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- ItemClimate change increases riverine carbon outgassing, while export to the ocean remains uncertain(München : European Geopyhsical Union, 2016) Langerwisch, F.; Walz, A.; Rammig, A.; Tietjen, B.; Thonicke, K.; Cramer, W.Any regular interaction of land and river during flooding affects carbon pools within the terrestrial system, riverine carbon and carbon exported from the system. In the Amazon basin carbon fluxes are considerably influenced by annual flooding, during which terrigenous organic material is imported to the river. The Amazon basin therefore represents an excellent example of a tightly coupled terrestrial–riverine system. The processes of generation, conversion and transport of organic carbon in such a coupled terrigenous–riverine system strongly interact and are climate-sensitive, yet their functioning is rarely considered in Earth system models and their response to climate change is still largely unknown. To quantify regional and global carbon budgets and climate change effects on carbon pools and carbon fluxes, it is important to account for the coupling between the land, the river, the ocean and the atmosphere. We developed the RIVerine Carbon Model (RivCM), which is directly coupled to the well-established dynamic vegetation and hydrology model LPJmL, in order to account for this large-scale coupling. We evaluate RivCM with observational data and show that some of the values are reproduced quite well by the model, while we see large deviations for other variables. This is mainly caused by some simplifications we assumed. Our evaluation shows that it is possible to reproduce large-scale carbon transport across a river system but that this involves large uncertainties. Acknowledging these uncertainties, we estimate the potential changes in riverine carbon by applying RivCM for climate forcing from five climate models and three CO2 emission scenarios (Special Report on Emissions Scenarios, SRES). We find that climate change causes a doubling of riverine organic carbon in the southern and western basin while reducing it by 20% in the eastern and northern parts. In contrast, the amount of riverine inorganic carbon shows a 2- to 3-fold increase in the entire basin, independent of the SRES scenario. The export of carbon to the atmosphere increases as well, with an average of about 30%. In contrast, changes in future export of organic carbon to the Atlantic Ocean depend on the SRES scenario and are projected to either decrease by about 8.9% (SRES A1B) or increase by about 9.1% (SRES A2). Such changes in the terrigenous–riverine system could have local and regional impacts on the carbon budget of the whole Amazon basin and parts of the Atlantic Ocean. Changes in riverine carbon could lead to a shift in the riverine nutrient supply and pH, while changes in the exported carbon to the ocean lead to changes in the supply of organic material that acts as a food source in the Atlantic. On larger scales the increased outgassing of CO2 could turn the Amazon basin from a sink of carbon to a considerable source. Therefore, we propose that the coupling of terrestrial and riverine carbon budgets should be included in subsequent analysis of the future regional carbon budget.
- ItemDecomposing uncertainties in the future terrestrial carbon budget associated with emission scenarios, climate projections, and ecosystem simulations using the ISI-MIP results(München : European Geopyhsical Union, 2015) Nishina, K.; Ito, A.; Falloon, P.; Friend, A.D.; Beerling, D.J.; Ciais, P.; Clark, D.B.; Kahana, R.; Kato, E.; Lucht, W.; Lomas, M.; Pavlick, R.; Schaphoff, S.; Warszawaski, L.; Yokohata, T.We examined the changes to global net primary production (NPP), vegetation biomass carbon (VegC), and soil organic carbon (SOC) estimated by six global vegetation models (GVMs) obtained from the Inter-Sectoral Impact Model Intercomparison Project. Simulation results were obtained using five global climate models (GCMs) forced with four representative concentration pathway (RCP) scenarios. To clarify which component (i.e., emission scenarios, climate projections, or global vegetation models) contributes the most to uncertainties in projected global terrestrial C cycling by 2100, analysis of variance (ANOVA) and wavelet clustering were applied to 70 projected simulation sets. At the end of the simulation period, changes from the year 2000 in all three variables varied considerably from net negative to positive values. ANOVA revealed that the main sources of uncertainty are different among variables and depend on the projection period. We determined that in the global VegC and SOC projections, GVMs are the main influence on uncertainties (60 % and 90 %, respectively) rather than climate-driving scenarios (RCPs and GCMs). Moreover, the divergence of changes in vegetation carbon residence times is dominated by GVM uncertainty, particularly in the latter half of the 21st century. In addition, we found that the contribution of each uncertainty source is spatiotemporally heterogeneous and it differs among the GVM variables. The dominant uncertainty source for changes in NPP and VegC varies along the climatic gradient. The contribution of GVM to the uncertainty decreases as the climate division becomes cooler (from ca. 80 % in the equatorial division to 40 % in the snow division). Our results suggest that to assess climate change impacts on global ecosystem C cycling among each RCP scenario, the long-term C dynamics within the ecosystems (i.e., vegetation turnover and soil decomposition) are more critical factors than photosynthetic processes. The different trends in the contribution of uncertainty sources in each variable among climate divisions indicate that improvement of GVMs based on climate division or biome type will be effective. On the other hand, in dry regions, GCMs are the dominant uncertainty source in climate impact assessments of vegetation and soil C dynamics.
