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Abstract The 1.5°C target is now widely considered as the maximum acceptable limit for global warming. However, it is at once recent and, as it appears increasingly unreachable, already almost obsolete. Adopted as an aspirational...
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Abstract The 1.5°C target is now widely considered as the maximum acceptable limit for global warming. However, it is at once recent and, as it appears increasingly unreachable, already almost obsolete. Adopted as an aspirational target in the Paris Agreement in 2015, the 1.5°C objective originated with a political impetus within UNFCCC negotiations. The Intergovernmental Panel on Climate Change (IPCC) endorsed this policy‐driven target when it produced the Special Report on 1.5°C. This article highlights the continuity of the history of the 1.5°C target with that of the 2°C target, but also the differences between the two. Because the 1.5°C target considerably raises the bar on mitigation efforts, it exacerbates political tensions and ambiguities that were already latent in the 2°C target. This article retraces the emergence of the 1.5°C in diplomatic negotiations, the preparation of the IPCC Special report on 1.5°C, and the new kinds of debates they provoked among climate scientists and experts. To explain how an unreachable target became the reference for climate action, we analyze the “political calibration” of climate science and politics, which can also be described as a codependency between climate science and politics. This article is categorized under: Integrated Assessment of Climate Change > Integrated Assessment Modeling Climate, History, Society, Culture > World Historical Perspectives Assessing Impacts of Climate Change > Evaluating Future Impacts of Climate Change
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This paper presents a range of future, spatially explicit, land use change scenarios for the EU15, Norway and Switzerland based on an interpretation of the global storylines of the Intergovernmental Panel on Climate Change (IPCC) ...
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This paper presents a range of future, spatially explicit, land use change scenarios for the EU15, Norway and Switzerland based on an interpretation of the global storylines of the Intergovernmental Panel on Climate Change (IPCC) that are presented inthe special report on emissions scenarios (SRES). The methodology is based on a qualitative interpretation of the SRES storylines for the European region, an estimation of the aggregate totals of land use change using various land use change models andthe allocation of these aggregate quantities in space using spatially explicit rules. The spatial patterns are further downscaled from a resolution of 10 min to 250 m using statistical downscaling procedures. The scenarios include the major land use/landcover classes urban, cropland, grassland and forest land as well as introducing new land use classes such as bioenergy crops. The scenario changes are most striking for the agricultural land uses, with large area declines resulting from assumptions about future crop yield development with respect to changes in the demand for agricultural commodities. Abandoned agricultural land is a consequence of these assumptions. Increases in urban areas (arising from population and economic change) are similar foreach scenario, but the spatial patterns are very different. This reflects alternative assumptions about urban development processes. Forest land areas increase in all scenarios, although such changes will occur slowly and largely reflect assumed policy objectives. The scenarios also consider changes in protected areas (for conservation or recreation goals) and how these might provide a break on future land use change. The approach to estimate new protected areas is based in part on the use of models ofspecies distribution and richness. All scenarios assume some increases in the area of bioenergy crops with some scenarios assuming a major development of this new land use. Several technical and conceptual difficulties in developing future land use change scenarios are discussed. These include the problems of the subjective nature of qualitative interpretations, the land use change models used in scenario development, the problem of validating future change scenarios, the quality of the observed baseline, and statistical downscaling techniques.
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摘要 :Monthly scenarios of relative humidity (R H) were obtained for the Malaprabha river basin in India using a statistical downscaling technique. Large-scale atmospheric variables (air temperature and specific humidity at 925 mb, surf...
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Monthly scenarios of relative humidity (R H) were obtained for the Malaprabha river basin in India using a statistical downscaling technique. Large-scale atmospheric variables (air temperature and specific humidity at 925 mb, surface air temperature and latent heat flux) were chosen as predictors. The predictor variables are extracted from the (1) National Centers for Environmental Prediction reanalysis dataset for the period 1978–2000, and (2) simulations of the third generation Canadian Coupled Global Climate Model for the period 1978–2100. The objective of this study was to investigate the uncertainties in regional scenarios developed for R H due to the choice of emission scenarios (A1B, A2, B1 and COMMIT) and the predictors selected. Multi-linear regression with stepwise screening is the downscaling technique used in this study. To study the uncertainty in the regional scenarios of R H, due to the selected predictors, eight sets of predictors were chosen and a downscaling model was developed for each set. Performance of the downscaling models in the baseline period (1978–2000) was studied using three measures (1) Nash–Sutcliffe error estimate (E f), (2) mean absolute error (MAE), and (3) product moment correlation (P). Results show that the performances vary between 0.59 and 0.68, 0.42 and 0.50 and 0.77 and 0.82 for E f, MAE and P. Cumulative distribution functions were prepared from the regional scenarios of R H developed for combinations of predictors and emission scenarios. Results show a variation of 1 to 6% R H in the scenarios developed for combination of predictor sets for baseline period. For a future period (2001–2100), a variation of 6 to 15% R H was observed for the combination of emission scenarios and predictors. The variation was highest for A2 scenario and least for COMMIT and B1 scenario.
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The Intergovernmental Panel on Climate Change (IPCC) described main-streaming climate change mitigation into development choices in its Fourth Assessment Report, chapter 12 of Working Group Ⅲ. It also pointed out that "few macro-...
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The Intergovernmental Panel on Climate Change (IPCC) described main-streaming climate change mitigation into development choices in its Fourth Assessment Report, chapter 12 of Working Group Ⅲ. It also pointed out that "few macro-indicators include measures of progress with respect to climate change" despite the needs for the inclusion. This paper tackled this point in the following ways by applying an integrated assessment model. First, this study applied shadow prices and production, endogenously obtained from the model, instead of using market prices and statistical data used in preceding studies in the economics literature. Second, this study measured forecasts of genuine saving (GS) and wealth globally up to the year 2100, while preceding studies were constrained to past and current savings and wealth. Third, this study examined changes in GS and wealth in different future scenarios on IPCC SRES (Special Report on Emissions Scenarios) with CO_2 emissions constraints. Finally, the authors adopted a GS estimation methodology of shadow prices in imperfect economies by Kenneth Arrow and Partha Dasgupta, instead of that of perfect economies by Kirk Hamilton et al., on which the authors had based previous studies. This makes the indicator consistent with changes of wealth.
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