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Now showing 1 - 5 of 5
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    Analytically tractable climate–carbon cycle feedbacks under 21st century anthropogenic forcing
    (München : European Geopyhsical Union, 2018) Lade, Steven J.; Donges, Jonathan F.; Fetzer, Ingo; Anderies, John M.; Beer, Christian; Cornell, Sarah E.; Gasser, Thomas; Norberg, Jon; Richardson, Katherine; Rockström, Johan; Steffen, Will
    Changes to climate–carbon cycle feedbacks may significantly affect the Earth system's response to greenhouse gas emissions. These feedbacks are usually analysed from numerical output of complex and arguably opaque Earth system models. Here, we construct a stylised global climate–carbon cycle model, test its output against comprehensive Earth system models, and investigate the strengths of its climate–carbon cycle feedbacks analytically. The analytical expressions we obtain aid understanding of carbon cycle feedbacks and the operation of the carbon cycle. Specific results include that different feedback formalisms measure fundamentally the same climate–carbon cycle processes; temperature dependence of the solubility pump, biological pump, and CO2 solubility all contribute approximately equally to the ocean climate–carbon feedback; and concentration–carbon feedbacks may be more sensitive to future climate change than climate–carbon feedbacks. Simple models such as that developed here also provide "workbenches" for simple but mechanistically based explorations of Earth system processes, such as interactions and feedbacks between the planetary boundaries, that are currently too uncertain to be included in comprehensive Earth system models.
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    Extreme fire events are related to previous-year surface moisture conditions in permafrost-underlain larch forests of Siberia
    (Bristol : IOP Publishing, 2012) Forkel, Matthias; Thonicke, Kirsten; Beer, Christian; Cramer, Wolfgang; Bartalev, Sergey; Schmullius, Christiane
    Wildfires are a natural and important element in the functioning of boreal forests. However, in some years, fires with extreme spread and severity occur. Such severe fires can degrade the forest, affect human values, emit huge amounts of carbon and aerosols and alter the land surface albedo. Usually, wind, slope and dry air conditions have been recognized as factors determining fire spread. Here we identify surface moisture as an additional important driving factor for the evolution of extreme fire events in the Baikal region. An area of 127 000 km2 burned in this region in 2003, a large part of it in regions underlain by permafrost. Analyses of satellite data for 2002–2009 indicate that previous-summer surface moisture is a better predictor for burned area than precipitation anomalies or fire weather indices for larch forests with continuous permafrost. Our analysis advances the understanding of complex interactions between the atmosphere, vegetation and soil, and how coupled mechanisms can lead to extreme events. These findings emphasize the importance of a mechanistic coupling of soil thermodynamics, hydrology, vegetation functioning, and fire activity in Earth system models for projecting climate change impacts over the next century.
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    A novel probabilistic risk analysis to determine the vulnerability of ecosystems to extreme climatic events
    (Bristol : IOP Publishing, 2013) van Oijen, Marcel; Beer, Christian; Cramer, Wolfgang; Rammig, Anja; Reichstein, Markus; Rolinski, Susanne; Soussana, Jean-Francois
    We present a simple method of probabilistic risk analysis for ecosystems. The only requirements are time series—modelled or measured—of environment and ecosystem variables. Risk is defined as the product of hazard probability and ecosystem vulnerability. Vulnerability is the expected difference in ecosystem performance between years with and without hazardous conditions. We show an application to drought risk for net primary productivity of coniferous forests across Europe, for both recent and future climatic conditions.
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    Asynchronous exposure to global warming: Freshwater resources and terrestrial ecosystems
    (Bristol : IOP Publishing, 2013) Gerten, Dieter; Beer, Christian; Ostberg, Sebastian; Heinke, Jens; Kowarsch, Martin; Kreft, Holger; Kundzewicz, Zbigniew W.; Rastgooy, Johann; Warren, Rachel; Schellnhuber, Hans Joachim
    This modelling study demonstrates at what level of global mean temperature rise (ΔTg) regions will be exposed to significant decreases of freshwater availability and changes to terrestrial ecosystems. Projections are based on a new, consistent set of 152 climate scenarios (eight ΔTg trajectories reaching 1.5–5 ° C above pre-industrial levels by 2100, each scaled with spatial patterns from 19 general circulation models). The results suggest that already at a ΔTg of 2 ° C and mainly in the subtropics, higher water scarcity would occur in >50% out of the 19 climate scenarios. Substantial biogeochemical and vegetation structural changes would also occur at 2 ° C, but mainly in subpolar and semiarid ecosystems. Other regions would be affected at higher ΔTg levels, with lower intensity or with lower confidence. In total, mean global warming levels of 2 ° C, 3.5 ° C and 5 ° C are simulated to expose an additional 8%, 11% and 13% of the world population to new or aggravated water scarcity, respectively, with >50% confidence (while ~1.3 billion people already live in water-scarce regions). Concurrently, substantial habitat transformations would occur in biogeographic regions that contain 1% (in zones affected at 2 ° C), 10% (3.5 ° C) and 74% (5 ° C) of present endemism-weighted vascular plant species, respectively. The results suggest nonlinear growth of impacts along with ΔTg and highlight regional disparities in impact magnitudes and critical ΔTg levels.
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    Evaluation of climate-related carbon turnover processes in global vegetation models for boreal and temperate forests
    (Oxford [u.a.] : Blackwell Science, 2017) Thurner, Martin; Beer, Christian; Ciais, Philippe; Friend, Andrew D.; Ito, Akihiko; Kleidon, Axel; Lomas, Mark R.; Quegan, Shaun; Rademacher, Tim T.; Schaphoff, Sibyll; Tum, Markus; Wiltshire, Andy; Carvalhais, Nuno
    Turnover concepts in state-of-the-art global vegetation models (GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate (k) derived from a combination of remote sensing based products of biomass and net primary production (NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation-based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation-based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation-based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large-scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models.