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Author | Heinke, J.; Ostberg, S.; Schaphoff, S.; Frieler, K.; Müller, C.; Gerten, D.; Meinshausen, M.; Lucht, W. | ||||
Title | A new climate dataset for systematic assessments of climate change impacts as a function of global warming | Type | Journal Article | ||
Year | 2013 | Publication | Geoscientific Model Development | Abbreviated Journal | Geosci. Model Dev. |
Volume | 6 | Issue | 5 | Pages | 1689-1703 |
Keywords | dangerous anthropogenic interference; vegetation model; carbon-cycle; emissions; targets | ||||
Abstract | In the ongoing political debate on climate change, global mean temperature change (Delta T-glob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of Delta T-glob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of Delta T-glob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere-Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs’ climate change properties, even though they, necessarily, utilise a simplified relationships between Delta T-glob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations. | ||||
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Language | English | Summary Language | Original Title | ||
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ISSN | 1991-9603 | ISBN | Medium | Article | |
Area | Expedition | Conference | |||
Notes | CropM | Approved | no | ||
Call Number | MA @ admin @ | Serial | 4490 | ||
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Author | Bodirsky, B.L.; Müller, C. | ||||
Title | Robust relationship between yields and nitrogen inputs indicates three ways to reduce nitrogen pollution | Type | Journal Article | ||
Year | 2014 | Publication | Environmental Research Letters | Abbreviated Journal | Environ. Res. Lett. |
Volume | 9 | Issue | 11 | Pages | 111005 |
Keywords | nitrogen use efficiency; nitrogen; fertilizer; nitrogen pollution; agriculture; yields; mitigation; framework | ||||
Abstract | Historic increases in agricultural production came at the expense of substantial environmental burden through nitrogen pollution. Lassaletta et al (2014 Environ. Res. Lett. 9 105011) examine the historic relationship of crop yields and nitrogen fertilizer inputs globally and find a simple and robust relationship of declining nitrogen use efficiency with increasing nitrogen inputs. This general relationship helps to understand the dilemma between increased agricultural production and nitrogen pollution and allows identifying pathways towards more sustainable agricultural production and necessary associated policies. | ||||
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Language | English | Summary Language | Original Title | ||
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ISSN | 1748-9326 | ISBN | Medium | Article | |
Area | Expedition | Conference | |||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 4514 | ||
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Author | Kriegler, E.; Bauer, N.; Popp, A.; Humpenöder, F.; Leimbach, M.; Strefler, J.; Baumstark, L.; Bodirsky, B.L.; Hilaire, J.; Klein, D.; Mouratiadou, I.; Weindl, I.; Bertram, C.; Dietrich, J.-P.; Luderer, G.; Pehl, M.; Pietzcker, R.; Piontek, F.; Lotze-Campen, H.; Biewald, A.; Bonsch, M.; Giannousakis, A.; Kreidenweis, U.; Müller, C.; Rolinski, S.; Schultes, A.; Schwanitz, J.; Stevanovic, M.; Calvin, K.; Emmerling, J.; Fujimori, S.; Edenhofer, O. | ||||
Title | Fossil-fueled development (SSP5): An energy and resource intensive scenario for the 21st century | Type | Journal Article | ||
Year | 2017 | Publication | Global Environmental Change | Abbreviated Journal | Glob. Environ. Change |
Volume | 42 | Issue | Pages | 297-315 | |
Keywords | Shared Socio-economic Pathway; SSP5; Emission scenario; Energy transformation; Land-use change; Integrated assessment modeling | ||||
Abstract | Highlights • The SSP5 scenarios mark the upper end of the scenario literature in fossil fuel use, food demand, energy use and greenhouse gas emissions. • The SSP5 marker scenario results in a radiative forcing pathway close to the highest Representative Concentration Pathway (RCP8.5). • An investigation of mitigation policies in SSP5 confirms high socio-economic challenges to mitigation in SSP5. • In SSP5, ambitious climate targets require land based carbon management options such as avoided deforestation and bioenergy production with CCS. • The SSP5 scenarios provide useful reference points for future climate change, impact, adaption, mitigation and sustainable development analysis. Abstract This paper presents a set of energy and resource intensive scenarios based on the concept of Shared Socio-Economic Pathways (SSPs). The scenario family is characterized by rapid and fossil-fueled development with high socio-economic challenges to mitigation and low