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    On the importance of cascading moisture recycling in South America
    (MĂ¼nchen : European Geopyhsical Union, 2014) Zemp, D.C.; Schleussner, C.-F.; Barbosa, H.M.J.; van der Ent, R.J.; Donges, J.F.; Heinke, J.; Sampaio, G.; Rammig, A.
    Continental moisture recycling is a crucial process of the South American climate system. In particular, evapotranspiration from the Amazon basin contributes substantially to precipitation regionally as well as over other remote regions such as the La Plata basin. Here we present an in-depth analysis of South American moisture recycling mechanisms. In particular, we quantify the importance of cascading moisture recycling (CMR), which describes moisture transport between two locations on the continent that involves re-evaporation cycles along the way. Using an Eulerian atmospheric moisture tracking model forced by a combination of several historical climate data sets, we were able to construct a complex network of moisture recycling for South America. Our results show that CMR contributes about 9–10% to the total precipitation over South America and 17–18% over the La Plata basin. CMR increases the fraction of total precipitation over the La Plata basin that originates from the Amazon basin from 18–23 to 24–29% during the wet season. We also show that the south-western part of the Amazon basin is not only a direct source of rainfall over the La Plata basin, but also a key intermediary region that distributes moisture originating from the entire Amazon basin towards the La Plata basin during the wet season. Our results suggest that land use change in this region might have a stronger impact on downwind rainfall than previously thought. Using complex network analysis techniques, we find the eastern side of the sub-tropical Andes to be a key region where CMR pathways are channeled. This study offers a better understanding of the interactions between the vegetation and the atmosphere on the water cycle, which is needed in a context of land use and climate change in South America.
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    Recommendations for reporting "black carbon" measurements
    (MĂ¼nchen : European Geopyhsical Union, 2013) Petzold, A.; Ogren, J.A.; Fiebig, M.; Laj, P.; Li, S.-M.; Baltensperger, U.; Holzer-Popp, T.; Kinne, S.; Pappalardo, G.; Sugimoto, N.; Wehrli, C.; Wiedensohler, A.; Zhang, X.-Y.
    Although black carbon (BC) is one of the key atmospheric particulate components driving climate change and air quality, there is no agreement on the terminology that considers all aspects of specific properties, definitions, measurement methods, and related uncertainties. As a result, there is much ambiguity in the scientific literature of measurements and numerical models that refer to BC with different names and based on different properties of the particles, with no clear definition of the terms. The authors present here a recommended terminology to clarify the terms used for BC in atmospheric research, with the goal of establishing unambiguous links between terms, targeted material properties and associated measurement techniques.
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    Projections of global warming-induced impacts on winter storm losses in the German private household sector
    (Dordrecht [u.a.] : Springer, 2013) Held, H.; Gerstengarbe, F.-W.; Pardowitz, T.; Pinto, J.G.; Ulbrich, U.; Born, K.; Donat, M.G.; Karremann, M.K.; Leckebusch, G.C.; Ludwig, P.; Nissen, K.M.; Ă–sterle, H.; Prahl, B.F.; Werner, P.C.; Befort, D.J.; Burghoff, O.
    We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971-2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6-35 % for 2011-2040, of 20-30 % for 2041-2070, and of 40-55 % for 2071-2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.
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    The challenge to detect and attribute effects of climate change on human and natural systems
    (Dordrecht [u.a.] : Springer, 2013) Stone, D.; Auffhammer, M.; Carey, M.; Hansen, G.; Huggel, C.; Cramer, W.; Lobell, D.; Molau, U.; Solow, A.; Tibig, L.; Yohe, G.
    Anthropogenic climate change has triggered impacts on natural and human systems world-wide, yet the formal scientific method of detection and attribution has been only insufficiently described. Detection and attribution of impacts of climate change is a fundamentally cross-disciplinary issue, involving concepts, terms, and standards spanning the varied requirements of the various disciplines. Key problems for current assessments include the limited availability of long-term observations, the limited knowledge on processes and mechanisms involved in changing environmental systems, and the widely different concepts applied in the scientific literature. In order to facilitate current and future assessments, this paper describes the current conceptual framework of the field and outlines a number of conceptual challenges. Based on this, it proposes workable cross-disciplinary definitions, concepts, and standards. The paper is specifically intended to serve as a baseline for continued development of a consistent cross-disciplinary framework that will facilitate integrated assessment of the detection and attribution of climate change impacts.
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    Climate of the last millennium: Ensemble consistency of simulations and reconstructions
    (Göttingen : Copernicus, 2013) Bothe, O.; Jungclaus, J.H.; Zanchettin, D.; Zorita, E.
