| Records |
| Author |
Elliott, J.; Müller, C.; Deryng, D.; Chryssanthacopoulos, J.; Boote, K.J.; Büchner, M.; Foster, I.; Glotter, M.; Heinke, J.; Iizumi, T.; Izaurralde, R.C.; Mueller, N.D.; Ray, D.K.; Rosenzweig, C.; Ruane, A.C.; Sheffield, J. |
| Title |
The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0) |
Type |
Journal Article |
| Year |
2015 |
Publication |
Geoscientific Model Development |
Abbreviated Journal |
Geosci. Model Dev. |
| Volume |
8 |
Issue |
2 |
Pages |
261-277 |
| Keywords |
land-surface model; climate-change; systems simulation; high-resolution; water; carbon; yield; agriculture; patterns; growth |
| Abstract |
We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project includes global simulations of yields, phenologies, and many land-surface fluxes using 12-15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification of key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record. |
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| ISSN |
1991-9603 |
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| Notes |
CropM, ft_macsur |
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no |
| Call Number |
MA @ admin @ |
Serial |
4559 |
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| Author |
Coucheney, E.; Buis, S.; Launay, M.; Constantin, J.; Mary, B.; García de Cortázar-Atauri, I.; Ripoche, D.; Beaudoin, N.; Ruget, F.; &rianarisoa, K.S.; Le Bas, C.; Justes, E.; Léonard, J. |
| Title |
Accuracy, robustness and behavior of the STICS soil–crop model for plant, water and nitrogen outputs: Evaluation over a wide range of agro-environmental conditions in France |
Type |
Journal Article |
| Year |
2015 |
Publication |
Environmental Modelling & Software |
Abbreviated Journal |
Env. Model. Softw. |
| Volume |
64 |
Issue |
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Pages |
177-190 |
| Keywords |
soil-crop model; stics; model performances; plant biomass; soil nitrogen; soil water; remote-sensing data; goodness-of-fit; hydrological model; simulation-models; solar-radiation; regional-scale; climate-change; generic model; data set; validation |
| Abstract |
Soil-crop models are increasingly used as predictive tools to assess yield and environmental impacts of agriculture in a growing diversity of contexts. They are however seldom evaluated at a given time over a wide domain of use. We tested here the performances of the STICS model (v8.2.2) with its standard set of parameters over a dataset covering 15 crops and a wide range of agropedoclimatic conditions in France. Model results showed a good overall accuracy, with little bias. Relative RMSE was larger for soil nitrate (49%) than for plant biomass (35%) and nitrogen (33%) and smallest for soil water (10%). Trends induced by contrasted environmental conditions and management practices were well reproduced. Finally, limited dependency of model errors on crops or environments indicated a satisfactory robustness. Such performances make STICS a valuable tool for studying the effects of changes in agro-ecosystems over the domain explored. (C) 2014 Elsevier Ltd. All rights reserved. |
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1364-8152 |
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CropM |
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MA @ admin @ |
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4554 |
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Nelson, G.C.; Valin, H.; Sands, R.D.; Havlík, P.; Ahammad, H.; Deryng, D.; Elliott, J.; Fujimori, S.; Hasegawa, T.; Heyhoe, E.; Kyle, P.; Von Lampe, M.; Lotze-Campen, H.; Mason d’Croz, D.; van Meijl, H.; van der Mensbrugghe, D.; Müller, C.; Popp, A.; Robertson, R.; Robinson, S.; Schmid, E.; Schmitz, C.; Tabeau, A.; Willenbockel, D. |
| Title |
Climate change effects on agriculture: economic responses to biophysical shocks |
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 |
3274-3279 |
| Keywords |
Agriculture/*economics; Carbon Dioxide/analysis; *Climate Change; Commerce/statistics & numerical data; Computer Simulation; Crops, Agricultural/*growth & development; Forecasting; Humans; *Models, Economic; agricultural productivity; climate change adaptation; integrated assessment; model intercomparison |
| Abstract |
Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m(2). The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change. |
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0027-8424 1091-6490 |
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CropM, TradeM, ft_macsur |
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no |
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MA @ admin @ |
Serial |
4535 |
