@article{SchneidervonDeimlingMeinshausenLevermannetal.2012,
  author    = {Schneider von Deimling, Thomas and Meinshausen, Malte and Levermann, Anders and Huber, Veronika and Frieler, Katja and Lawrence, D. M. and Brovkin, Victor},
  title     = {Estimating the near-surface permafrost-carbon feedback on global warming},
  series = {Biogeosciences},
  volume    = {9},
  journal   = {Biogeosciences},
  number    = {2},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1726-4170},
  doi       = {10.5194/bg-9-649-2012},
  pages     = {649 -- 665},
  year      = {2012},
  abstract  = {Thawing of permafrost and the associated release of carbon constitutes a positive feedback in the climate system, elevating the effect of anthropogenic GHG emissions on global-mean temperatures. Multiple factors have hindered the quantification of this feedback, which was not included in climate carbon-cycle models which participated in recent model intercomparisons (such as the Coupled Carbon Cycle Climate Model Intercomparison Project - (CMIP)-M-4). There are considerable uncertainties in the rate and extent of permafrost thaw, the hydrological and vegetation response to permafrost thaw, the decomposition timescales of freshly thawed organic material, the proportion of soil carbon that might be emitted as carbon dioxide via aerobic decomposition or as methane via anaerobic decomposition, and in the magnitude of the high latitude amplification of global warming that will drive permafrost degradation. Additionally, there are extensive and poorly characterized regional heterogeneities in soil properties, carbon content, and hydrology. Here, we couple a new permafrost module to a reduced complexity carbon-cycle climate model, which allows us to perform a large ensemble of simulations. The ensemble is designed to span the uncertainties listed above and thereby the results provide an estimate of the potential strength of the feedback from newly thawed permafrost carbon. For the high CO2 concentration scenario (RCP8.5), 33-114 GtC (giga tons of Carbon) are released by 2100 (68\% uncertainty range). This leads to an additional warming of 0.04-0.23 degrees C. Though projected 21st century permafrost carbon emissions are relatively modest, ongoing permafrost thaw and slow but steady soil carbon decomposition means that, by 2300, about half of the potentially vulnerable permafrost carbon stock in the upper 3 m of soil layer (600-1000 GtC) could be released as CO2, with an extra 1-4\% being released as methane. Our results also suggest that mitigation action in line with the lower scenario RCP3-PD could contain Arctic temperature increase sufficiently that thawing of the permafrost area is limited to 9-23\% and the permafrost-carbon induced temperature increase does not exceed 0.04-0.16 degrees C by 2300.},
  language  = {en}
}
@article{HuberKrummenauerPenaOrtizetal.2020,
  author    = {Huber, Veronika and Krummenauer, Linda and Pe{\~n}a-Ortiz, Cristina and Lange, Stefan and Gasparrini, Antonio and Vicedo-Cabrera, Ana Maria and Garcia-Herrera, Ricardo and Frieler, Katja},
  title     = {Temperature-related excess mortality in German cities at 2 °C and higher degrees of global warming},
  series = {Environmental Research},
  volume    = {186},
  journal   = {Environmental Research},
  publisher = {Elsevier},
  address   = {San Diego, California},
  issn      = {0013-9351},
  doi       = {10.1016/j.envres.2020.109447},
  pages     = {1 -- 10},
  year      = {2020},
  abstract  = {Background: Investigating future changes in temperature-related mortality as a function of global mean temperature (GMT) rise allows for the evaluation of policy-relevant climate change targets. So far, only few studies have taken this approach, and, in particular, no such assessments exist for Germany, the most populated country of Europe. Methods: We assess temperature-related mortality in 12 major German cities based on daily time-series of all-cause mortality and daily mean temperatures in the period 1993-2015, using distributed-lag non-linear models in a two-stage design. Resulting risk functions are applied to estimate excess mortality in terms of GMT rise relative to pre-industrial levels, assuming no change in demographics or population vulnerability. Results: