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| Author |
Barnes, A.; Moran, D. |
| Title |
Modelling Food Security and Climate Change: Scenario Analysis |
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| Year |
2013 |
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FACCE MACSUR Reports |
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1 |
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D-T1.2 |
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Developing scenarios is a common interest within MACSUR researchers. This report outlines the main results of a survey of TRADE-M participants with respect to the scenarios used within modelling, the time frame and the importance of factors in their development. Most researchers are generating their own regionally defined scenarios, though some are basing these on IPCC scenarios. Generally, they adopt a short-term time frame of up to 2020 to estimate impacts. Most see food production as the main driver behind the scenarios followed by climate change mitigation and adaptation. The main weakness seems to be lack of interest in modelling variability due to weather effects, these may be an argument for stronger cross-collaboration between different MACSUR consortia within the crops and animals groups. No Label |
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MA @ admin @ |
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2262 |
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| Author |
Bojar, W. |
| Title |
Factsheets of the models |
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Report |
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2013 |
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FACCE MACSUR Reports |
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1 |
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D-T1.1 |
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The exploration of adaptation and mitigation measures in the context of global challenges like climate change, food security and expected demographic boom is an field of research of growing importance. Over the last decades many research groups have been developing economic-trade models to analyse consequences on farm welfare, market supply and trade, some of them also address food security and other global concerns. There are many different ways to tackle these issues and the specific advantages and limitations of alternative modelling strategies are not yet well understood. The objective of the WP1 T1.1 task within TradeM theme of MACSUR is to use the results of a survey on trade and economic models of MACSUR Consortium partners to show which topics are currently addressed in the different models, which methods are used and how well these tools are prepared for an integration with other models like climate, crop and livestock models. This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER No Label |
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2261 |
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| Author |
Bojar, W. |
| Title |
MACSUR TradeM Workshop Exploring new ideas for trade and agriculture model integration for assessing the impacts of climate change on food security |
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Report |
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2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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1 |
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M-T0.3 |
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The first TradeM workshop was held at Haifa University (Israel), 3-5 March 2013. It was a state-of-the-art Workshop ‘Economic Modelling on Agriculture with Climate Change for Food Security’. Sixteen papers are presented, following a call for abstracts submitted in December 2012. Presented, reviewed and discussed models, their inputs, outputs and main results of case-study analyses let indicate of how the model can be used to analyze the impacts of climate change on food security, how the model can contribute to, and benefit from other economic and/or crop and livestock models and what input is needed from CropM and LiveM. There were explored ideas for closer integration and linkage between agriculture and economic models and between economic models at different levels, addressing issues of model structure, scale and data processing. Focus was on model comparison, gap analysis, scientific advancements and improvements. We also addressed the key challenges of the economic models (macro- versus micro-economics; uncertainty versus risks; variability and distribution), and identified ways to cope with scaling, uncertainty, risks. The workshop let identify the requirements from CropM and LiveM, find policy questions that MACSUR is going to address, start with the content of the case studies and plan for publication of scientific papers. The sessions were broadcast live via the internet. Twenty-four registered participants and about 65 local visitors attended the workshop.This work was co-financed by NCBiR, Contract no. FACCE JPI/04/2012 – P100 PARTNER No Label |
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MA @ admin @ |
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2260 |
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Rolinski, S.; Sætnan, E. |
| Title |
Uncertainties in climate change prediction and modelling |
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2013 |
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FACCE MACSUR Reports |
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1 |
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D-L1.5 |
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As models become increasingly complex and integrated, uncertainty among model parameters, variables and processes become critical for evaluating model outcomes and predictions. A framework for understanding uncertainty in climate modelling has been developed by the IPCC and EEA which provides a framework for discussion of uncertainty in models in general. Here we report on a review of this framework along with the results of a survey of sources of uncertainty in livestock and grassland models. Along with the identification of key sources of uncertainty in livestock and grassland modelling, the survey highlighted the need for a development of a common typology for uncertainty. When collaborating across traditionally separate research fields, or when communicating with stakeholders, differences in understanding, interpretation or emphasis can cause confusion. Further work in MACSUR should focus on improving model intercomparison methods to better understand model uncertainties, and improve availability of high quality datasets which can reduce model uncertainties. No Label |
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2259 |
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Braunmiller, K.; Köchy, M. |
| Title |
Grassland datasets |
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Report |
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2013 |
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FACCE MACSUR Reports |
Abbreviated Journal |
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1 |
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D-L1.3 |
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In the MACSUR project, there are several grassland models in use that were designed for and adjusted with data from different climatic regions. To be able to run these modelsfor a wide geographical range, there is a need to validate and calibrate them on the same basis.Therefore, a high-quality dataset is needed, which includes a wide range of climatic conditions, management systems and other variables.Through this search 23 grassland related institutes from eleven countries were found and contacted, where 12 of them responded to the request. Nine institutes from cooler (e.g. Finland) and warmer regions (e.g. Israel) are now willing to provide their experimental data. One contributor is even planning to join the project bringing its own grassland model.These new grassland datasets cover in addition to already available ones (Fig. 1) a wide range of climatic regions for a substantiated calibration and validation of the models. Data supplied by the institutes have been checked for internal consistency and cast into a common format. The data have been passed on to WP L2 (Model intercomparison on climate change in relation to livestock and grassland). No Label |
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