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Now showing 1 - 10 of 84
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    DIVA: An iterative method for building modular integrated models
    (München : European Geopyhsical Union, 2005) Hinkel, J.
    Integrated modelling of global environmental change impacts faces the challenge that knowledge from the domains of Natural and Social Science must be integrated. This is complicated by often incompatible terminology and the fact that the interactions between subsystems are usually not fully understood at the start of the project. While a modular modelling approach is necessary to address these challenges, it is not sufficient. The remaining question is how the modelled system shall be cut down into modules. While no generic answer can be given to this question, communication tools can be provided to support the process of modularisation and integration. Along those lines of thought a method for building modular integrated models was developed within the EU project DINAS-COAST and applied to construct a first model, which assesses the vulnerability of the world’s coasts to climate change and sea-level-rise. The method focuses on the development of a common language and offers domain experts an intuitive interface to code their knowledge in form of modules. However, instead of rigorously defining interfaces between the subsystems at the project’s beginning, an iterative model development process is defined and tools to facilitate communication and collaboration are provided. This flexible approach has the advantage that increased understanding about subsystem interactions, gained during the project’s lifetime, can immediately be reflected in the model.
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    Agents, Bayes, and Climatic Risks - a modular modelling approach
    (München : European Geopyhsical Union, 2005) Haas, A.; Jaeger, C.
    When insurance firms, energy companies, governments, NGOs, and other agents strive to manage climatic risks, it is by no way clear what the aggregate outcome should and will be. As a framework for investigating this subject, we present the LAGOM model family. It is based on modules depicting learning social agents. For managing climate risks, our agents use second order probabilities and update them by means of a Bayesian mechanism while differing in priors and risk aversion. The interactions between these modules and the aggregate outcomes of their actions are implemented using further modules. The software system is implemented as a series of parallel processes using the CIAMn approach. It is possible to couple modules irrespective of the language they are written in, the operating system under which they are run, and the physical location of the machine
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    Impacts of global change on water-related sectors and society in a trans-boundary central European river basin – Part 2: From eco-hydrology to water demand management
    (München : European Geopyhsical Union, 2007) Conradt, T.; Kaltofen, M.; Hentschel, M.; Hattermann, F.F.; Wechsung, F.
    This second part of the paper presents the details of the eco-hydrological model SWIM simulating the natural water supply and its coupling to WBalMo, a water management model. Based on the climate scenarios of the STAR model, SWIM simulates the natural water and matter fluxes for the entire Elbe River area. All relevant processes are modelled for hydrotopes and the resulting discharges are accumulated in subbasins. The output data are input for the water management model WBalMo and the quality models Moneris and QSim. WBalMo takes storage management, inputs and withdrawals into account and analyses how demands by industry, power plants and households will be met at changing natural supply conditions. Some of the first results shall be presented here.
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    Integrated analysis of water quality in a mesoscale lowland basin
    (München : European Geopyhsical Union, 2005) Habeck, A.; Krysanova, V.; Hattermann, F.
    This article describes a modelling study on nitrogen transport from diffuse sources in the Nuthe catchment, representing a typical lowland region in the north-eastern Germany. Building on a hydrological validation performed in advance using the ecohydrological model SWIM, the nitrogen flows were simulated over a 20-year period (1981-2000). The relatively good quality of the input data, particularly for the years from 1993 to 2000, enabled the nitrogen flows to be reproduced sufficiently well, although modelling nutrient flows is always associated with a great deal of uncertainty. Subsequently, scenario calculations were carried out in order to investigate how nitrogen transport from the catchment could be further reduced. The selected scenario results with the greatest reduction of nitrogen washoff will briefly be presented in the paper.
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    Human alterations of the terrestrial water cycle through land management
    (Göttingen : Copernicus GmbH, 2008) Rost, S.; Gerten, D.; Heyder, U.