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Piontek, F.; Müller, C.; Pugh, T.A.; Clark, D.B.; Deryng, D.; Elliott, J.; Colón González, F.J.; Flörke, M.; Folberth, C.; Franssen, W.; Frieler, K.; Friend, A.D.; Gosling, S.N.; Hemming, D.; Khabarov, N.; Kim, H.; Lomas, M.R.; Masaki, Y.; Mengel, M.; Morse, A.; Neumann, K.; Nishina, K.; Ostberg, S.; Pavlick, R.; Ruane, A.C.; Schewe, J.; Schmid, E.; Stacke, T.; Tang, Q.; Tessler, Z.D.; Tompkins, A.M.; Warszawski, L.; Wisser, D.; Schellnhuber, H.J. |
| Title |
Multisectoral climate impact hotspots in a warming world |
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 |
3233-3238 |
| Keywords |
Agriculture/statistics & numerical data; Computer Simulation; Conservation of Natural Resources/*methods; Ecosystem; *Environment; Geography; Global Warming/economics/*statistics & numerical data; Humans; Malaria/epidemiology; *Models, Theoretical; *Public Policy; Temperature; Water Supply/statistics & numerical data; Isi-mip; coinciding pressures; differential climate impacts |
| Abstract |
The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty. |
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0027-8424 |
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CropM |
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MA @ admin @ |
Serial |
4538 |
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Kersebaum, K.C.; Nendel, C. |
| Title |
Site-specific impacts of climate change on wheat production across regions of Germany using different CO2 response functions |
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Journal Article |
| Year |
2014 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
52 |
Issue |
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Pages |
22-32 |
| Keywords |
climate change; co2 effect; crop yield; water use efficiency; groundwater; modeling nitrogen dynamics; winter-wheat; carbon-dioxide; assessing uncertainties; agricultural crops; potential impact; enrichment face; elevated co2; soil; simulation |
| Abstract |
Impact of climate change on crop growth, groundwater recharge and nitrogen leaching in winter wheat production in Germany was assessed using the agro-ecosystem model HERMES with a downscaled (WETTREG) climate change scenario A1B from the ECHAM5 global circulation model. Three alternative algorithms describing the impact of atmospheric CO2 concentration on crop growth (a simple Farquhar-type algorithm, a combined light-use efficiency – maximum assimilation approach and a simple scaling of the maximum assimilation rate) in combination with a Penman-Monteith approach which includes a simple stomata conduction model for evapotranspiration under changing CO2 concentrations were compared within the framework of the HERMES model. The effect of differences in regional climate change, site conditions and different CO2 algorithms on winter wheat yield, groundwater recharge and nitrogen leaching was assessed in 22 regional simulation case studies across Germany. Results indicate that the effects of climate change on wheat production will vary across Germany due to different regional expressions of climate change projection. Predicted yield changes between the reference period (1961-1990) and a future period (2021-2050) range from -0.4 t ha(-1), -0.8 t ha(-1) and -0.6 t ha(-1) at sites in southern Germany to +0.8 t ha(-1), +0.6 t ha(-1) and +0.8 t ha(-1) at coastal regions for the three CO2 algorithms, respectively. On average across all regions, a relative yield change of +0.9%, +3.0%, and +6.0%, respectively, was predicted for Germany. In contrast, a decrease of -11.6% was predicted without the consideration of a CO2 effect. However, simulated yield changes differed even within regions as site conditions had a strong influence on crop growth. Particularly, groundwater-affected sites showed a lower vulnerability to increasing drought risk. Groundwater recharge was estimated to change correspondingly to changes in precipitation. The consideration of the CO2 effect on transpiration in the model led to a prediction of higher rates of annual deep percolation (+16 mm on average across all sites), which was due to higher water-use efficiency of the crops. In contrast to groundwater recharge, simulated nitrogen leaching varied with the choice of the photosynthesis algorithm, predicting a slight reduction in most of the areas. The results underline the necessity of high-resolution data for model-based regional climate change impact assessment and development of adaptation measures. (C) 2013 Elsevier B.V. All rights reserved. |
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1161-0301 |
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CropM |
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MA @ admin @ |
Serial |
4527 |
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