- ItemProjecting Antarctica's contribution to future sea level rise from basal ice shelf melt using linear response functions of 16 ice sheet models (LARMIP-2)(Göttingen : Copernicus Publ., 2020) Levermann, Anders; Winkelmann, Ricarda; Albrecht, Torsten; Goelzer, Heiko; Golledge, Nicholas R.; Greve, Ralf; Huybrechts, Philippe; Jordan, Jim; Leguy, Gunter; Martin, Daniel; Morlighem, Mathieu; Pattyn, Frank; Pollard, David; Quiquet, Aurelien; Rodehacke, Christian; Seroussi, Helene; Sutter, Johannes; Zhang, Tong; Van Breedam, Jonas; Calov, Reinhard; DeConto, Robert; Dumas, Christophe; Garbe, Julius; Gudmundsson, G. Hilmar; Hoffman, Matthew J.; Humbert, Angelika; Kleiner, Thomas; Lipscomb, William H.; Meinshausen, Malte; Ng, Esmond; Nowicki, Sophie M.J.; Perego, Mauro; Price, Stephen F.; Saito, Fuyuki; Schlegel, Nicole-Jeanne; Sun, Sainan; van de Wal, Roderik S.W.The sea level contribution of the Antarctic ice sheet constitutes a large uncertainty in future sea level projections. Here we apply a linear response theory approach to 16 state-of-the-art ice sheet models to estimate the Antarctic ice sheet contribution from basal ice shelf melting within the 21st century. The purpose of this computation is to estimate the uncertainty of Antarctica's future contribution to global sea level rise that arises from large uncertainty in the oceanic forcing and the associated ice shelf melting. Ice shelf melting is considered to be a major if not the largest perturbation of the ice sheet's flow into the ocean. However, by computing only the sea level contribution in response to ice shelf melting, our study is neglecting a number of processes such as surface-mass-balance-related contributions. In assuming linear response theory, we are able to capture complex temporal responses of the ice sheets, but we neglect any self-dampening or self-amplifying processes. This is particularly relevant in situations in which an instability is dominating the ice loss. The results obtained here are thus relevant, in particular wherever the ice loss is dominated by the forcing as opposed to an internal instability, for example in strong ocean warming scenarios. In order to allow for comparison the methodology was chosen to be exactly the same as in an earlier study (Levermann et al., 2014) but with 16 instead of 5 ice sheet models. We include uncertainty in the atmospheric warming response to carbon emissions (full range of CMIP5 climate model sensitivities), uncertainty in the oceanic transport to the Southern Ocean (obtained from the time-delayed and scaled oceanic subsurface warming in CMIP5 models in relation to the global mean surface warming), and the observed range of responses of basal ice shelf melting to oceanic warming outside the ice shelf cavity. This uncertainty in basal ice shelf melting is then convoluted with the linear response functions of each of the 16 ice sheet models to obtain the ice flow response to the individual global warming path. The model median for the observational period from 1992 to 2017 of the ice loss due to basal ice shelf melting is 10.2 mm, with a likely range between 5.2 and 21.3 mm. For the same period the Antarctic ice sheet lost mass equivalent to 7.4mm of global sea level rise, with a standard deviation of 3.7mm (Shepherd et al., 2018) including all processes, especially surface-mass-balance changes. For the unabated warming path, Representative Concentration Pathway 8.5 (RCP8.5), we obtain a median contribution of the Antarctic ice sheet to global mean sea level rise from basal ice shelf melting within the 21st century of 17 cm, with a likely range (66th percentile around the mean) between 9 and 36 cm and a very likely range (90th percentile around the mean) between 6 and 58 cm. For the RCP2.6 warming path, which will keep the global mean temperature below 2 °C of global warming and is thus consistent with the Paris Climate Agreement, the procedure yields a median of 13 cm of global mean sea level contribution. The likely range for the RCP2.6 scenario is between 7 and 24 cm, and the very likely range is between 4 and 37 cm. The structural uncertainties in the method do not allow for an interpretation of any higher uncertainty percentiles.We provide projections for the five Antarctic regions and for each model and each scenario separately. The rate of sea level contribution is highest under the RCP8.5 scenario. The maximum within the 21st century of the median value is 4 cm per decade, with a likely range between 2 and 9 cm per decade and a very likely range between 1 and 14 cm per decade. © Author(s) 2020.
