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End date: 2020 × Start date: 2019 × End date: 2014 × Start date: 2013 × DDC: 500 × Has files: Yes × Type: Text ×

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Now showing 1 - 10 of 39
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    Quantifying uncertainties in soil carbon responses to changes in global mean temperature and precipitation
    (München : European Geopyhsical Union, 2014) Nishina, K.; Ito, A.; Beerling, D.J.; Cadule, P.; Ciais, P.; Clark, D.B.; Friend, A.D.; Kahana, R.; Kato, E.; Keribin, R.; Lucht, W.; Lomas, M.; Rademacher, T.T.; Pavlick, R.; Schaphoff, S.; Vuichard, N.; Warszawaski, L.; Yokohata, T.
    Soil organic carbon (SOC) is the largest carbon pool in terrestrial ecosystems and may play a key role in biospheric feedbacks with elevated atmospheric carbon dioxide (CO2) in a warmer future world. We examined the simulation results of seven terrestrial biome models when forced with climate projections from four representative-concentration-pathways (RCPs)-based atmospheric concentration scenarios. The goal was to specify calculated uncertainty in global SOC stock projections from global and regional perspectives and give insight to the improvement of SOC-relevant processes in biome models. SOC stocks among the biome models varied from 1090 to 2650 Pg C even in historical periods (ca. 2000). In a higher forcing scenario (i.e., RCP8.5), inconsistent estimates of impact on the total SOC (2099–2000) were obtained from different biome model simulations, ranging from a net sink of 347 Pg C to a net source of 122 Pg C. In all models, the increasing atmospheric CO2 concentration in the RCP8.5 scenario considerably contributed to carbon accumulation in SOC. However, magnitudes varied from 93 to 264 Pg C by the end of the 21st century across biome models. Using the time-series data of total global SOC simulated by each biome model, we analyzed the sensitivity of the global SOC stock to global mean temperature and global precipitation anomalies (ΔT and ΔP respectively) in each biome model using a state-space model. This analysis suggests that ΔT explained global SOC stock changes in most models with a resolution of 1–2 °C, and the magnitude of global SOC decomposition from a 2 °C rise ranged from almost 0 to 3.53 Pg C yr−1 among the biome models. However, ΔP had a negligible impact on change in the global SOC changes. Spatial heterogeneity was evident and inconsistent among the biome models, especially in boreal to arctic regions. Our study reveals considerable climate uncertainty in SOC decomposition responses to climate and CO2 change among biome models. Further research is required to improve our ability to estimate biospheric feedbacks through both SOC-relevant and vegetation-relevant processes.
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    Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models
    (München : European Geopyhsical Union, 2013) Menon, A.; Levermann, A.; Schewe, J.; Lehmann, J.; Frieler, K.
    The possibility of an impact of global warming on the Indian monsoon is of critical importance for the large population of this region. Future projections within the Coupled Model Intercomparison Project Phase 3 (CMIP-3) showed a wide range of trends with varying magnitude and sign across models. Here the Indian summer monsoon rainfall is evaluated in 20 CMIP-5 models for the period 1850 to 2100. In the new generation of climate models, a consistent increase in seasonal mean rainfall during the summer monsoon periods arises. All models simulate stronger seasonal mean rainfall in the future compared to the historic period under the strongest warming scenario RCP-8.5. Increase in seasonal mean rainfall is the largest for the RCP-8.5 scenario compared to other RCPs. Most of the models show a northward shift in monsoon circulation by the end of the 21st century compared to the historic period under the RCP-8.5 scenario. The interannual variability of the Indian monsoon rainfall also shows a consistent positive trend under unabated global warming. Since both the long-term increase in monsoon rainfall as well as the increase in interannual variability in the future is robust across a wide range of models, some confidence can be attributed to these projected trends.
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    A trend-preserving bias correction – The ISI-MIP approach
    (München : European Geopyhsical Union, 2013) Hempel, S.; Frieler, K.; Warszawski, L.; Schewe, J.; Piontek, F.
    Statistical bias correction is commonly applied within climate impact modelling to correct climate model data for systematic deviations of the simulated historical data from observations. Methods are based on transfer functions generated to map the distribution of the simulated historical data to that of the observations. Those are subsequently applied to correct the future projections. Here, we present the bias correction method that was developed within ISI-MIP, the first Inter-Sectoral Impact Model Intercomparison Project. ISI-MIP is designed to synthesise impact projections in the agriculture, water, biome, health, and infrastructure sectors at different levels of global warming. Bias-corrected climate data that are used as input for the impact simulations could be only provided over land areas. To ensure consistency with the global (land + ocean) temperature information the bias correction method has to preserve the warming signal. Here we present the applied method that preserves the absolute changes in monthly temperature, and relative changes in monthly values of precipitation and the other variables needed for ISI-MIP. The proposed methodology represents a modification of the transfer function approach applied in the Water Model Intercomparison Project (Water-MIP). Correction of the monthly mean is followed by correction of the daily variability about the monthly mean. Besides the general idea and technical details of the ISI-MIP method, we show and discuss the potential and limitations of the applied bias correction. In particular, while the trend and the long-term mean are well represented, limitations with regards to the adjustment of the variability persist which may affect, e.g. small scale features or extremes.