    Are simulations and reconstructions of past climate and its variability consistent with each other? We assess the consistency of simulations and reconstructions for the climate of the last millennium under the paradigm of a statistically indistinguishable ensemble. In this type of analysis, the null hypothesis is that reconstructions and simulations are statistically indistinguishable and, therefore, are exchangeable with each other. Ensemble consistency is assessed for Northern Hemisphere mean temperature, Central European mean temperature and for global temperature fields. Reconstructions available for these regions serve as verification data for a set of simulations of the climate of the last millennium performed at the Max Planck Institute for Meteorology. Consistency is generally limited to some sub-domains and some sub-periods. Only the ensemble simulated and reconstructed annual Central European mean temperatures for the second half of the last millennium demonstrates unambiguous consistency. Furthermore, we cannot exclude consistency of an ensemble of reconstructions of Northern Hemisphere temperature with the simulation ensemble mean. If we treat simulations and reconstructions as equitable hypotheses about past climate variability, the found general lack of their consistency weakens our confidence in inferences about past climate evolutions on the considered spatial and temporal scales. That is, our available estimates of past climate evolutions are on an equal footing but, as shown here, inconsistent with each other.
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    Global and regional effects of land-use change on climate in 21st century simulations with interactive carbon cycle
    (Göttingen : Copernicus GmbH, 2014) Boysen, L.R.; Brovkin, V.; Arora, V.K.; Cadule, P.; De Noblet-Ducoudré, N.; Kato, E.; Pongratz, J.; Gayler, V.
    Biogeophysical (BGP) and biogeochemical (BGC) effects of land-use and land cover change (LULCC) are separated at the global and regional scales in new interactive CO2simulations for the 21st century. Results from four earth system models (ESMs) are analyzed for the future RCP8.5 scenario from simulations with and without land-use and land cover change (LULCC), contributing to the Land-Use and Climate, IDentification of robust impacts (LUCID) project. Over the period 2006-2100, LULCC causes the atmospheric CO2concentration to increase by 12, 22, and 66 ppm in CanESM2, MIROC-ESM, and MPI-ESM-LR, respectively. Statistically significant changes in global near-surface temperature are found in three models with a BGC-induced global mean annual warming between 0.07 and 0.23 K. BGP-induced responses are simulated by three models in areas of intense LULCC of varying sign and magnitude (between g 0.47 and 0.10 K). Modifications of the land carbon pool by LULCC are disentangled in accordance with processes that can lead to increases and decreases in this carbon pool. Global land carbon losses due to LULCC are simulated by all models: 218, 57, 35 and 34 Gt C by MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR and CanESM2, respectively. On the contrary, the CO2-fertilization effect caused by elevated atmospheric CO2concentrations due to LULCC leads to a land carbon gain of 39 Gt C in MPI-ESM-LR and is almost negligible in the other models. A substantial part of the spread in models' responses to LULCC is attributed to the differences in implementation of LULCC (e.g., whether pastures or crops are simulated explicitly) and the simulation of specific processes. Simple idealized experiments with clear protocols for implementing LULCC in ESMs are needed to increase the understanding of model responses and the statistical significance of results, especially when analyzing the regional-scale impacts of LULCC.
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    Climate impacts on human livelihoods: Where uncertainty matters in projections of water availability
    (MĂ¼nchen : European Geopyhsical Union, 2014) Lissner, T.K.; Reusser, D.E.; Schewe, J.; Lakes, T.; Kropp, J.P.
    Climate change will have adverse impacts on many different sectors of society, with manifold consequences for human livelihoods and well-being. However, a systematic method to quantify human well-being and livelihoods across sectors is so far unavailable, making it difficult to determine the extent of such impacts. Climate impact analyses are often limited to individual sectors (e.g. food or water) and employ sector-specific target measures, while systematic linkages to general livelihood conditions remain unexplored. Further, recent multi-model assessments have shown that uncertainties in projections of climate impacts deriving from climate and impact models, as well as greenhouse gas scenarios, are substantial, posing an additional challenge in linking climate impacts with livelihood conditions. This article first presents a methodology to consistently measure what is referred to here as AHEAD (Adequate Human livelihood conditions for wEll-being And Development). Based on a trans-disciplinary sample of concepts addressing human well-being and livelihoods, the approach measures the adequacy of conditions of 16 elements. We implement the method at global scale, using results from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) to show how changes in water availability affect the fulfilment of AHEAD at national resolution. In addition, AHEAD allows for the uncertainty of climate and impact model projections to be identified and differentiated. We show how the approach can help to put the substantial inter-model spread into the context of country-specific livelihood conditions by differentiating where the uncertainty about water scarcity is relevant with regard to livelihood conditions – and where it is not. The results indicate that livelihood conditions are compromised by water scarcity in 34 countries. However, more often, AHEAD fulfilment is limited through other elements. The analysis shows that the water-specific uncertainty ranges of the model output are outside relevant thresholds for AHEAD for 65 out of 111 countries, and therefore do not contribute to the overall uncertainty about climate change impacts on livelihoods. In 46 of the countries in the analysis, water-specific uncertainty is relevant to AHEAD. The AHEAD method presented here, together with first results, forms an important step towards making scientific results more applicable for policy decisions.
