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Author |
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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Journal Article |
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Year |
2018 |
Publication |
Field Crops Research |
Abbreviated Journal |
Field Crops Research |
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Volume |
216 |
Issue |
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Pages |
75-88 |
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Keywords |
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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Abstract |
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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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 |
Siebert, S.; Webber, H.; Zhao, G.; Ewert, F.; Siebert, S.; Webber, H.; Zhao, G.; Ewert, F. |
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Title |
Heat stress is overestimated in climate impact studies for irrigated agriculture |
Type |
Journal Article |
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Year |
2017 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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Volume |
12 |
Issue |
5 |
Pages |
054023 |
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Keywords |
heat stress; climate change impact assessment; irrigation; canopy temperature; CANOPY TEMPERATURE; WINTER-WHEAT; WATER-STRESS; CROP YIELDS; GROWTH; MAIZE; DROUGHT; UNCERTAINTY; ENVIRONMENT; PHENOLOGY |
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Abstract |
Climate change will increase the number and severity of heat waves, and is expected to negatively affect crop yields. Here we show for wheat and maize across Europe that heat stress is considerably reduced by irrigation due to surface cooling for both current and projected future climate. We demonstrate that crop heat stress impact assessments should be based on canopy temperature because simulations with air temperatures measured at standard weather stations cannot reproduce differences in crop heat stress between irrigated and rainfed conditions. Crop heat stress was overestimated on irrigated land when air temperature was used with errors becoming larger with projected climate change. Corresponding errors in mean crop yield calculated across Europe for baseline climate 1984-2013 of 0.2 Mg yr(-1) (2%) and 0.6 Mg yr(-1) (5%) for irrigated winter wheat and irrigated grain maize, respectively, would increase to up to 1.5 Mg yr (1) (16%) for irrigated winter wheat and 4.1 Mg yr (1) (39%) for irrigated grain maize, depending on the climate change projection/GCM combination considered. We conclude that climate change impact assessments for crop heat stress need to account explicitly for the impact of irrigation. |
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2017-06-22 |
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1748-9326 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
5035 |
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Author |
Semenov, M.A.; Pilkington-Bennett, S.; Calanca, P. |
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Title |
Validation of ELPIS 1980-2010 baseline scenarios using the observed European Climate Assessment data set |
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Journal Article |
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Year |
2013 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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57 |
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1 |
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1-9 |
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Keywords |
climate change; impact assessment; downscaling; lars-wg; stochastic weather generators; diverse canadian climates; lars-wg; aafc-wg; radiation; impacts |
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Abstract |
Local-scale daily climate scenarios are required for assessment of climate change impacts. ELPIS is a repository of local-scale climate scenarios for Europe, which are based on the LARS-WG weather generator and future projections from 2 multi-model ensembles, CMIP3 and EU-ENSEMBLES. In ELPIS, the site parameters for the 1980-2010 baseline scenarios were estimated by LARS-WG using daily weather from the European Crop Growth Monitoring System (CGMS) used in many European agricultural assessment studies. The objective of this paper was to compare ELPIS baseline scenarios with observed daily weather obtained independently from the European Climate Assessment (ECA) data set. Several statistical tests were used to compare distributions of climatic variables derived from ECA-observed daily weather and ELPIS-generated baseline scenarios. About 30% of selected sites have a difference in altitude of > 50 m compared with the CGMS grid-cell altitude that was selected to represent agricultural land within a grid-cell. Differences in altitude can explain significant Kolmogorov-Smirnov test (KS-test) results for distribution of daily temperature and in t-tests for temperature monthly means, because of the well-known negative correlation between temperature and elevation. For daily precipitation, the KS-test showed little difference between generated and observed data; however, the more sensitive t-test showed significant results for the sites where altitude differences were large. Approximately 11% of sites showed small positive or negative bias in monthly solar radiation, although 86% sites showed > 3 significant t-test results for monthly means. These results can be explained by differences in conversion of sunshine hours to solar radiation used in CGMS and LARS-WG. We conclude that, considering the limitations above, ELPIS baseline scenarios are suitable for agricultural impact assessments in Europe. |
