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  • 1
    Online Resource
    Online Resource
    Springer Science and Business Media LLC ; 2020
    In:  Climatic Change Vol. 163, No. 3 ( 2020-12), p. 1587-1601
    In: Climatic Change, Springer Science and Business Media LLC, Vol. 163, No. 3 ( 2020-12), p. 1587-1601
    Abstract: Bioenergy is expected to play an important role in the achievement of stringent climate-change mitigation targets requiring the application of negative emissions technology. Using a multi-model framework, we assess the effects of high bioenergy demand on global food production, food security, and competition for agricultural land. Various scenarios simulate global bioenergy demands of 100, 200, 300, and 400 exajoules (EJ) by 2100, with and without a carbon price. Six global energy-economy-agriculture models contribute to this study, with different methodologies and technologies used for bioenergy supply and greenhouse-gas mitigation options for agriculture. We find that the large-scale use of bioenergy, if not implemented properly, would raise food prices and increase the number of people at risk of hunger in many areas of the world. For example, an increase in global bioenergy demand from 200 to 300 EJ causes a − 11% to + 40% change in food crop prices and decreases food consumption from − 45 to − 2 kcal person −1  day −1 , leading to an additional 0 to 25 million people at risk of hunger compared with the case of no bioenergy demand (90th percentile range across models). This risk does not rule out the intensive use of bioenergy but shows the importance of its careful implementation, potentially including regulations that protect cropland for food production or for the use of bioenergy feedstock on land that is not competitive with food production.
    Type of Medium: Online Resource
    ISSN: 0165-0009 , 1573-1480
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
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    detail.hit.zdb_id: 1477652-2
    SSG: 14
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  • 2
    Online Resource
    Online Resource
    Wiley ; 2023
    In:  International Journal of Climatology Vol. 43, No. 2 ( 2023-02), p. 1167-1178
    In: International Journal of Climatology, Wiley, Vol. 43, No. 2 ( 2023-02), p. 1167-1178
    Abstract: El Niño–Southern Oscillation (ENSO) is one of the most important modes of climate variability on interannual timescales. We aim to find out whether a change in ENSO frequency can be predicted for the nearer future. We analyse the unforced pre‐industrial control run and the forced 1%/year CO 2 increase run for an ensemble of 43 general circulation models that participated in the Coupled Model Intercomparison Project Phase 6 (CMIP6). We assume that the uncertainty of ENSO frequency trend estimates from an ensemble is caused by apparent trends as well as model differences. The part of the uncertainty caused by apparent trends is estimated from the pre‐industrial control simulations. As a measure for ENSO frequency, we use the number of El Niño‐ and La Niña‐like months in a moving 30‐year time window. Its linear decadal trend is calculated for every member. The multimember mean of the trend for both experiments is less than 0.7 events per decade. Given that the standard error is of the same order of magnitude, we consider this a negligible trend. The uncertainties are large in both experiments and we can attribute most of the intermember variability to apparent trends due to natural variability rather than different model reactions to CO 2 forcing. This means that the impact of intermodel differences might have been overstated in previous studies. Apparent trends make it very difficult to make reliable predictions of changes in ENSO frequency based on 120‐year time series.
    Type of Medium: Online Resource
    ISSN: 0899-8418 , 1097-0088
    URL: Issue
    RVK:
    Language: English
    Publisher: Wiley
    Publication Date: 2023
    detail.hit.zdb_id: 1491204-1
    SSG: 14
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  • 3
    In: Monthly Weather Review, American Meteorological Society, Vol. 148, No. 9 ( 2020-09-01), p. 3653-3680
    Abstract: The representation of tropical precipitation is evaluated across three generations of models participating in phases 3, 5, and 6 of the Coupled Model Intercomparison Project (CMIP). Compared to state-of-the-art observations, improvements in tropical precipitation in the CMIP6 models are identified for some metrics, but we find no general improvement in tropical precipitation on different temporal and spatial scales. Our results indicate overall little changes across the CMIP phases for the summer monsoons, the double-ITCZ bias, and the diurnal cycle of tropical precipitation. We find a reduced amount of drizzle events in CMIP6, but tropical precipitation occurs still too frequently. Continuous improvements across the CMIP phases are identified for the number of consecutive dry days, for the representation of modes of variability, namely, the Madden–Julian oscillation and El Niño–Southern Oscillation, and for the trends in dry months in the twentieth century. The observed positive trend in extreme wet months is, however, not captured by any of the CMIP phases, which simulate negative trends for extremely wet months in the twentieth century. The regional biases are larger than a climate change signal one hopes to use the models to identify. Given the pace of climate change as compared to the pace of model improvements to simulate tropical precipitation, we question the past strategy of the development of the present class of global climate models as the mainstay of the scientific response to climate change. We suggest the exploration of alternative approaches such as high-resolution storm-resolving models that can offer better prospects to inform us about how tropical precipitation might change with anthropogenic warming.