    This study quantifies current and potential future changes in transpiration, evaporation, interception loss and river discharge in response to land use change, irrigation and climate change, by performing several distinct simulations within the consistent hydrology and biosphere modeling framework LPJmL (Lund-Potsdam-Jena managed Land). We distinguished two irrigation simulations: a water limited one in which irrigation was restricted by local renewable water resources (ILIM), and a potential one in which no such limitation was assumed but withdrawals from deep groundwater or remote rivers allowed (IPOT). We found that the effect of historical land use change as compared to potential natural vegetation was pronounced, including a reduction in interception loss and transpiration by 25.9% and 10.6%, respectively, whereas river discharge increased by 6.6% (climate conditions of 1991-2000). Furthermore, we estimated that about 1170km3yr-1 of irrigation water could be withdrawn from local renewable water resources (in ILIM), which resulted in a reduction of river discharge by 1.5%. However, up to 1660km3yr-1 of water withdrawals were required in addition under the assumption that optimal growth of irrigated crops was sustained (IPOT), which resulted in a slight net increase in global river discharge by 2.0% due to return flows. Under the HadCM3 A2 climate and emission scenario, climate change alone will decrease total evapotranspiration by 1.5% and river discharge by 0.9% in 2046-2055 compared to 1991-2000 average due to changes in precipitation patterns, a decrease in global precipitation amount, and the net effect of CO2 fertilization. A doubling of agricultural land in 2046-2055 compared to 1991-2000 average as proposed by the IMAGE land use change scenario will result in a decrease in total evapotranspiration by 2.5% and in an increase in river discharge by 3.9%. That is, the effects of land use change in the future will be comparable in magnitude to the effects of climate change in this particular scenario. On present irrigated areas future water withdrawal will increase especially in regions where climate changes towards warmer and dryer conditions will be pronounced.
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    Small-scale mixing processes enhancing troposphere-to-stratosphere transport by pyro-cumulonimbus storms
    (Göttingen : Copernicus GmbH, 2007) Luderer, G.; Trentmann, J.; Hungershöfer, K.; Herzog, M.; Fromm, M.; Andreae, M.O.
    Deep convection induced by large forest fires is an efficient mechanism for transport of aerosol particles and trace gases into the upper troposphere and lower stratosphere (UT/LS). For many pyro-cumulonimbus clouds (pyroCbs) as well as other cases of severe convection without fire forcing, radiometric observations of cloud tops in the thermal infrared (IR) reveal characteristic structures, featuring a region of relatively high brightness temperatures (warm center) surrounded by a U-shaped region of low brightness temperatures. We performed a numerical simulation of a specific case study of pyroCb using a non-hydrostatic cloud resolving model with a two-moment cloud microphysics parameterization and a prognostic turbulence scheme. The model is able to reproduce the thermal IR structure as observed from satellite radiometry. Our findings establish a close link between the observed temperature pattern and small-scale mixing processes atop and downwind of the overshooting dome of the pyroCb. Such small-scale mixing processes are strongly enhanced by the formation and breaking of a stationary gravity wave induced by the overshoot. They are found to increase the stratospheric penetration of the smoke by up to almost 30 K and thus are of major significance for irreversible transport of forest fire smoke into the lower stratosphere.
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    Changes in alpine plant growth under future climate conditions
    (München : European Geopyhsical Union, 2010) Rammig, A.; Jonas, T.; Zimmermann, N.E.; Rixen, C.
    Alpine shrub- and grasslands are shaped by extreme climatic conditions such as a long-lasting snow cover and a short vegetation period. Such ecosystems are expected to be highly sensitive to global environmental change. Prolonged growing seasons and shifts in temperature and precipitation are likely to affect plant phenology and growth. In a unique experiment, climatology and plant growth was monitored for almost a decade at 17 snow meteorological stations in different alpine regions along the Swiss Alps. Regression analyses revealed highly significant correlations between mean air temperature in May/June and snow melt out, onset of plant growth, and plant height. These correlations were used to project plant growth phenology for future climate conditions based on the gridded output of a set of regional climate models runs. Melt out and onset of growth were projected to occur on average 17 days earlier by the end of the century than in the control period from 1971–2000 under the future climate conditions of the low resolution climate model ensemble. Plant height and biomass production were expected to increase by 77% and 45%, respectively. The earlier melt out and onset of growth will probably cause a considerable shift towards higher growing plants and thus increased biomass. Our results represent the first quantitative and spatially explicit estimates of climate change impacts on future growing season length and the respective productivity of alpine plant communities in the Swiss Alps.
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    Temperature sensitivity of decomposition in relation to soil organic matter pools: Critique and outlook
    (Göttingen : Copernicus GmbH, 2005) Reichstein, M.; Kätterer, T.; Andrén, O.; Ciais, P.; Schulze, E.-D.; Cramer, W.; Papale, D.; Valentini, R.