- ItemMulti-model climate impact assessment and intercomparison for three large-scale river basins on three continents(München : European Geopyhsical Union, 2015) Vetter, T.; Huang, S.; Aich, V.; Yang, T.; Wang, X.; Krysanova, V.; Hattermann, F.Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years, climate impact assessment has been performed for many river basins worldwide using different climate scenarios and models. However, their results are hardly comparable, and do not allow one to create a full picture of impacts and uncertainties. Therefore, a systematic intercomparison of impacts is suggested, which should be done for representative regions using state-of-the-art models. Only a few such studies have been available until now with the global-scale hydrological models, and our study is intended as a step in this direction by applying the regional-scale models. The impact assessment presented here was performed for three river basins on three continents: the Rhine in Europe, the Upper Niger in Africa and the Upper Yellow in Asia. For that, climate scenarios from five general circulation models (GCMs) and three hydrological models, HBV, SWIM and VIC, were used. Four representative concentration pathways (RCPs) covering a range of emissions and land-use change projections were included. The objectives were to analyze and compare climate impacts on future river discharge and to evaluate uncertainties from different sources. The results allow one to draw some robust conclusions, but uncertainties are large and shared differently between sources in the studied basins. Robust results in terms of trend direction and slope and changes in seasonal dynamics could be found for the Rhine basin regardless of which hydrological model or forcing GCM is used. For the Niger River, scenarios from climate models are the largest uncertainty source, providing large discrepancies in precipitation, and therefore clear projections are difficult to do. For the Upper Yellow basin, both the hydrological models and climate models contribute to uncertainty in the impacts, though an increase in high flows in the future is a robust outcome ensured by all three hydrological models.
- ItemA framework for the cross-sectoral integration of multi-model impact projections: Land use decisions under climate impacts uncertainties(München : European Geopyhsical Union, 2015) Frieler, K.; Levermann, A.; Elliott, J.; Heinke, J.; Arneth, A.; Bierkens, M.F.P.; Ciais, P.; Clark, D.B.; Deryng, D.; Döll, P.; Falloon, P.; Fekete, B.; Folberth, C.; Friend, A.D.; Gellhorn, C.; Gosling, S.N.; Haddeland, I.; Khabarov, N.; Lomas, M.; Masaki, Y.; Nishina, K.; Neumann, K.; Oki, T.; Pavlick, R.; Ruane, A.C.; Schmid, E.; Schmitz, C.; Stacke, T.; Stehfest, E.; Tang, Q.; Wisser, D.; Huber, V.; Piontek, F.; Warszawski, L.; Schewe, J.; Lotze-Campen, H.; Schellnhuber, H.J.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.