    Type of Medium: Online Resource
    ISSN: 0027-0644 , 1520-0493
    RVK:
    Language: English
    Publisher: American Meteorological Society
    Publication Date: 2020
    detail.hit.zdb_id: 2033056-X
    detail.hit.zdb_id: 202616-8
    SSG: 14
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  • 4
    In: Climatic Change, Springer Science and Business Media LLC, Vol. 163, No. 3 ( 2020-12), p. 1569-1586
    Abstract: In the twenty-first century, modern bioenergy could become one of the largest sources of energy, partially replacing fossil fuels and contributing to climate change mitigation. Agricultural and forestry biomass residues form an inexpensive bioenergy feedstock with low greenhouse gas (GHG) emissions, if harvested sustainably. We analysed quantities of biomass residues supplied for energy and their sensitivities in harmonised bioenergy demand scenarios across eight integrated assessment models (IAMs) and compared them with literature-estimated residue availability. IAM results vary substantially, at both global and regional scales, but suggest that residues could meet 7–50% of bioenergy demand towards 2050, and 2–30% towards 2100, in a scenario with 300 EJ/year of exogenous bioenergy demand towards 2100. When considering mean literature-estimated availability, residues could provide around 55 EJ/year by 2050. Inter-model differences primarily arise from model structure, assumptions, and the representation of agriculture and forestry. Despite these differences, drivers of residues supplied and underlying cost dynamics are largely similar across models. Higher bioenergy demand or biomass prices increase the quantity of residues supplied for energy, though their effects level off as residues become depleted. GHG emission pricing and land protection can increase the costs of using land for lignocellulosic bioenergy crop cultivation, which increases residue use at the expense of lignocellulosic bioenergy crops. In most IAMs and scenarios, supplied residues in 2050 are within literature-estimated residue availability, but outliers and sustainability concerns warrant further exploration. We conclude that residues can cost-competitively play an important role in the twenty-first century bioenergy supply, though uncertainties remain concerning (regional) forestry and agricultural production and resulting residue supply potentials.
    Type of Medium: Online Resource
    ISSN: 0165-0009 , 1573-1480
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 751086-X
    detail.hit.zdb_id: 1477652-2
    SSG: 14
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  • 5
    Online Resource
    Online Resource
    Elsevier BV ; 2022
    In:  Geoderma Vol. 427 ( 2022-12), p. 116132-
    In: Geoderma, Elsevier BV, Vol. 427 ( 2022-12), p. 116132-
    Type of Medium: Online Resource
    ISSN: 0016-7061
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 281080-3
    detail.hit.zdb_id: 2001729-7
    SSG: 13
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  • 6
    In: Quaternary Science Reviews, Elsevier BV, Vol. 308 ( 2023-05), p. 108099-
    Type of Medium: Online Resource
    ISSN: 0277-3791
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2023
    detail.hit.zdb_id: 780249-3
    detail.hit.zdb_id: 1495523-4
    SSG: 14
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  • 7
    In: Climatic Change, Springer Science and Business Media LLC, Vol. 172, No. 1-2 ( 2022-05)
    Abstract: Bioenergy is projected to have a prominent, valuable, and maybe essential, role in climate management. However, there is significant variation in projected bioenergy deployment results, as well as concerns about the potential environmental and social implications of supplying biomass. Bioenergy deployment projections are market equilibrium solutions from integrated modeling, yet little is known about the underlying modeling of the supply of biomass as a feedstock for energy use in these modeling frameworks. We undertake a novel diagnostic analysis with ten global models to elucidate, compare, and assess how biomass is supplied within the models used to inform long-run climate management. With experiments that isolate and reveal biomass supply modeling behavior and characteristics (costs, emissions, land use, market effects), we learn about biomass supply tendencies and differences. The insights provide a new level of modeling transparency and understanding of estimated global biomass supplies that informs evaluation of the potential for bioenergy in managing the climate and interpretation of integrated modeling. For each model, we characterize the potential distributions of global biomass supply across regions and feedstock types for increasing levels of quantity supplied, as well as some of the potential societal externalities of supplying biomass. We also evaluate the biomass supply implications of managing these externalities. Finally, we interpret biomass market results from integrated modeling in terms of our new understanding of biomass supply. Overall, we find little consensus between models on where biomass could be cost-effectively produced and the implications. We also reveal model specific biomass supply narratives, with results providing new insights into integrated modeling bioenergy outcomes and differences. The analysis finds that many integrated models are considering and managing emissions and land use externalities of supplying biomass and estimating that environmental and societal trade-offs in the form of land emissions, land conversion, and higher agricultural prices are cost-effective, and to some degree a reality of using biomass, to address climate change.
    Type of Medium: Online Resource
    ISSN: 0165-0009 , 1573-1480
    RVK:
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
    detail.hit.zdb_id: 751086-X
    detail.hit.zdb_id: 1477652-2
    SSG: 14
    Location Call Number Limitation Availability
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