    Knorr et al. (2005) concluded that soil organic carbon pools with longer turnover times are more sensitive to temperature. We show that this conclusion is equivocal, largely dependent on their specific selection of data and does not persist when the data set of Kätterer et al. (1998) is analysed in a more appropriate way. Further, we analyse how statistical properties of the model parameters may interfere with correlative analyses that relate the Q 10 of soil respiration with the basal rate, where the latter is taken as a proxy for soil organic matter quality. We demonstrate that negative parameter correlations between Qio-values and base respiration rates are statistically expected and not necessarily provide evidence for a higher temperature sensitivity of low quality soil organic matter. Consequently, we propose it is premature to conclude that stable soil carbon is more sensitive to temperature than labile carbon.
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    The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: Results from a process-based model
    (München : European Geopyhsical Union, 2010) Thonicke, K.; Spessa, A.; Prentice, I.C.; Harrison, S.P.; Dong, L.; Carmona-Moreno, C.
    A process-based fire regime model (SPITFIRE) has been developed, coupled with ecosystem dynamics in the LPJ Dynamic Global Vegetation Model, and used to explore fire regimes and the current impact of fire on the terrestrial carbon cycle and associated emissions of trace atmospheric constituents. The model estimates an average release of 2.24 Pg C yr−1 as CO2 from biomass burning during the 1980s and 1990s. Comparison with observed active fire counts shows that the model reproduces where fire occurs and can mimic broad geographic patterns in the peak fire season, although the predicted peak is 1–2 months late in some regions. Modelled fire season length is generally overestimated by about one month, but shows a realistic pattern of differences among biomes. Comparisons with remotely sensed burnt-area products indicate that the model reproduces broad geographic patterns of annual fractional burnt area over most regions, including the boreal forest, although interannual variability in the boreal zone is underestimated.
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    Towards global empirical upscaling of FLUXNET eddy covariance observations: Validation of a model tree ensemble approach using a biosphere model
    (München : European Geopyhsical Union, 2009) Jung, M.; Reichstein, M.; Bondeau, A.
    Global, spatially and temporally explicit estimates of carbon and water fluxes derived from empirical up-scaling eddy covariance measurements would constitute a new and possibly powerful data stream to study the variability of the global terrestrial carbon and water cycle. This paper introduces and validates a machine learning approach dedicated to the upscaling of observations from the current global network of eddy covariance towers (FLUXNET). We present a new model TRee Induction ALgorithm (TRIAL) that performs hierarchical stratification of the data set into units where particular multiple regressions for a target variable hold. We propose an ensemble approach (Evolving tRees with RandOm gRowth, ERROR) where the base learning algorithm is perturbed in order to gain a diverse sequence of different model trees which evolves over time. We evaluate the efficiency of the model tree ensemble (MTE) approach using an artificial data set derived from the Lund-Potsdam-Jena managed Land (LPJmL) biosphere model. We aim at reproducing global monthly gross primary production as simulated by LPJmL from 1998–2005 using only locations and months where high quality FLUXNET data exist for the training of the model trees. The model trees are trained with the LPJmL land cover and meteorological input data, climate data, and the fraction of absorbed photosynthetic active radiation simulated by LPJmL. Given that we know the "true result" in the form of global LPJmL simulations we can effectively study the performance of the MTE upscaling and associated problems of extrapolation capacity. We show that MTE is able to explain 92% of the variability of the global LPJmL GPP simulations. The mean spatial pattern and the seasonal variability of GPP that constitute the largest sources of variance are very well reproduced (96% and 94% of variance explained respectively) while the monthly interannual anomalies which occupy much less variance are less well matched (41% of variance explained). We demonstrate the substantially improved accuracy of MTE over individual model trees in particular for the monthly anomalies and for situations of extrapolation. We estimate that roughly one fifth of the domain is subject to extrapolation while MTE is still able to reproduce 73% of the LPJmL GPP variability here. This paper presents for the first time a benchmark for a global FLUXNET upscaling approach that will be employed in future studies. Although the real world FLUXNET upscaling is more complicated than for a noise free and reduced complexity biosphere model as presented here, our results show that an empirical upscaling from the current FLUXNET network with MTE is feasible and able to extract global patterns of carbon flux variability.