In the observational period, cold contributes stronger to temperature-related mortality than heat, with overall attributable fractions of 5.49\% (95\%CI: 3.82-7.19) and 0.81\% (95\%CI: 0.72-0.89), respectively. Future projections indicate that this pattern could be reversed under progressing global warming, with heat-related mortality starting to exceed cold-related mortality at 3 degrees C or higher GMT rise. Across cities, projected net increases in total temperature-related mortality were 0.45\% (95\%CI: -0.02-1.06) at 3 degrees C, 1.53\% (95\%CI: 0.96-2.06) at 4 degrees C, and 2.88\% (95\%CI: 1.60-4.10) at 5 degrees C, compared to today's warming level of 1 degrees C. By contrast, no significant difference was found between projected total temperature-related mortality at 2 degrees C versus 1 degrees C of GMT rise. Conclusions: Our results can inform current adaptation policies aimed at buffering the health risks from increased heat exposure under climate change. They also allow for the evaluation of global mitigation efforts in terms of local health benefits in some of Germany's most populated cities.},
  language  = {en}
}
@article{HuberGaedke2006,
  author    = {Huber, Veronika and Gaedke, Ursula},
  title     = {The role of predation for seasonal variability patterns among phytoplankton and ciliates},
  issn      = {0030-1299},
  doi       = {10.1111/j.2006.0030-1299.14753.x},
  year      = {2006},
  abstract  = {Investigating the mechanisms which underlie the biomass fluctuations of populations and communities is important to better understand the processes which buffer community biomass in a variable environment. Based on long- term data of plankton biomass in Lake Constance (Bodensee), this study aims at explaining the different degree of synchrony among populations observed within two freshwater plankton groups, phytoplankton and ciliates. Established measures of temporal variability such as the variance ratio and cross-correlation coefficients were combined with first- order autoregressive models that allow estimating species interactions from time-series data. We found that predation was an important driver of the observed seasonal variability patterns in phytoplankton and ciliates, and that competitive interactions only played a subordinate role. In Lake Constance copepods and cladocerans, two major invertebrate predator groups, focus their grazing pressure at different times of the season. Model results suggested that compensatory dynamics detected in phytoplankton originate from the differential vulnerability of species to either one of these two predator groups. For ciliates model results advocated that synchrony among species occurs because ciliates tend to be vulnerable to both predator groups. Our findings underline the necessity of extending studies of community variability to multiple trophic levels because accounting for predator-prey interactions may often be more important than accounting for competitive interactions at one trophic level},
  language  = {en}
}
@article{FrielerLevermannElliottetal.2015,
  author    = {Frieler, Katja and Levermann, Anders and Elliott, J. and Heinke, Jens and Arneth, A. and Bierkens, M. F. P. and Ciais, Philippe and Clark, D. B. and Deryng, D. and Doell, P. and Falloon, P. and Fekete, B. and Folberth, Christian and Friend, A. D. and Gellhorn, C. and Gosling, S. N. and Haddeland, I. and Khabarov, N. and Lomas, M. and Masaki, Y. and Nishina, K. and Neumann, K. and Oki, T. and Pavlick, R. and Ruane, A. C. and Schmid, E. and Schmitz, C. and Stacke, T. and Stehfest, E. and Tang, Q. and Wisser, D. and Huber, Veronika and Piontek, Franziska and Warszawski, Lila and Schewe, Jacob and Lotze-Campen, Hermann and Schellnhuber, Hans Joachim},
  title     = {A framework for the cross-sectoral integration of multi-model impact projections},
  series = {Earth system dynamics},
  volume    = {6},
  journal   = {Earth system dynamics},
  number    = {2},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {2190-4979},
  doi       = {10.5194/esd-6-447-2015},
  pages     = {447 -- 460},
  year      = {2015},
  abstract  = {Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop-and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.},
  language  = {en}
}