socio-economic challenges to adaptation (SSP5). A special focus is placed on the SSP5 marker scenario developed by the REMIND-MAgPIE integrated assessment modeling framework. The SSP5 baseline scenarios exhibit very high levels of fossil fuel use, up to a doubling of global food demand, and up to a tripling of energy demand and greenhouse gas emissions over the course of the century, marking the upper end of the scenario literature in several dimensions. These scenarios are currently the only SSP scenarios that result in a radiative forcing pathway as high as the highest Representative Concentration Pathway (RCP8.5). This paper further investigates the direct impact of mitigation policies on the SSP5 energy, land and emissions dynamics confirming high socio-economic challenges to mitigation in SSP5. Nonetheless, mitigation policies reaching climate forcing levels as low as in the lowest Representative Concentration Pathway (RCP2.6) are accessible in SSP5. The SSP5 scenarios presented in this paper aim to provide useful reference points for future climate change, climate impact, adaption and mitigation analysis, and broader questions of sustainable development. | ||||
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ISSN | 0959-3780 | ISBN | Medium | ||
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Notes | TradeM, ftnotmacsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 5005 | ||
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Author | Houska, T.; Kraft, P.; Liebermann, R.; Klatt, S.; Kraus, D.; Haas, E.; Santabarbara, I.; Kiese, R.; Butterbach-Bahl, K.; Müller, C.; Breuer, L. | ||||
Title | Rejecting hydro-biogeochemical model structures by multi-criteria evaluation | Type | Journal Article | ||
Year | 2017 | Publication | Environmental Modelling & Software | Abbreviated Journal | Env. Model. Softw. |
Volume | 93 | Issue | Pages | 1-12 | |
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Abstract | Highlights • New method to investigate biogeochemical model structure performance. • Process based hydrological modelling can improve biogeochemical model predictions. • Modelling efficiency dramatically drops with multiple objectives. Abstract This work presents a novel way for assessing and comparing different hydro-biogeochemical model structures and their performances. We used the LandscapeDNDC modelling framework to set up four models of different complexity, considering two soil-biogeochemical and two hydrological modules. The performance of each model combination was assessed using long-term (8 years) data and applying different thresholds, considering multiple criteria and objective functions. Our results show that each model combination had its strength for particular criteria. However, only 0.01% of all model runs passed the complete rejectionist framework. In contrast, our comparatively applied assessments of single thresholds, as frequently used in other studies, lead to a much higher acceptance rate of 40–70%. Therefore, our study indicates that models can be right for the wrong reasons, i.e., matching GHG emissions while at the same time failing to simulate other criteria such as soil moisture or plant biomass dynamics. | ||||
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ISSN | 1364-8152 | ISBN | Medium | ||
Area | Expedition | Conference | |||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 4983 | ||
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Author | Challinor, A.J.; Müller, C.; Asseng, S.; Deva, C.; Nicklin, K.J.; Wallach, D.; Vanuytrecht, E.; Whitfield, S.; Ramirez-Villegas, J.; Koehler, A.-K. | ||||
Title | Improving the use of crop models for risk assessment and climate change adaptation | Type | Journal Article | ||
Year | 2017 | Publication | Agricultural Systems | Abbreviated Journal | Agric. Syst. |
Volume | 159 | Issue | Pages | 296-306 | |
Keywords | Crop model; Risk assessment; Climate change impacts; Adaptation; Climate models; Uncertainty | ||||
Abstract | Highlights • 14 criteria for use of crop models in assessments of impacts, adaptation and risk • Working with stakeholders to identify timing of risks is key to risk assessments. • Multiple methods needed to critically assess the use of climate model output • Increasing transparency and inter-comparability needed in risk assessments Abstract Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper. |
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Publisher | Place of Publication | Editor | |||
Language | Summary Language | phase 2+ | Original Title | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 0308521x | ISBN | Medium | ||
Area | CropM | Expedition | Conference | ||
Notes | CropM, ft_macsur | Approved | no | ||
Call Number | MA @ admin @ | Serial | 5175 | ||
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