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    Modelling flood damages under climate change conditions-a case study for Germany
    (Göttingen : Copernicus GmbH, 2014) Hattermann, F.F.; Huang, S.; Burghoff, O.; Willems, W.; Ă–sterle, H.; BĂ¼chner, M.; Kundzewicz, Z.
    The aim of the study is to analyze and discuss possible climate change impacts on flood damages in Germany. The study was initiated and supported by the German insurance sector whereby the main goal was to identify general climate-related trends in flood hazard and damages and to explore sensitivity of results to climate scenario uncertainty. The study makes use of climate scenarios regionalized for the main river basins in Germany. A hydrological model (SWIM) that had been calibrated and validated for the main river gauges, was applied to transform these scenarios into discharge for more than 5000 river reaches. Extreme value distribution has been fitted to the time series of river discharge to derive the flood frequency statistics. The hydrological results for each river reach have been linked using the flood statistics to related damage functions provided by the German Insurance Association, considering damages on buildings and small enterprises. The result is that, under the specific scenario conditions, a considerable increase in flood related losses can be expected in Germany in future, warmer, climate.
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    Decomposing the effects of ocean warming on chlorophyll a concentrations into physically and biologically driven contributions
    (Bristol : IOP Publishing, 2013) Olonscheck, D.; Hofmann, M.; Worm, B.; Schellnhuber, H.J.
    Recently compiled observational data suggest a substantial decline in the global median chlorophyll a concentration over the 20th century, a trend that appears to be linked to ocean warming. Several modelling studies have considered changes in the ocean's physical structure as a possible cause, while experimental work supports a biological mechanism, namely an observed increase in zooplankton grazing rate that outpaces phytoplankton production at higher temperatures. Here, we present transient simulations derived from a coupled ocean general circulation and carbon cycle model forced by atmospheric fields under unabated anthropogenic global warming (IPCC SRES A1FI scenario). The simulations account for both physical and biological mechanisms, and can reproduce about one quarter of the observed chlorophyll a decline during the 20th century, when using realistically parameterized temperature sensitivity of zooplankton metabolism (Q10 between 2 and 4) and phytoplankton growth (Q10 ~ 1.9). Therefore, we have employed and re-calibrated the standard ecosystem model which assumes a lower temperature sensitivity of zooplankton grazing (Q10 = 1.1049) by re-scaling phytoplankton growth rates and zooplankton grazing rates. Our model projects a global chlorophyll a decline of >50% by the end of the 21st century. While phytoplankton abundance and chlorophyll a experience pronounced negative effects, primary production and zooplankton concentrations are less sensitive to ocean warming. Although changes in physical structure play an important role, much of the simulated change in chlorophyll a and productivity is related to the uneven temperature sensitivity of the marine ecosystem.
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    A multi-model analysis of risk of ecosystem shifts under climate change
    (Bristol : IOP Publishing, 2013) Warszawski, Lila; Friend, Andrew; Ostberg, Sebastian; Frieler, Katja; Lucht, Wolfgang; Schaphoff, Sibyll; Beerling, David; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B.; Kahana, Ron; Ito, Akihiko; Keribin, Rozenn; Kleidon, Axel; Lomas, Mark; Nishina, Kazuya; Pavlick, Ryan; Rademacher, Tim Tito; Buechner, Matthias; Piontek, Franziska; Schewe, Jacob; Serdeczny, Olivia; Schellnhuber, Hans Joachim
    Climate change may pose a high risk of change to Earth's ecosystems: shifting climatic boundaries may induce changes in the biogeochemical functioning and structures of ecosystems that render it difficult for endemic plant and animal species to survive in their current habitats. Here we aggregate changes in the biogeochemical ecosystem state as a proxy for the risk of these shifts at different levels of global warming. Estimates are based on simulations from seven global vegetation models (GVMs) driven by future climate scenarios, allowing for a quantification of the related uncertainties. 5–19% of the naturally vegetated land surface is projected to be at risk of severe ecosystem change at 2 ° C of global warming (ΔGMT) above 1980–2010 levels. However, there is limited agreement across the models about which geographical regions face the highest risk of change. The extent of regions at risk of severe ecosystem change is projected to rise with ΔGMT, approximately doubling between ΔGMT = 2 and 3 ° C, and reaching a median value of 35% of the naturally vegetated land surface for ΔGMT = 4 °C. The regions projected to face the highest risk of severe ecosystem changes above ΔGMT = 4 °C or earlier include the tundra and shrublands of the Tibetan Plateau, grasslands of eastern India, the boreal forests of northern Canada and Russia, the savanna region in the Horn of Africa, and the Amazon rainforest.