- ItemProjecting Antarctic ice discharge using response functions from SeaRISE ice-sheet models(München : European Geopyhsical Union, 2014) Levermann, A.; Winkelmann, R.; Nowicki, S.; Fastook, J.L.; Frieler, K.; Greve, R.; Hellmer, H.H.; Martin, M.A.; Meinshausen, M.; Mengel, M.; Payne, A.J.; Pollard, D.; Sato, T.; Timmermann, R.; Wang, W.L.; Bindschadler, R.A.The largest uncertainty in projections of future sea-level change results from the potentially changing dynamical ice discharge from Antarctica. Basal ice-shelf melting induced by a warming ocean has been identified as a major cause for additional ice flow across the grounding line. Here we attempt to estimate the uncertainty range of future ice discharge from Antarctica by combining uncertainty in the climatic forcing, the oceanic response and the ice-sheet model response. The uncertainty in the global mean temperature increase is obtained from historically constrained emulations with the MAGICC-6.0 (Model for the Assessment of Greenhouse gas Induced Climate Change) model. The oceanic forcing is derived from scaling of the subsurface with the atmospheric warming from 19 comprehensive climate models of the Coupled Model Intercomparison Project (CMIP-5) and two ocean models from the EU-project Ice2Sea. The dynamic ice-sheet response is derived from linear response functions for basal ice-shelf melting for four different Antarctic drainage regions using experiments from the Sea-level Response to Ice Sheet Evolution (SeaRISE) intercomparison project with five different Antarctic ice-sheet models. The resulting uncertainty range for the historic Antarctic contribution to global sea-level rise from 1992 to 2011 agrees with the observed contribution for this period if we use the three ice-sheet models with an explicit representation of ice-shelf dynamics and account for the time-delayed warming of the oceanic subsurface compared to the surface air temperature. The median of the additional ice loss for the 21st century is computed to 0.07 m (66% range: 0.02–0.14 m; 90% range: 0.0–0.23 m) of global sea-level equivalent for the low-emission RCP-2.6 (Representative Concentration Pathway) scenario and 0.09 m (66% range: 0.04–0.21 m; 90% range: 0.01–0.37 m) for the strongest RCP-8.5. Assuming no time delay between the atmospheric warming and the oceanic subsurface, these values increase to 0.09 m (66% range: 0.04–0.17 m; 90% range: 0.02–0.25 m) for RCP-2.6 and 0.15 m (66% range: 0.07–0.28 m; 90% range: 0.04–0.43 m) for RCP-8.5. All probability distributions are highly skewed towards high values. The applied ice-sheet models are coarse resolution with limitations in the representation of grounding-line motion. Within the constraints of the applied methods, the uncertainty induced from different ice-sheet models is smaller than that induced by the external forcing to the ice sheets.
- ItemClimate impact research: Beyond patchwork(München : European Geopyhsical Union, 2014) Huber, V.; Schellnhuber, H.J.; Arnell, N.W.; Frieler, K.; Gerten, D.; Haddeland, I.; Kabat, P.; Lotze-Campen, H.; Lucht, W.; Parry, M.; Piontek, F.; Rosenzweig, C.; Schewe, J.; Warszawski, L.Despite significant progress in climate impact research, the narratives that science can presently piece together of a 2, 3, 4, or 5 °C warmer world remain fragmentary. Here we briefly review past undertakings to characterise comprehensively and quantify climate impacts based on multi-model approaches. We then report on the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), a community-driven effort to compare impact models across sectors and scales systematically, and to quantify the uncertainties along the chain from greenhouse gas emissions and climate input data to the modelling of climate impacts themselves. We show how ISI-MIP and similar efforts can substantially advance the science relevant to impacts, adaptation and vulnerability, and we outline the steps that need to be taken in order to make the most of the available modelling tools. We discuss pertinent limitations of these methods and how they could be tackled. We argue that it is time to consolidate the current patchwork of impact knowledge through integrated cross-sectoral assessments, and that the climate impact community is now in a favourable position to do so.
- ItemPrenormative verification and validation of a protocol for measuring magnetite–maghemite ratios in magnetic nanoparticles(Sèvres : Bureau, 2021) Bogart, Lara K.; Fock, Jeppe; da Costa, Geraldo M.; Witte, Kerstin; Greneche, Jean-Marc; Zukrowski, Jan; Sikora, Marcin; Latta, Drew E.; Scherer, Michelle M.; Hansen, Mikkel Fougt; Frandsen, Cathrine; Pankhurst, Quentin A.An important step in establishing any new metrological method is a prenormative interlaboratory study, designed to verify and validate the method against its stated aims. Here, the 57Fe Mössbauer spectrometric ‘centre of gravity’ (COG) method was tested as a means of quantifying the magnetite/maghemite (Fe3O4/γ-Fe2O3) composition ratio in biphasic magnetic nanoparticles. The study involved seven laboratories across Europe and North and South America, and six samples—a verification set of three microcrystalline mixtures of known composition, and a validation set of three nanoparticle samples of unknown composition. The spectra were analysed by each participant using in-house fitting packages, and ex post facto by a single operator using an independent package. Repeatability analysis was performed using Mandel’s h statistic and modified Youden plots. It is shown that almost all (83/84) of the Mandel h statistic values fall within the 0.5% significance level, with the one exception being borderline. Youden-based pairwise analysis indicates the dominance of random uncertainties; and in almost all cases the data analysis phase is only a minor contributor to the overall measurement uncertainty. It is concluded that the COG method is a robust and promising candidate for its intended purpose.
