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- ItemDIVA: 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.
- ItemAgents, 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
- ItemIntegrated 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.
- ItemTemperature 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.
- ItemHow tight are the limits to land and water use? - Combined impacts of food demand and climate change(München : European Geopyhsical Union, 2005) Lotze-Campen, H.; Lucht, W.; Müller, C.; Bondeau, A.; Smith, P.In the coming decades, world agricultural systems will face serious transitions. Population growth, income and lifestyle changes will lead to considerable increases in food demand. Moreover, a rising demand for renewable energy and biodiversity protection may restrict the area available for food production. On the other hand, global climate change will affect production conditions, for better or worse depending on regional conditions. In order to simulate these combined effects consistently and in a spatially explicit way, we have linked the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ) with a "Management model of Agricultural Production and its Impact on the Environment" (MAgPIE). LPJ represents the global biosphere with a spatial resolution of 0.5 degree. MAgPIE covers the most important agricultural crop and livestock production types. A prototype has been developed for one sample region. In the next stage this will be expanded to several economically relevant regions on a global scale, including international trade. The two models are coupled through a layer of productivity zones. In the paper we present the modelling approach, develop first joint scenarios and discuss selected results from the coupled modelling system.
- ItemRegional climate model simulations as input for hydrological applications: Evaluation of uncertainties(München : European Geopyhsical Union, 2005) Kotlarski, S.; Block, A.; Böhm, U.; Jacob, D.; Keuler, K.; Knoche, R.; Rechid, D.; Walter, A.The ERA15 Reanalysis (1979-1993) has been dynamically downscaled over Central Europe using 4 different regional climate models. The regional simulations were analysed with respect to 2m temperature and total precipitation, the main input parameters for hydrological applications. Model results were validated against three reference data sets (ERA15, CRU, DWD) and uncertainty ranges were derived. For mean annual 2 m temperature over Germany, the simulation bias lies between -1.1°C and +0.9°C depending on the combination of model and reference data set. The bias of mean annual precipitation varies between -31 and +108 mm/year. Differences between RCM results are of the same magnitude as differences between the reference data sets.
- ItemImpacts of large-scale climatic disturbances on the terrestrial carbon cycle(London : BioMed Central, 2006) Erbrecht, Tim; Lucht, WolfgangBackground: The amount of carbon dioxide in the atmosphere steadily increases as a consequence of anthropogenic emissions but with large interannual variability caused by the terrestrial biosphere. These variations in the CO2 growth rate are caused by large-scale climate anomalies but the relative contributions of vegetation growth and soil decomposition is uncertain. We use a biogeochemical model of the terrestrial biosphere to differentiate the effects of temperature and precipitation on net primary production (NPP) and heterotrophic respiration (Rh) during the two largest anomalies in atmospheric CO2 increase during the last 25 years. One of these, the smallest atmospheric year-to-year increase (largest land carbon uptake) in that period, was caused by global cooling in 1992/93 after the Pinatubo volcanic eruption. The other, the largest atmospheric increase on record (largest land carbon release), was caused by the strong El Niño event of 1997/98. Results: We find that the LPJ model correctly simulates the magnitude of terrestrial modulation of atmospheric carbon anomalies for these two extreme disturbances. The response of soil respiration to changes in temperature and precipitation explains most of the modelled anomalous CO2 flux. Conclusion: Observed and modelled NEE anomalies are in good agreement, therefore we suggest that the temporal variability of heterotrophic respiration produced by our model is reasonably realistic. We therefore conclude that during the last 25 years the two largest disturbances of the global carbon cycle were strongly controlled by soil processes rather then the response of vegetation to these large-scale climatic events.
- ItemTerrestrial vegetation redistribution and carbon balance under climate change(London : BioMed Central, 2006) Lucht, Wolfgang; Schaphoff, Sibyll; Erbrecht, Tim; Heyder, Ursula; Cramer, WolfgangBackground Dynamic Global Vegetation Models (DGVMs) compute the terrestrial carbon balance as well as the transient spatial distribution of vegetation. We study two scenarios of moderate and strong climate change (2.9 K and 5.3 K temperature increase over present) to investigate the spatial redistribution of major vegetation types and their carbon balance in the year 2100. Results The world's land vegetation will be more deciduous than at present, and contain about 125 billion tons of additional carbon. While a recession of the boreal forest is simulated in some areas, along with a general expansion to the north, we do not observe a reported collapse of the central Amazonian rain forest. Rather, a decrease of biomass and a change of vegetation type occurs in its northeastern part. The ability of the terrestrial biosphere to sequester carbon from the atmosphere declines strongly in the second half of the 21st century. Conclusion Climate change will cause widespread shifts in the distribution of major vegetation functional types on all continents by the year 2100.
- ItemModelling carbon dynamics from urban land conversion: Fundamental model of city in relation to a local carbon cycle(London : Biomed Central, 2006) Svirejeva-Hopkins, A.; Schellnhuber, H.-J.Background: The main task is to estimate the qualitative and quantitative contribution of urban territories and precisely of the process of urbanization to the Global Carbon Cycle (GCC). Note that, on the contrary to many investigations that have considered direct anthropogenic emission of CO2(urbanized territories produce ca. 96-98% of it), we are interested in more subtle, and up until the present time, weaker processes associated with the conversion of the surrounding natural ecosystems and landscapes into urban lands. Such conversion inevitably takes place when cities are sprawling and additional "natural" lands are becoming "urbanized". Results: In order to fulfil this task, we first develop a fundamental model of urban space, since the type of land cover within a city makes a difference for a local carbon cycle. Hence, a city is sub-divided by built-up, "green"(parks, etc.) and informal settlements (favelas) fractions. Another aspect is a sub-division of the additional two regions, which makes the total number reaching eight regions, while the UN divides the world by six. Next, the basic model of the local carbon cycle for urbanized territories is built. We consider two processes: carbon emissions as a result of conversion of natural lands caused by urbanization; and the transformation of carbon flows by "urbanized" ecosystems; when carbon, accumulated by urban vegetation, is exported to the neighbouring territories. The total carbon flow in the model depends, in general, on two groups of parameters. The first includes the NPP, and the sum of living biomass and dead organic matter of ecosystems involved in the process of urbanization, and namely them we calculate here, using a new more realistic approach and taking into account the difference in regional cities' evolution. Conclusion: There is also another group of parameters, dealing with the areas of urban territories, and their annual increments. A method of dynamic forecasting of these parameters, based on the statistical regression model, was already suggested; nevertheless we shall further develop a new technique based on one idea to use the gamma-distribution. This will allow us to calculate the total carbon balance and to show how urbanization shifts it. © 2006 Svirejeva-Hopkins and Schellnhuber; licensee BioMed Central Ltd.
- ItemReliability of regional climate model simulations of extremes and of long-term climate(Göttingen : Copernicus GmbH, 2004) Böhm, U.; Kücken, M.; Hauffe, D.; Gerstengarbe, E.-W.; Werner, P.C.; Flechsig, M.; Keuler, K.; Block, A.; Ahrens, W.; Nocke, T.We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Niño event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near-surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our methodology to be applied as a common test bed to different fields of research in regional climate modeling.