Podcasts about upper danube

In the last decades regional climate models (RCMs) have proven their ability to provide valuable information about potential future changes in the earth’s climate system. Research projects like GLOWA-Danube (Global Change of the Water Cycle) are given the possibility to utilize RCM simulations as meteorological drivers for land surface model components. To adequately describe all sorts of water fluxes in the research area of the Upper Danube watershed the different components of the interdisciplinary DANUBIA model require data in high spatial and temporal resolution. While the latter can be satisfactorily provided by most RCMs, the spatial resolution at which atmospheric processes can be resolved is computationally limited to at best 10 x 10 km at present. A clear need has been identified to develop appropriate methods to bridge the gap between RCMs and high resolution land surface models. The application of such downscaling techniques is in particularly necessary in highly complex terrain, where the limited spatial resolution of RCM simulations does not fully capture the natural climatic variability. In the present work a model interface has been developed that provides adequate scaling techniques to overcome the mismatch between the model scales permitting the investigation of climate change impacts at regional to local scales. Besides the downscaling of meteorological simulations, the coupler scales up fluxes calculated at the land surface and provides the aggregated fluxes as inputs for the RCMs. As the latter allows to consider the nonlinearity and complexity of the interactions between the atmosphere and the land surface as well as the mutual dependency of the respective processes at the investigated scale the approach can be expected to contribute to a better understanding of the complex land-atmosphere-system. A comprehensive description of the implemented algorithms is given. Further first results of one-way coupled model runs using the regional climate model REMO to simulate the atmosphere and the hydrological model PROMET to describe all hydrological relevant processes at the land surface are presented. By comparing the results achieved for a potential future climate to those achieved for past climate conditions the climate change impact on the water resources is analyzed. The model interface SCALMET has been developed in the framework of the GLOWA-Danube Project at the Ludwig-Maximilians-University in Munich. The financial funding of GLOWA-Danube by the German Ministry of Education and Research (BMB+F) is gratefully acknowledged.

The investigation of the impact of Global Change on the basic resources on which life, and man, depends, is the main objective of the environmental science community at the beginning of the 21st century. Advances in information technology, new methods of spatially distributed data retrieval and increased understanding of the physical, chemical and biological processes in the Earth system facilitate integrative models of the dynamic processes under change. Together with the integration of deep actors models from social and economical sciences into a common model framework, scenario runs based on inputs from Regional Climate Models (RCMs) and constrained by prognoses of the future developments in demography, economy and human behaviour are now possible. The objective of the integrative project GLOWA-Danube is the development of such a modelling system and its application on the mesoscale catchment of the Upper Danube river with an area of about 77,000 km2. The decision support system DANUBIA is designed for plausible predictions of the impact of changes in climate, human behaviour and land use on the future of the water and related matter cycles. DANUBIA is able to assist knowledge-based management decisions, by predicting the effects of adaptation and mitigation strategies on the natural resources of the Upper Danube basin. The closure of the water, energy, nitrogen and carbon cycles in the soil-vegetation-atmosphere system relies on the adequate representation of all processes involved and their interaction. To close the energy cycle in the soil-vegetation-atmosphere system and provide valuable input data for biochemical models of soil nitrogen and carbon transformation, this thesis presents the Soil Heat Transfer Module (SHTM) together with an energy balance algorithm of the soil surface for regional scale simulations. SHTM combines simplified physical algorithms for the computation of the actual temperature in the upper soil layers and a dynamic lower boundary condition to represent Climate Change conditions. Changes in soil moisture and soil freezing are explicitly taken into account. The surface ground heat flux as the driving force of the model is provided by an explicit solution of the soil surface energy balance and a snow-soil coupling algorithm, respectively. This thesis shows, that the soil temperature and energy balance modules developed as extensions of PROMET (PROcesses of Matter and Energy Transfer) are ready to bridge the gap between regional scale (up to 100,000 km2) application and the requirement of physical process models in predictive, coupled modelling systems like DANUBIA.

