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Semenov, M.A.; Stratonovitch, P. |
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Local-scale CMIP5-based climate scenarios for MACSUR2 |
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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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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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MA @ admin @ |
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2233 |
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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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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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2232 |
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Ewert, F.; Rötter, R.P.; Bindi, M.; Webber, H.; Trnka, M.; Kersebaum, K.; Christian,; Olesen, J.E.; Van Ittersum, M.K.; Janssen, S.; Rivington, M.; Semenov, M.A.; Wallach, D.; Porter, J.R.; Stewart, D.; Verhagen, J.; Gaiser, T.; Palosuo, T.; Tao, F.; Nendel, C.; Roggero, P.P.; Bartošová, L.; Asseng, S. |
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Crop modelling for integrated assessment of risk to food production from climate change |
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2015 |
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FACCE MACSUR Reports |
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6 |
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D-C0.3 |
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The complexity of risks posed by climate change and possible adaptations for crop production has called for integrated assessment and modelling (IAM) approaches linking biophysical and economic models. This paper attempts to provide an overview of the present state of crop modelling to assess climate change risks to food production and to which extent crop models comply with IAM demands. Considerable progress has been made in modelling effects of climate variables, where crop models best satisfy IAM demands. Demands are partly satisfied for simulating commonly required assessment variables. However, progress on the number of simulated crops, uncertainty propagation related to model parameters and structure, adaptations and scaling are less advanced and lagging behind IAM demands. The limitations are considered substantial and apply to a different extent to all crop models. Overcoming these limitations will require joint efforts, and consideration of novel modelling approaches. No Label |
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2089 |
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Trnka, M.; Hlavinka, P.; Wimmerová, M.; Pohanková, E.; Rötter, R.; Olesen, J.E.; Kersebaum, K.-C.; Semenov, M. |
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Paper on model responses to selected adverse weather conditions |
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2017 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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10 |
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C1.2-D |
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Based on the Trnka et al. (2015) study that indicated that heat and drought will be the most important stress factors for most of the European what area the further effort focused on these two extremes. The crop model HERMES has been tested for its ability to replicate correctly drought stress, heat stress and combination of both stresses. While data on the drought stress were available for both field and growth chambers, heat stress and its combination with heat stress was available only for the growth chambers. The modified version of the HERMES crop model was developed by Dr. Kersebaum and is being currently prepared for the journal paper publication. |
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MA @ admin @ |
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4954 |
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