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    Climate change impact on available water resources obtained using multiple global climate and hydrology models
    (München : European Geopyhsical Union, 2013) Hagemann, S.; Chen, C.; Clark, D.B.; Folwell, S.; Gosling, S.N.; Haddeland, I.; Hanasaki, N.; Heinke, J.; Ludwig, F.; Voss, F.; Wiltshire, A.J.
    Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.
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    Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa
    (München : European Geopyhsical Union, 2013) Lindeskog, M.; Arneth, A.; Bondeau, A.; Waha, K.; Seaquist, J.; Olin, S.; Smith, B.
    Dynamic global vegetation models (DGVMs) are important tools for modelling impacts of global change on ecosystem services. However, most models do not take full account of human land management and land use and land cover changes (LULCCs). We integrated croplands and pasture and their management and natural vegetation recovery and succession following cropland abandonment into the LPJ-GUESS DGVM. The revised model was applied to Africa as a case study to investigate the implications of accounting for land use on net ecosystem carbon balance (NECB) and the skill of the model in describing agricultural production and reproducing trends and patterns in vegetation structure and function. The seasonality of modelled monthly fraction of absorbed photosynthetically active radiation (FPAR) was shown to agree well with satellite-inferred normalised difference vegetation index (NDVI). In regions with a large proportion of cropland, the managed land addition improved the FPAR vs. NDVI fit significantly. Modelled 1991–1995 average yields for the seven most important African crops, representing potential optimal yields limited only by climate forcings, were generally higher than reported FAO yields by a factor of 2–6, similar to previous yield gap estimates. Modelled inter-annual yield variations during 1971–2005 generally agreed well with FAO statistics, especially in regions with pronounced climate seasonality. Modelled land–atmosphere carbon fluxes for Africa associated with land use change (0.07 PgC yr−1 release to the atmosphere for the 1980s) agreed well with previous estimates. Cropland management options (residue removal, grass as cover crop) were shown to be important to the land–atmosphere carbon flux for the 20th century.
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    The role of the North Atlantic overturning and deep ocean for multi-decadal global-mean-temperature variability
    (München : European Geopyhsical Union, 2014) Schleussner, C.F.; Runge, J.; Lehmann, J.; Levermann, A.
    Earth's climate exhibits internal modes of variability on various timescales. Here we investigate multi-decadal variability of the Atlantic meridional overturning circulation (AMOC), Northern Hemisphere sea-ice extent and global mean temperature (GMT) in an ensemble of CMIP5 models under control conditions. We report an inter-annual GMT variability of about ±0.1° C originating solely from natural variability in the model ensemble. By decomposing the GMT variance into contributions of the AMOC and Northern Hemisphere sea-ice extent using a graph-theoretical statistical approach, we find the AMOC to contribute 8% to GMT variability in the ensemble mean. Our results highlight the importance of AMOC sea-ice feedbacks that explain 5% of the GMT variance, while the contribution solely related to the AMOC is found to be about 3%. As a consequence of multi-decadal AMOC variability, we report substantial variations in North Atlantic deep-ocean heat content with trends of up to 0.7 × 1022 J decade−1 that are of the order of observed changes over the last decade and consistent with the reduced GMT warming trend over this period. Although these temperature anomalies are largely density-compensated by salinity changes, we find a robust negative correlation between the AMOC and North Atlantic deep-ocean density with density lagging the AMOC by 5 to 11 yr in most models. While this would in principle allow for a self-sustained oscillatory behavior of the coupled AMOC–deep-ocean system, our results are inconclusive about the role of this feedback in the model ensemble.
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    Extreme summer heat in Phoenix, Arizona (USA) under global climate change (2041-2070)
    (Berlin : Gesellschaft für Erdkunde, 2014) Grossman-Clarke, Susanne; Schubert, Sebastian; Clarke, Thomas R.; Harlan, Sharon L.
    Summer extreme heat events in the arid Phoenix, Arizona (USA) metropolitan region for the period 2041-2070 are projected based on the ensemble of ten climate models from the North American Regional Climate Change Assessment Program for the SRES A2 greenhouse gas emissions scenario by the Intergovernmental Panel on Climate Change. Extreme heat events are identified by measures related to two thresholds of the maximum daily air temperature distribution for the historical reference period 1971-2000. Comparing this reference period to the model ensemble-mean, the frequency of extreme heat events is projected to increase by a factor of six to 1.9 events per summer and the average number of event days per year is projected to increase by a factor of 14. The inter-model range for the average number of EHE days per summer is larger for the projected climate, 10.6 to 42.2 days, than for simulations of the past climate simulations (1.5 to 2.4 days).
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    Comparing projections of future changes in runoff from hydrological and biome models in ISI-MIP
    (München : European Geopyhsical Union, 2013) Davie, J.C.S.; Falloon, P.D.; Kahana, R.; Dankers, R.; Betts, R.; Portmann, F.T.; Wisser, D.; Clark, D.B.; Ito, A.; Masaki, Y.; Nishina, K.; Fekete, B.; Tessler, Z.; Wada, Y.; Liu, X.; Tang, Q.; Hagemann, S.; Stacke, T.; Pavlick, R.; Schaphoff, S.; Gosling, S.N.; Franssen, W.; Arnell, N.