The central questions of this thesis are concerned with the investigation of vegetation related landsurface parameters under the impact of changing climate conditions. The spatial extent of the study is limited to the borders of the Upper Danube drainage basin, according to the requirements of the cooperative Project GLOWA-Danube (Global change of the Hydrological Cycle), funded by the German Ministry of Education and research (BMB+F). Current publications are indicating that the dynamic behaviour of the vegetation cover often is inadequately accounted for in studies that are investigating the impacts of climate change with respect to the landsurface water cycle. In order to enable a dynamic feedback between the animate land cover and the atmosphere, which might be sensitive enough to trace active reactions of the vegetation cover on changing climatic conditions, the physically based land surface process model PROMET (Process of Radiation Mass and Energy Transfer Model) was enhanced by an explicit description of the growth activity of different plant types. The introduced model approach was tested against measured data for a variety of parameters. The different validation efforts all returned good to very good results. It therefore can be stated that the model soundly demonstrated its capability concerning the precise reproduction of a variety of structural landsurface variables on different scales under observed climatic conditions. An application of the model to the calculation of climate scenarios therefore seems appropriate. In order to enable comparability with international research approaches, the internationally acknowledged global change scenarios developed by the Intergovernmental Panel on Climate Change (IPCC), are basically applied. The moderate A1B emissions scenario, which is based on the assumption of a balanced future development of different energy technologies, was selected and modified by a regional impact factor that is assumed to apply to the local situation of the Upper Danube catchment. Being applied to the regionally adapted IPCC A1B climate scenario, the model returned clear statements, projecting a possible future development of selected landsurface parameters within the Upper Danube area. Concerning the phenological behaviour of forest trees, the model simulated a strong trend towards earlier incidence of the leaf emergence of deciduous as well as of the mayshoot of coniferous trees, contributing to a significant elongation of the vegetation period. These longer phases of active growth in combination with the rising temperatures and the elevated supply of atmospheric carbon dioxide led to an increase of biological activity in the model results that manifested in increasing rates of biomass accumulation for the Upper Danube area. The increased biological activity in combination with the strong decrease of summer precipitation, which was assumed in the climate scenario, again led to an escalating frequency of drought stress events in the Upper Danube Basin. Not only the average count of water stress events per year was modelled to increase, but also a spatial extension of the regions that are affected by drought stress was mapped by the model. This general increase of water stress and the significant decrease of summer precipitation entailed a slight decline of the transpiration and evapotranspiration of the Upper Danube area in the scenario results. The modelled decline of the summer precipitation also resulted in a noticeable decrease of the modelled average discharge rates at the main gauge of the basin. The base flow rates during the summer months thereby are likely to be primarily affected. Since the model results for the scenario period featured temporal and spatial variations and standard deviations that were closely matching the statistics of the reference period, while at the same time they showed clear trends though they were avoiding extreme realizations, the scenario assumptions can be considered to be reliable. The baseline scenario, which was spot-checked for a set of reference proxels, did not return any trends as expected, indicating that the observed future trends are not of systematic origin. The further development of the introduced model approach is an appealing challenge, which might considerably contribute to the improvement of computer aided decision support systems. It can be assumed that the progress of the development of physically based models due to a more profound understanding of the processes on one hand and the sophistication and refinement of the model algorithms that result from the increase of knowledge on the other, may contribute to the development of reliable systems, that will be able to sustainably assist humanity with the handling of future environmental challenges. The author gratefully acknowledges the finacial support of the German Research Foundation (DFG) in the frame of the project "Coupled Analysis of Vegetation Chlorophyll and Water Content Using Hyperspectral, Bidirectional Remote Sensing".

This work has been carried out in the framework of the project GLOWA-Danube (GLObal WAter cycle) where a joint effort is made by several groups to model the interaction of the water cycle and society in the Upper Danube catchment area. In particular regional climate models are used to simulate and eventually predict precipitation in this research area, while other groups convert this information into river runoff estimates and groundwater fluxes. It has been agreed in the project that precipitation data and other meteorological data must be handed over to the hydrological groups with a spatial resolution of 1 km. Long term runs with regional climate models are, however, not feasible at 1 km resolution, because they would exceed available computer resources by far. Therefore, a pragmatic downscaling method for precipitation must be implemented which provides data of 1 km resolution on the basis of model results of fairly coarse resolution. This downscaling uses extensively climatological precipitation observations where such downscaling relations can be derived. These observed rates are then adapted to the model results. The data are provided by the German Weather Service (DWD) and the Austrian Weather Service (ZAMG). The years 1991-2000 have been chosen as a reference period for the analysis. The climate simulation is carried out by the mesoscale model MM5 at a resolution of 45 km. The model MM5 offers a wide range of parameterizations with respect to convective processes, the boundary layer, cloud microphysics, and the radiation balance, all directly or indirectly responsible for generating precipitation. Sensitivity studies are performed to find the best configuration for the research area and reference period. A variety of methods is tested to generate observed and simulated climatological time series of precipitation. In particular, a linear average, a running average, a Fourier analysis, and spline interpolation are intercompared. In the end, spline interpolation between monthly values showed the best results for both time series and is used as a basis for the downscaling method. The downscaling method has to correct two major discrepancies between the observed precipitation distribution at the 1 km resolution and the simulated distribution at the 45 km resolution. First, these are small scale details related to topography in the rainfall distribution at the 1 km resolution, which lack in the 45 km resolution. Second, there is an unrealistic southward shift of the rainfall maximum at the northern rim of the Alps in the simulations, which needs to be corrected. A specific correction factor is introduced for each problem. The correlation between the spatial distribution of observed and simulated distributions increases after using the correction factors. Due to the climatological relationships, the results time periods of 10 days and longer are superior to those for periods shorter than 10 days. The precipitation distribution depends, of course, on the wind direction in particular so near the Alps. Wind direction and wind speed are simulated by the MM5 model and combined with the correction factors described above. The correlation between the spatial distribution of observed and simulated precipitation increases more if the wind direction dependent correction factors are introduced. These improved correction factors depend less on climatological relationships and perform therefore better for shorter time periods. Additionally, they will be able to respond better on changes in the weather regime in future climates. Altogether, this investigation provides a new pragmatic method to downscale model simulations on the basis of observations. This method will be used in the project GLOWA-Danube.