| Records |
Author  |
Semenov, M.A.; Stratonovitch, P. |
| Title |
Local-scale CMIP5-based climate scenarios for MACSUR2 |
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Report |
| Year |
2016 |
Publication |
FACCE MACSUR Reports |
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8 |
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Pages |
C2.2-D |
| Keywords |
CropM |
| Abstract |
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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Semenov, M.A.; Stratonovitch, P. |
| Title |
Adapting wheat ideotypes for climate change: accounting for uncertainties in CMIP5 climate projections |
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Journal Article |
| Year |
2015 |
Publication |
Climate Research |
Abbreviated Journal |
Clim. Res. |
| Volume |
65 |
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123-139 |
| 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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0936-577x 1616-1572 |
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CropM, ft_macsur |
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MA @ admin @ |
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4701 |
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Semenov, M.A.; Stratonovitch, P. |
| Title |
Adapting wheat for uncertain future |
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2014 |
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XIII ESA congress, Debrecen, Hungary, 2014-08-25 to 2014-08-29 |
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MA @ admin @ |
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2823 |
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| Author |
Semenov, M.A.; Stratonovitch, P. |
| Title |
Designing high-yielding wheat ideotypes for a changing climate |
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Journal Article |
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2013 |
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Food and Energy Security |
Abbreviated Journal |
Food Energy Secur. |
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2 |
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3 |
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185-196 |
| Keywords |
Climate change impacts; crop modeling; LARS-WG; Sirius; wheat |
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Global warming is characterized by shifts in weather patterns and increases in climatic variability and extreme events. New wheat cultivars will be required for a rapidly changing environment, putting severe pressure on breeders who must select for climate conditions which can only be predicted with a great degree of uncertainty. To assist breeders to identify key wheat traits for improvements under climate change, wheat ideotypes can be designed and tested in silico using a wheat simulation model for a wide range of future climate scenarios predicted by global climate models. A wheat ideotype is represented by a set of cultivar parameters in a model, which could be optimized for best wheat performance under projected climate change. As an example, high-yielding wheat ideotypes were designed at two contrasting European sites for the 2050 (A1B) climate scenario. Simulations showed that wheat yield potential can be substantially increased for new ideotypes compared with current wheat varieties under climate change. The main factors contributing to yield increase were improvement in light conversion efficiency, extended duration of grain filling resulting in a higher harvest index, and optimal phenology. |
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2048-3694 |
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CropM, ft_macsur |
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MA @ admin @ |
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4505 |
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Semenov, M.A.; Stratonovitch, P. |
| Title |
Application of evolutionary algorithms for model calibration |
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Conference Article |
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2012 |
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Genetic and Evolutionary Computation Conference (GECCO 2012), Philadelphia, USA., 2012-07-07 to 2012-07-11 |
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MA @ admin @ |
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2821 |
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