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Author |
König, H.; Helming, K.; Ayalon, O.; Benami, E.; Palatnik, R.R. |
Title |
Curriculum for training course on policy impact assessment |
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Year |
2014 |
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FACCE MACSUR Reports |
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3 |
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D-T4.1 |
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A one-week MACSUR training course on policy impact assessment was held in March 2014 at Haifa University in Israel. The course was organised by ZALF (Hannes König, Katharina Helming) and Haifa University (Ofira Ayalon, Edan Benami, Ruslana Palatnik), targeting at the participation of Post-Docs and PhD students associated to the MACSUR consortium. The Framework for Participatory Impact Assessment (FoPIA) was used as the main method for the course to support structuring the policy impact assessment. The Israelian MACSUR case study of the Ramat Menashe Biosphere was used the test case of assessing alternative policy options and sustainability trade-offs. No Label |
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MA @ admin @ |
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2236 |
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Author |
Kipling, R.; Topp, K.; Don, A. |
Title |
Appropriate meta-data for modellers |
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Report |
Year |
2014 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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3 |
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D-L1.4.1 |
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Report D-L1.4.1 provided an overview of the data and related resources available online and through EU funded projects, relating to soil organic carbon (SOC), and carbon sequestration in grasslands in particular. Building on D-L1.4.1, the report presented here discusses how meta-data describing these types of data (and experimental data more generally) can best be presented in an online resource useful to grassland modellers requiring data to use in their modelling work. Identifying the useful categories of meta-data is a necessary precursor to providing such a resource, which could facilitate better communication between modelling and experimental research groups, allowing researchers to more efficiently locate relevant data and to link up with other scientists working on similar topics. A survey among grassland modelling teams and an assessment of online meta-data resources was used to produce recommendations about the meta-data categories that should be included in an online resource. The categories are generic, so that the recommendations can be followed in the design of meta-data resources for the more general agricultural modelling community. No Label |
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MA @ admin @ |
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2235 |
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Bellocchi, G.; Ma, S. |
Title |
Results of uncalibrated grassland model runs |
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Report |
Year |
2014 |
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FACCE MACSUR Reports |
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3 |
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D-L2.3 |
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This deliverable focuses on the some illustrative results obtained with the grassland models selected (D-L2.1.1) to simulate biomass and flux data from grassland sites in Europe and peri-Mediterranean regions (D-L2.1.1 and D-L2.1.2). This is a blind exercise, carried out without model calibration. The complete set of results will include simulations from calibrated models. The results shown are illustrative of the methodology adopted for grassland model intercomparison in MACSUR. The insights gained from this ongoing study are relevant for some crop and vegetation models, which in some cases proved comparable to grassland-specific models to simulate biomass data from managed grasslands. The results reported here cannot be considered conclusive. Additional results will be published as they become available together with calibration results, as well as the comprehensive evaluation of models with fuzzy logic-based indicators. No Label |
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MA @ admin @ |
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2234 |
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Rötter, R.P.; Semenov, M.A. |
Title |
Development of methods for the probabilistic assessment of climate change impacts on crop production |
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Report |
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2014 |
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FACCE MACSUR Reports |
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3 |
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Pages |
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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Author |
Semenov, M. |
Title |
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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Pages |
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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