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Start date: 2000 × End date: 2009 × WGL Institute: PIK ×

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Now showing 1 - 10 of 65
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    Sensitivity of polar stratospheric ozone loss to uncertainties in chemical reaction kinetics
    (Göttingen : Copernicus GmbH, 2009) Kawa, S.R.; Stolarski, R.S.; Newman, P.A.; Douglass, A.R.; Rex, M.; Hofmann, D.J.; Santee, M.L.; Frieler, K.
    The impact and significance of uncertainties in model calculations of stratospheric ozone loss resulting from known uncertainty in chemical kinetics parameters is evaluated in trajectory chemistry simulations for the Antarctic and Arctic polar vortices. The uncertainty in modeled ozone loss is derived from Monte Carlo scenario simulations varying the kinetic (reaction and photolysis rate) parameters within their estimated uncertainty bounds. Simulations of a typical winter/spring Antarctic vortex scenario and Match scenarios in the Arctic produce large uncertainty in ozone loss rates and integrated seasonal loss. The simulations clearly indicate that the dominant source of model uncertainty in polar ozone loss is uncertainty in the Cl2O 2 photolysis reaction, which arises from uncertainty in laboratory-measured molecular cross sections at atmospherically important wavelengths. This estimated uncertainty in JCl 2O2 from laboratory measurements seriously hinders our ability to model polar ozone loss within useful quantitative error limits. Atmospheric observations, however, suggest that the Cl2O2 photolysis uncertainty may be less than that derived from the lab data. Comparisons to Match, South Pole ozonesonde, and Aura Microwave Limb Sounder (MLS) data all show that the nominal recommended rate simulations agree with data within uncertainties when the Cl2O2 photolysis error is reduced by a factor of two, in line with previous in situ ClOx measurements. Comparisons to simulations using recent cross sections from Pope et al. (2007) are outside the constrained error bounds in each case. Other reactions producing significant sensitivity in polar ozone loss include BrO + ClO and its branching ratios. These uncertainties challenge our confidence in modeling polar ozone depletion and projecting future changes in response to changing halogen emissions and climate. Further laboratory, theoretical, and possibly atmospheric studies are needed.
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    Terrestrial vegetation redistribution and carbon balance under climate change
    (London : BioMed Central, 2006) Lucht, Wolfgang; Schaphoff, Sibyll; Erbrecht, Tim; Heyder, Ursula; Cramer, Wolfgang
    Background 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.
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    A hindcast simulation of Arctic and Antarctic sea ice variability, 1955-2001
    (Tromsø : Norwegian Polar Institute, 2003) Fichefet, T.; Goosse, H.; Morales Maqueda, M.A.
    A hindcast simulation of the Arctic and Antarctic sea ice variability during 1955-2001 has been performed with a global, coarse resolution ice-ocean model driven by the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis daily surface air temperatures and winds. Both the mean state and variability of the ice packs over the satellite observing period are reasonably well reproduced by the model. Over the 47-year period, the simulated ice area (defined as the total ice-covered oceanic area) in each hemisphere experiences large decadal variability together with a decreasing trend of ∼1% per decade. In the Southern Hemisphere, this trend is mostly caused by an abrupt retreat of the ice cover during the second half of the 1970s and the beginning of the 1980s. The modelled ice volume also exhibits pronounced decadal variability, especially in the Northern Hemisphere. Besides these fluctuations, we detected a downward trend in Arctic ice volume of 1.8% per decade and an upward trend in Antarctic ice volume of 1.5% per decade. However, caution must be exercised when interpreting these trends because of the shortness of the simulation and the strong decadal variations. Furthermore, sensitivity experiments have revealed that the trend in Antarctic ice volume is model-dependent.
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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 large-scale climatic disturbances on the terrestrial carbon cycle
    (London : BioMed Central, 2006) Erbrecht, Tim; Lucht, Wolfgang
    Background: 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.
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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.
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    How 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.
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    Abschätzung der regionalen Kohlenstoffbilanz von mitteleuropäischen Wäldern unter dem Aspekt des Globalen Wandels : Abschlußbericht
    (Hannover : Technische Informationsbibliothek (TIB), 2002) Suckow, Felicitas; Lasch, Petra; Klöcking, Beate; Hauf, Ylva; Badeck, Franz
    [no abstract available]
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    Long-term evolution of the global carbon cycle: Historic minimum of global surface temperature at present
    (Abingdon : Taylor and Francis Ltd., 2002) Franck, S.; Kossacki, K.J.; Von Bloh, W.; Bounama, C.
    We present a minimal model for the global carbon cycle of the Earth containing the reservoirs mantle, ocean floor, continental crust, continental biosphere, and the kerogen, as well as the aggregated reservoir ocean and atmosphere. This model is coupled to a parameterised mantle convection model for describing the thermal and degassing history of the Earth. In this study the evolution of the mean global surface temperature, the biomass, and reservoir sizes over the whole history and future of the Earth under a maturing Sun is investigated. We obtain reasonable values for the present distribution of carbon in the surface reservoirs of the Earth and find that the parameterisation of the hydrothermal flux and the evolution of the ocean pH in the past has a strong influence on the atmospheric carbon reservoir and surface temperature. The different parameterisations give a rather hot as well as a freezing climate on the early Earth (Hadean and early Archaean). Nevertheless, we find a pronounced global minimum of mean surface temperature at the present state at 4.6 Gyr. In the long-term future the external forcing by increasing insolation dominates and the biosphere extincts in about 1.2 Ga. Our study has the implication that the Earth system is just before the point of evolution where this external forcing takes over the main influence from geodynamic effects acting in the past.