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| Author | Makowski, D.; Asseng, S.; Ewert, F.; Bassu, S.; Durand, J.L.; Li, T.; Martre, P.; Adam, M.; Aggarwal, P.K.; Angulo, C.; Baron, C.; Basso, B.; Bertuzzi, P.; Biernath, C.; Boogaard, H.; Boote, K.J.; Bouman, B.; Bregaglio, S.; Brisson, N.; Buis, S.; Cammarano, D.; Challinor, A.J.; Confalonieri, R.; Conijn, J.G.; Corbeels, M.; Deryng, D.; De Sanctis, G.; Doltra, J.; Fumoto, T.; Gaydon, D.; Gayler, S.; Goldberg, R.; Grant, R.F.; Grassini, P.; Hatfield, J.L.; Hasegawa, T.; Heng, L.; Hoek, S.; Hooker, J.; Hunt, L.A.; Ingwersen, J.; Izaurralde, R.C.; Jongschaap, R.E.E.; Jones, J.W.; Kemanian, R.A.; Kersebaum, K.C.; Kim, S.-H.; Lizaso, J.; Marcaida, M.; Müller, C.; Nakagawa, H.; Naresh Kumar, S.; Nendel, C.; O’Leary, G.J.; Olesen, J.E.; Oriol, P.; Osborne, T.M.; Palosuo, T.; Pravia, M.V.; Priesack, E.; Ripoche, D.; Rosenzweig, C.; Ruane, A.C.; Ruget, F.; Sau, F.; Semenov, M.A.; Shcherbak, I.; Singh, B.; Singh, U.; Soo, H.K.; Steduto, P.; Stöckle, C.; Stratonovitch, P.; Streck, T.; Supit, I.; Tang, L.; Tao, F.; Teixeira, E.I.; Thorburn, P.; Timlin, D.; Travasso, M.; Rötter, R.P.; Waha, K.; Wallach, D.; White, J.W.; Wilkens, P.; Williams, J.R.; Wolf, J.; Yin, X.; Yoshida, H.; Zhang, Z.; Zhu, Y. | ||||
| Title | A statistical analysis of three ensembles of crop model responses to temperature and CO2 concentration | Type | Journal Article | ||
| Year | 2015 | Publication | Agricultural and Forest Meteorology | Abbreviated Journal | Agricultural and Forest Meteorology |
| Volume | 214-215 | Issue | Pages | 483-493 | |
| Keywords | climate change; crop model; emulator; meta-model; statistical model; yield; climate-change; wheat yields; metaanalysis; uncertainty; simulation; impacts | ||||
Abstract  |
Ensembles of process-based crop models are increasingly used to simulate crop growth for scenarios of temperature and/or precipitation changes corresponding to different projections of atmospheric CO2 concentrations. This approach generates large datasets with thousands of simulated crop yield data. Such datasets potentially provide new information but it is difficult to summarize them in a useful way due to their structural complexities. An associated issue is that it is not straightforward to compare crops and to interpolate the results to alternative climate scenarios not initially included in the simulation protocols. Here we demonstrate that statistical models based on random-coefficient regressions are able to emulate ensembles of process-based crop models. An important advantage of the proposed statistical models is that they can interpolate between temperature levels and between CO2 concentration levels, and can thus be used to calculate temperature and [CO2] thresholds leading to yield loss or yield gain, without rerunning the original complex crop models. Our approach is illustrated with three yield datasets simulated by 19 maize models, 26 wheat models, and 13 rice models. Several statistical models are fitted to these datasets, and are then used to analyze the variability of the yield response to [CO2] and temperature. Based on our results, we show that, for wheat, a [CO2] increase is likely to outweigh the negative effect of a temperature increase of +2 degrees C in the considered sites. Compared to wheat, required levels of [CO2] increase are much higher for maize, and intermediate for rice. For all crops, uncertainties in simulating climate change impacts increase more with temperature than with elevated [CO2]. | ||||
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| Language | English | Summary Language | Original Title | ||
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| Series Volume | Series Issue | Edition | |||
| ISSN | 0168-1923 | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM, ft_macsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4714 | ||
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| Author | Rosenzweig, C.; Elliott, J.; Deryng, D.; Ruane, A.C.; Müller, C.; Arneth, A.; Boote, K.J.; Folberth, C.; Glotter, M.; Khabarov, N.; Neumann, K.; Piontek, F.; Pugh, T.A.; Schmid, E.; Stehfest, E.; Yang, H.; Jones, J.W. | ||||
| Title | Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison | Type | Journal Article | ||
| Year | 2014 | Publication | Proceedings of the National Academy of Sciences of the United States of America | Abbreviated Journal | Proc. Natl. Acad. Sci. U. S. A. |
| Volume | 111 | Issue | 9 | Pages | 3268-3273 |
| Keywords | Agriculture/*methods/statistics & numerical data; *Climate Change; Computer Simulation; Crops, Agricultural/*growth & development; Forecasting; Geography; *Models, Theoretical; Nitrogen/*analysis; Risk Assessment; Temperature; AgMIP; Isi-mip; agriculture; climate impacts; food security | ||||
| Abstract |
Here we present the results from an intercomparison of multiple global gridded crop models (GGCMs) within the framework of the Agricultural Model Intercomparison and Improvement Project and the Inter-Sectoral Impacts Model Intercomparison Project. Results indicate strong negative effects of climate change, especially at higher levels of warming and at low latitudes; models that include explicit nitrogen stress project more severe impacts. Across seven GGCMs, five global climate models, and four representative concentration pathways, model agreement on direction of yield changes is found in many major agricultural regions at both low and high latitudes; however, reducing uncertainty in sign of response in mid-latitude regions remains a challenge. Uncertainties related to the representation of carbon dioxide, nitrogen, and high temperature effects demonstrated here show that further research is urgently needed to better understand effects of climate change on agricultural production and to devise targeted adaptation strategies. | ||||
| Address | 2016-10-31 | ||||
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| Language | English | Summary Language | Original Title | ||
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| ISSN | 1091-6490 (Electronic) 0027-8424 (Linking) | ISBN | Medium | Article | |
| Area | Expedition | Conference | |||
| Notes | CropM | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 4801 | ||
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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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| 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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| 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 | 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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| Series Volume | Series Issue | Edition | |||
| ISSN | 0959-3780 | ISBN | Medium | ||
| Area | Expedition | Conference | |||
| Notes | TradeM, ftnotmacsur | Approved | no | ||
| Call Number | MA @ admin @ | Serial | 5005 | ||
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