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Webber, H.; White, J.W.; Kimball, B.A.; Ewert, F.; Asseng, S.; Rezaei, E.E.; Pinter, P.J., Jr.; Hatfield, J.L.; Reynolds, M.P.; Ababaei, B.; Bindi, M.; Doltra, J.; Ferrise, R.; Kage, H.; Kassie, B.T.; Kersebaum, K.-C.; Luig, A.; Olesen, J.E.; Semenov, M.A.; Stratonovitch, P.; Ratjen, A.M.; LaMorte, R.L.; Leavitt, S.W.; Hunsaker, D.J.; Wall, G.W.; Martre, P. |
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Title |
Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions |
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2018 |
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Field Crops Research |
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Field Crops Research |
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216 |
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75-88 |
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Heat stress; Crop model improvement; Heat and drought interactions; Climate change impact assessments; Canopy temperature; Wheat; Air CO2 Enrichment; Elevated Carbon-Dioxide; Water-Use Efficiency; Climate-Change; Wheat Evapotranspiration; Stomatal Conductance; Multimodel Ensembles; Farming Systems; Drought-Stress; Spring Wheat |
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Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating Tc simulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulate Tc. Model performance in predicting Tc was evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions. |
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2018-02-19 |
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English |
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0378-4290 |
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CropM, ft_macsur |
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no |
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Call Number |
MA @ admin @ |
Serial |
5189 |
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Author |
Semenov, M.A.; Stratonovitch, P. |
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Title |
Local-scale CMIP5-based climate scenarios for MACSUR2 |
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Report |
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2016 |
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FACCE MACSUR Reports |
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8 |
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C2.2-D |
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CropM |
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Climate sensitivity of GCMs was used to select 5 GCMs from the CMIP5 ensemble for impact studies in MACSUR2. Selected GCMs for MACSUR2 are EC-EARTH (7), GFDL-CM3 (8) HadGEM2-ES (10), MIROC5 (13), and MPI-ESM-MR (15). These GCMs are evenly distributed among CMIP5 (Fig 1) and should capture, in principal, climate uncertainty of the CMIP5 ensemble. Using 5 GCMs will enable us to assess uncertainties in impacts related to uncertainty in climate projections. The selection of GCMs in MACSUR2 has a good overlap with selections of GCMs used in CORDEX and AgMIP projects. We used the LARS-WG generator to construct local-scale CMIP5-based climate scenarios for Europe (Semenov & Stratonovitch, 2015). Fifteen sites were selected in Europe for MACSUR2. For each site and each selected GCM, 100 yrs climate daily data were generated by LARS-WG for RCP4.5 and RCP8.5 emission scenarios and for baseline and 3 future periods: near-term (2021-2040), mid-term (2041-2060) and long-term (2081-2100). |
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MA @ admin @ |
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2270 |
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Author |
Rötter, R.P.; Semenov, M.A. |
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Title |
Development of methods for the probabilistic assessment of climate change impacts on crop production |
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2014 |
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FACCE MACSUR Reports |
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3 |
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D-C4.4.1 |
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Various attempts have been made to determine the relative importance of uncertainties in climate change impact assessments stemming from climate projections and crop models, respectively, and to analyse yield outputs probabilistically. For example, in the ENSEMBLES project, probabilistic climate projections (Harris et al. 2010) have been applied in conjunction with impact response surfaces (IRS), constructed by using impact models, to estimate the future likelihood (risk) of exceeding critical thresholds of crop yield impact (see, Fronzek et al., 2011, for an explanation of the method). In this task, we aimed to further develop and operationalize these methods and testing them in different case study regions in Europe. The method combines results of a sensitivity analysis of (one or more) impact model(s) with probabilistic projections of future temperature and precipitation (Fronzek et al., 2011). Such an overlay is one way of portraying probabilistic estimates of future impacts. By further accounting for the uncertainties in crop and biophysical parameters (using perturbed parameter approaches), the outcome represents an ensemble of impact risk estimates, encapsulating both climate and crop model uncertainties. No Label |
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no |
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MA @ admin @ |
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2233 |
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Author |
Semenov, M. |
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Local-scale climate scenarios based on ensembles of global/regional climate models for regional applications in Europe |
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Report |
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2015 |
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FACCE MACSUR Reports |
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3 |
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D-C4.3.1 |
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Local-scale climate scenarios based on ensembles of global/regional climate models for regional applications in Europe is a deliverable for WP4 ‘Scenario development and impact uncertainty evaluation’. We developed the integration of 21st century climate projections for Europe based on simulations carried out within the EU-ENSEMBLES and CMIP3 projects with the LARS-WG stochastic weather generator. The aim was to update ELPIS, a repository of local-scale climate scenarios, for use in impact assessment studies in Europe. No Label |
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MA @ admin @ |
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2232 |
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Semenov, M.A. |
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Title |
Heat tolerance in wheat identified as a key trait for increased yield potential in Europe under climate change |
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2015 |
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FACCE MACSUR Reports |
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5 |
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Sp5-60 |
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To deliver food security for the 9 billon population in 2050, a 70% increase in world food supply will be required. Predicted climate change emphasises the need for breeding strategies that delivers both a substantial increase in yield potential and resilience to extreme weather events such as heat waves, late frost or severe drought. Heat stress around sensitive stages of wheat development has been identified as a possible threat to wheat production in Europe. However, no estimates have been made to assess yield losses due to increased frequency and magnitude of heat stress under climate change. Using existing experimental data, we refined the Sirius wheat model and incorporated effects of extreme temperature during flowering and grain filling on accelerated leaf senescence, grain number and grain weight. This allowed us, for the first time, to quantify yield losses resulting from heat stress under climate change. We used Sirius to design wheat ideotypes optimised for CMIP5-based climate scenarios for 2050 at 6 wheat growing areas in Europe. The yield potential for heat-tolerant ideotypes can be substantially increased compared with the current cultivars in the future by selecting optimal combination of wheat traits, e.g. optimal phenology and extended duration of grain filling. However, grain yield of heat-sensitive ideotypes was substantially lower and more variable in Hungary and Spain, because extending grain filling for increased yield potential was in conflict with high temperature episodes during flowering and grain filling. Despite much earlier flowering at these sites, the risk of heat stress affecting yields of heat-sensitive ideotypes remained high. Therefore, heat tolerance in wheat is likely to become a key trait for increased yield potential and yield stability in southern Europe in the future. No Label |
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MACSUR Science Conference 2015 »Integrated Climate Risk Assessment in Agriculture & Food«, 8–9+10 April 2015, Reading, UK |
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MA @ admin @ |
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2175 |
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