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2016-10-31 |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4812 |
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Author |
Webber, H.; Gaiser, T.; Oomen, R.; Teixeira, E.; Zhao, G.; Wallach, D.; Zimmermann, A.; Ewert, F. |
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Title |
Uncertainty in future irrigation water demand and risk of crop failure for maize in Europe |
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Journal Article |
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Year |
2016 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
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Keywords |
crop model; impact assessment; crop water use; evapotranspiration; irrigation; drought; uncertainty |
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Abstract |
While crop models are widely used to assess the change in crop productivity with climate change, their skill in assessing irrigation water demand or the risk of crop failure in large area impact assessments is relatively unknown. The objective of this study is to investigate which aspects of modeling crop water use (reference crop evapotranspiration (ET0), soil water extraction, soil evaporation, soil water balance and root growth) contributes most to the variability in estimates of maize crop water use and the risk of crop failure, and demonstrate the resulting uncertainty in a climate change impact study for Europe. The SIMPLACE crop modeling framework was used to couple the LINTUL5 crop model in factorial combinations of 2-3 different approaches for simulating the 5 aspects of crop water use, resulting in 51 modeling approaches. Using experiments in France and New Zeland, analysis of total sensitivity revealed that ET0 explained the most variability in both irrigated maize water use and rainfed grain yield levels, with soil evaporation also imporatant in the French experiment. In the European impact study, net irrigation requirement differed by 36% between the Penman and Hargreaves ET0 methods in the baseline period. Average EU grain yields were similar between models, but differences approached 1-2 tonnes in parts of France and Southern Europe. EU wide esimates of crop failure in the historical period ranged between 5.4 years for Priestley-Taylor to every 7.9 years for the Penman ET0 methods. While the uncertainty in absolute values between models was significant, estimates of relative changes were similar between models, confirming the utility of crop models in assessing climate change impacts. If ET0 estimates in crop models can be improved, through the use of appropriate methods, uncertainty in irrigation water demand as well as in yield estimates under drought can be reduced. |
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2016-09-13 |
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Newsletter July |
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CropM; wos; ft=macsur; |
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MA @ admin @ |
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4778 |
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Author |
Semenov, M.A.; Stratonovitch, P. |
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Title |
Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections |
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Journal Article |
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Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
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65 |
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123-139 |
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Keywords |
sirius wheat model; lars-wg weather generator; downscaling; cmip5 ensemble; impact assessment; stochastic weather generators; earth system model; diverse canadian climates; high-temperature stress; change scenarios; lars-wg; decadal prediction; yield progress; heat-stress; aafc-wg |
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This study describes integration of climate change projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) multi-model ensemble with the LARS-WG weather generator, which delivers an attractive option for the downscaling of large-scale climate projections from global climate models (GCMs) to local-scale climate scenarios for impact assessments. A subset of 18 GCMs from the CMIP5 ensemble and 2 Representative Concentration Pathways (RCPs), RCP4.5 and RCP8.5, were integrated with LARS-WG. For computationally demanding impact assessments, where it is not practical to explore all possible combinations of GCM x RCP, a climate sensitivity index could be used to select a subset of GCMs which preserves the range of uncertainty found in CMIP5. This would allow us to quantify uncertainty in predictions of impacts resulting fromthe CMIP5 ensemble by conducting fewer simulation experiments. In a case study, we describe the use of the Sirius wheat simulation model to design in silico wheat ideotypes that are optimised for future climates in Europe, sampling uncertainty in GCMs, emission scenarios, time periods and European locations with contrasting climates. Two contrasting GCMs were selected for the analysis, ‘hot’ HadGEM2-ES and ‘cool’ GISS-E2-R-CC. Despite large uncertainty in future climate projections, we were able to identify target traits for wheat improvement which may assist breeding for high-yielding wheat cultivars with increased yield stability. |
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2015-10-12 |
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English |
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0936-577x 1616-1572 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4701 |
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