    Future changes in runoff can have important implications for water resources and flooding. In this study, runoff projections from ISI-MIP (Inter-sectoral Impact Model Intercomparison Project) simulations forced with HadGEM2-ES bias-corrected climate data under the Representative Concentration Pathway 8.5 have been analysed for differences between impact models. Projections of change from a baseline period (1981–2010) to the future (2070–2099) from 12 impacts models which contributed to the hydrological and biomes sectors of ISI-MIP were studied. The biome models differed from the hydrological models by the inclusion of CO2 impacts and most also included a dynamic vegetation distribution. The biome and hydrological models agreed on the sign of runoff change for most regions of the world. However, in West Africa, the hydrological models projected drying, and the biome models a moistening. The biome models tended to produce larger increases and smaller decreases in regionally averaged runoff than the hydrological models, although there is large inter-model spread. The timing of runoff change was similar, but there were differences in magnitude, particularly at peak runoff. The impact of vegetation distribution change was much smaller than the projected change over time, while elevated CO2 had an effect as large as the magnitude of change over time projected by some models in some regions. The effect of CO2 on runoff was not consistent across the models, with two models showing increases and two decreases. There was also more spread in projections from the runs with elevated CO2 than with constant CO2. The biome models which gave increased runoff from elevated CO2 were also those which differed most from the hydrological models. Spatially, regions with most difference between model types tended to be projected to have most effect from elevated CO2, and seasonal differences were also similar, so elevated CO2 can partly explain the differences between hydrological and biome model runoff change projections. Therefore, this shows that a range of impact models should be considered to give the full range of uncertainty in impacts studies.
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    Critical impacts of global warming on land ecosystems
    (München : European Geopyhsical Union, 2013) Ostberg, S.; Lucht, W.; Schaphoff, S.; Gerten, D.
    Globally increasing temperatures are likely to have impacts on terrestrial, aquatic and marine ecosystems that are difficult to manage. Quantifying impacts worldwide and systematically as a function of global warming is fundamental to substantiating the discussion on climate mitigation targets and adaptation planning. Here we present a macro-scale analysis of climate change impacts on terrestrial ecosystems based on newly developed sets of climate scenarios featuring a step-wise sampling of global mean temperature increase between 1.5 and 5 K by 2100. These are processed by a biogeochemical model (LPJmL) to derive an aggregated metric of simultaneous biogeochemical and structural shifts in land surface properties which we interpret as a proxy for the risk of shifts and possibly disruptions in ecosystems. Our results show a substantial risk of climate change to transform terrestrial ecosystems profoundly. Nearly no area of the world is free from such risk, unless strong mitigation limits global warming to around 2 degrees above preindustrial level. Even then, our simulations for most climate models agree that up to one-fifth of the land surface may experience at least moderate ecosystem change, primarily at high latitudes and high altitudes. If countries fulfil their current emissions reduction pledges, resulting in roughly 3.5 K of warming, this area expands to cover half the land surface, including the majority of tropical forests and savannas and the boreal zone. Due to differences in regional patterns of climate change, the area potentially at risk of major ecosystem change considering all climate models is up to 2.5 times as large as for a single model.
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    Can bioenergy cropping compensate high carbon emissions from large-scale deforestation of high latitudes?
    (München : European Geopyhsical Union, 2013) Dass, P.; Müller, C.; Brovkin, V.; Cramer, W.
    Numerous studies have concluded that deforestation of the high latitudes result in a global cooling. This is mainly because of the increased albedo of deforested land which dominates over other biogeophysical and biogeochemical mechanisms in the energy balance. This dominance, however, may be due to an underestimation of the biogeochemical response, as carbon emissions are typically at or below the lower end of estimates. Here, we use the dynamic global vegetation model LPJmL for a better estimate of the carbon cycle under such large-scale deforestation. These studies are purely theoretical in order to understand the role of vegetation in the energy balance and the earth system. They must not be mistaken as possible mitigation options, because of the devastating effects on pristine ecosystems. For realistic assumptions of land suitability, the total emissions computed in this study are higher than that of previous studies assessing the effects of boreal deforestation. The warming due to biogeochemical effects ranges from 0.12 to 0.32 °C, depending on the climate sensitivity. Using LPJmL to assess the mitigation potential of bioenergy plantations in the suitable areas of the deforested region, we find that the global biophysical bioenergy potential is 68.1 ± 5.6 EJ yr−1 of primary energy at the end of the 21st century in the most plausible scenario. The avoided combustion of fossil fuels over the time frame of this experiment would lead to further cooling. However, since the carbon debt caused by the cumulative emissions is not repaid by the end of the 21st century, the global temperatures would increase by 0.04 to 0.11 °C. The carbon dynamics in the high latitudes especially with respect to permafrost dynamics and long-term carbon losses, require additional attention in the role for the Earth's carbon and energy budget.