- ItemUncertainty of simulated groundwater recharge at different global warming levels: a global-scale multi-model ensemble study(Munich : EGU, 2021) Reinecke, Robert; Müller Schmied, Hannes; Trautmann, Tim; Andersen, Lauren Seaby; Burek, Peter; Flörke, Martina; Gosling, Simon N.; Grillakis, Manolis; Hanasaki, Naota; Koutroulis, Aristeidis; Pokhrel, Yadu; Thiery, Wim; Wada, Yoshihide; Yusuke, Satoh; Döll, PetraBillions of people rely on groundwater as being an accessible source of drinking water and for irrigation, especially in times of drought. Its importance will likely increase with a changing climate. It is still unclear, however, how climate change will impact groundwater systems globally and, thus, the availability of this vital resource. Groundwater recharge is an important indicator for groundwater availability, but it is a water flux that is difficult to estimate as uncertainties in the water balance accumulate, leading to possibly large errors in particular in dry regions. This study investigates uncertainties in groundwater recharge projections using a multi-model ensemble of eight global hydrological models (GHMs) that are driven by the bias-adjusted output of four global circulation models (GCMs). Pre-industrial and current groundwater recharge values are compared with recharge for different global warming (GW) levels as a result of three representative concentration pathways (RCPs). Results suggest that projected changes strongly vary among the different GHM–GCM combinations, and statistically significant changes are only computed for a few regions of the world. Statistically significant GWR increases are projected for northern Europe and some parts of the Arctic, East Africa, and India. Statistically significant decreases are simulated in southern Chile, parts of Brazil, central USA, the Mediterranean, and southeastern China. In some regions, reversals of groundwater recharge trends can be observed with global warming. Because most GHMs do not simulate the impact of changing atmospheric CO2 and climate on vegetation and, thus, evapotranspiration, we investigate how estimated changes in GWR are affected by the inclusion of these processes. In some regions, inclusion leads to differences in groundwater recharge changes of up to 100 mm per year. Most GHMs with active vegetation simulate less severe decreases in groundwater recharge than GHMs without active vegetation and, in some regions, even increases instead of decreases are simulated. However, in regions where GCMs predict decreases in precipitation and where groundwater availability is the most important, model agreement among GHMs with active vegetation is the lowest. Overall, large uncertainties in the model outcomes suggest that additional research on simulating groundwater processes in GHMs is necessary.
- ItemUnderstanding flood regime changes in Europe: A state-of-the-art assessment(Göttingen : Copernicus GmbH, 2014) Hall, J.; Arheimer, B.; Borga, M.; Brázdil, R.; Claps, P.; Kiss, A.; Kjeldsen, T.R.; Kriauĉuniene, J.; Kundzewicz, Z.W.; Lang, M.; Llasat, M.C.; Macdonald, N.; McIntyre, N.; Mediero, L.; Merz, B.; Merz, R.; Molnar, P.; Montanari, A.; Neuhold, C.; Parajka, J.; Perdigão, R.A.P.; Plavcová, L.; Rogger, M.; Salinas, J.L.; Sauquet, E.; Schär, C.; Szolgay, J.; Viglione, A.; Blöschl, G.There is growing concern that flooding is becoming more frequent and severe in Europe. A better understanding of flood regime changes and their drivers is therefore needed. The paper reviews the current knowledge on flood regime changes in European rivers that has traditionally been obtained through two alternative research approaches. The first approach is the data-based detection of changes in observed flood events. Current methods are reviewed together with their challenges and opportunities. For example, observation biases, the merging of different data sources and accounting for nonlinear drivers and responses. The second approach consists of modelled scenarios of future floods. Challenges and opportunities associated with flood change scenarios are discussed such as fully accounting for uncertainties in the modelling cascade and feedbacks. To make progress in flood change research, we suggest that a synthesis of these two approaches is needed. This can be achieved by focusing on long duration records and flood-rich and flood-poor periods rather than on short duration flood trends only, by formally attributing causes of observed flood changes, by validating scenarios against observed flood regime dynamics, and by developing low-dimensional models of flood changes and feedbacks. The paper finishes with a call for a joint European flood change research network.