models have not been successful in improving the Quantitative Precipitation Forecast during the last 16 years. One reason for this stagnation is the lack of comprehensive, high-quality data sets usable for model validation as well as for data assimilation, thus leading to improved initial fields in numerical models. Theoretical analyses have identified the requirements measured data have to meet in order to close the gaps in process understanding. In field campaigns, it has been shown that the newest generation of remote sensing systems has the potential to yield data sets of the required quality. It is therefore time to combine the most powerful remote sensing instruments with proven ground-based and airborne measurement techniques in an Intensive Observations Period (IOP). Its goal is to serve as a backbone for the SPP 1167 by producing the demanded data sets of unachieved accuracy and resolution. This requires a sophisticated scientific preparation and a careful coordination between the efforts of the institutions involved. For the first time, the pre-convective environment, the formation of clouds and the onset and development of precipitation as well as its intensity will be observed in four dimensions simultaneously in a region of sufficient size. This shall be achieved by combining the IOP with international programs and by collaboration between leading scientists in Europe, US and other countries. Thus, the IOP is a unique opportunity to make Germany the setting of an international field campaign featuring the newest generation of measurement systems such as scanning radar and lidar and leading to outstanding advances in atmospheric sciences.
The goal of this study was to enable a prognosis on the future rainfall conditions of the Nile Equatorial Lakes regions by delivering time-series of monthly rainfall sums for the time-period from 2021 to 2050 that can be used for all kinds of applications. One example might be the dimensioning of hydraulic structures. In these very long lasting investments, future climatic conditions have to be considered during present planning and construction.The principal sources of information on future climate conditions are General Circulation Models (GCMs). These are physically based atmospheric models that resemble a numerical weather prediction system but on a much coarser scale. This forecast cannot be perfect. Especially, it cannot predict single values, e. g. if January 2050 will be rather wet or dry, but only climatic references, i.e. state, if Januaries in general will become wetter or dryer in the future. Even if the predictions of a GCM were perfect, its output could not be used directly for hydrological purposes, due to its coarse resolution. The monthly precipitation values that are provided by the GCM present the spatially averaged precipitation over a grid cell of several thousand square kilometres. This 'block rainfall' can differ significantly from rainfall measured at the ground. Rain gauges are influenced by local effects like micro climatic conditions or orographic effects of mountain ranges that GCMs are not able to resolve.This study combined the information from different data sources. As global trend information, monthly precipitation values from two GCMs (ECHAM5 and HadCM3) were used. Three CO2-emission scenarios (A1b, A2 and B1) were considered in this data. As local ground reference observed monthly rainfall sums from several rain gauges in East Africa as well as from three reanalysis projects (Climate Research Unit, University of Delaware and GPCC) were used.At each rain gauge or observation point in the reanalysis a technique called 'Quantile-Quantile-Transformation' was applied to establish a relationship between the Cumulative Distribution Function (CDF) of the GCMs and that of the ground references during the calibration period from 1961-1990. The CDFs were fitted by non-parametric Kernel-Smoothing. To account for potential shifts in the annual cycles of GCMs and ground references, the transformations was done separately for each month.Assuming that the relation between Global Model and local response will be constant in the future, the global predictions of the GCM can be downscaled to local scale, leading to future rainfall scenarios that are coherent with observed past rainfall.Combining the data from three CO2-emission scenarios of two GCM with three reanalysis data sets, an ensemble of 18 different rainfall time-series was created for each observation point. The range of this ensemble helps to estimate the possible uncertainties in the prognosis of future monthly precipitation sums from 2021 to 2050.
One unsolved problem of the micrometeorological community is the unclosed energy balance when its components are independently measured in the field. This so-called energy balance closure gap was investigated with focus on sinks and sources (storage change terms) and on the uncertainties involved in the estimation of the available energy. The second main topic was the assessment of the non-turbulent fluxes of sensible heat and latent heat as well as the horizontal turbulent flux in case of sensible heat. These fluxes are commonly neglected as their assessment is difficult. The third main point was the comparison of advective fluxes of sensible heat and carbon dioxide with the aim to facilitate an easier assessment of the advective fluxes of carbon dioxide. Analyses were based on the ADVEX- and the MORE II-dataset. For the investigated sites it could be shown that the energy balance closure improved when the storage terms were carefully considered. An inspection of the uncertainties involved in the available energy revealed that these uncertainties cannot explain the lack of energy balance closure alone. An inclusion of the non-turbulent advective fluxes of latent heat and sensible heat changed the corresponding budgets and improved the energy balance closure partly. However, residuals did not vanish. The horizontal turbulent flux divergence of sensible heat turned out to be negligible for the investigated site and time period. The comparison of the non-turbulent advective fluxes of sensible heat and carbon dioxide showed that advective fluxes of both scalars are larger during night than during day and that they both share a considerable scatter. On a mean diurnal basis, the advective fluxes of sensible heat and carbon dioxide turned out to be of opposite sign especially during night.
Soil moisture - the water stored in soil within reach of the plants - is a crucial parameter for a large number of applications. Consequently, the field of microwave remote sensing of soil moisture has been an important research topic since the 1970s. But only in the last few years significant progress towards operational soil moisture services has been made. This progress became possible due to advances in sensor technology and new algorithmic approaches. With the improved algorithms it has been possible to derive soil moisture from existing operational microwave sensors. The first global soil moisture dataset derived from ERS-1/2 scatterometer measurements was released in 2002. The first near-real-time operational soil moisture service was started by EUMETSAT in May 2008 based on METOP ASCAT, which is the successor instrument of the ERS-1/2 scatterometer. Austria has made important contributions to these developments. The algorithms for retrieving soil moisture from the C-band scatterometers on board of ERS-1/2 and METOP have been developed by the Vienna University of Technology (TU Wien). Within EUMETSAT's Satellite Application Facility in Support to Operational Hydrology and Water Management (Hydrology SAF) the Austrian meteorological service (ZAMG) coordinates the soil moisture activities and is responsible for building up operational services for value-added METOP ASCAT soil moisture products. The overall goal of the proposed project is to advance the use of soil moisture services based on METOP ASCAT and complementary satellite systems, most importantly SMOS and ENVISAT ASAR, by extending the Hydrology SAF products to Africa and Australia, carrying out extensive calibration and validation (Cal/Val) activities and by developing novel water hazards applications. The considered applications are weather forecasting, drought and yield monitoring, hydrologic prediction, epidemiological modelling, climate change, desertification monitoring and societal risks assessment. A project of comparable thematic focus and breath has not been proposed before. It is expected that the interdisciplinary cooperation of specialists from different fields will lead to important scientific innovations that will promote a wide use of satellite technology in water hazards applications.
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