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- ItemCrop productivity changes in 1.5 °C and 2 °C worlds under climate sensitivity uncertainty(Bristol : IOP Publ., 2018) Schleussner, Carl-Friedrich; Deryng, Delphine; Müller, Christoph; Elliott, Joshua; Saeed, Fahad; Folberth, Christian; Liu, Wenfeng; Wang, Xuhui; Pugh, Thomas A. M.; Thiery, Wim; Seneviratne, Sonia I.; Rogelj, JoeriFollowing the adoption of the Paris Agreement, there has been an increasing interest in quantifying impacts at discrete levels of global mean temperature (GMT) increase such as 1.5 °C and 2 °C above pre-industrial levels. Consequences of anthropogenic greenhouse gas emissions on agricultural productivity have direct and immediate relevance for human societies. Future crop yields will be affected by anthropogenic climate change as well as direct effects of emissions such as CO2 fertilization. At the same time, the climate sensitivity to future emissions is uncertain. Here we investigate the sensitivity of future crop yield projections with a set of global gridded crop models for four major staple crops at 1.5 °C and 2 °C warming above pre-industrial levels, as well as at different CO2 levels determined by similar probabilities to lead to 1.5 °C and 2 °C, using climate forcing data from the Half a degree Additional warming, Prognosis and Projected Impacts project. For the same CO2 forcing, we find consistent negative effects of half a degree warming on productivity in most world regions. Increasing CO2 concentrations consistent with these warming levels have potentially stronger but highly uncertain effects than 0.5 °C warming increments. Half a degree warming will also lead to more extreme low yields, in particular over tropical regions. Our results indicate that GMT change alone is insufficient to determine future impacts on crop productivity.
- ItemEvapotranspiration simulations in ISIMIP2a—Evaluation of spatio-temporal characteristics with a comprehensive ensemble of independent datasets(Bristol : IOP Publ., 2018) Wartenburger, Richard; Seneviratne, Sonia I; Hirschi, Martin; Chang, Jinfeng; Ciais, Philippe; Deryng, Delphine; Elliott, Joshua; Folberth, Christian; Gosling, Simon N; Gudmundsson, Lukas; Henrot, Alexandra-Jane; Hickler, Thomas; Ito, Akihiko; Khabarov, Nikolay; Kim, Hyungjun; Leng, Guoyong; Liu, Junguo; Liu, Xingcai; Masaki, Yoshimitsu; Morfopoulos, Catherine; Müller, Christoph; Müller Schmied, Hannes; Nishina, Kazuya; Orth, Rene; Pokhrel, Yadu; Pugh, Thomas A M; Satoh, Yusuke; Schaphoff, Sibyll; Schmid, Erwin; Sheffield, Justin; Stacke, Tobias; Steinkamp, Joerg; Tang, Qiuhong; Thiery, Wim; Wada, Yoshihide; Wang, Xuhui; Weedon, Graham P; Yang, Hong; Zhou, TianActual land evapotranspiration (ET) is a key component of the global hydrological cycle and an essential variable determining the evolution of hydrological extreme events under different climate change scenarios. However, recently available ET products show persistent uncertainties that are impeding a precise attribution of human-induced climate change. Here, we aim at comparing a range of independent global monthly land ET estimates with historical model simulations from the global water, agriculture, and biomes sectors participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). Among the independent estimates, we use the EartH2Observe Tier-1 dataset (E2O), two commonly used reanalyses, a pre-compiled ensemble product (LandFlux-EVAL), and an updated collection of recently published datasets that algorithmically derive ET from observations or observations-based estimates (diagnostic datasets). A cluster analysis is applied in order to identify spatio-temporal differences among all datasets and to thus identify factors that dominate overall uncertainties. The clustering is controlled by several factors including the model choice, the meteorological forcing used to drive the assessed models, the data category (models participating in the different sectors of ISIMIP2a, E2O models, diagnostic estimates, reanalysis-based estimates or composite products), the ET scheme, and the number of soil layers in the models. By using these factors to explain spatial and spatio-temporal variabilities in ET, we find that the model choice mostly dominates (24%–40% of variance explained), except for spatio-temporal patterns of total ET, where the forcing explains the largest fraction of the variance (29%). The most dominant clusters of datasets are further compared with individual diagnostic and reanalysis-based estimates to assess their representation of selected heat waves and droughts in the Great Plains, Central Europe and western Russia. Although most of the ET estimates capture these extreme events, the generally large spread among the entire ensemble indicates substantial uncertainties.
- ItemRapid aggregation of global gridded crop model outputs to facilitate cross-disciplinary analysis of climate change impacts in agriculture(Amsterdam [u.a.] : Elsevier Science, 2015) Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, CarolWe discuss an on-line tool that facilitates access to the large collection of climate impacts on crop yields produced by the Agricultural Model Intercomparison and Improvement Project. This collection comprises the output of seven crop models which were run on a global grid using climate data from five different general circulation models under the current set of representative pathways. The output of this modeling endeavor consists of more than 36,000 publicly available global grids at a spatial resolution of one half degree. We offer flexible ways to aggregate these data while reducing the technical barriers implied by learning new download platforms and specialized formats. The tool is accessed trough any standard web browser without any special bandwidth requirement.
- ItemComparing impacts of climate change and mitigation on global agriculture by 2050(Bristol : IOP Publ., 2018) van Meijl, Hans; Havlik, Petr; Lotze-Campen, Hermann; Stehfest, Elke; Witzke, Peter; Pérez Domínguez, Ignacio; Bodirsky, Benjamin Leon; van Dijk, Michiel; Doelman, Jonathan; Fellmann, Thomas; Humpenöder, Florian; Koopman, Jason F. L.; Müller, Christoph; Popp, Alexander; Tabeau, Andrzej; Valin, Hugo; van Zeist, Willem-JanSystematic model inter-comparison helps to narrow discrepancies in the analysis of the future impact of climate change on agricultural production. This paper presents a set of alternative scenarios by five global climate and agro-economic models. Covering integrated assessment (IMAGE), partial equilibrium (CAPRI, GLOBIOM, MAgPIE) and computable general equilibrium (MAGNET) models ensures a good coverage of biophysical and economic agricultural features. These models are harmonized with respect to basic model drivers, to assess the range of potential impacts of climate change on the agricultural sector by 2050. Moreover, they quantify the economic consequences of stringent global emission mitigation efforts, such as non-CO2 emission taxes and land-based mitigation options, to stabilize global warming at 2 °C by the end of the century under different Shared Socioeconomic Pathways. A key contribution of the paper is a vis-à-vis comparison of climate change impacts relative to the impact of mitigation measures. In addition, our scenario design allows assessing the impact of the residual climate change on the mitigation challenge. From a global perspective, the impact of climate change on agricultural production by mid-century is negative but small. A larger negative effect on agricultural production, most pronounced for ruminant meat production, is observed when emission mitigation measures compliant with a 2 °C target are put in place. Our results indicate that a mitigation strategy that embeds residual climate change effects (RCP2.6) has a negative impact on global agricultural production relative to a no-mitigation strategy with stronger climate impacts (RCP6.0). However, this is partially due to the limited impact of the climate change scenarios by 2050. The magnitude of price changes is different amongst models due to methodological differences. Further research to achieve a better harmonization is needed, especially regarding endogenous food and feed demand, including substitution across individual commodities, and endogenous technological change.